
Asif Ahmed NeloyVancouver Island University | VIU · Department of Computing Science
Asif Ahmed Neloy
MSc
Lecturer @ Vancouver Island University
Research Interest: Dimension Reduction and Auto-Encoders
About
16
Publications
17,573
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Citations
Introduction
Asif Ahmed Neloy is a Lecturer at the Vancouver Island University. Asif is a Business & Data Science professional specializing in Machine Learning, passionate about uncovering insights from complex data. With a Master of Science degree in Computer Science from the University of Manitoba, Asif has extensive experience in machine learning tools, including data structures, clustering and classification, natural language processing, and unravelling business decisions.
Additional affiliations
January 2021 - present
January 2021 - present
January 2020 - January 2021
Education
January 2021 - January 2023
January 2015 - December 2018
Publications
Publications (16)
Apartment rental prices are influenced by various factors. The aim of this study is to analyze the different features of an apartment and predict the rental price of it based on multiple factors. An ensemble learning based prediction model is created to reach the goal. We have used a dataset from bProperty.com which includes the rental price and di...
In this study, the authors propose a generic architecture, associated terminology and a classificatory model for observing ICU patient's health condition with a Content-Based Recommender (CBR) system consisting of K-Nearest Neighbors (KNN) and Association Rule Mining (ARM). The aim of this research is to predict or classify the critically condition...
An improved version of Alpha-N, a self-powered, wheel-driven Automated Delivery Robot (ADR), is presented in this study. Alpha-N V2 is capable of navigating autonomously by detecting and avoiding objects or obstacles in its path. For autonomous navigation and path planning, Alpha-N uses a vector map and calculates the shortest path by Grid Count Me...
Recommender Systems (RSs) have become an essential part of most e-commerce sites nowadays. Though there are several studies conducted on RSs, a hybrid recommender system for the real state search engine to find appropriate rental apartment taking users preferences into account is still due. To address this problem, a hybrid recommender system is pr...
This paper presents the design and integration of 3 Survivor, a rough terrain negotiable teleoperated mobile rescue and service robot. 3 Survivor is an improved version of two previously studied surveillance robots named Sigma 3 and Alpha N. In 3 Survivor, a modified double tracked with caterpillar mechanism is incorporated in the body design. A pa...
Alpha-N - A self-powered, wheel-driven Automated Delivery Robot (ADR) is presented in this paper. The ADR is capable of navigating autonomously by detecting and avoiding objects or obstacles in its path. It uses a vector map of the path and calculates the shortest path by Grid Count Method (GCM) of Dijkstra’s Algorithm. Landmark determination with...
This paper presents the design and integration of
3-Survivor: a rough terrain negotiable teleoperated mobile
rescue and service robot. 3-Survivor is an improved version of
two previously studied surveillance robots named Sigma-3 and
Alpha-N. In 3-Survivor, a modified double-tracked with
caterpillar mechanism is incorporated in the body design. A
pa...
This paper introduces a rescue robot named Sigma 3 which is developed for potential applications such as helping hands for humans where a human can not reach to have an assessment of the hazardous environment. Also, these kinds of robot can be controlled remotely with an adequate control system. The proposed methodology forces on two issues : 1. No...
An Automated Mobile Robot can navigate on a floor freely by avoiding obstacles and walking on the shortest path between two points. It uses a vector map of the floor and Dijkstra's shortest path algorithm for calculating shortest path. For obstacle avoidance, it uses ultrasonic sensor modules and pre-loaded intelligence. The RFID scanner is used fo...
This paper introduces a rescue robot named Sigma-3 which is developed for potential applications such as helping hands for humans where a human can't reach to have an assessment of the hazardous environment. Also, these kinds of robot can be controlled remotely with an adequate control system. The proposed methodology forces on two issues-1. Novel...
Adaptable Intensive Care Unit (ICU) system is a key concern for hospitals in developing countries like Bangladesh. Most of the hospital in Bangladesh lack serving proper health service due to unavailability of appropriate, easy and scalable systems. There also appears communication and information gaps between hospital authority and patient's relat...
Adaptable Critical Patient Caring system is a key
concern for hospitals in developing countries like Bangladesh.
Most of the hospital in Bangladesh lack serving proper health
service due to unavailability of appropriate, easy and scalable
smart systems. The aim of this project is to build an adequate
system for hospitals to serve critical patients...
For different purposes, a service robot that can be controlled remotely will play a significant role in the expansion of robotics automation systems. In the developing countries like Bangladesh, everyone is concerned about safety from both natural and human-made situations like Disposal of Bombs, rescuing objects from dangerous places, a useful ass...
An Automated Mobile Robot can navigate on a floor freely by avoiding obstacles and walking on
the shortest path between two points. It uses a vector map of the floor and Dijkstra's shortest path
algorithm for calculating shortest path. For obstacle avoidance, it uses ultrasonic sensor modules and preloaded
intelligence. The RFID scanner is used for...
Questions
Questions (5)
Dear Altruists,
Can you guys suggest any research article where I can learn the mathematical formulation of relational auto-encoder? I have been seeing this paper -
Conference Paper Relational Autoencoder for Feature Extraction
but require a more specific layer config to replicate that model in python.
Any resource or suggestion will be highly appreciated.
[P.S: Primarily I'm trying models on the MNIST dataset]
I am building a Hybrid recommender system with KNN. But my dataset contains lots of missing data as well as too sparse and dense data. Other than the traditional dataset normalization methods, is there any way to minimize these phenomena for building the recommender system?
I am trying to build a house price recommender system that will work as a search engine in a real estate property website. Any suggestions on how to achieve that using ML algorithms? I have planning to use the Hybrid method stacking classification models.
I have been using Jupyter Notebook for my ML models. I have ideas about Plotly for downloading graph. But most of them aren't good enough to use as high quality. Any alternative solutions for plotting these graphs with good quality?
I am working in a house price recommender system and wanted to know how can I evaluate my model just like other single stacked models (e.g cross-Val, k-fold and so on).