S. Hamed Javadi | Ghent University (original) (raw)

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Papers by S. Hamed Javadi

Research paper thumbnail of Data Fusion of XRF and Vis-NIR Using Outer Product Analysis, Granger–Ramanathan, and Least Squares for Prediction of Key Soil Attributes

Remote Sensing

Visible-near-infrared (vis-NIR) and X-ray fluorescence (XRF) are key technologies becoming pervas... more Visible-near-infrared (vis-NIR) and X-ray fluorescence (XRF) are key technologies becoming pervasive in proximal soil sensing (PSS), whose fusion holds promising potential to improve the estimation accuracy of soil attributes. In this paper, we examine different data fusion methods for the prediction of key soil fertility attributes including pH, organic carbon (OC), magnesium (Mg), and calcium (Ca). To this end, the vis-NIR and XRF spectra of 267 soil samples were collected from nine fields in Belgium, from which the soil samples of six fields were used for calibration of the single-sensor and data fusion models while the validation was performed on the remaining three fields. The first fusion method was the outer product analysis (OPA), for which the outer product (OP) of the two spectra is computed, flattened, and then subjected to partial least squares (PLS) regression model. Two versions of OPA were evaluated: (i) OPA-FS in which the full spectra were used as input; and (ii) OP...

Research paper thumbnail of Data Fusion of XRF and Vis-NIR Using Outer Product Analysis, Granger–Ramanathan, and Least Squares for Prediction of Key Soil Attributes

Remote Sensing

Visible-near-infrared (vis-NIR) and X-ray fluorescence (XRF) are key technologies becoming pervas... more Visible-near-infrared (vis-NIR) and X-ray fluorescence (XRF) are key technologies becoming pervasive in proximal soil sensing (PSS), whose fusion holds promising potential to improve the estimation accuracy of soil attributes. In this paper, we examine different data fusion methods for the prediction of key soil fertility attributes including pH, organic carbon (OC), magnesium (Mg), and calcium (Ca). To this end, the vis-NIR and XRF spectra of 267 soil samples were collected from nine fields in Belgium, from which the soil samples of six fields were used for calibration of the single-sensor and data fusion models while the validation was performed on the remaining three fields. The first fusion method was the outer product analysis (OPA), for which the outer product (OP) of the two spectra is computed, flattened, and then subjected to partial least squares (PLS) regression model. Two versions of OPA were evaluated: (i) OPA-FS in which the full spectra were used as input; and (ii) OP...

Research paper thumbnail of Combined Use of Vis-NIR and XRF Sensors for Tropical Soil Fertility Analysis: Assessing Different Data Fusion Approaches

Sensors

Visible and near infrared (vis-NIR) diffuse reflectance and X-ray fluorescence (XRF) sensors are ... more Visible and near infrared (vis-NIR) diffuse reflectance and X-ray fluorescence (XRF) sensors are promising proximal soil sensing (PSS) tools for predicting soil key fertility attributes. This work aimed at assessing the performance of the individual and combined use of vis-NIR and XRF sensors to predict clay, organic matter (OM), cation exchange capacity (CEC), pH, base saturation (V), and extractable (ex-) nutrients (ex-P, ex-K, ex-Ca, and ex-Mg) in Brazilian tropical soils. Individual models using the data of each sensor alone were calibrated using multiple linear regressions (MLR) for the XRF data, and partial least squares (PLS) regressions for the vis-NIR data. Six data fusion approaches were evaluated and compared against individual models using relative improvement (RI). The data fusion approaches included (i) two spectra fusion approaches, which simply combined the data of both sensors in a merged dataset, followed by support vector machine (SF-SVM) and PLS (SF-PLS) regressi...

Research paper thumbnail of Radar networks: A review of features and challenges

Research paper thumbnail of Serial Plackett fusion for decision making

IEEE Transactions on Aerospace and Electronic Systems

Research paper thumbnail of Fire detection by fusing correlated measurements

Journal of Ambient Intelligence and Humanized Computing

Research paper thumbnail of Bayesian fuzzy hypothesis test in wireless sensor networks with noise uncertainty

Applied Soft Computing

Reliable event detection is an essential task of wireless sensor networks (WSNs) in which there a... more Reliable event detection is an essential task of wireless sensor networks (WSNs) in which there are different types of uncertainty. In this paper, we consider a decentralized detection problem for a WSN and use fuzzy hypothesis test (FHT) in the Bayesian perspective to model the noise power uncertainty. FHT employs membership functions as hypotheses for modeling and analyzing the uncertainty. Using Bayesian FHT (BFHT), a local detector scheme is proposed at each sensor node in which the threshold depends on the noise power uncertainty bound. Local decisions of sensors are sent to the fusion center (FC) and combined to make a final decision about the absence/presence of the event. The proposed algorithm is evaluated in terms of probabilities of detection and false alarm. Simulations show that the proposed BFHT detector considerably outperforms the Anderson-Darling method as well as the conventional energy detector in the presence of the noise power uncertainty.

