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Keyword: MACPower Saving MAC Protocols in Wireless Sensor Networks: A Performance Assessment Analysis
Wireless sensor networks are an emerging technology that is used to monitor points or objects of interest in an area. Despite its many applications, this kind of network is often limited by the fact that it is difficult to provide energy to the nodes continuously, forcing the use of batteries, which restricts its operations. Network…
Read MoreElectroencephalogram Based Medical Biometrics using Machine Learning: Assessment of Different Color Stimuli
A methodology of medical signal-based biometrics has been proposed in this paper for implementing a human identification system controlled by electroencephalogram in respect of different color stimuli. The advantage of biosignal based biometrics is that they provide more efficient operation in simple experimental condition to ensure accurate identification. Red, Green, Blue (primary colors) and Yellow…
Read MoreDevelopment of an EEG Controlled Wheelchair Using Color Stimuli: A Machine Learning Based Approach
Brain-computer interface (BCI) has extensively been used for rehabilitation purposes. Being in the research phase, the brainwave based wheelchair controlled systems suffer from several limitations, e.g., lack of focus on mental activity, complexity in neural behavior in different conditions, and lower accuracy. Being sensitive to the color stimuli, the EEG signal changes promises a better…
Read MoreBlockchain Technology-Based Good Distribution Practice Model of Pharmacy Industry in Indonesia
Distribution is the main activity in integrated product supply chain management. In the pharmaceutical industry, the process of drug distribution is important because of the handling, storage, and distribution of medicinal products with good standards and quality. The problem that occurs in the pharmaceutical industry is the circulation of counterfeit drugs by related parties, for…
Read MoreFault Diagnosis and Noise Robustness Comparison of Rotating Machinery using CWT and CNN
For systems using rotating machinery, diagnosing the faults of the rotating machinery is critical for system maintenance. Recently, a machine learning algorithm has been employed as one of the methods for diagnosing the faults of rotating machinery. This algorithm has an advantage of automatically classifying faults without an expert knowledge. However, despite a good training…
Read MoreChallenges and New Paradigms in Conservation of Heritage-based Villages in Rural India -A case of Pragpur and Garli Villages in Himachal Pradesh
The research paper aims to focus on the issues and challenges in developing a sustainable model of an ideal heritage village project by using descriptive and empirical investigation methods. To capture the perception and understanding of the concept of sustainability of a Heritage Village, a mixed-methods approach was conducted by the researcher where document where…
Read MoreActive Disturbance Rejection Control Design for a Haptic Machine Interface Platform
This paper proposes an active disturbance rejection control (ADRC) design for a haptic display platform structure. The motivation for the following scheme originates from the shortcomings faced by classical proportional integral derivative (PID) controllers in control theory. The ADRC is an unconventional model-independent approach, acknowledged as an effective controller in the existence of total plant…
Read MoreDiagnosis of Tobacco Addiction using Medical Signal: An EEG-based Time-Frequency Domain Analysis Using Machine Learning
Addiction such as tobacco smoking affects the human brain and thus causes significant changes in the brainwaves. The changes in brain wave due to smoking can be identified by focusing on changes in electroencephalogram pattern, extracting different time-frequency domain features. In this aspect, a laboratory-based study has been presented in this paper, for assessing the…
Read MoreMultiple Machine Learning Algorithms Comparison for Modulation Type Classification Based on Instantaneous Values of the Time Domain Signal and Time Series Statistics Derived from Wavelet Transform
Modulation type classification is a part of waveform estimation required to employ spectrum sharing scenarios like dynamic spectrum access that allow more efficient spectrum utilization. In this work multiple classification features, feature extraction, and classification algorithms for modulation type classification have been studied and compared in terms of classification speed and accuracy to suggest the…
Read MoreComparison of Machine Learning Parametric and Non-Parametric Techniques for Determining Soil Moisture: Case Study at Las Palmas Andean Basin
Soil moisture is one of the most important variables to monitor in agriculture. Its analysis gives insights about strategies to utilize better a particular area regarding its use, i.e., pasture for cows (or similar), production forests, or even to answer what crops should be planted. The vertical structure of the soil moisture plays an important…
Read MoreAnalysis of Pharmaceutical Company Websites using Innovation Diffusion Theory and Technology Acceptance Model
The progress of information using websites is developing fast, impacting various sectors, one of which is pharmaceutical companies. Pharmaceutical companies have roles in drug manufacturing, pharmaceutical distribution, and essential services for the community—the most important and challenging activity in the IT department. The researcher is responsible for one of the Bandung pharmaceutical companies. Researchers are…
Read MoreAn Evaluation of some Machine Learning Algorithms for the detection of Android Applications Malware
Android Operating system (OS) has been used much more than all other mobile phone’s OS turning android OS to a major point of attack. Android Application installation serves as a major avenue through which attacks can be perpetrated. Permissions must be first granted by the users seeking to install these third-party applications. Some permissions can…
Read MoreA Machine Vision Approach for Underwater Remote Operated Vehicle to Detect Drowning Humans
