Jasmin Kevric

Jasmin Kevric
International BURCH University · Department of Electrical and Electronics Engineering

PhD

About

66
Publications
18,454
Reads
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1,326
Citations
Introduction
My main research interests are machine learning, pattern recognition and biomedical signal with a recent focus on big-data. My work spans both theoretical an experimental aspects in Biomedical Engineering. I am a strong believer in inter-disciplinary research and much of my work is collaborative with experts from fields other than machine learning, data mining and pattern recognition. Currently I am working on epileptic seizure prediction and detection and Brain Computer Interface.
Additional affiliations
September 2012 - October 2015
International BURCH University
Position
  • Senior Researcher
September 2012 - present
International BURCH University
Position
  • Senior Teaching Assistant
Description
  • Calculus 1, Calculus 2, Telecommunications 1, Telecommunications 2, Circuit Theory 2, Fundamentals of Biomedical Engineering, Signals and Systems
August 2010 - September 2012
International BURCH University
Position
  • Systems Engineer
Education
September 2012 - June 2015
International BURCH University
Field of study
  • Electrical and Electronics Engineering
September 2010 - July 2012
International BURCH University
Field of study
  • Information Technologies
September 2007 - September 2010
University of Sarajevo
Field of study
  • Electrical and Electronics Engineering

