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No 31
Vol. 8 No. 3
Summer 2020
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Visible Light Communication (VLC) has emerged as a powerful technique for wireless communication systems. Providing high data rate and increasing capacity are the major problems in VLC. Recent evidence suggests that Multiple Input Multiple Output (MIMO) technique can offers improved data rates and increased link range. This paper describes the design and implementation of visible light communication system in indoor environment exploring the benefits of MIMO. The specific objective of this research was to implement a 4×4 Multiple Input (LEDs) Multiple Output (photodetectors)-VLC communication system, where a 16 white power LEDs in four arrays are setting up at transmitter and four RX modules are setting up at receiver side without the need for additional power or bandwidth as well as analyze a mathematical model for a VLC- 4×4 MIMO with different modes such as the suitable angles to cover the entire room. The research designs practically an electronic circuit for the transmitter and receiver with inexpensive components. The power distribution of different propagation modes is calculated for Single Input Single Output (SISO) and MIMO channels in typical room dimensions. The results in this paper indicate that the power is distributed uniformly for entire room when implemented VLC-MIMO as compared to VLC-SISO. Furthermore, a 4×4 MIMO implementing VLC is compared in term of BER vs. SINR with SISO communication system for both Line of Sight (LOS) and Non Line of Sight (NLOS) propagation modes. Comparing the two results of LOS and NLOS, it can be seen that a 4×4 MIMO implementing VLC for LOS perform better than the same system with NLOS due to decreasing in the received power resulted from the multipath effect.
lwaa abdulameer - Ahmed Hassan - Aliaa T. Obeed - Aya N. Dahir
DOI : 0
Keywords : MIMO ، SISO ، VLC ، Optical ، Indoor ، Power Distribution
Various studies have shown that markets are not separated and that fluctuations in different markets affect each other. Therefore, awareness of connectedness is needed for investors and policymakers for making appropriate decisions. The aim of this paper is to measure the dynamics connectedness of selected stock markets in the Middle East, oil markets, gold, the dollar index, and euro-dollar and pound-dollar exchange rates during the period February 2007 to August 2019 in networks with different weekly horizons. In this paper, we intend to evaluate the pairwise impact of crude oil and the Middle East stock markets, in particular on the Tehran Stock Exchange, and to analyze this variance using different time horizons. The results show that in all time horizons the variance of forecast error in most markets is due to the shocks themselves. The Saudi Arabian Stock Exchange has the most impact on other Middle Eastern stocks. The dynamics connectedness of the oil markets is remarkable, however, as the time horizon increases, dynamic connectedness between the two markets decreases and they are mostly affected by other markets, especially the Middle East stock exchanges except for Iran. Moreover, Iran stock market is an isolated market. About the gold market, there is a significant connectedness with the pound-dollar exchange rate and gold market; however, the dynamics connectedness of this market with other markets are not significant. Therefore, this market and Iran stock exchange can be used as a tool to hedge risk for investors.
Nasser Gholami - Teymor Mohammadi - Hamid Amadeh - Morteza Khorsandi
DOI : 0
Keywords : Oil Markets ، System Design ، Volatility ، Variance Decomposition Approach ، Dynamics Connectedness ، Network
Blockchain can reduce bureaucracy and increase the efficiency and performance of administrative processes through a platform possessing features and attributes such as storing and exchanging electronic messages in a decentralized environment and executing high level of security transactions and transparency, if used in government public service delivery. Many scholars believe that this distributed technology can bring new utilizations to a variety of industries and fields, including finance and banking, economics, supply chain, and authentication and increase economic productivity and efficiency dramatically by transforming many industries in the context of today's economy. The present study, presents the characteristics of the localized blockchain and e-currency conceptual model for the evolution of e-government services. It also examines the impact of the blockchain and e-currency model on the economy and electronic financial transactions as a viable, practical and constructive solution (rather than blocking and filtering of e-currency and blockchain). Ultimately designing a localized block chain and e-currency model, has played an effective role in exploit its high potential to speed up the administrative processes and reduce costs related to electronic transactions and payments in e-government and increase e-government revenues and ultimately it can speed up the customer service delivery and increase their satisfaction with the government.
Maryam Niknezhad - Sajjad Shokouhyar - Mehrzad Minouei
DOI : 0
Keywords : Blockchain ، E-Currency ، E-Government ، Distributed Ledger Technology ، Artificial Intelligence
Iteratively decoding and reconstruction of encoded data has been considered in recent decades. Most of these iterative schemes are based on graphical codes. Messages are passed through space graphs to reach a reliable belief of the original data. This paper presents a performance analysis of the Low-Density Parity-Check (LDPC) code design method which approach the capacity of the Additive White Gaussian Noise (AWGN) model for communication channels. We investigate the reliability of the system under Phase Shift Keying (PSK) modulation. We study the effects and advantages of variation in the codeword length, the rate of parity-check matrix of the LDPC codes, and the number of iterations in the Sum-Product Algorithm (SPA). By employing an LDPC encoder prior to the PSK modulation block and the SPA in the decoding part, the Bit Error Rate (BER) performance of the PSK modulation system can improve significantly. The BER performance improvement of a point-to-point communication system is measured in different cases. Our analysis is capable for applying any other iterative message-passing algorithm. The code design process of the communication systems and parameter selection of the encoding and decoding algorithms are accomplished by considering hardware limitations in a communication system. Our results help to design and select paramours efficiently.
