International Journal of Machine Learning and Networked Collaborative Engineering (IJMLNCE)
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USAGE OF THE BIG DATA IDEA IN ASSOCIATIONS POTENTIAL OUTCOMES, OBSTRUCTIONS AND DIFFICULTIES
No full textThis research report the examination of the Big data’s considered. It has seven zones. In the standard, the developing bit of information and facts and it’s fast in-wrinkle in the new socio-quiet the truth, are talked about. Next, the likelihood of The Big data’s is portrayed and the fundamental wellsprings of headway of information are delineated. In the running with bit of the research paper the most essential conceivable outcomes related with The Big data’s are introduced and investigated. The going with part is focused on the consume factorization of contraptions, systems and the most steady information as for The Big data’s works out. In the running with bit of the father per the achievement sections of The Big data’s practices are dissected, afterwards an examination of the most essential issues and tests related with The Big data’s. In the last piece of the research report, the most vital results and proposition are advanced
Emerging Trends on Big Data & Cloud Computing
No full textIn this paper we focused on the emerging trends and various approaches for carrying out analytics on clouds for Big Data application. It revolves around four important analytics and Big Data. We also discussed about the some of the real world challenges in this cloud and Big Data computing era. This paper also focused on the implementation strategy of Big Data like Management, Data Varity etc. It helps to identify the technology gaps which may help to research communities so that they will have a directions for future scope of Big Data based on cloud computing
Machine Learning Approach for User Accounts Identification with Unwanted Information and data
No full textMachine Learning used for many real time issues in many organizations and for the purpose of social media analytics machine learning models is used most prominently and to identify the genuine accounts and the information in the social media we are her with a new pattern of identification. In this pattern of model we are proposing some words which are hidden to identify the accounts with fake data and the some of the steps we are proposing will be help to identify the fake and unwanted accounts in Facebook in an efficient manner. Clustering in machine learning will be used and in prior to that we are proposing an efficient architecture and the process flow which can identify the fake and suspicious accounts in the social media. This article will be on machine learning implementations and will be working on OSN (online social networks). Our work will be more on Facebook which is maintaining more amount of accounts and identifying which are over ruling the rules of privacy and protection of the user content. Machine learning supervised models will be used for text classification and the image classification is performed by CNN of unsupervised learning and the explanation will be given in the implementation phas
IoT Based Intelligent Vehicle Parking Solution System
No full textWith rapid increase in population in urban cities, availability of parking space is real issue. This parking issue lead to traffic and encroachment of roads for parking. With implementation of smart cities is real time development, smart parking is integral part of this development. Intelligent parking system describe in this paper solve the parking issue and fits in the smart city development, this system is based on cloud-based parking system where user is able to get location of parking spot with helps sensors network and cloud computing. The user is updated with real time data of available parking spot near their destination, and they can choose the spot according to their convenience. The main components of the system are sensor layer, hardware layer, cloud layer and application layer. The sensor layer is controlled by Arduino board or other system on chip which manages the data collected by sensors, this data is sent to cloud through hardware layer cloud layer manages the data accordingly and data is sent to users’ application on the reception of request through application. This interconnection of all the layers is main aspect of IoT (Internet of Things). This system will help user to get the spot in hassle free and quick way
Smart Advisor: An Intelligent Inventory Prediction Based On Regression Model
No full textToday one of the biggest expense items of the enterprises is raw material and stock amounts. Therefore, proper inventory management is very important for the profitability of the enterprises. Products that are not purchased on time cause interruptions in production and products left over because the expiration date has passed will also cause losses for businesses. Therefore, proper inventory management is critical for profit / loss situations of businesses. In this paper we presented a model to predict the demand of certain stock items by using a regression model. Our model can analysis and computer the prediction results on a given dataset. We evaluate our model on sample dataset and provide the analysis as well calculations over the existing inventory. Accurate analysis of stock consumption enables accurate estimation of the amount of stock to be consumed in the future. Accurate forecasting of stock consumption helps to take corrective steps in decision making. That is, it only allows you to buy in sufficient quantity when necessary. These stages are critical for economic stock management. For this reason, robust and adaptable approaches that can provide models ensure that stock consumption can be managed properly. It is difficult to find previously written sources on estimating the direction of stock movements. One of the most important reasons for this is the lack of incentive to make such studies in the academic literature. As a result, articles written about the subject and the work done have been limited, the results have not reached the reproducible level
IJMLNCE Editorial Note Volume No 02, Issue No 03
No full textThe International Journal of Machine Learning and Networked CollaborativeEngineering (IJMLNCE) ISSN 2581-3242 continues to evolve and expand, receiving moreand more quality articles for evaluation and possible publication. We are happy to sharewith you that apart from the existing indexing, we are able to place our journal manuscriptwith two more indexing e.g., WorldCat-OCLC and Dimensions. We are now proud topresent the Volume No-02 Issue No-03, on this occasion, we have selected five interestingpapers that are framed in the scope of the journal, covering different aspects related tomachine learning and collaborative engineering.
Küçük and Kiani [1] published a work entitled “Smart Advisor: An IntelligentInventory Prediction Based On Regression Model”. Authors focus on inventorymanagement of raw material and stock amounts in enterprises and present a model topredict the demand of stock items by using a regression model. They analyze the outputsof the model on a sample dataset to enable accurate estimation of the amount of stock to beconsumed in the future and to facilitate decision making.
