Cooperative spectrum sensing is used to overcome limited computing power of individual nodes to correctly estimate existence of primary user in presence of multipath fading, shadowing and receiver uncertainty. However, conventional cooperative spectrum sensing is not reliable in case when users suffer different fading environment. Thus, to enhance the detection probability of the system weighted cooperative spectrum sensing has been introduced. In this paper, use of weighted cooperative sensing in cognitive radio has been discussed. Weight initially assigned is a constant real value which updates in each round. The procedure has been completed in various rounds and in each round the weight depends on the detection in the previous round. Two methods for spectrum sensing have been compared to find which gives better result.
Falls are a frequent cause of unintentional injuries. The development of a water sports fall detection algorithm usually requires a dataset collection of fall events that are difficult to replicate in a laboratory environment. To address that problem, this article proposes a simulated boat falls protocol that can be used to record a dataset of falls for various water sports. A dataset of 296 samples comprised in 129 falls and in 167 non-fall events was gathered using the protocol. The data collection was made with 3 different smartphones and with 1 external IMU. A fall detection algorithm was trained with the dataset with machine learning techniques and tested over the same dataset and real sailing data. The algorithm achieved 99.9% of accuracy, 99% of specificity and 100% of sensitivity when tested in the dataset and detected the only fall that occurred in one hour and a half of a real sailing activitiy.
Routing in a Wireless Sensor Network (WSN) is an important function for performance of the system in terms of energy efficiency. The WSN nodes have limited computing and processing power. For successful delivery of information in the event/data driven network of sensor nodes, distributive and/or collaborative approach is having high importance. In this paper, we have presented a set of mechanisms by which routing decision and path optimization can be decided. In this paper we have described briefly about Fuzzy based routing, Neural Network and modified Q-Learning based routing. We have shown that choice of action may give reward in the long run. We have also presented a modified ant routing algorithm, where link probabilities are randomly assigned. The probabilities will update by the backward ant process. However, the updating process is different from that of traditional Ant colony optimization (ACO) based routing. Our results are useful in this area of research.
Relational databases remain the leading data storage technology. Nevertheless, many companies want to reduce operating expenses, to make scalable applications that use cloud computing technologies. Use of NoSQL database is one of the possible solutions, and it is forecasted that the NoSQL market will be growing at a CAGR of approximately 50 percent over the next five years. The paper offers a solution for quick data migration from a relational database into a document-oriented database. We have created semi-automatically two logical levels over physical data. Users can refine generated logical data model and configure data migration template for each needed document. Data migration features are implemented into relational database browser Dig Browser. Real patients' database was migrated to Clasterpoint database. The offered approach provides means to obtain at least proof-of-concept for new document-oriented database solution in a couple of days.
The rapid development of MANETs poses substantially different challenges for routing protocols in comparison with traditional wired networks. New classes for routing algorithms have emerged, for example Ant Colony Optimization (ACO), which is inspired by the collective behavior of various ant species. ACO algorithms use control packets to search for the shortest path from source to destination. The heuristic of ACO is able to find alternative paths to the same destination. A data packet is transferred along a path selected based on a favorability probability. In this paper we propose ANTMANET, a novel ACO routing protocol utilizing the location information by adding a local zone technique to create faster route discovery by using less control packets resulting in less overhead. ANTMANET has proven better overhead and less delay when compared to different MANET routing protocols.
In this paper a user verification system on mobile phones is proposed. This system is based on behavioral biometric traits which is a keystroke dynamics derived from a touchable keyboard. A mobile application is developed for collecting those touch keystroke dynamics. In contrast to other systems, no specific text or numbers are used to build our dataset. The Median Vector Proximity classifier is applied on the touch keystroke data (touchable keyboard) and the performance of the system is investigated using different number of features and we found that the system with 31 features gained an average EER=12.9%. While with an extra two features (average of finger size and pressure) the average EER=12.2%. This shows that the more features used results in more accurate systems. The proposed system is compared against other systems and shows promising results in dynamic authentication area.
The paper presents main results received within the project 'Integrated Intelligent Platform for Monitoring the Cross-Border Natural-Technological systems' (INFROM) in the area of integrated monitoring of complex systems, which contain natural, technological and social elements, based on heterogeneous data received from space and ground-based information sources. An integrated conceptual framework for monitoring as well as technologies supporting information processing, crowd sourcing and integration, process modeling and simulation, and visualization of modeling results are described. Monitoring facilities and support tools are considered as well. The demonstration case and real-time experiments for a short-term flooding forecast are described in the paper.
