SIGHTED: A Framework for Semantic Integration of Heterogeneous Sensor Data on the Internet of Things

AbstractSensors are embedded nowadays in a growing number of everyday life objects. Smartphones, wearables, and sensor networks together play an important role in bridging the gap between physical and cyber worlds, a fundamental aspect of the Internet of Things vision. The ability to reuse sensor data integrated from multiple heterogeneous sources is a step towards building innovative applications and services. In this paper SIGHTED, a sensor data integration framework, is proposed exploiting semantic web technologies and linked data principles. It provides a layered structure as a guideline for integrating sensor data from various sources supporting accessibility and usability. DotThing, a demo platform, is implemented as an instantiation of SIGHTED framework and evaluated. Smartphones and sensor nodes are connected to DotThing showing the ability to query and reuse integrated sensor data from multiple sources to create more flexible horizontal applications. DotThing implementation also demonstrates the need for adding a semantic layer to existing IoT cloud-based platforms, like Xively, that generally lack such layer resulting in proprietary vertical solutions with limited data integration and discovery capabilities. DotThing makes use of vocabularies from existing ontologies on the linked data cloud providing a unified model to annotate data and link it to existing resources on the web

Kinetics and isotherm studies of methyl orange adsorption by a highly recyclable immobilized polyaniline on a glass plate

AbstractImmobilized polyaniline on glass plates (PANI/glass) and its powder form were compared for the adsorption of methyl orange (MO) dye from aqueous solutions. The effects of operational parameters such as pH, sorbent dosage, initial concentration, contact time, aeration rate and the thermodynamics of the uptake of MO had been exhaustively evaluated. The maximum adsorption capacity (qmax) for PANI/glass and PANI powder was 93 and 147mgg−1, respectively. In addition, pseudo-second order model was the best fitted kinetic model for both systems, suggesting that the rate-limiting step may be chemisorptions. The obtained negative values of free energy and enthalpy indicated the adsorption process was spontaneous and exothermic. In contrast to PANI powder, PANI/glass yielded negative entropy. Photocatalytic regeneration of used PANI/glass was found to be highly effective where the desorbed MO was completely mineralized. This study showed that immobilized PANI offered the unique advantage of convenient use and reuse over an extended period of applications

Analysis and Simulation of Active Filters Using Operational Transconductance Amplifier (OTA)

As the transistors are continuously scaling down, it becomes necessary to reduce voltage supply and power requirements of the circuit to increase its performance and stability. Whereas, current- mode devices require less number of stages with high output impedance results in improved performance and large bandwidth as compared to voltage-mode techniques. OTA are current-mode device that takes voltage as input and produces current as output with high gain and large bandwidth. The frequency bands were parameters were determined such as the cutoff frequency (fc), the band width (BW), the quality factor (Q), and the angular frequency (Wo). In this paper the design and the simulation of the transfer function has been done by using (MATLAB) in order to obtain the frequency response for all types of filter (the low pass filter, high pass filter, band pass filter and band stop filter)

Integration of Linux TCP and Simulation: Verification, Validation and Application

Network simulator has been acknowledged as one of the most flexible means in studying and developing protocol as it allows virtually endless numbers of simulated network environments to be setup and protocol of interest to be fine-tuned without requiring any real-world complicated and costly network experiment. However, depending on researchers, the same protocol of interest can be developed in different ways and different implementations may yield the outcomes that do not accurately capture the dynamics of the real protocol. In the last decade, TCP, the protocol on which the Internet is based, has been extensively studied in order to study and reevaluate its performance particularly when TCP based applications and services are deployed in an emerging Next Generation Network (NGN) and Next Generation Internet (NGI). As a result, to understand the realistic interaction of TCP with new types of networks and technologies, a combination of a real-world TCP and a network simulator seems very essential. This work presents an integration of real-world TCP implementation of Linux TCP/IP network stack into a network simulator, called INET. Moreover, verification and validation of the integrated Linux TCP are performed within INET framework to ensure the validity of the integration. The results clearly confirm that the integrated Linux TCP displays reasonable and consistent dynamics with respect to the behaviors of the real-world Linux TCP. Finally, to demonstrate the application of the INET with Linux TCP extension, algorithms of other Linux TCP variants and their dynamic over a large-bandwidth long-delay network are briefly presented

Neural network to investigate gaming addiction and its impact on health effects during the COVID-19 Pandemic

