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Keyword: AccuracyApplication of EARLYBREAK for Line Segment Hausdorff Distance for Face Recognition
The Hausdorff distance (HD) is defined as MAX-MIN distance between two geometric objects for measuring the dissimilarity between two objects. Because MAX-MIN distance is sensitive with the outliers, in face recognition field, average Hausdorff distance is used for measuring the dissimilarity between two sets of features. The computational complexity of HD, and also average HD,…
Read MoreNeural Network-Based Fault Diagnosis of Joints in High Voltage Electrical Lines
In this paper a classification system based on a complex-valued neural network is used to evaluate the health state of joints in high voltage overhead transmission lines. The aim of this method is to prevent breakages on the joints through the frequency response measurements obtained at the initial point of the network. The specific advantage…
Read MoreThe Sound of Trust: Towards Modelling Computational Trust using Voice-only Cues at Zero-Acquaintance
Trust is essential in many interdependent human relationships. Trustworthiness is measured via the effectiveness of the relationships involving human perception. The decision to trust others is often made quickly (even at zero acquaintance). Previous research has shown the significance of voice in perceived trustworthiness. However, the listeners’ characteristics were not considered. A system has yet…
Read MoreA CNN-based Differential Image Processing Approach for Rainfall Classification
With the aim of preventing hydro-geological risks and overcoming the problems of current rain gauges, this paper proposes a low-complexity and cost-effective video rain gauge. In particular, in this paper the authors propose a new approach to rainfall classification based on image processing and video matching process employing convolutional neural networks (CNN). The system consists…
Read MoreEffects of Oversampling SMOTE in the Classification of Hypertensive Dataset
Hypertensive or high blood pressure is a medical condition that can be driven by several factors. These factors or variables are needed to build a classification model of the hypertension dataset. In the construction of classification models, class imbalance problems are often found due to oversampling. This research aims to obtain the best classification model…
Read MoreThe Role of KM in Enhancing AI Algorithms and Systems
Knowledge Management processes present a vital role in improving AI systems and algorithms. Many studies and reviews were carried out to examine the relationship between KM processes and AI systems. However, studies were focusing on specific methods and the impact on some AI algorithms, neglecting the role of other KM processes and how it may…
Read MoreBilateral Communication Device for Deaf-Mute and Normal People
Communication is a bilateral process and being understood by the person you are talking to is a must. Without the ability to talk nor hear, a person would endure such handicap. Given that hearing and speech are missing, many have ventured to open new communication methods for them through sign language. This bilateral communication device…
Read MoreFraud Detection Call Detail Record Using Machine Learning in Telecommunications Company
Fraud calls have a serious impact on telecommunications operator revenues. Fraud detection is very important because service providers can feel a significant loss of income. We conducted a fraud research case study on one of the operators that experienced fraud in 2009 and 2018. Call Detail Record (CDR) containing records of customer conversations such as…
Read MoreA Novel Representative k-NN Sampling-based Clustering Approach for an Effective Dimensionality Reduction-based Visualization of Dynamic Data
Visualization plays a crucial role in the exploratory analysis of Big Data. The direct visualization of Big Data is a challenging task and difficult to analyze. Dimensionality Reduction techniques extract the features in the context of visualization. Due to the unsupervised and non-parametric nature, most of the dimensionality reduction techniques are not evaluated quantitatively and…
Read MoreOffline Signature Recognition and Verification Using ORB Key Point Matching Techniques
An extensive work has been carried out in the field of human transcribe-verification and transcribe-recognition by extensive scholars across the globe from past decades. In order to demeanour immense experiments for considering the performance of the newly intended models and to substantiate the efficacy of the proposed model which is moderately required. This paper monologue…
Read MoreRisk Management: The Case of Intrusion Detection using Data Mining Techniques
Every institution nowadays relies on their online system and framework to do businesses. Such procedures need more attention due to the massive amount of attacks that occurs. These procedures have to go first through the management team of the institution, in order to prevent exploits of the attackers. Thus, the risk management can easily control…
Read MoreAutomated Abaca Fiber Grade Classification Using Convolution Neural Network (CNN)
This paper presents a solution that automates Abaca fiber grading which would help the time-consuming baling of Abaca fiber produce. The study introduces an objective instrument paired with a system to automate the grade classification of Abaca fiber using Convolutional Neural Network (CNN). In this study, 140 sample images of abaca fibers were used, which…
Read MoreNon Parallelism and Cayley-Menger Determinant in Submerged Localization
This research paper portraits the technique to determine location of submerged nodes with Cayley-Menger determinant and associated problems with non-parallel states. Cayley-Menger determinant is considered to be the usual means to determine the coordinates of the nodes with a single node where the plane of beacon i.e. beacon’s surfing plane and the plane created by…
