An adaptive ARQ–HARQ interworking scheme in WiMAX systems

For reliable data transmissions, WiMAX systems support automatic repeat query (ARQ) that operates at the upper MAC and hybrid automatic repeat query (HARQ) that operates at the lower MAC and PHY. ARQ and HARQ schemes have their own weakness that results in low throughput and high delay in WiMAX systems. Although ARQ and HARQ schemes can complement with each other, they operate independently. Some studies focus on the benefits of the interaction between ARQ and HARQ schemes, but these studies have limitations. In this paper, we propose an adaptive ARQ and HARQ interworking scheme to provide reliable transmissions without performance degradation in WiMAX systems. The proposed scheme has five features that are designed to solve the weaknesses of the ARQ and HARQ schemes. We compare the proposed scheme with existing schemes that utilize the ARQ and HARQ interaction through simulations, and the simulation results show that the proposed scheme shows improved performance over existing schemes.     

Signal characteristics of differential-pulsed eddy current sensors in the evaluation of plate thickness

Differential-pulsed eddy current (PEC) signals and their characteristics are investigated as tools for the evaluation of plate thickness by using the reflection-type PEC probe, which consists of an exciter coil and two sensor coils in a differential arrangement. Numerical and experimental signals are first compared to validate numerical simulation results, and good agreement between them is achieved. Investigation of differential PEC signals and their characteristics against thickness and conductivity variations shows that time-related features, such as the time-to-peak and the zero-crossing time, correspond well to plate thickness and conductivity. However, the feature quality of peak value turns out to be very poor. To improve this, the effects of coil characteristics on the input pulse, and consequently on differential PEC signals, are investigated. Results show that the feature quality of peak value may be improved by reducing the time constant, but doing so would worsen the quality of the other two features. Lift-off signals obtained by this probe show that the lift-off point of intersection also appears in the differential reflection-type PEC signals.     

PR-MAC: A practical approach for exploiting relay transmissions in multi-rate WLANs

In this paper, we propose a new MAC protocol, called proxy relay-enabled MAC (PR-MAC), to improve the capacity of multi-rate WLANs. PR-MAC introduces a new entity called Proxy Relay Point (PRP), which serves as a relay between the AP and stations. The cooperation of the AP with PRP replaces direct transmissions for low-rate stations with fast two-hop transmissions while the stations think that they communicate directly with the AP. Our experiment and simulation results showed that PR-MAC can significantly improve the throughput of legacy stations without any modification on the MAC operation of the stations.     

A Robust and Cooperative MAC Protocol for IEEE 802.11a Wireless Networks

In wireless networks, it is well known that the interference of hidden nodes can interrupt frame receptions. Although several solutions have been proposed to alleviate the problem of DATA corruptions at receivers, control frame corruptions at transmitters have not been considered yet. In this paper, we propose an enhanced MAC protocol, called Robust and Cooperative Medium Access Control (RCMAC), to improve the network throughput and fairness by reducing control frame losses at transmitters. RCMAC uses a relay mechanism to allow transmitters of long distance links to receive control frames more robustly by relaying control frames via relay nodes. Furthermore, RCMAC improves the network throughput through fast two-hop DATA transmissions via relay nodes. Our extensive simulation results show that RCMAC has better performance than existing well-known MAC protocols.     

Effects of electrolytes variation on formation of oxide layers of 6061 A1 alloys by plasma electrolytic oxidation

Plasma electrolytic oxidation(PEO) processes were carried out to produce ceramic layers on 6061 aluminum substrates in four kinds of electrolytes such as silicate and aluminate solution with and without sodium fluorosilicate. The PEO processes were carried out under a hybrid voltage (260 V DC combined with 200 V, 60 Hz AC amplitude) at room temperature for 5 min. The composition, microstructure and element distribution analyses of the PEO-treated layers were carried out by XRD and SEM & EDS. The effect of the electrolyte contents on the growth mechanism, element distribution and properties of oxide layers were studied. It is obvious that the layers generated in aluminate solutions show smoother surfaces than those in silicate solutions. Moreover, an addition of fluorine ion can effectively control the layer porosity; therefore, it can enhance the properties of the layers.     

