Periodicals of Engineering and Natural Sciences (PEN - International University of Sarajevo)
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1290 research outputs found
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GSM Based Gas Leak Monitoring System
Full text linkThis paper used a safe wireless module to detect a gas leakage. The module is household use application where home fires or Liquefied Petroleum Gas (LPG) are classified as the reason of the disasters. The LPG is considered as the most inflammable gases that can ignite fires even in the far distances where gas leak exists. The module can be applied in several places particularly in the fabrications that depend mainly on LPG gas to manage their works. According to the facilities offered by this work, the whole module is functionally separated to perform two tasks identified by gas leak monitoring and the precautions taken accordingly. The module reads the gas sensor in a proposed environment to discover whether gas concentration exceeds a specified range. The system will be activated once the module detects that the gas concentration is altered, and accordingly the control action turns the alarm system alongside with air puller device ON, and sends a warning SMS to a certain recipient using GSM module
Assessement of Managers Satisfaction regarding the HR Function in developing countries through a quantitative research method: The Moroccan context
Full text linkThis paper presents a practice-oriented study that aims to reveal challenges faced by HR managers within developing countries through studying the Moroccan context. Indeed, we conducted a quantitative inquiry that evaluates the HR function performance based on Ulrich model. This study revealed the existence of several difficulties in terms of implementing a suitable HR function within industrial companies. The reliability of the inquiry was proven by calculating Cronbach Alphas. This research has important implications for HR professionals and strategic leaders that are especially interested in developing countries which will account for nearly 60% of global GDP in 2030, according to new estimates (OECD, 2018)
Review of neural networks and particle swarm optimization contribution in intrusion detection
Full text linkThe progress in the field of computer networks and internet is increasing with tremendous volume in recent years. This raises important issues concerning security. Several solutions emerged in the past, which provide security at the host or network level. These traditional solutions like antivirus, firewall, spyware and authentication mechanism provide security to some extents but they still face the challenges of inherent system flaws and social engineering attacks. Some interesting solution emerged like intrusion detection and prevention systems but these too have some problems like detecting and responding in real time and discovering novel attacks. Because the network intrusion behaviors are characterized with uncertainty, complexity and diversity, an intrusion detection method based on neural network and Particle Swarm Optimization (PSO) algorithm is widely used in order to address the problem. This paper gives an insight into how PSO and its variants can be combined with various neural network techniques in order to be used for anomaly detection in network intrusion detection system in order to enhance the performance of intrusion detection system
Hair analysis based on medical history and spatial-temporal data
Full text linkOver the course of time, machine learning has improved the data analysis technique such as face detection and recognition. Many machine learning researches have been implemented in medical treatments. This concept which is proposed is inspired from different aspects of hair scalp and other factors. Spatial-temporal data is very useful in weather forecasting and satellite image analysis. This technique is implemented to capture necessary data from hair follicle images. Hair is also a subject of human body. There are many factors which can be used to determine health of hair. All these factors including spatial-temporal images, gender, age and hair style are used to predict health of hair. This paper presents machine learning algorithm for analysis of medical data for determining health of hair. We use the SVM (support-vector machines) model classifier for analysis of data. After that, we get values such as short, straight, wavy and curly.In this paper, J48 Algorithms were used to obtain an accurate result compared with other algorithms.J48 with bagging is creating different decision trees for same data that why it is given more accurate results, J48 algorithms will split continuous values through using threshold. This paper 1066 samples were tested using cross validation technique, according to the test, it is found 87.14 % was a correctly classified and 12.85 % was incorrectly classifier. So at the end we get a real time performance is 89.5 %. This paper proves the compatible between hair style and Age-Gender
Project management information system effect decision making in the construction industry of Iraq