Publications

Publications (66)
Article
Full-text available
In this paper we describe the effect of Multiscale Principal Component Analysis (MSPCA) de-noising method in terms of epileptic seizure detection. In addition, we developed a patient-independent seizure detection algorithm using Freiburg EEG database. Each patient contains datasets called "ictal" and "interictal". Window length of 16 s was applied...
Article
Full-text available
In this paper, we developed a combining classifier model based on tree-based algorithms for network intrusion detection. The NSL-KDD dataset, a much improved version of the original KDDCUP’99 dataset, was used to evaluate the performance of our detection algorithm. The task of our detection algorithm was to classify whether the incoming network tra...
Article
In this study, three popular signal processing techniques (Empirical Mode Decomposition, Discrete Wavelet Transform, and Wavelet Packet Decomposition) were investigated for the decomposition of Electroencephalography (EEG) Signals in Brain Computer Interface (BCI) system for a classification task. Publicly available BCI competition III dataset IVa,...
Article
Full-text available
The aim of this study is to establish a hybrid model for epileptic seizure detection with genetic algorithm (GA) and particle swarm optimization (PSO) to determine the optimum parameters of support vector machines (SVMs) for classification of EEG data. SVMs are one of the robust machine learning techniques and have been extensively used in many app...
Article
This study proposes a new model which is fully specified for automated seizure onset detection and seizure onset prediction based on electroencephalography (EEG) measurements. We processed two archetypal EEG databases, Freiburg (intracranial EEG) and CHB-MIT (scalp EEG), to find if our model could outperform the state-of-the art models. Four key co...
Article
Despite the fact that technology is improving day by day and that the medical devices (MDs) are being constantly upgraded, their malfunction is not a rare occurrence. The aim of this research is to develop an expert system that can predict whether the device will satisfy functional and safety requirements during a regular inspection. This expert sy...
Article
Age estimation has become inordinately significant for human beings for many reasons, such as detecting legal and criminal responsibility and other social events like a marriage license, birth certificate, etc. This paper aims to decide on the most desirable machine learning algorithm (from conventional machine learning algorithms to deep learning)...
Chapter
Due to more radical escalation in essentials for goods exchange an increase in the traffic is observed which is proportional to the roadway breakdown. Research conducted is to measure the traffic and erosion proportions. Digital data collection is in the form of a video file. From audiovisual file foundations information concerning the number of ve...
Book
This book presents the innovative and interdisciplinary application of advanced technologies. It includes the scientific outcomes and results of the conference 12th Day of Bosnian-Herzegovinian American Academy of Art and Sciences held in Mostar, Bosnia, and Herzegovina, June 24-27, 2021. The latest developments in various fields of engineering hav...
Article
The magnitude of soft error rate (SER) of integrated circuits (ICs) utilized in space missions is jeopardized due to the inconsistent intensity of radiation exposure. To protect critical electronic elements and ensure desired system performance, it is necessary to establish the real-time detection of space particle events (SPE). This research study...
Article
Full-text available
With the exponential growth of the amount of data being generated, stored and processed on a daily basis in the machine learning, data analytics and decision-making systems, the data preprocessing established itself as the key factor for building reliable high-performance machine learning models. One of the roles in preprocessing is variable reduct...
Article
Full-text available
This research paper deals with the problem of Metal-Oxide Surge Arrester (MOSA) condition monitoring and a new methodology in surge arrester monitoring and diagnostics is presented. A machine learning algorithm (back propagation regression) is used to estimate the non-linearity coefficient of the surge arrester, based on operating voltage and leaka...
Chapter
Heart diseases are the number one cause of death all over the world. Many deaths are caused due to late detection of heart diseases. During the process of heart sound recording, beside heart sound, environment noise is being recorded too. In this work signal denoising was performed using wavelet denoising method. Furthermore, parameter values are c...
Article
Full-text available
Brain tumors diagnosis in children is a scientific concern due to rapid anatomical, metabolic, and functional changes arising in the brain and non-specific or conflicting imaging results. Pediatric brain tumors diagnosis is typically centralized in clinical practice on the basis of diagnostic clues such as, child age, tumor location and incidence,...
Chapter
In grid-connected applications, grid-connected converters require a precise and accurate detection of frequency, amplitude, and a phase angle of a grid voltage. For estimation of these grid parameters, a well-known method, Phase-locked loop (PLL) can be used. There are different types of PLLs and all of them have advantages and disadvantages. Most...
Chapter
In grid connected applications, grid-connected converters require a precise and accurate detection of frequency, an amplitude and a phase-angle of a grid voltage. For estimation of these grid parameters, a well-known method, Phase-locked loop (PLL) can be used. There are different types of PLLs and all of them have advantages and disadvantages. Mos...
Article
Based on previous research on energy efficiency of the buildings, particularly their cooling load capabilities we will develop a collection of machine learning methods for detecting buildings with best cooling load capabilities. This collection will study the influence of 8 input variables (relative compactness, surface area, wall area, roof area,...
Article
Full-text available
There are numerous algorithms and solutions for car or object detection as humanity is aiming towards the smart city solutions. Most solutions are based on counting, speed detection, traffic accidents and vehicle classification. The mentioned solutions are mostly based on high-quality videos, wide angles camera view, vehicles in motion, and are opt...
Article
Security is one of the most actual topics in the online world. Lists of security threats are constantly updated. One of those threats are phishing websites. In this work, we address the problem of phishing websites classification. Three classifiers were used: K-Nearest Neighbor, Decision Tree and Random Forest with the feature selection methods fro...
