TCP with header checksum option for wireless links: An analytical approach towards performance evaluation

TCP performs poorly in wireless mobile networks due to large bit error rates. Basically, the TCP sender responds to these losses as if they were due to congestion in the network, and reduces the congestion window unnecessarily. In earlier work, it has been shown that adding a TCP header checksum is very useful in differentiating between congestion loss and corruption loss. With the modified TCP, receivers can explicitly indicate corruption of received packets by generating “Explicit Loss Notifications (ELNs).” This paper focuses on an analytical study of this modified TCP protocol. We derive an expression for the probability of a receiver generating successful ELN, assuming a generic link layer protocol for data transfer over wireless links. Next, we develop an analytical approach for TCP throughput evaluation under the modified scheme. We compare the throughput results obtained by analysis and simulation, and find very close agreement between the two sets. We also compare the performance of the modified scheme with the standard NewReno TCP, and find considerable improvement in data throughput over wireless links.     

Statistical,Evolutionary, and Neurocomputing Clustering Techniques: Cluster-Based vs Object-Based Approaches

Modern day computers cannot provide optimal solution to the clustering problem. There are many clustering algorithms that attempt to provide an approximation of the optimal solution. These clustering techniques can be broadly classified into two categories. The techniques from first category directly assign objects to clusters and then analyze the resulting clusters. The methods from second category adjust representations of clusters and then determine the object assignments. In terms of disciplines, these techniques can be classified as statistical, genetic algorithms based, and neural network based. This paper reports the results of experiments comparing five different approaches: hierarchical grouping, object-based genetic algorithms, cluster-based genetic algorithms, Kohonen neural networks, and K-means method. The comparisons consist of the time requirements and within-group errors. The theoretical analyses were tested for clustering of highway sections and supermarket customers. All the techniques were applied to clustering of highway sections. The hierarchical grouping and genetic algorithms approaches were computationally infeasible for clustering a larger set of supermarket customers. Hence only Kohonen neural networks and K-means techniques were applied to the second set to confirm some of the results from previous experiments.     

Visual observation of phase transitions in LiKSO4 under pressure

Phase transitions in LiKSO₄ have been visually observed in a diamond-anvil cell up to 16 GPa. The observations confirm a symmetry change at 0·9 GPa and a solidstate crystal to amorphous transition at 12 GPa. The crystal exhibits a memory across the crystalline transitions. Interesting microstructural features were observed in the range of the amorphous phase.     

Mechanical property characterization in support of elevated temperature reactor design

The mechanical properties data used for the design of nuclear reactors and reactor components for operation at elevated temperatures often show considerable variation. In types 304 and 316 stainless steels, much of the heat-to-heat variation is due to variation in chemical composition and grain size. For a heat-treatable ferritic steel such as 2 1/4 Cr-1 Mo steel, chemical composition is again important, but the heat treatment is more important. An understanding of the metallurgical processes that lead to data variation and property changes in these steels can be used to optimize reactor design.     

Automation of human behaviors and its prediction using machine learning

Microsystem Technologies - Prediction is a method of detecting a person's behavior toward online buying by evaluating publically available evaluations on the web. Understanding expressive human...     

Stability of ceramic matrix materials in molten hydroxide under oxidizing and reducing conditions

The degradation mechanism of ceramic matrix materials used as molten hydroxide electrolyte support for steam electrolysis cells, is not well documented. In this study, we have investigated the structural and chemical stability of non-oxide and oxide ceramics (SiC, YSZ, Li₂ZrO_3, LiAlO₂, and SrZrO₃) in the presence of molten hydroxide under oxidizing and reducing conditions with humidity levels of 3 and 85% at 550 °C. SiC, YSZ, Li₂ZrO₃ and LiAlO₂ showed structural and chemical changes due to dissolution of the ceramic particles in the hydroxide melt followed by precipitation. The SrZrO₃ powder, on the other hand, remained both chemically and structurally stable during 500 h test under both oxidizing and reducing atmospheres. The findings of a stable ceramic matrix in molten hydroxide contribute to the enhancement of the durability and performance of intermediate temperature water electrolysis system.