Hadi Khodaei Jooshin - Mahdi Nangir
DOI : 0
Keywords : LDPC Codes ، BER Performance ، SPA ، Channel Decoding Algorithm ، Rate ، Channel Capacity
The Localization is the core element in Wireless Sensor Network WSN, especially for those nodes without GPS or BDS; leaning towards improvement, based on its effective and increased use in the past decade. Localization methods are thus very important for estimating the position of relative nodes in the network allowing a better and effective network for increasing the efficiency and thus increasing the lifeline of the network. Determining the current limitations in FA that are applied for solving different optimization problems is poor exploitation capability when the randomization factor is taken large during firefly changing position. This poor exploitation may lead to skip the most optimal solution even present in the vicinity of the current solution which results in poor local convergence rate that ultimately degrades the solution quality. This paper presents GEFIR (GenFire) algorithm to calculate position of unknown nodes for the fishermen in the ocean. The proposed approach calculates the position of unknown nodes, the proposed method effectively selects the anchor node in the cluster head to reduce the energy dissipation. Major benefits over other similar localization algorithms are a better positioning of nodes is provided and average localization error is reduced which eventually leads to better efficiency thus optimize the lifetime of the network for sailors. The obtained results depict that the proposed model surpasses the previous generation of localization algorithm in terms of energy dispersion and location estimation which is suitable for fishermen on the ocean bed.
Shruti Gupta - Dr Ajay Rana - Dr Vineet Kansal
DOI : 0
Keywords : Wireless Sensor Network ، localization ، firefly ، Genetic Algorithm
Farsi font detection is considered as the first stage in the Farsi optical character recognition (FOCR) of scanned printed texts. To this aim, this paper proposes an improved version of the speeded-up robust features (SURF) algorithm, as the feature detector in the font recognition process. The SURF algorithm suffers from creation of several redundant features during the detection phase. Thus, the presented version employs the redundant keypoint elimination method (RKEM) to enhance the matching performance of the SURF by reducing unnecessary keypoints. Although the performance of the RKEM is acceptable in this task, it exploits a fixed experimental threshold value which has a detrimental impact on the results. In this paper, an Adaptive RKEM is proposed for the SURF algorithm which considers image type and distortion, when adjusting the threshold value. Then, this improved version is applied to recognize Farsi fonts in texts. To do this, the proposed Adaptive RKEM-SURF detects the keypoints and then SURF is used as the descriptor for the features. Finally, the matching process is done using the nearest neighbor distance ratio. The proposed approach is compared with recently published algorithms for FOCR to confirm its superiority. This method has the capability to be generalized to other languages such as Arabic and English.
Zahra Hossein-Nejad - Hamed Agahi - Azar Mahmoodzadeh
DOI : 0
Keywords : Adaptivity ، Feature Extraction ، Font Detection ، Redundant Keypoint Elimination Method (RKEM) ، Speeded-Up Robust Features (SURF)
Cardiac resynchronization therapy (CRT) improves cardiac function in patients with heart failure (HF), and the result of this treatment is decrease in death rate and improving quality of life for patients. This research is aimed at predicting CRT response for the prognosis of patients with heart failure under CRT. According to international instructions, in the case of approval of QRS prolongation and decrease in ejection fraction (EF), the patient is recognized as a candidate of implanting recognition device. However, regarding many intervening and effective factors, decision making can be done based on more variables. Computer-based decision-making systems especially machine learning (ML) are considered as a promising method regarding their significant background in medical prediction. Collective intelligence approaches such as particles swarm optimization (PSO) algorithm are used for determining the priorities of medical decision-making variables. This investigation was done on 209 patients and the data was collected over 12 months. In HESHMAT CRT center, 17.7% of patients did not respond to treatment. Recognizing the dominant parameters through combining machine recognition and physician’s viewpoint, and introducing back-propagation of error neural network algorithm in order to decrease classification error are the most important achievements of this research. In this research, an analytical set of individual, clinical, and laboratory variables, echocardiography, and electrocardiography (ECG) are proposed with patients’ response to CRT. Prediction of the response after CRT becomes possible by the support of a set of tools, algorithms, and variables.
Mohammad Nejadeh - Peyman Bayat - Jalal Kheirkhah - Hassan Moladoust
DOI : 0
Keywords : Cardiac resynchronization therapy ، Neural Networks ، Particle swarm optimization ، HESHMAT_CRT dataset ، Machine Learning ،

About Journal

Affiliated to :ICT Research Institute of ACECR
Manager in Charge :Habibollah Asghari
Editor in Chief :Masood Shafiei
Editorial Board :
Abdolali Abdipour
Mahmoud Naghibzadeh
Zabih Ghasemlooy
Mahmoud Moghavemi
Aliakbar Jalali
Ramazan Ali Sadeghzadeh
Hamidreza Sadegh Mohammadi
Saeed Ghazimaghrebi
Shaban Elahi
Alireza Montazemi
Ali Mohammad Djafari
Rahim Saeidi
Shohreh Kasaei
Mehrnoush Shamsfard
ISSN :2322-1437
eISSN :2345-2773

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