Full text linkThis study was intended to theorize fresh conceptual links between two common project management studies, the PMIS and paradigms of decision-making. This research examined the pragmatic conceptual connection between project management information system and low / high decision-making. The findings indicate that the function of Project Management Information Systems negotiation information overload and design overload for decision-making has been practiced and monitored. Overall, this provides a nice review of Western theories and ideas in the distinctive eastern framework
Study and Analysis of Intrusion Detection System Using Random Forest and Linear Regression
Full text linkThe cyber security is the challenging job in present network system. There are number of existing Intrusion Detection Systems are available to overcome the issues, in this paper we proposed the linear regression and random forest technique is used. The latest UNSW-NB15 dataset is used for analyzing the proposed methods. Selecting significant features and removing irrelevant features by using proposed learning methods as well as identifying the best method by evaluating the results obtained
A Reduced Size Look Up Table for Sinusoidal Wave Generation in Digital Modulators Applications
Full text linkDigital Modulators is one of the areas that have received great attention recently due to the tremendous developments in Radio Frequency (RF) frond ends and system on chips (soc) architecture in general. Building any kind of digital modulators using soc type Field Programmable Gate Array (FPGA), like ZYBO, depends heavily on how the carrier signal got generated since it consumes a lot of utilization recourses. This paper presents a new method of generating sinusoidal carrier signal based on Direct Digital Synthesizer (DDS) concept using small size Look Up Table (LUT). 64 samples of a quarter period of the sine wave signal were stored in a fixed point format in small LUT to generate the carrier at the desire frequency. The paper used Very high speed integrated circuit Hardware Descriptive Language (VHDL) without the help of DSP Builder Tools or XILINX System Generator. The suggested method was tested by building simple modulators like On-Off Keying (OOK) and Amplitude Shift Keying (ASK). Low utilization was achieved as compared to other implementation methods
Intelligent Vision-based Navigation System for Mobile Robot: A Technological Review
Full text linkVision system is gradually becoming more important. As computing technology advances, it has been widely utilized in many industrial and service sectors. One of the critical applications for vision system is to navigate mobile robot safely. In order to do so, several technological elements are required. This article focuses on reviewing recent researches conducted on the intelligent vision-based navigation system for the mobile robot. These include the utilization of mobile robot in various sectors such as manufacturing, warehouse, agriculture, outdoor navigation and other service sectors. Multiple intelligent algorithms used in developing robot vision system were also reviewed
Parameter identification of PMSM using EKF with temperature variation tracking in automotive applications
Full text linkPermanent magnet synchronous machine is widely used for electric vehicles traction because of its high power density and its efficiency on a large flux weakening range. This paper focuses in particular on the estimation of PMSM parameters using EKF, we present a study assessing the temperature variations impact on the behavior of PMSM motor, and therefore we propose to estimate the temperature-dependent parameters. The main contribution in this work is an effective method for estimating parameters or their temperature variation, makes it possible to study and to avoid performance degradation by tracking and adapting the parameters in torque observer in order to find the same performance at any temperature and can be also used for thermal monitoring, which allows for better availability of motor, without causing damage, however, the knowledge of degradation mechanisms also gives insight for the design of this machine. Nowadays, there are essentially maps of reference currents according to the torque and speed that are used by car manufacturers and no account is then given of the parameter variations. The effectiveness of the proposed estimation method verified by both simulation and experiment
Semiautomatic Detection of Cardiac Diseases employing Dual Tree Complex Wavelet Transform
Full text linkElectrocardiogram (ECG) contains lot of information which can be utilized for a mechanism to detect cardiac abnormalities. The ECG signal is too sensitive to various types of noises as it is of low frequency and has weak amplitude, these noises reduce the diagnostic accuracy and may lead to the incorrect decision of the clinician. So, denoising of ECG signal is an essential requirement for an accurate detection of Heart disease. In this paper, a Dual-Tree Complex Wavelet Transform technique (DTCWT) is presented to denoise the noisy ECG signal and to extract the Principal features followed by implementation of Peak Detection Algorithm. The performance is evaluated on the basis of performance metrics and an increase in SNR is achieved using the technique. With the proposed technique, calculated heart rate is in consensus with the gold standard of the various bench mark databases used and accurate heart disease was determined