Küçük and Kiani [1] published a work entitled “Smart Advisor: An IntelligentInventory Prediction Based On Regression Model”. Authors focus on inventorymanagement of raw material and stock amounts in enterprises and present a model topredict the demand of stock items by using a regression model. They analyze the outputsof the model on a sample dataset to enable accurate estimation of the amount of stock to beconsumed in the future and to facilitate decision making.
Kalaskar et al. [2] published a work entitled “Forecasting Ventricular Deviation inMonitoring of Live ECG Signal”. This work shows the problem of the increasing numberof coronary artery diseases and ventricular arrhythmias cases. Authors propose a novelplatform for real time diagnosis of Ventricular Tachyarrhythmia with the help of a portableelectrocardiography device. In addition, it includes a solution for signal analysis andcloud-based processing for the diagnosis.International Journal of Machine Learning and Networked Collaborative Engineering, ISSN: 2581-3242, Vol.2 No. 3iii
Hoang et al. [3] published a work entitled “Cow Behavior Monitoring Using aMultidimensional Acceleration Sensor and Multiclass SVM”. In this work, authors talkabout the health of cows based on their daily behavior. Thus, they propose an automatedmonitoring system for suitable management. Cow’s activities are monitored by using amultidimensional acceleration sensor and data is processed in a server through analgorithm based on multiclass support vector machine.
Kumar and Sairam [4] published a work entitled “Machine Learning Approach forUser Accounts Identification with Unwanted Information and data”. Authors focus onidentifying fake and suspicious accounts in Facebook in an effective way through a novelarchitecture and a process flow. They also apply machine learning supervised models fortext classification and machine learning unsupervised models for image classificationrespectively.
Puri et al [5] published a work entitled “Internet of Things and HealthcareTechnologies: A Valuable Synergy from Design to Implementation”. In this work, authorsintroduce a review on various enabling Internet of Medical Things technologies based onthe latest research work and technology available in the marketplace. The work alsoanalyzes different software platforms available in the field and the current challenges thatthe industry is addressing
Eight Legs Rimless Wheel Robot Model Driven on Level Ground Using one actuator
No full textoai:ojs2.mlnce.net:article/4It is outstanding that a rimless wheel (RW) needs actuators to walk on the level ground. There is the primary test hard to discover an appropriate control framework to accomplish a stable RW movement. There is the model of the eight-legged underactuated rimless wheel with the middle. To start with, we created 4-DOF numerical model of an underactuated rimless wheel (URW) and figured the condition of movement as per the Lagrange\u27s technique. We likewise perform numerical recreations utilizing the model created and demonstrate that a steady stride can be produced with the appropriate introductory condition and physical parameters. The numerical recreations demonstrate that, by embracing this control framework, the URW with middle can walk steadily on level ground, and the URW can be driven with an extensive variety of speed and high productivity by changing the control parameter
Survey on Security Issues and Concerns in Cloud Computing Technology
No full textCloud computing is starting a few tremendous changes to individuals\u27 way of life and hindering position recently for its various preferences. Despite, the security of cloud computing is dependably the concentration of heteromorphy likely cloud clients, and a noteworthy impediment for it’s across the board utilizations. In this paper, to elevate customers to see the wellbeing limit of cloud computing and put insufficient Endeavor to redesigning the security level of cloud computing, we gauged the current conceivable security models of cloud computing, e.g. diverse settlement design, hazard accumulation show, 3D square model of cloud computing, and abridged the real security dangers of cloud computing acquiring from irregular systems. Eventually, we permit few security techniques from the idea of objects of cloud computing
A Detailed Analysis of Core NLP for Information Extraction
No full textThe amount of unstructured text present in all electronic media is increasing periodically day after day. In order to extract relevant and succinct information, extraction algorithms are limited to entity relationships. This paper is compendium of different bootstrapping approaches which have their own subtask of extracting dependencies like who did, what, whom, from natural language sentence. This can be extremely helpful in both feature design and error analysis in application of machine learning to natural language processing
Forecasting Ventricular Deviation in Monitoring of Live ECG Signal
No full textNumber of coronary artery disease cases and ventricular arrhythmias has been increasing in India. One of the common forms of cardiac disorder is Ventricular Tachycardia(VT). Due to improper electrical activities in the ventricles, consistent and rapid heart rate occurs, which produces Ventricular Tachycardia disorder. Short time period may not lead to severe heart problem, but the longer duration increases it may be a severe heart issue. In this disorder,for short durations it is possible that there may not be any symptoms or few symptoms with palpitations(increase / decrease in heart beats), dizziness or pain in chest. This disorder may result in cardiac arrest. This may also results into ventricular fibrillation. initially it was found that near about 7% of people in cardiac arrest are caused by Ventricular Tachycardia. In this work, a novel platform for real time diagnosis of Ventricular Tachyarrhythmia with the help of a portable Single lead ECG device is proposed. The gateway for signal analysis and combined edge and cloud based processing for the diagnosis is used. The biosignal captured by the device in LEAD II configuration is pushed to a cloud based diagnosis API through a mobile gateway. An algorithm in the cloud analyses this signal and finds out P, Q, R, S, T, their amplitude positions, onset and offset. From the onset and offset ST segment slope, elevation, depression, S morphology and ST segment variation statistics is captured and classified using rule based classifier. The work evaluates the performance of the classifier with Physionet dataset. The accuracy of the system was found to be 90% with accuracy of detecting normal ECG being 100% where as the accuracy of detection of VT being 80%. Results shows that the system is extremely efficient in detecting Ventricular Tachyarrhythmia and many related cardio vascular diseases