The Playing games become a serious issue and may have adverse effects on the quality of life of children. The research aims at identify in the factors and degree of influence which lead to gaming addiction and its impact on the quality of life of world children employing a comprehensive. Our method collects 2,526 children and adults’ data for five significant regions globally contain schools and universities in municipal and non-municipal areas. The research also aims to investigate the effect that gaming addiction has on the quality of life of children. Structural equation test and the (NNM) were uutilized to analyze the data. The results indicate some differences between boys and girls as to what factors lead to gaming addiction. The average Root Means Square Error (RMSE) of the neural network model is relatively low (.0103 for male training data and .0113 for male examining data, while for females it was .0103 for exercising data and .0104 for examining data), But gaming addiction was found to harm the life for both genders. Discussions comprising both academic as well as practical perspectives are also presented

EEG-based image classification using an efficient geometric deep network based on functional connectivity

To ensure that the FC-GDN is properly calibrated for the EEG-ImageNet dataset, we subject it to extensive training and gather all of the relevant weights for its parameters. Making use of the FC-GDN pseudo-code. The dataset is split into a "train" and "test" section in Kfold cross-validation. Ten-fold recommends using ten folds, with one fold being selected as the test split at each iteration. This divides the dataset into 90% training data and 10% test data. In order to train all 10 folds without overfitting, it is necessary to apply this procedure repeatedly throughout the whole dataset. Each training fold is arrived at after several iterations. After training all ten folds, results are analyzed. For each iteration, the FC-GDN weights are optimized by the SGD and ADAM optimizers. The ideal network design parameters are based on the convergence of the trains and the precision of the tests. This study offers a novel geometric deep learning-based network architecture for classifying visual stimulation categories using electroencephalogram (EEG) data from human participants while they watched various sorts of images. The primary goals of this study are to (1) eliminate feature extraction from GDL-based approaches and (2) extract brain states via functional connectivity. Tests with the EEG-ImageNet database validate the suggested method's efficacy. FC-GDN is more efficient than other cutting-edge approaches for boosting classification accuracy, requiring fewer iterations. In computational neuroscience, neural decoding addresses the problem of mind-reading. Because of its simplicity of use and temporal precision, Electroencephalographys (EEG) are commonly employed to monitor brain activity. Deep neural networks provide a variety of ways to detecting brain activity. Using a Function Connectivity (FC) - Geometric Deep Network (GDN) and EEG channel functional connectivity, this work directly recovers hidden states from high-resolution temporal data. The time samples taken from each channel are utilized to represent graph signals on a topological connection network based on EEG channel functional connectivity. A novel graph neural network architecture evaluates users' visual perception state utilizing extracted EEG patterns associated to various picture categories using graphically rendered EEG recordings as training data. The efficient graph representation of EEG signals serves as the foundation for this design. Proposal for an FC-GDN EEG-ImageNet test. Each category has a maximum of 50 samples. Nine separate EEG recorders were used to obtain these images. The FC-GDN approach yields 99.4% accuracy, which is 0.1% higher than the most sophisticated method presently availabl

DDR: efficient computational method to predict drug-target interactions using graph mining and machine learning approaches.

Motivation: Finding computationally drug-target interactions (DTIs) is a convenient strategy to identify new DTIs at low cost with reasonable accuracy. However, the current DTI prediction methods suffer the high false positive prediction rate. Results: We developed DDR, a novel method that improves the DTI prediction accuracy. DDR is based on the use of a heterogeneous graph that contains known DTIs with multiple similarities between drugs and multiple similarities between target proteins. DDR applies non-linear similarity fusion method to combine different similarities. Before fusion, DDR performs a pre-processing step where a subset of similarities is selected in a heuristic process to obtain an optimized combination of similarities. Then, DDR applies a random forest model using different graph-based features extracted from the DTI heterogeneous graph. Using 5-repeats of 10-fold cross-validation, three testing setups, and the weighted average of area under the precision-recall curve (AUPR) scores, we show that DDR significantly reduces the AUPR score error relative to the next best start-of-the-art method for predicting DTIs by 34% when the drugs are new, by 23% when targets are new and by 34% when the drugs and the targets are known but not all DTIs between them are not known. Using independent sources of evidence, we verify as correct 22 out of the top 25 DDR novel predictions. This suggests that DDR can be used as an efficient method to identify correct DTIs. Availability and implementation: The data and code are provided at https://bitbucket.org/RSO24/ddr/. Contact: [email protected]. Supplementary information: Supplementary data are available at Bioinformatics online