The present article describes simulation results for single queue P/M/1/K model. Simulink has been used to create this model and evaluate its performance. The main purpose of the research made is to optimize costs of resources allocation for TCP traffic type at the same time striving to achieve the best packet loss probability. The optimization was made with dynamic programming method by using Bellman algorithm for simulated traffic with different self-similarity (Hurst) parameter and utilization coefficient values. The results of this work indicate that Hurst parameter affects greatly the costs of resources to be allocated. With estimation of Hurst parameter for network traffic these results can be used to estimate buffer memory capacity and ensure the specified value of packet loss probability. The research made also suggests to increase buffer memory capacity rather than channel bandwidth, whenever it is possible.
As one of the most basic and key steps in the white blood cell (WBC) automatic recognition system, the accuracy and stability of WBC segmentation greatly affect the recognition accuracy of the whole system. Inspired by co segmentation, this paper presents a new method to obtain the entire WBC contour in order to solve the adhesion problem. Firstly, the color space transformation and thresholding are employed to obtain sub images. Among them, a sub image called reference image only includes plasma and red blood cells (RBCs), while the others contain WBCs. Then, a similarity measurement is introduced into the region-based active contour model in order to co segment between the reference image and the other sub images. Due to full use of cross information, such as color and shape, the proposed method has been successfully applied to a large number of microscopic cell images, showing promising segmentation results for diverse cell appearance and image quality.
Location aware applications are constantly under development. By using an Indoor Location System (ILS), a user can localize himself, plan an indoor route and destination, or receive useful information and services in malls, airports, shopping centers, etc. To this purpose, various signal strength or timing based localization methods exist, each one having their own advantages and disadvantages. Localization based on the Received Signal Strength (RSS) methods, typically require only off-the-shelf equipment to operate. Moreover, they can utilize the existing infrastructure. This paper presents a new method on how to use the captured RSS values for localization purposes. The proposed method analyses a captured signal over a short distance and stores it into the fingerprint database for later comparison, rather than using an average value obtained from static measurements. Real-world measurements are used in order to validate our approach.
In this paper the analysis of the stacked patch antennas on two different substrates namely Arlon and Polymide at terahertz frequency is presented. The analysis is carried out with two parameters namely by varying the distance of separation of patches and varying the substrates. Electrical parameters like return loss, gain, and bandwidth are compared with conventional patch antenna at same resonant frequency. This proposed model is useful in applications like terahertz sensing and communications. Apart from applications the electrical performance of proposed model shows improvement in terms of gain and reflection for the substrate having low dielectric permittivity. The finite integral technique is used to analyze the proposed model by way of CST microwave studio a proven electromagnetic tool.
In the last decades Model predictive control (MPC) is the leading paradigm for high-performance and cost-effective control of complex systems. MPC contains powerful technique for optimizing the performance of constrained systems on state and control variables. For this reason, we use a distributed controller to coordinate a fleet of moving robots with unicycle kinematics. The proposed algorithm is based on the concept of robust MPC control with tube based strategy (i.e. It imposes low complexity and conservativeness). Using this approach we are able to guarantee that the real controlled system, on which a bounded disturbance is supposed to act, remains constrained in a neighborhood of the trajectory of the ideal system, which is defined by neglecting the effect of uncertainties. Obstacle avoidance function introduced for prevent collision between robot coordination. Matlab implementation and real robot results are used to show the efficacy of the proposed control strategy.
Among the various types of artificial neural networks used for event detection in visual contents, those with the ability of processing temporal information, such as recurrent neural networks, have been proved to be more effective. However, training of such networks is often difficult and time consuming. In this work, we show how Reservoir Computing Networks (RCNs) can be used for detecting purposes on raw images. The applicability of RCNs is illustrated using two example challenges, namely isolated digit handwriting recognition on the MNIST dataset as well as detection of the status of a door using self-developed moving pictures from a surveillance camera. Achieving an error rate of 0.92 percent on MNIST, we show that RCN can be a serious competitor to the state-of-the-art. Moreover, we show how RCNs with their simple and yet robust training procedure can be practically used for real surveillance tasks using very low resolution camera sensors.