Read MorePerformance Analysis of Joint Precoding and Equalization Design with Shared Redundancy for Imperfect CSI MIMO Systems
Analytical researches on a potential performance of multipath multiple-input multiple-output (MIMO) systems inspire the development of new technologies that decompose a MIMO channel into independent sub-channels on the condition of constrained transmit power. Moreover, in current studies of inter-symbol interference (ISI) MIMO systems, there is an assumption that channel state information (CSI) at receivers and/or…
Read MoreUniversity Students Result Analysis and Prediction System by Decision Tree Algorithm
The main assets of universities are students. The performance of students plays a vital role in producing excellent graduate students who will be the future viable leader and manpower in charge of a country’s financial and societal progress. The purpose of this research is to develop a “University Students Result Analysis and Prediction System” that…
Read MoreIntrusion Detection in Cyber Security: Role of Machine Learning and Data Mining in Cyber Security
In recent years, cyber security has been received interest from several research communities with respect to Intrusion Detection System (IDS). Cyber security is “a fast-growing field demanding a great deal of attention because of remarkable progresses in social networks, cloud and web technologies, online banking, mobile environment, smart grid, etc.” An IDS is a software…
Read MoreOrganizational, Social and Individual Aspect on Acceptance of Computerized Audit in Financial Audit Work
Auditors now can no longer rely on the old-fashioned way of auditing manually. More and more jobs, increasingly complex work environment, the demands of the times, accuracy and speed of work require auditors inevitably must adopt technology. This research began with our success as academics in the audit family. Related to Indonesia, a large country…
Read MoreA Novel Hybrid Method for Segmentation and Analysis of Brain MRI for Tumor Diagnosis
It is difficult to accurately segment brain MRI in the complex structures of brain tumors, blurred borders, and external variables such as noise. Much research in developing as well as developed countries show that the number of individuals suffering tumor of the brain has died as a result of the inaccurate diagnosis. The proposed article,…
Read MoreEvaluation of Uncertainty Measurement Calculation for Vector Network Analyzer From 300 kHz to 8.5 GHz
Increasing the telecommunications products that allow Vector Network Analyzer is becoming more common tools to measure the S-Parameter. It will be an absolute number from the S-Parameter measurements produced in real and imaginary, other words it is also known as the product of the calculation. The calculation findings do not include the systematic and random…
Read MoreReview on Smart Electronic Nose Coupled with Artificial Intelligence for Air Quality Monitoring
With the advent of the Internet of Things Technologies (IOT), smart homes, and smart city applications, E-Nose was created. Almost of gas sensors consisting the electronic nose system suffer from cross sensitivity and lack of selectivity. Coupling smart gas sensors with artificial intelligence algorithms can thus empower conventional gas sensing technologies and increase accuracy in…
Read MoreFace Recognition on Low Resolution Face Image With TBE-CNN Architecture
Face recognition in low resolution images has challenges in active research because face recognition is usually implemented in high resolution images (HR). In general, research leads to a combination of pre-processing and training models. Therefore, this study aims to classify low-resolution face images using a combination of pre-processing and deep learning. In addition, this study…
Read MoreNeural Network-based Efficient Measurement Method on Upside Down Orientation of a Digital Document
As many digital documents are required in various environments, paper documents are digitized by scanner, fax, digital camera and specific software. In the case of a scanned document, we need to check whether the document is right sided or upside down because the orientation of the scanned document is determined by the orientation in which…
Read MoreUnderstanding Human Perception of Vibrotactile Feedback in Walking and Running Tasks
Vibrotactile feedback is increasingly becoming an essential feedback component in several non-medical and medical areas. One area that vibrotactile feedback has not been explored as an intervention tool is in sports science. In addition, vibrotactile feedback lacks scientific evidence as a feedback mechanism within the sports world. A portable vibrotactile feedback system was developed to…
Read MoreOn the Ensemble of Recurrent Neural Network for Air Pollution Forecasting: Issues and Challenges
Time-series is a sequence of observations that are taken sequentially over time. Modelling a system that generates a future value from past observations is considered as time-series forecasting system. Recurrent neural network is a machine learning method that is widely used in the prediction of future values. Due to variant improvements on recurrent neural networks,…
Read MoreEnhancing an SDN Architecture with DoS Attack Detection Mechanisms
A Software Defined Network (SDN) architecture is characterized by decoupling the data plane and control plane. This feature enables the establishment of a programmable environ- ment in which the control plane acts under the data plane, managing and configuring the network over a standard protocol, such as OpenFlow. Although there are numerous benefits to the…
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