GEOGRAPHIC INFORMATION SYSTEM (GIS) SPATIAL ANALYST TECHNIQUES A REFERENCE FOR DETERMINING THE POSITION OF CELLULAR SYSTEMS

The Base Transverse Station (BTS) is one of the main units in the mobile communication system task. It represents the connection chain between the mobile station and the server, and it plays a major role for the completion of the process of communication between users. The towers locations (BTS) and its distributions have negative or positive effect on the active coverage power which affects the communication system. In this paper, the real locations for twenty two towers had been taken and these towers were distributed in six regions in the southern west side of sulaimany city in Iraq. By drawing the pattern for these BTS with radius equal to 200m and 300m using the Geographic Information System (GIS) program, a remarkable difference had been noticed in the radius of these cells. There active coverage areas which are suitable for good communication. Also there are interference regions and weak regions, which are areas with a weak signal or hidden areas; thus both can cause some types of fading. The weakness of the signal at these areas appears because of the irregular distribution of the towers. Finally, this paper summarizes the re-distribution of the towers and as a result the number of the towers had been - eliminated and the - weak area and the - Interference region - had been reduced in order to ensure maximum access of the active coverage area

GEOGRAPHIC INFORMATION SYSTEM (GIS) SPATIAL ANALYST TECHNIQUES A REFERENCE FOR DETERMINING THE POSITION OF CELLULAR SYSTEMS

The Base Transverse Station (BTS) is one of the main units in the mobile communication system task. It represents the connection chain between the mobile station and the server, and it plays a major role for the completion of the process of communication between users. The towers locations (BTS) and its distributions have negative or positive effect on the active coverage power which affects the communication system. In this paper, the real locations for twenty two towers had been taken and these towers were distributed in six regions in the southern west side of sulaimany city in Iraq. By drawing the pattern for these BTS with radius equal to 200m and 300m using the Geographic Information System (GIS) program, a remarkable difference had been noticed in the radius of these cells. There active coverage areas which are suitable for good communication. Also there are interference regions and weak regions, which are areas with a weak signal or hidden areas; thus both can cause some types of fading. The weakness of the signal at these areas appears because of the irregular distribution of the towers. Finally, this paper summarizes the re-distribution of the towers and as a result the number of the towers had been - eliminated and the - weak area and the - Interference region - had been reduced in order to ensure maximum access of the active coverage area

A numerical study of heat and momentum transfer over a bank of flat tubes

The present study considers steady laminar two-dimensional incompressible flow over both in-line and staggered flat tube bundles used in heat exchanger applications. The effects of various independent parameters, such as Reynolds number (Re), Prandtl number (Pr), length ratio (L/Da), and height ratio (H/Da), on the pressure drop and heat transfer were studied. A finite volume based FORTRAN code was developed to solve the governing equations. The scalar and velocity variables were stored at staggered grid locations. Scalar variables (pressure and temperature) and all thermophysical properties were stored at the main grid location and velocities were stored at the control volume faces. The solution to a one-dimensional convection diffusion equation was represented by the power law. The locations of grid points were generated by the algebraic grid generation technique. The curvilinear velocity and pressure fields were linked by the Semi-Implicit Method for Pressure Linked Equations (SIMPLE) algorithm. The line-by-line method, which is a combination of the Tri-Diagonal Matrix Algorithm (TDMA) and the Gauss-Seidel procedure, was used to solve the resulting set of discretization equations. The result of the study established that the flow is observed to attain a periodically fully developed profile downstream of the fourth module. The strength increases and the size of the recirculation gets larger as the Reynolds number increases. As the height ratio increases, the strength and size of the recirculation decreases because the flow has enough space to expand through the tube passages. The increase in length ratio does not significantly impact the strength and size of the recirculation. The non-dimesionalized pressure drop monotonically decreased with an increase in the Reynolds number. In general, the module average Nusselt number increases with an increase in the Reynolds number. The results at Pr = 7.0 indicate a significant increase in the computed module average Nusselt number when compared to those for Pr = 0.7. The overall performance of in-line configuration for lower height ratio (H/Da = 2) and higher length ratio (L/Da = 6) is preferable since it provides higher heat transfer rate for all Reynolds numbers except for the lowest Re value of 25. As expected the staggered configurations perform better than the in-line configuration from the heat transfer point of view