Research paper thumbnail of Hierarchical copula-based distributed detection

Research paper thumbnail of Plackett Fusion of Correlated Decisions

AEU - International Journal of Electronics and Communications

Research paper thumbnail of Detection over sensor networks: a tutorial

IEEE Aerospace and Electronic Systems Magazine

Research paper thumbnail of Decision fusion: Sparse network vs. dense network

2016 24th Iranian Conference on Electrical Engineering (ICEE), 2016

Research paper thumbnail of Design and Implementation of a High Bit Rate HDLC Transceiver Based on a Modified MT8952B Controller

Australian Journal of Basic and Applied Sciences

To transmit and receive data over any network successfully, a protocol is required to manage the ... more To transmit and receive data over any network successfully, a protocol is required to manage the flow. High-level Data Link Control (HDLC) protocol is defined in Layer 2 of OSI model and is one of the most commonly used layer 2 protocols. HDLC supports both full-duplex and half-duplex data transfer. In addition, it offers error control and flow control. Using a modified MT8952B controller design, the current research presents a new method for implementing an ultra high bit rate HDLC Controller that is compatible with ST-BUS format using Xilinx Virtex FPGA as the target technology using VHDL for implementation. The HDLC Transceiver is used to transmit and receive the HDLC frames. Implementing the HDLC protocol transceiver in FPGA offers the flexibility, upgradeability and customization benefits of programmable logic and also reduces the total cost of every project which involves HDLC protocol controllers.

Research paper thumbnail of Fusion of weighted decisions in wireless sensor networks

IET Wireless Sensor Systems, 2015

Detection of an event occurrence is one of the main tasks of a wireless sensor network (WSN) in m... more Detection of an event occurrence is one of the main tasks of a wireless sensor network (WSN) in many applications. Sensors observe the environment and send either their raw measurements or their decisions about the event occurrence to a fusion centre (FC) where the final decision is made. It is desired to obtain a decision fusion scheme in which detection performance is optimised while considering resource limitations of WSNs. In this study, a weighted decision fusion (WDF) scheme is proposed. In WDF, each sensor that detects the event sends its quantised estimated signal-to-noise ratio to the FC if it is more than a prespecified value. The FC uses the information in order to weigh each sensor's decision and makes the final decision using an adaptive threshold scheme. More efficient use of bandwidth and adaptive thresholding at the FC result in considerable improvement. The substantial improvement of detection performance compared with existing methods is shown by analysis and simulation.

Research paper thumbnail of Weighted decision fusion vs. counting rule over wireless sensor networks: A realistic comparison

2013 21st Iranian Conference on Electrical Engineering (ICEE), 2013

are weighted based on their estimated SNR values. In addition, each sensor which detects the even... more are weighted based on their estimated SNR values. In addition, each sensor which detects the event sends data to the FC if its received SNR is more than a pre-specified value. Detection performances of WDF and CRF are compared using a practical data-set.

Research paper thumbnail of Radar networks: A review of features and challenges

Research paper thumbnail of Reliable distributed detection in multi-hop clustered wireless sensor networks

Research paper thumbnail of Design and Implementation of a High Bit Rate HDLC Transceiver Based on a Modified MT8952B Controller

Australian Journal of Basic and Applied …, Jan 1, 2009

Research paper thumbnail of An Optimal Energy-efficient Clustering Method in Wireless Sensor Networks Using Multi-objective Genetic Algorithm

In this study, an optimal method of clustering homogeneous wireless sensor networks using a multi... more In this study, an optimal method of clustering homogeneous wireless sensor networks using a multi-objective two-nested genetic algorithm is presented. The top level algorithm is a multi-objective genetic algorithm (GA) whose goal is to obtain clustering schemes in which the network lifetime is optimized for different delay values. The low level GA is used in each cluster in order to get the most efficient topology for data transmission from sensor nodes to the cluster head. The presented clustering method is not restrictive, whereas existing intelligent clustering methods impose certain conditions such as performing two-tiered clustering. A random deployed model is used to demonstrate the efficiency of the proposed algorithm. In addition, a comparison is made between the presented algorithm other GA-based clustering methods and the Low Energy Adaptive Clustering Hierarchy protocol. The results obtained indicate that using the proposed method, the network's lifetime would be extended much more than it would be when using the other methods.

