Conceptual Design of Low Altitude Unmanned Small Hybrid Airship

In the last two decades, popularity of Unmanned Air Systems (UAS) are at their peaks. Their capacities and abilities are advancing day by day in parallel with development of science and technology. They are doing almost everything what conventional aircrafts are doing except passenger transfer, for now. Despite an UAS can be controlled from thousands of miles away, they are still limited in range and endurance because of their energy storage capacities. Most of the energy sources of an aircraft is used against to gravitational force. However, Lighter Than Air(LTA) gases like helium, hydrogen etc. provides an option to aircrafts using lifting capacity of these gases and combination of lifting capacity of LTA gases and mechanical forces produced by engines allows engineers to create hybrid airships. Hybrid Airships gains flight altitude by using static lifting force of lighter than air gases in addition of the mechanical force which is produced by the propulsion system of the vehicle. Engines makes necessary maneuver with direction units to control the airship in all directions. Static lift from the LTA gases provide additional payload capacity to vehicle without consuming energy. Therefore, unlike the conventional aircrafts, hybrid airship has more flight duration than the others and more payload capacity. Aim of this work is, developing a low-cost small hybrid airship by using static lift force of the lighter than air gases and present to advantages of hybrid aircrafts

Dynamic Multi Threshold Priority Packet Scheduling Algorithms

Packet scheduling algorithms are developed in order to use shared transmission resources efficiently. Various application packets such as real and non-real time packets might have different QoS requirements and traditional scheduling algorithms might be insufficient to respond to the applications needs. In this paper, two packet scheduling algorithms are proposed to overcome this problem: Dynamic multi threshold priority packet scheduling (DMTPS) and dynamic multi threshold priority with urgency packet scheduling (DMTPUS). The proposed algorithms aim to provide a better QoS level with a decrease in delay time and loss ratio for the low priority packets while still maintaining acceptable fairness towards high priority packets. To evaluate the performance of DMTPS and DMTPUS algorithms, they are compared with the commonly used scheduling algorithms such as first come first served (FCFS) and fixed priority. Simulation results illustrate that the dynamic multi threshold priority packet scheduling algorithms can provide a better QoS for low priority packets without decreasing the QoS levels of high priority packets

In silico identification of critical proteins associated with learning process and immune system for Down syndrome.

Understanding expression levels of proteins and their interactions is a key factor to diagnose and explain the Down syndrome which can be considered as the most prevalent reason of intellectual disability in human beings. In the previous studies, the expression levels of 77 proteins obtained from normal genotype control mice and from trisomic Ts65Dn mice have been analyzed after training in contextual fear conditioning with and without injection of the memantine drug using statistical methods and machine learning techniques. Recent studies have also pointed out that there may be a linkage between the Down syndrome and the immune system. Thus, the research presented in this paper aim at in silico identification of proteins which are significant to the learning process and the immune system and to derive the most accurate model for classification of mice. In this paper, the features are selected by implementing forward feature selection method after preprocessing step of the dataset. Later, deep neural network, gradient boosting tree, support vector machine and random forest classification methods are implemented to identify the accuracy. It is observed that the selected feature subsets not only yield higher accuracy classification results but also are composed of protein responses which are important for the learning and memory process and the immune system

Dynamic Multi Threshold Priority Packet Scheduling Algorithms

Packet scheduling algorithms are developed in order to use shared transmission resources efficiently. Various application packets such as real and non-real time packets might have different QoS requirements and traditional scheduling algorithms might be insufficient to respond to the applications needs. In this paper, two packet scheduling algorithms are proposed to overcome this problem: Dynamic multi threshold priority packet scheduling (DMTPS) and dynamic multi threshold priority with urgency packet scheduling (DMTPUS). The proposed algorithms aim to provide a better QoS level with a decrease in delay time and loss ratio for the low priority packets while still maintaining acceptable fairness towards high priority packets. To evaluate the performance of DMTPS and DMTPUS algorithms, they are compared with the commonly used scheduling algorithms such as first come first served (FCFS) and fixed priority. Simulation results illustrate that the dynamic multi threshold priority packet scheduling algorithms can provide a better QoS for low priority packets without decreasing the QoS levels of high priority packets

Toward a Time-Scale Based Framework for ABR Traffic Management

This paper discusses some issues and possibilities for more effective ABR (Available Bit Rate) traffic management which arise from a careful consideration of various time scales present in an ATM networking environment. Since the ABR applications will typically use the remaining resources after CBR (Constant Bit Rate) and VBR (Variable Bit Rate) applications have been accommodated, the ABR rate should be controlled through a feedback based flow control scheme to avoid excessive losses. It is well known that the increased propagation delay between the (controlled) ABR source and the network node leads to increased time horizons over which the source rate is based on outdated information, resulting in increased amount of bandwidth mismatch and, thus, cell losses. For this reason, the effectiveness of feedback based flow control schemes reduces with increased propagation delay. Besides the physical distance, some other system parameters - namely the network, ABR and VBR time scales - may ..

A Proactive Feedback Based Flow Control Scheme for ABR Services

By design, the Available Bit Rate (ABR) applications will be allocated the networking capacity which is not utilized by Variable Bit Rate (VBR) and Constant Bit Rate (CBR) applications. The ABR traffic entering the network will be controlled by a feedback based scheme. As the distance between the ABR source and the network access node increases, the feedback based flow control mechanisms become less effective due to the increased propagation delay. This is known as the bandwidth mismatch problem. In this paper, a proactive feedback based flow control scheme for the ABR service class is introduced by attempting to reduce the induced bandwidth mismatch. It also can provide for a fair rate allocation to ABR sources with different propagation delays. 1 Introduction The Asynchronous Transfer Mode (ATM) has been selected as the CCITT standard for the switching and multiplexing technique of the BroadbandIntegrated Services Digital Networks (B-ISDN) currently under development. ATM networks a..