Article
Full-text available
This research presents the epileptic focus region localization during epileptic seizures by applying different signal processing and ensemble machine learning techniques in intracranial recordings of electroencephalogram (EEG). Multi-scale Principal Component Analysis (MSPCA) is used for denoising EEG signals and the autoregressive (AR) algorithm w...
Chapter
Prostate cancer is a widespread disease among the male population. Its early diagnosis and prognosis are challenging tasks for clinical researchers due to the lack of very precise, fast and human error free diagnostic method. The purpose of this research is to develop a novel prototype of clinical management in diagnosis and management of patients...
Chapter
Bees immensely contribute to mankind. Over the years, bees have performed a task that is vital to the survival of agriculture and pollination. One third of our global food supply is depends on bees’ pollination, which simply means that bees keep crops and plants alive. If bees were to go extinct, mankind would not survive because the food we eat de...
Chapter
Diagnosing ovarian cancer is a medical challenge to clinical researchers. This study aims to develop a novel prototype of clinical management in diagnosis and management of patients with ovarian cancer. Various classification algorithms can be applied to cancer databases to devise methods that can predict cancer manifestation. Various methods, howe...
Chapter
Most common pathologic conditions in the alveolar bone derived from necrotic dental pulp are periapical inflammatory lesions (periapical granuloma and periapical cyst). The early diagnosis of lesions of the oral cavity is challenging for clinical practitioners. This research implements a computer-aided diagnostic system for classification of periap...
Chapter
This paper presents methods for prediction of the power output of the combined cycle power plant (CCPP) with a full load. A dataset comprising 9568 samples include measurements of ambient temperature (AT), atmospheric pressure (AP), relative humidity (RH), exhaust steam pressure, i.e. vacuum (V) and power output of the CCPP (EP). The research was d...
Chapter
Diabetes Mellitus type-2 is one of the diseases of a modern age treated as a serious illness due to its symptoms in later stages, consequences if left untreated and its complexity in terms of detection, diagnosis, and prognosis widely spread among the Pima Indian population. The process of detecting the diabetes will require analysis of the data, p...
Article
Localization of epileptogenic foci is an essential phase in surgical treatment planning using the earliest time detection of the seizure onset in the recordings of electroencephalogram (EEG). These recordings are defined as the areas of the brain which can be surgically removed to reach control of seizure. The characteristics of the brain area affe...
Conference Paper
In this contribution, a number of Machine Learning Techniques (MLT), such as Rotation Forest, Random Forest, Bagging, Voting, Ada Boost, are compared by terms of epileptic seizure prediction using Hadoop environment. Based on obtained results, considered MLTs are ranked and used to establish patient individualized approach for epileptic seizure pre...
Conference Paper
Assessment of skeletal maturity is typical strategy applied in clinical pediatrics today. The main goal of adequate bone age assessment is to determine endocrinology and growth structural disorders by comparing the bone and chronological patient age. There are several methods developed to estimate bone maturity, but Greulich-Pyle and Tanner-Whiteho...
Article
A car price prediction has been a high-interest research area, as it requires noticeable effort and knowledge of the field expert. Considerable number of distinct attributes are examined for the reliable and accurate prediction. To build a model for predicting the price of used cars in Bosnia and Herzegovina, we applied three machine learning techn...
Chapter
Up to now, primary way of producing honey relied heavily on the experience and “gut feeling” of the individual beekeepers, who are utilizing traditional agricultural methods of placing the hives at locations that are predicted to be suitable for higher honey gain by visually inspecting the hives. HaBEEtat mission is to enable more efficient honey p...
Chapter
This paper presents methods for prediction of energy usage of different appliances in homes. Dataset comprising 14804 samples include measurements of weather from a nearby airport station, temperature and humidity sensors from a wireless network and recorded energy use of lighting fixtures. These measurements are sorted into 32 features, from which...
Chapter
With the increase in Internet use throughout the world, expansion in network security is indispensable since it decreases the chances of privacy spoofing, identity or information theft and bank frauds. Two of the most frequent network security breaches involve phishing and spam emails as they are an easy way to pass a virus or a malicious site, whi...
Conference Paper
The regulation of functions such as respiratory or heart rate in human body as well as the control of motor movements are under the control of nervous system. As these actions and correlated tasks are directly influenced by the brain, the brain monitoring gives the possibility to differentiate the tasks, enabling at the same time the prediction of...
Article
Full-text available
The regulation of functions such as respiratory or heart rate in human body as well as the control of motor movements are under the control of nervous system. As these actions and correlated tasks are directly influenced by the brain, the brain monitoring gives the possibility to differentiate the tasks, enabling at the same time the prediction of...
Article
Full-text available
Cancer classification is one of the main steps during patient healing process. This fact enforces modern clinical researchers to use advanced bioinformatics methods for cancer classification. Cancer classification is usually performed using gene expression data gained in microarray experiment and advanced machine learning methods. Microarray experi...
Article
Abstract The problem of nonperforming loans is one of the biggest problems in the banking sector. In order to mitigate this problem, it is necessary to improve the methods of credit risk assessment. One way to minimize credit risk is to improve the assessment of the creditworthiness of the applicant. In order to make a more accurate assessment, man...
Article
The main aim of the study is to develop a real-time epilepsy prediction approach by using the ensemble machine learning techniques that might predict offline seizure paradigms. The proposed seizure prediction algorithm is patient-specific since generalization showed no satisfactory results in our previous studies. The algorithm is tested on CHB-MIT...