Compositional and structural identification of natural gas hydrates collected at site 1249 on ocean drilling program leg 204

In contrast to the structural studies of laboratory-grown gas hydrate, this study has been performed on naturally grown clathrate hydrates from the sea floor. The PXRD pattern of natural gas hydrate shows that the sample had a structure I hydrate. The¹³C NMR spectrum was obtained for the natural gas hydrate sample in order to identify the cage occupancy of guest molecules and determine the hydration number. The NMR spectrum reveal that the natural gas hydrates used in this study contain only methane with no noticeable amount of other hydrocarbons. The existence of two peaks at different chemical shifts indicates that methane molecules are encapsulated in both large and small cages. In addition, Raman spectroscopic analysis is also carried out to identify natural hydrates and compared with the NMR results. Investigating the composition and structure of natural gas hydrates is essential for applying natural gas hydrates as a novel energy source.     

An elastic compensation model for frame-based scheduling algorithms in wireless networks

Scheduling algorithms for high-speed wireless networks need to be simple to implement for serving packets while ensuring quality-of-service (QoS). The ordinary frame-based scheduling principle is well-known for providing fair service with low implementation complexity. However, existing frame-based scheduling algorithms cannot properly handle location-dependent burst errors in wireless networks. To utilize the advantages of frame-based scheduling algorithms in error-prone wireless networks, we propose an elastic compensation model that provides not only smooth compensations without any service disruptions of flows but also flexible compensations to flows that experience frequent errors to provide flows with fairness of service. From our analysis and simulation studies, we found that the proposed compensation model shows smooth compensation performance without any service disruption periods and good fairness performance when channel errors occur.     

Negative Offset Operation of Four-Transistor CMOS Image Pixels for Increased Well Capacity and Suppressed Dark Current

This letter presents an electrical method to reduce dark current as well as increase well capacity of four-transistor pixels in a CMOS image sensor, utilizing a small negative offset voltage to the gate of the transfer (TX) transistor particularly only when the TX transistor is off. As a result, using a commercial pixel in a 0.18 mum CMOS process, the voltage drop due to dark current of the pinned photodiode (PPD) is reduced by 6.1 dB and the well capacity is enhanced by 4.4 dB, which is attributed to the accumulated holes and the increased potential barrier near the PPD, respectively.     

All-to-all personalized communication in multidimensional torus andmesh networks

All-to-all personalized communication commonly occurs in many important parallel algorithms, such as FFT and matrix transpose. This paper presents new algorithms for all-to-all personalized communication or complete exchange in multidimensional torus- or mesh-connected multiprocessors. For an R×C torus or mesh where R⩽C, the proposed algorithms have time complexities of O(C) message startups and O(RC²) message transmissions. The algorithms for three- or higher-dimensional tori or meshes follow a similar structure. Unlike other existing message-combining algorithms in which the number of nodes in each dimension should be a power-of-two and square, the proposed algorithms accommodate non-power-of-two tori or meshes where the number of nodes in each dimension need not be power-of-two and square. In addition, destinations remain fixed over a larger number of steps in the proposed algorithms, thus making them amenable to optimizations. Finally, the data structures used are simple, hence making substantial savings of message-rearrangement time     

A constructive design method for two-layer perceptrons and its applicatio to the design of modular neural networks

Abstract: A multilayer perceptron is known to be capable of approximating any smooth function to any desired accuracy if it has a sufficient number of hidden neurons. But its training, based on the gradient method, is usually a time consuming procedure that may converge toward a local minimum, and furthermore its performance is greatly influenced by the number of hidden neurons and their initial weights. Usually these crucial parameters are determined based on the trial and error procedure, requiring much experience on the designer's part.
In this paper, a constructive design method (CDM) has been proposed for a two-layer perceptron that can approximate a class of smooth functions whose feature vector classes are linearly separable. Based on the analysis of a given data set sampled from the target function, feature vectors that can characterize the function'well'are extracted and used to determine the number of hidden neurons and the initial weights of the network. But when the classes of the feature vectors are not linearly separable, the network may not be trained easily, mainly due to the interference among the hyperplanes generated by hidden neurons. Next, to compensate for this interference, a refined version of the modular neural network (MNN) has been proposed where each network module is created by CDM. After the input space has been partitioned into many local regions, a two-layer perceptron constructed by CDM is assigned to each local region. By doing this, the feature vector classes are more likely to become linearly separable in each local region and as a result, the function may be approximated with greatly improved accuracy by MNN. An example simulation illustrates the improvements in learning speed using a smaller number of neurons.