Today, Drowning is the 3rd major cause for unintentional injury death accounting for 7% of deaths of all injury deaths. Drowning is a state of suffocation when water or other fluids accumulate the lungs, resulting in respiratory impairment, ultimately leading to death. The predominant problem during rescue operations of such accidental drowning is to locate…
Read MoreHandling Priority Data in Smart Transportation System by using Support Vector Machine Algorithm
In an intelligent transportation system (ITS), time is a big challenge since processing a huge amount of data in a short time is very difficult, especially when the processed data is heterogeneous, consisting of a mixture of emergency data, normal data, and noise. In an ITS, an ambulance is one of the priority vehicles, and…
Read MoreTowards a Documents Processing Tool using Traceability Information Retrieval and Content Recognition Through Machine Learning in a Big Data Context
In 1980, an application was developed to track, manage and store documents in electronic format. Scan technology has enabled organizations to digitize papers for easier document storage and tracking. Document management tools have since developed by introducing new functionalities, related to security, users services, workflow and audit. Our research is part of the context of…
Read MoreComparison of Support Vector Machine-Based Equalizer and Code-Aided Expectation Maximization on Fiber Optic Nonlinearity Compensation Using a Proposed BER Normalized by Power and Distance Index
Advances in optimizing optical fiber communications have been on the rise these recent years due to the increasing demand for larger data bandwidths and overall better efficiency. Coherent optics have focused on many kinds of research due to its ability to transport greater amounts of information, have better flexibility in network implementations, and support different…
Read MoreExtending the Classifier Algorithms in Machine Learning to Improve the Performance in Spoken Language Understanding Systems Under Deficient Training Data
One of the open domain challenges for Spoken Dialogue System (SDS) is to maintain a natural conversation for rarely visited domain i.e. domain with fewer data. Spoken Language Understanding (SLU) is a component of SDS that converts user utterance into a semantic form that a computer can understand. If we scale SDS open domain challenge…
Read MoreComplex Order PI\(^{\alpha + j\beta} \)D\(^{\gamma+j\theta}\) Design for Surface Roughness Control in Machining CNT Al-Mg Hybrid Composites
Accurate machining control is indispensable for the smart factories of tomorrow. Variations in controller responses may cause unacceptable process deviations during machining leading to productivity losses and possible damage. In the present work, a complex order PIα+jβDγ+jθ(COPID) controller was designed to effectively control surface roughness generation while machining CNT Al-Mg hybrid composites. Performance of the…
Read MoreOvermind: A Collaborative Decentralized Machine Learning Framework
This paper is an extension of work originally presented in PM2.5 Prediction-based Weather Forecast Information and Missingness Challenges: A Case Study Industrial and Metropolis Areas, which focused on imputation algorithm to solve missingness challenge and demonstrated a basic prediction system to prove the proposed algorithm, II-MPA. Distributed and decentralized systems, recently, have been proven for…
Read MoreReview of Orange Juice Extractor Machines
There is some agricultural equipment for post harvesting of Orange fruit Juice, all the machine is geared towards extraction of the fruit juice. Fruit juice extraction is the act of wringing out the juice content of fruits by way of an effective processing and storage which enhance reduction in wastage. Fruit juices which literally have…
Read MoreInterpretation of Machine Learning Models for Medical Diagnosis
Machine learning has been dramatically advanced over several decades, from theory context to a general business and technology implementation. Especially in healthcare research, it is obvious to perceive the scrutinizing implementation of machine learning to warranty the rewarded benefits in early disease detection and service recommendation. Many practitioners and researchers have eventually recognized no absolute…
Read MoreSentiment Analysis on Utilizing Online Transportation of Indonesian Customers Using Tweets in the Normal Era and the Pandemic Covid-19 Era with Support Vector Machine
Online transportation in Indonesia is a new trend of transportation that is currently used among the lower to upper society. The change in behavior began in 2011 and is growing to this day, The comments that are growing on social media are very important for the online transportation company the negative comments lower the level…
Read MoreSupervised Machine Learning Based Medical Diagnosis Support System for Prediction of Patients with Heart Disease
Application in the field of medical development has always been one of the most important research areas. One of these medical applications is the early prediction system for heart diseases especially; coronary artery disease (CAD) also called atherosclerosis. The need for a medical diagnosis support system is to detect atherosclerosis at the earlier stages to…
Read MoreMachine Learning for Network Intrusion Detection Based on SVM Binary Classification Model
Recently, the number of connected machines around the worldwide has become very large, generating a huge amount of data either to be stored or to be communicated. Data protection is a concern for all institutions, it is difficult to manage the masses of data that are susceptible to multiple threats. In this work, we present…
Read MoreCustomer Satisfaction Recognition Based on Facial Expression and Machine Learning Techniques
Nowadays, Customer satisfaction is important for businesses and organizations. Manual methods exist, namely surveys and distributing questionnaires to customers. However, marketers and businesses are looking for quick ways to get effective and efficient feedback results for their potential customers. In this paper, we propose a new method for facial emotion detection to recognize customer’s satisfaction…
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