Research paper thumbnail of Data Fusion of XRF and Vis-NIR Using Outer Product Analysis, Granger–Ramanathan, and Least Squares for Prediction of Key Soil Attributes

Remote Sensing

Visible-near-infrared (vis-NIR) and X-ray fluorescence (XRF) are key technologies becoming pervas... more Visible-near-infrared (vis-NIR) and X-ray fluorescence (XRF) are key technologies becoming pervasive in proximal soil sensing (PSS), whose fusion holds promising potential to improve the estimation accuracy of soil attributes. In this paper, we examine different data fusion methods for the prediction of key soil fertility attributes including pH, organic carbon (OC), magnesium (Mg), and calcium (Ca). To this end, the vis-NIR and XRF spectra of 267 soil samples were collected from nine fields in Belgium, from which the soil samples of six fields were used for calibration of the single-sensor and data fusion models while the validation was performed on the remaining three fields. The first fusion method was the outer product analysis (OPA), for which the outer product (OP) of the two spectra is computed, flattened, and then subjected to partial least squares (PLS) regression model. Two versions of OPA were evaluated: (i) OPA-FS in which the full spectra were used as input; and (ii) OP...

Research paper thumbnail of Data Fusion of XRF and Vis-NIR Using Outer Product Analysis, Granger–Ramanathan, and Least Squares for Prediction of Key Soil Attributes

Remote Sensing

Visible-near-infrared (vis-NIR) and X-ray fluorescence (XRF) are key technologies becoming pervas... more Visible-near-infrared (vis-NIR) and X-ray fluorescence (XRF) are key technologies becoming pervasive in proximal soil sensing (PSS), whose fusion holds promising potential to improve the estimation accuracy of soil attributes. In this paper, we examine different data fusion methods for the prediction of key soil fertility attributes including pH, organic carbon (OC), magnesium (Mg), and calcium (Ca). To this end, the vis-NIR and XRF spectra of 267 soil samples were collected from nine fields in Belgium, from which the soil samples of six fields were used for calibration of the single-sensor and data fusion models while the validation was performed on the remaining three fields. The first fusion method was the outer product analysis (OPA), for which the outer product (OP) of the two spectra is computed, flattened, and then subjected to partial least squares (PLS) regression model. Two versions of OPA were evaluated: (i) OPA-FS in which the full spectra were used as input; and (ii) OP...

Research paper thumbnail of Combined Use of Vis-NIR and XRF Sensors for Tropical Soil Fertility Analysis: Assessing Different Data Fusion Approaches

Sensors

Visible and near infrared (vis-NIR) diffuse reflectance and X-ray fluorescence (XRF) sensors are ... more Visible and near infrared (vis-NIR) diffuse reflectance and X-ray fluorescence (XRF) sensors are promising proximal soil sensing (PSS) tools for predicting soil key fertility attributes. This work aimed at assessing the performance of the individual and combined use of vis-NIR and XRF sensors to predict clay, organic matter (OM), cation exchange capacity (CEC), pH, base saturation (V), and extractable (ex-) nutrients (ex-P, ex-K, ex-Ca, and ex-Mg) in Brazilian tropical soils. Individual models using the data of each sensor alone were calibrated using multiple linear regressions (MLR) for the XRF data, and partial least squares (PLS) regressions for the vis-NIR data. Six data fusion approaches were evaluated and compared against individual models using relative improvement (RI). The data fusion approaches included (i) two spectra fusion approaches, which simply combined the data of both sensors in a merged dataset, followed by support vector machine (SF-SVM) and PLS (SF-PLS) regressi...

Research paper thumbnail of Radar networks: A review of features and challenges

Research paper thumbnail of Serial Plackett fusion for decision making

IEEE Transactions on Aerospace and Electronic Systems

Research paper thumbnail of Fire detection by fusing correlated measurements

Journal of Ambient Intelligence and Humanized Computing

Research paper thumbnail of Bayesian fuzzy hypothesis test in wireless sensor networks with noise uncertainty

Applied Soft Computing

Reliable event detection is an essential task of wireless sensor networks (WSNs) in which there a... more Reliable event detection is an essential task of wireless sensor networks (WSNs) in which there are different types of uncertainty. In this paper, we consider a decentralized detection problem for a WSN and use fuzzy hypothesis test (FHT) in the Bayesian perspective to model the noise power uncertainty. FHT employs membership functions as hypotheses for modeling and analyzing the uncertainty. Using Bayesian FHT (BFHT), a local detector scheme is proposed at each sensor node in which the threshold depends on the noise power uncertainty bound. Local decisions of sensors are sent to the fusion center (FC) and combined to make a final decision about the absence/presence of the event. The proposed algorithm is evaluated in terms of probabilities of detection and false alarm. Simulations show that the proposed BFHT detector considerably outperforms the Anderson-Darling method as well as the conventional energy detector in the presence of the noise power uncertainty.

