International Journal of Machine Learning and Networked Collaborative Engineering (IJMLNCE)
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Machine Learning: An Effective Technique in Bio-Medical Signal Analysis and Classification
No full textAdvancement in the field of digital signal processing and modern machine learning (ML) approaches has witnessed substantial growth in biomedical engineering. The diagnostic power of these machines has grown manifolds mainly due to the exploration of effective and discriminate feature spaces that remain crucial for pattern recognition. It has enhanced the ability of machine learners to model the complex patterns accurately and make them adaptable to new task domains with explanation/experience learning approaches. Many vivid application domains including the artificial intelligent systems and robotics with critical and innovative thinking are going to rely on effective ML systems for efficiency and optimization. This has made the Artificial Neural Networks (NN) an emerging field of research and motivates the authors to classify the MIT-BIH arrhythmia data as abnormal or normal using different ANN models. Finally, the results have been validated with that of the colon cancer gene data
Domestic Mechanization System with IoT and Robotics
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In this paper, we discuss home automation IoT based and we show three projects about IoT. IoT or internet of things is an upcoming innovation which is an arrangement of interrelated computing devices, mechanical and computerized machines, articles, creatures or individuals that are given one kind of identifiers and the capacity to exchange information over a system without expecting human-to-human or human-to-PC association. It\u27s an achievement though it will change our whole world. New Horizons will begin in our lives by this. The premise of this research was to diminish the anguish of human. IoT based home mechanization can make the life an excessive amount of less demanding. In this research, we will attempt to interface the normal devices which are utilized as a part of a home. This paper is giving the design part of the point of the smart window, smart almirah, and smart bookshelf. One of the three projects is the smart windows system. It can be controlled in accordance with the weather conditions of the owner\u27s house, and the house temperature, the proper balance of gas in the air. Using this system, the user will get comfortable weather at home and will be able to predict any external danger to the environment. And it can be done by a mobile phone or an internet-enabled device
IJMLNCE Editorial Note Volume No 02, Issue No 02
No full textPreface
After more than a year, The International Journal of Machine Learning and Networked Collaborative Engineering (IJMLNCE) ISSN 2581-3242 has experienced a great growth from every possible point of view. After publishing three editions, we are now indexed in popular sources like BASE, CrossRef, CiteFactor, DRJI, Google Scholar, Index Copernicus, J-Gate, PKP-Index, ROAD, Scilit and Socolar.
We are now proud to present the fourth number, corresponding to Volume No-02 Issue No-02. On this occasion, we have five interesting papers that are framed in the scope of the journal, covering different aspects related to machine learning and collaborative engineering.
For example, Huong Thom et al. use neural networks to perform steganalysis for reversible data hiding. The aim is to restore original images after extracting information from a hidden image with secret data. Authors propose a method to improve detection rate of such type of images with 96% correct detection rates using neural networks and 94% with convolutional neural networks [1].
Maldonado et al. design a prediction model for pollutants with onboard diagnostic sensors in vehicles. The aim is to show the relation between the internal parameters of on-road vehicles and their emissions. Internal values are collected through the On-Board Diagnostics port, while values of the emissions are measured from the exhaust pipe using an Arduino board. There are observable correlations between carbon dioxide emissions and vehicle speed, as well as carbon dioxide emissions and engine revolutions per minute [2].
Choudhary et al. base their work in neural networks to process information. They extend the Leaky Integrate-and-Fire model and analyze the impact of exponentially distributed delay memory kernel on spiking activity and steady state membrane potential distribution. Authors propose their model to implement recurrent neural networks with more accuracy and as a potential way to implement chip level artificial intelligence [3].
Kiani proposes a new approach to improve automated learning methods based on the reinforcement learning technique. The effectiveness of the interactions with the environment is evaluated by the number of rewards and penalties that are taken from it. Kiani proposes three versions: simple, sequential and unstructured linear learning methods,that focus on different scenarios and areas [4].
