STATISTICS OF SIGNAL TO INTERFERENCE RATIO PROCESS AT OUTPUT OF MOBILE-TO-MOBILE RAYLEIGH FADING CHANNEL IN THE PRESENCE OF COCHANNEL INTERFERENCE

Dual-hop cooperative communications in interference-limited Rayleigh fading channel will be investigated in this paper. The paper considers the first- and second-order statistics of the signal to interference ratio process at the input of the destination mobile station. The exact closed-form expressions for the first-order statistical measures, the probability density function and cumulative distribution function, will be derived. We will also derive approximate closed form expressions for the second-order statistics, the level crossing rate and the average fade duration. The obtained theoretical results will be verified by the Monte-Carlo simulations

α-Q fading model: Statistical analisis of the first order

In this paper starting from the well known Nakagami-q fading model we are proposing its improvement by introducing an additional flexibility, in the form of a parameter, which is power of the modulus of complex Gaussian process, in order to provide better matching between theoretical results and experimental values measured in a real environment. Within this paper, we will also present the first order statistical analysis of the proposed α-q model. In this paper, a statistical analysis of the first order of the new α-q model that includes derived analytical expressions for: probability density function, cumulative distribution function, moment n-th order are presented, variance and moment genereting function of one α-q process. Results for the probability density function and cumulative distribution function α-q process are graphically presented

Outage probability analysis in shadowed fading channel with multiple cochannel interferencesac

In wireless communication systems received signal may suffer from the both multipath fading (fading) and shadowing. In this paper, ascertaining on the suitability of the Weibull distribution to model fading channel and by utilizing the fact that the gamma distribution is more convenient for manipulation than the lognormal distribution, shadowed fading channel is modeled as the Weibull-gamma. The closed-form expressions for the probability density function (PDF) and cumulative distribution function (CDF) of the received signal are derived in terms of Bessel's and Meijer's G-functions, respectively. The synergy between the Weibull-gamma and the Weibull-lognormal model is explored and established by calculating the outage probability (Pout) and average bit error probability (ABEP). This is followed by the analysis carried out for the both fixed and random number of gamma shadowed Nakagami-m cochannel interferences (CCIs) in interference-plus-noise and interference-limited environment. The proposed mathematical analysis is complimented by various numerical results

Performance Analysis of an IEEE 802.15.4 Network Operating Under κ–μ Fading, Interference and AWGN

IEEE 802.15.4 standard is widely used in the field of low-power, low-cost and low-bit rate communications. In this paper, we analyze performance of an IEEE 802.15.4 network operating in 2450 MHz ISM (Industry, Science and Medicine) band in the presence of κ–μ fading, interference and additive white Gaussian noise. A novel analytical expression for the chip error probability evaluation of an IEEE 802.15.4 wireless channel has been derived. Its correctness is validated by Monte Carlo simulations. Capitalizing on the derived CEP expression, the symbol error probability and the packet error probability are also evaluated for various values of the κ–μ fading channel parameters and signal-to-interference-to-noise ratios

ENERGETSKA EFIKASNOST SOLARNIH KOLEKTORA I NJIHOV UTICAJ NA ŽIVOTNU SREDINU

This paper compares the energy efficiency and environmental impact of solar collectors versus individual furnaces for the purpose of heating sanitary water in a five-person household. The heat calculation results from the water heating collectors are proposed, along with the necessary number of solar collectors for the aforementioned household in Niš month by month. The amount of lignite needed to calculate the thermal power of lignite for heating water is shown, along with the calculations' results for the mass value of the pollutants released during lignite's complete combustion (kJ/kg) and their retention times in the atmosphere for a day and a month, from April to November.Rad se bavi određivanjem energetske efikasnosti i uticajem solarnih kolektora na životnu sredinu, u odnosu na individualne peći za zagrevanje sanitarne vode u petočlanom domaćinstvu. Dati su rezultati izračunavanja toplote koja se dobija pomoću kolektora za zagrevanje vode, kao i potreban broj solarnih kolektora za domaćinstvo u Nišu po mesecima. Prikazani su rezultati izračunavanja potrebne količine lignita za zagrevanje vode, data je toplotna moć lignita kao i rezultati izračunavanja vrednosti mase emitovanih zagađujućih supstanci koje nastaju pri potpunom sagorevanju lignita (kJ/kg) i vreme zadržavanja u atmosferi za dan, mesec u periodu od aprila do novembra

Multi-Agent System Observer: Intelligent Support for Engaged E-Learning

Moodle is a widely deployed distance learning platform that provides numerous opportunities to enhance the learning process. Moodle’s importance in maintaining the continuity of education in states of emergency and other circumstances has been particularly demonstrated in the context of the COVID-19 virus’ rapid spread. However, there is a problem with personalizing the learning and monitoring of students’ work. There is room for upgrading the system by applying data mining and different machine-learning methods. The multi-agent Observer system proposed in our paper supports students engaged in learning by monitoring their work and making suggestions based on the prediction of their final course success, using indicators of engagement and machine-learning algorithms. A novelty is that Observer collects data independently of the Moodle database, autonomously creates a training set, and learns from gathered data. Since the data are anonymized, researchers and lecturers can freely use them for purposes broader than that specified for Observer. The paper shows how the methodology, technologies, and techniques used in Observer provide an autonomous system of personalized assistance for students within Moodle platforms

Robust enhancement of fingerprint images obtained by ink method

A method for fingerprint enhancement in the frequency domain based on directional log-Gabor filtering is proposed. Experimental results show that the method can successfully enhance even low-quality fingerprint images obtained by the ink method, outperforming standard, well-known techniques including Gabor filtering

Improving minutiae extraction in fingerprint images through robust enhancement

The paper describes in detail the skeletonbased algorithm for the automatic extraction of fingerprint minutiae. These distinguishing characteristics are used both in the manual and automatic (AFIS-Automatic Fingerprint Identification System) fingerprint matching process for identification purpose. Proposed enhancement algorithm, utilizing multiscale orientation field estimation along with Log-Gabor filters in frequency domain, significantly improves fingerprint image quality, resulting in reduced number of falsely minutiae extracted. Results of experiments conducted on collections of fingerprint images show competitive performance of proposed algorithm

Different methods for fingerprint image orientation estimation

Orientation field as a global feature of fingerprints is very important in automatic fingerprint identification systems (AFIS). In fact the overall performance of fingerprint recognition process largely depends on it's accurate estimation. The subject of this paper is to present different methods for fingerprint image orientation estimation, including novel one based on multiscale approach

Influence of Image Enhancement Techniques on Effectiveness of Unconstrained Face Detection and Identification

In a criminal investigation, along with processing forensic evidence, different investigative techniques are used to identify the perpetrator of the crime. It includes collecting and analyzing unconstrained face images, mostly with low resolution and various qualities, making identification difficult. Since police organizations have limited resources, in this paper, we propose a novel method that utilizes off-the-shelf solutions (Dlib library Histogram of Oriented Gradients-HOG face detectors and the ResNet faces feature vector extractor) to provide practical assistance in unconstrained face identification. Our experiment aimed to establish which one (if any) of the basic image enhancement techniques should be applied to increase the effectiveness. Results obtained from three publicly available databases and one created for this research (simulating police investigators’ database) showed that resizing the image (especially with a resolution lower than 150 pixels) should always precede enhancement to improve face detection accuracy. The best results in determining whether they are the same or different persons in images were obtained by applying sharpening with a high-pass filter, whereas normalization gives the highest classification scores when a single weight value is applied to data from all four databases