Research paper thumbnail of Hierarchical copula-based distributed detection

Research paper thumbnail of Plackett Fusion of Correlated Decisions

AEU - International Journal of Electronics and Communications

Research paper thumbnail of Detection over sensor networks: a tutorial

IEEE Aerospace and Electronic Systems Magazine

Research paper thumbnail of Decision fusion: Sparse network vs. dense network

2016 24th Iranian Conference on Electrical Engineering (ICEE), 2016

Research paper thumbnail of Design and Implementation of a High Bit Rate HDLC Transceiver Based on a Modified MT8952B Controller

Australian Journal of Basic and Applied Sciences

To transmit and receive data over any network successfully, a protocol is required to manage the ... more To transmit and receive data over any network successfully, a protocol is required to manage the flow. High-level Data Link Control (HDLC) protocol is defined in Layer 2 of OSI model and is one of the most commonly used layer 2 protocols. HDLC supports both full-duplex and half-duplex data transfer. In addition, it offers error control and flow control. Using a modified MT8952B controller design, the current research presents a new method for implementing an ultra high bit rate HDLC Controller that is compatible with ST-BUS format using Xilinx Virtex FPGA as the target technology using VHDL for implementation. The HDLC Transceiver is used to transmit and receive the HDLC frames. Implementing the HDLC protocol transceiver in FPGA offers the flexibility, upgradeability and customization benefits of programmable logic and also reduces the total cost of every project which involves HDLC protocol controllers.

Research paper thumbnail of Fusion of weighted decisions in wireless sensor networks

IET Wireless Sensor Systems, 2015

Detection of an event occurrence is one of the main tasks of a wireless sensor network (WSN) in m... more Detection of an event occurrence is one of the main tasks of a wireless sensor network (WSN) in many applications. Sensors observe the environment and send either their raw measurements or their decisions about the event occurrence to a fusion centre (FC) where the final decision is made. It is desired to obtain a decision fusion scheme in which detection performance is optimised while considering resource limitations of WSNs. In this study, a weighted decision fusion (WDF) scheme is proposed. In WDF, each sensor that detects the event sends its quantised estimated signal-to-noise ratio to the FC if it is more than a prespecified value. The FC uses the information in order to weigh each sensor's decision and makes the final decision using an adaptive threshold scheme. More efficient use of bandwidth and adaptive thresholding at the FC result in considerable improvement. The substantial improvement of detection performance compared with existing methods is shown by analysis and simulation.

Research paper thumbnail of Weighted decision fusion vs. counting rule over wireless sensor networks: A realistic comparison

2013 21st Iranian Conference on Electrical Engineering (ICEE), 2013

are weighted based on their estimated SNR values. In addition, each sensor which detects the even... more are weighted based on their estimated SNR values. In addition, each sensor which detects the event sends data to the FC if its received SNR is more than a pre-specified value. Detection performances of WDF and CRF are compared using a practical data-set.

Research paper thumbnail of Radar networks: A review of features and challenges

Research paper thumbnail of Reliable distributed detection in multi-hop clustered wireless sensor networks

Research paper thumbnail of Design and Implementation of a High Bit Rate HDLC Transceiver Based on a Modified MT8952B Controller

Australian Journal of Basic and Applied …, Jan 1, 2009

Research paper thumbnail of An Optimal Energy-efficient Clustering Method in Wireless Sensor Networks Using Multi-objective Genetic Algorithm

In this study, an optimal method of clustering homogeneous wireless sensor networks using a multi... more In this study, an optimal method of clustering homogeneous wireless sensor networks using a multi-objective two-nested genetic algorithm is presented. The top level algorithm is a multi-objective genetic algorithm (GA) whose goal is to obtain clustering schemes in which the network lifetime is optimized for different delay values. The low level GA is used in each cluster in order to get the most efficient topology for data transmission from sensor nodes to the cluster head. The presented clustering method is not restrictive, whereas existing intelligent clustering methods impose certain conditions such as performing two-tiered clustering. A random deployed model is used to demonstrate the efficiency of the proposed algorithm. In addition, a comparison is made between the presented algorithm other GA-based clustering methods and the Low Energy Adaptive Clustering Hierarchy protocol. The results obtained indicate that using the proposed method, the network's lifetime would be extended much more than it would be when using the other methods.