Chatterjee work on a big data framework mixed with the Internet of Things using machine learning. Author gives an explanation about the relationship between big data and the Internet of Things, together with different issues and challenges, all from the point of view of offering solutions using an approach based on machine learning strategies [5]
IJMLNCE Editorial Note Volume No 02, Issue No 01
No full textPreface
It gives us immense pleasure to start the Editorial Note for the International Journal of Machine Learning and Networked Collaborative Engineering (IJMLNCE) ISSN No. 2581-3242, a quarterly published, Open Access, peer-reviewed, International Journal. In the New Year 2018, we would like to convey our warm greetings to each one of you. Our wish with the New Year brings happy research outcomes & brings happiness-prosperity in your lives. In the Volume No 02, Issue No 01, we are happy to write that our journal manuscript information available with CrossRef, CiteFactor, DRJI, Google Scholar, Index Copernicus, J-Gate, ROAD and Scilit.
In the Volume No. 02 Issue No. 01, we have five research papers, within the scope of the journal, which covers various aspects of machine learning and collaborative engineering.
The first paper in this list is “Eight Legs Rimless Wheel Robot Model Driven on Level Ground Using one Actuator”, authored by Mohammad Farhan Ferdous. This paper explores how a rimless wheel can walk on the level ground with the help of actuators. A control framework has been set up to establish the fact they have proposed. The researchers have created a 4 DOF numerical model of an under actuated rimless while [1].
In the next paper, authored by Surbhi Sharma et al., “An Innovative Approach for Quick Shopping using QR Code”, has been wisely demonstrated. This paper focuses on the advancement in virtual shopping via QR Code using smart phones, which can be simple and easily approachable as well as customer friendly. In this paper, the authors have represented an app where using the QR Code the URL can be found as well as purchase of the product, order inclusion and bill generation after purchase is also possible using the technique. This work is an innovative concept in the world of digital marketing and management area doubtlessly [2].
The next paper in the list, authored by Nguyen Hoang Ha and Nguyen Hoang Nguyen, covers the area of cloud computing. The paper is based on a heuristic algorithm on Particle Swarm Optimization (PSO) on cloud computing. The authors have chosen SaaS providers as their target object and they have compared their results with the existing solutions available using CloudSim simulation. The work focuses on the issue of admission control and the schedule for the requirements of users toward of multi-objective optimization. The novelty of the work is due to the specific calculation of fitness function, the local best position of each particle and the global best position of the entire swarm [3].
Our fourth paper, authored by Sunil Kumar Joshi et al., has been selected from Mobile Ad Hoc networking area (MANET), again a highly demanding research area. This paper focuses on Multidimensional performance analysis for packet delivery and calculating the routing overhead. The authors have considered two routing protocols, namely AODV and AOMDV for their proposed work and correlation has been made between Ad-hoc On Demand Distance Vector convention and Ad-hoc On Multipath Demand Distance Vector convention utilizing system test system. NS2 has been preferred as the simulation tool for the work. [4].
The last paper selected for this version, authored by Vishal Dutt, Akhansha Jain and Abhilash Parashar, focuses on research centric approach and utilization of Big Data management in case of virtual shopping or window shopping. The main focus of their proposed work is on the consume factorization of contraptions, systems and the most steady information as for The Big data’s works out. They have shown how effectively use of Big Data can give an association a centered favored edge and be of respect, rather than being satisfactory to simply assemble and have the sensible edifying collection [5]
Study of Concurrency Control Techniques in Distributed DBMS
No full textConcurrency control focuses on maintaining consistency and integrity of database through synchronized access. The complexity relating to concurrency control in a distributed context is very high as compared to centralized framework due to maintaining consistency within the multiple fragments / copies of the database. This paper consolidates and discusses various lock based concurrency control techniques for Distributed DBMS. The paper also presents a comparative study of various two phase locking based concurrency control techniques