With the flood of using smartphones in Saudi society and among public, it has become increasingly necessary for companies and individuals to use smartphone tools for m-shopping. The researcher started with tackling the descriptive statistical analyses including weighted arithmetic means, standard deviation, coefficient of standard variation, and order so as to determine the research of the research sample's individuals in terms of the extent of agreement on dominating practices via using mobile phones in marketing and shopping. The study used Cronbach's alpha to measure the validity and stability of the study questionnaire's content. In addition, the Spearman Correlation and Stepwise Multiple Linear Regression analysis (as artificial intelligence method) was used to determine the impact of the dominating practices such as educational level, occupation, and monthly income on the variables of using mobile phone in marketing and shopping.
In this paper three different acquisition algorithms are implemented in a GPS software receiver and compared by the correlation strategy employed. Their theoretical models are first analyzed and then implemented in Mat lab. Both simulated GPS data and realistic signals from a Sat-Surf receiver are used to verify the performance of the acquisition schemes. The software acquisition approach provides flexibility and low cost for algorithm redesign and improved intermediate frequency selection capability. The performances of serial search in time domain, parallel search in time and frequency domain acquisition algorithms are compared and evaluated using different incoming signals Carrier-to-Noise density ratios. The serial search acquisition algorithm in time domain has the advantage of working both on block of data or sample. The main disadvantage is the bigger acquisition time it requires. The acquisition in time domain employing FFT is a very fast acquisition algorithm.
In this paper an operational amplifier of general purpose is presented. The unified current-control model is used to synthesize a standard, two-stage topology based circuit. The design procedure is discussed thoroughly and every step is explained in details. The results obtained include open loop gain of 74 dB, the gain-bandwidth product of 100 MHz and the phase margin higher than 46°. Supply voltage and temperature coefficients are analyzed and discussed within the paper. Process variations are investigated through corner analysis. The results presented are obtained through schematic level simulations using the Spectre Simulator from Cadence Design System and a standard 130 nm CMOS technology process.
Cloud Computing allows the user to access the cloud services dynamically over the internet wherever and whenever needed. Open Stack is an open source software used to build a public or a private cloud. In its raw form Open Stack is not flexible enough to accommodate an organizational hierarchy. In this paper we propose a novel approach to modify the OpenStack Dashboard's structure to adapt to an organization's hierarchy and in addition we also integrate modules like user and tenant registration, role based access control and custom flavour creation onto the Open Stack dashboard to make it more flexible and easy to use. The implementation is done using a sample organizational hierarchy which is discussed in detail in this paper and we have designed an Open Stack dashboard using Open Stack Icehouse version deployed on Ubuntu.
Web services have been widely accepted as a server-side technology and are the key component to cloud computing. How to effectively compose a service from a number of services is a still an issue. The current solutions are either too specialized or too complex. In this paper we present a workflow that models service composition as a service graph where each node is an individual service. Then the problem of service composition becomes the problem of path optimization. In our approach the services are first evaluated and ranked according to their quality of services. The highly ranked services are selected to construct a service graph determined by the correlation values among them. Finally, several service selection strategies are developed according to different correlation and path optimization policies. These mechanisms are further evaluated and validated by simulations. The experiments show the proposed methods are feasible and not complex.
The authors propose a runtime verification mechanism for business processes. This mechanism allows verifying the correctness of business process execution and it runs in parallel with the base processes affecting them insignificantly. The authors have identified the case where the use of business process runtime verification is helpful and applicable. The verification mechanism monitors the business process execution and verifies compliance with the base process description. The verification mechanism prototype was developed and tested in real business processes, as well as limits of runtime verification overhead were evaluated.
In this paper a novel concept of data transmission system based on the orthogonal chaotic code division multiplexing (CDM) is discussed. The algorithm how to create a full set of orthogonal binary sequences from a single chaotic sequence is proposed. Moreover, the criteria for selection of the chaotic sequence for the particular communication channel statistics are formulated. Performance of the transmission system is evaluated using numerical simulations and side by side comparison to the orthogonal frequency division multiplexing (OFDM) is provided. It is shown that in some cases the orthogonal chaotic CDM transmission system employing set of binary sequences, which is tailored to the particular communication channel, outperforms OFDM.
