Search

To efficiently utilize the total resources and to serve mobile users demanding for different types of service, system resource utilization of these services should be considered, and efficient resource management techniques should be developed. In this paper, we propose a new call admission control (CAC) scheme jointly with resource management by considering the two service types: prioritized calls and nonprioritized calls. Proposed scheme limits the new and handoff prioritized and non-prioritized call arrivals according to call-level quality of service (QoS) requirements. By searching algorithm, admission parameters are obtained optimally and required QoS are guaranteed. Due to high priority of the prioritized calls, the admittance of non-prioritized calls into channel is restricted, while prioritized calls are admitted as long as there is sufficient bandwidth. To evaluate the performance of the proposed CAC scheme, we have compared the numerical results from the analytical model with those of New Call Bounding scheme. It is shown that the proposed CAC scheme uses the resources effectively and improves all the upper-bound QoS requirements with respect to the New Call Bounding scheme for prioritized and non-prioritized users.

Online services on the Internet are increasing day by day, and in parallel, the number of cyber-attacks is rapidly increasing. These attacks are not always about data theft, but they can cause severe damage by denial of service attacks. Intrusion Prevention System products that many organizations use at the border of their enterprise networks are not strong enough to protect against DoS attacks. The typical way to mitigate such attacks is to get support from a service provider. However, a service provider only provides solutions for the traffic originating from itself. If the source of attack is in another ISP domain, it is possible to inform that ISP via phone or e-mail. As a result, the source of the attack is blocked by the manual intervention of the service provider whose domain hosts it. Border Gateway Protocol (BGP) based solutions are also available for automating a blocking system, but not all enterprise networks support BGP. In this research, we have developed a centralized automation solution for software defined network (SDN) environments that is capable of preventing cyber-attacks at the source of attack. This solution does not require any BGP support. Non-SDN environments can also use this attack mitigation and notification system. In the long run, we may use this system to create a national protection shield in order to mitigate Cybersecurity attacks. [ABSTRACT FROM AUTHOR]

Extracting the user reviews in websites such as forums, blogs, newspapers, commerce, trips, etc. is crucial for text processing applications (e.g. sentiment analysis, trend detection/monitoring and recommendation systems) which are needed to deal with structured data. Traditional algorithms have three processes consisting of Document Object Model (DOM) tree creation, extraction of features obtained from this tree and machine learning. However, these algorithms increase time complexity of extraction process. This study proposes a novel algorithm that involves two complementary stages. The first stage determines which HTML tags correspond to review layout for a web domain by using the DOM tree as well as its features and decision tree learning. The second stage extracts review layout for web pages in a web domain using the found tags obtained from the first stage. This stage is more time-efficient, being approximately 21 times faster compared to the first stage. Moreover, it achieves a relatively high accuracy of 96.67% in our experiments of review block extraction. [ABSTRACT FROM AUTHOR]

The aim of this study is to design and implement a system that detect driver sleepiness and warn driver in real-time using image processing and machine learning techniques. Viola-Jones detector was used for segmenting face and eye images from the cameraacquired driver video. Left and right eye images were combined into a single image. Thus, an image was obtained in minimum dimensions containing both eyes. Features of these images were extracted by using Gabor filters. These features were used to classifying images for open and closed eyes. Five machine learning algorithms were evaluated with four volunteer's eye image data set obtained from driving simulator. Nearest neighbor IBk algorithm has highest accuracy by 94.76% while J48 decision tree algorithm has fastest classification speed with 91.98% accuracy. J48 decision tree algorithm was recommended for real time running. PERCLOS the ratio of number of closed eyes in one minute period and CLOSDUR the duration of closed eyes were calculated. The driver is warned with the first level alarm when the PERCLOS value is 0.15 or above, and with second level alarm when it is 0.3 or above. In addition, when it is detected that the eyes remain closed for two seconds, the driver is also warned by the second level alarm regardless of the PERCLOS value. Designed and developed real-time application can able to detect driver sleepiness with 24 FPS image processing speed and 90% real time classification accuracy. Driver sleepiness were able to detect and driver was warned successfully in real time when sleepiness level of driver is achieved the defined threshold values. [ABSTRACT FROM AUTHOR]

Complementary resistive switches (CRSs) are suggested as an alternative to one-cell memristor memories to decrease leakage currents. However, their sensing is more difficult and complex than one-cell memristor memories. A method has been given for sensing their state using only DC voltages in the literature. However, in this strategy, sensing one of the logic states results in the destruction of the state and the destroyed state must be written again. To the best of our knowledge, a circuit with this sensing strategy does not exist in the literature yet. In this paper, such a circuit employing this method, which is able to read the CRS cells and able to reconstruct their data if the data are destroyed, is given. A new CRS model is also constructed in this paper and used for simulations to verify the operation of the circuit. The circuit is simulated using Simulink. We expect this circuit implementation to find use in the design and testing of CRS cells. [ABSTRACT FROM AUTHOR]

OpenFlow is an open platform that manages flow tables and packet forwarding in the network switches and other network components. The OpenFlow controller, connected network switch's control path with secure channel that is basically flow control software. This paper focused performance of newly adopted OpenFlow controller POX in a simple network controlled by a HP network switch. Jitter values analyzed with different size of packets and three distinct state of OpenFlow protocol. [ABSTRACT FROM AUTHOR]

Aim: To investigate whether electroencephalographic (EEG) frequency bands are applicable in distinguishing abnormal respiratory events such as obstructive apnea and hypopnea in patients with sleep apnea. Materials and methods: The polysomnographic recordings of 20 patients were examined retrospectively. EEG record segments were taken from C4-A1 and C3-A2 channels and were analyzed with software that uses digital signal processing methods, developed by the study team. Percentage values of delta, theta, alpha, and beta frequency bands were evaluated through discriminant and receiver-operator curve (ROC) analysis to distinguish between apneas and hypopneas. Results: For the C4-A1 channel, delta (%) provided the highest discriminative value (AUC = 0.563; P < 0.001); on the other hand, alpha (%) gave the lowest discriminative value (AUC = 0.519; P = 0.041). Likewise, whereas for the C3-A2 channel delta (%) gave the highest discriminative value (AUC = 0.565; P < 0.001), alpha produced the lowest discriminative value (AUC = 0.501; P = 0.943). Conclusion: As a result of discriminant analysis, the accurate classification rate of hypopneas was 44.8% and the accurate classification of obstructive apneas was 63.5%. Of the 4 frequency bands, the most significant was delta. The predictive values were not at significance level. [ABSTRACT FROM AUTHOR]

The article offers information on radio frequency identification (RFID) technology that was used for evaluating negative symptoms exhibited by schizophrenic individuals. The symptoms included social withdrawal, sedentary behavior, motionlessness, and/or hyperactivity. Amongst other uses, the system controlled patient check-ins and check-outs for psychiatry services by automatically monitoring facility entrances and exits. The RFID tags triggered an alarm if a patient attempted to enter an unauthorized location.

The article offers information on an electronic, ultrasonic walking stick for the blind. This device will aid in establishing independence for the visually impaired. The system's design is comprised of two main modules: a control mechanism with a PIC-16C84 microcontroller and an ultrasonic transceiver. The microcontroller estimates the distance to an object using the time elapsed between sending and receiving sound waves. The distance is then converted into sound signals to inform the patient that an obstacle is close by.