Earticle

Even though many wireless communication standards specify multicast as well as unicast traffic in layer 2, most parts in the specifications are contributed for unicast methods. In addition, while the wireless standards provide reliable unicast methods by using ARQ and retransmission, multicast packets are not reliably transmitted per the standards. To retransmit a multicast packet, the acknowledgements from the receivers need to be transmitted to the sender so that the sender knows whether or not the retransmission is required. However, transmitting an ACK from each group member degrades the network performance due to the overhead of multiple ACK packet transmissions and channel access processes for the ACKs. In this paper, States-of-the-arts in Layer-2 wireless multicast protocol are investigated in wide areas such as commercial communication standards as well as academic researches. Through the investigation, the research on reliable wireless multicast protocol is imposed.

The self-structuring patch antenna has a geometry very similar to that of a traditional pin-fed microstrip patch antenna, with the addition of an array of shorting pins that selectively connect the ground plane to the surface of the patch. This makes the self-structuring patch antenna unique in several ways.. The self-structuring patch antenna is also capable of achieving higher percentage bandwidths than a traditional patch antenna. The characteristics such as high gain and narrow beam width are required in waveguide type array antenna for radar.

The feature selection approach has been regarded as an effective way to remove redundant and irrelevant features. Thus it increases the efficiency of the learning task and improves the learning performance such as learning time, convergence rate, accuracy, etc. Machine learning approaches such as Neural network, Decision tree, Support Vector Machines are well suited for domains characterized by the presence of large amount of data, noisy patterns, and absence of general theory. The main goal of our research is to propose an efficient feature selection algorithm to achieve a cancer diagnosis system with high accuracies, and good adaptability to clinical dataset. We propose a new feature selection algorithm using Random Forest(RF) to be applicable to the learning algorithm for diagnosing Cancer. The experiments on clinical dataset such as leukemia cancer indicate that our proposed methods obtain higher and more stable classification performance than the baseline methods.

This paper addresses the design of trTCM (Two Rate Three Color Marker) described in RFC2698. RFC2698 has proposed trTCM to be used at the ingress of Differentiated Service network that provides AF PHB (Assured Forwarding Per Hop Behavior). trTCM is the marker with the metering function, and consists of the token updating function and the marking function. The token updating function uses the dual token bucket. Token update rate for two buckets is decided by CIR (Committed Information Rate) and PIR (Peak Information Rate) respectively. The marking function compares the token values with the length of input packet, and then marks the result into IP QoS field (ToS or DSCP). This paper designs trTCM function for implementing its function using VHDL and FPGA technology.