Article
Objective of this study is to parallelize and apply distributed system paradigm to the whole process of EEG signal analysis including the signal segmentation, signal processing, feature extraction, and classification. This study is focused only on time required for execution of every signal processing part within real-time epileptic seizure predict...
Article
Full-text available
This paper presents a new algorithm for distribution system reconstruction planning based on Mamdani type fuzzy inference and Bellman - Zadeh multi criteria decision making method. The proposed algorithm takes system attributes as inputs (number of customers served by renewed infrastructure, energy losses, power demand and cost of investment) and r...
Chapter
This paper shows electroencephalograph (EEG) controlled robotic arm based on Brain–computer interfaces (BCI). BCIs are systems that enable bypassing conventional methods of communication (i.e., muscles and thoughts) and provide direct communication and control between the human brain and physical devices using the power of the human brain. The main...
Chapter
Recently research on Human Activity Recognition (HAR) has been reported on systems showing good overall recognition performance. A machine learning based HAR classifier was proposed in several experimental setups. A public domain dataset comprising 165,633 samples was used for this purpose. Models of machine learning algorithms are built up using A...
Chapter
Detection of Parkinson Disease by Voice Signal is based on noninvasive method for disease detection. Here we used Speech Dataset of sound records which has been shown as most effective up to now. In order to detect presence of disease by using different classifiers. At the end accuracy of each of them have been calculated and compared.
Chapter
This paper presents significantly facilitated ways of controlling an electric wheelchair using the power of the human brain for persons getting motor neuron disease (MND) and the difference in efficiency and accuracy between. The proposed BCI was developed in .NET framework which uses NeuroSky Mindwave’s single dry electrode as the only way of comm...
Chapter
The heart sound signal (heartbeat) recorded from normal subjects usually contains two separate tones, S1 and S2. In addition, an auscultation technique used to provide physicians with accurate and objective interpretation of heart sounds can be used to detect four sounds, namely, S1, S2, S3, and S4, during the heart cycle. In this project, we propo...
Chapter
Chronic kidney disease (CKD) is a global public health problem, affecting approximately 10% of the population worldwide. Yet, there is little direct evidence on how CKD can be diagnosed in a systematic and automatic manner. This paper investigates how CKD can be diagnosed by using machine learning (ML) techniques. ML algorithms have been a driving...
Conference Paper
Full-text available
This research implements decision tree classifiers and artificial neural network to predict whether the patient will live with ovary cancer or not. Dataset was obtained from Danish Cancer Register and contains five Input parameters. Dataset contains some missing values and a noticeable improvement in accuracy was detected after removing them. Three...
Poster
Full-text available
INTRODUCTION: Breast cancer is the most frequently diagnosed cancer and the leading cause of cancer death among females, accounting for 23% of the total cancer cases and 14% of total cancer deaths. Weka is a collection of machine learning algorithms for data mining tasks, and contains tools for data pre-processing, classification, and visualization...
Conference Paper
It is estimated that there are millions of people with epilepsy around the world. Seizure detection and prediction systems are built to improve lifestyle of patients. Closed-loop systems are designed to predict and detect seizures and inform patient and caretakers. Ideally, wireless technologies are used in order not to interfere with patient's lif...
Article
Full-text available
Uncertainty is one of the most important factors which contributes to the complexity of the power system operation and management. This paper presents some of the most important uncertainty modelling techniques and compares their advantages and disadvantage. In particular, this paper focuses on identification, classification and comparison of uncer...
Conference Paper
Nonintrusive load monitoring (NILM) is a procedure for the analysis of the changes in the power (current and voltage) that goes into households and classifying the appliances used in the house according to their individual energy consumption. Utility companies use smart electric meters accompanied with NILM to examine the particular uses of electri...
Conference Paper
Full-text available
Phishing is one among the luring strategies utilized by phishing artist in the aim of abusing the personal details of unsuspected clients. Phishing website is a counterfeit website with similar appearance, but changed destination. The unsuspected client post their information thinking that these websites originate from trusted financial institution...
Article
Full-text available
E-mail still proves to be very popular and an efficient communication tool. Due to its misuse, however, managing e-mails problem for organizations and individuals. Spam, known as unwanted message, is an example of misuse. Specifically, spam is defined as the arrival of unwelcomed bulk email not being requested for by recipients. This paper compares...
Article
Full-text available
This paper presents the practical implementation of the motor imagery BCI system using MATLAB GUI. EEG signals were recorded usingMindwave Mobile Headset from one subject for two motor imagery tasks: right hand and left hand. The offline analysis showed decent performance of the combination between MSPCA de-noising of EEG signals and statistical fe...
Conference Paper
Full-text available
In this paper, we developed a model for classification of EEG signals. The aim of the study is to determine whether this model can be used for epileptic seizure prediction if “pre-ictal” stages were successfully detected. We analyzed long-term Freiburg EEG data. Each of 21 patients contains datasets called “ictal” (seizure) and “inter-ictal” (seizu...

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Projects

Projects (7)
Project
Days of BHAAAS in Bosnia and Herzegovina
Archived project
The aim of this project to develop a simple prototype of a wireless monitoring device which will measure the heart rate of the patient. The device will also publish the graph of the heart rate on the WAN network. These devices should be used in the hospital rooms so that the physician can always check the condition of the patient's heart and thereby, executes interventions in alarm situations.