Modeling the effect of deep traps on the capacitance–voltage characteristics of p-type Si-doped GaAs Schottky diodes grown on high index GaAs substrates

Numerical simulation, using SILVACO-TCAD, is carried out to explain experimentally observed effects of different types of deep levels on the capacitance–voltage characteristics of p-type Si-doped GaAs Schottky diodes grown on high index GaAs substrates. Two diodes were grown on (311)A and (211)A oriented GaAs substrates using Molecular Beam Epitaxy (MBE). Although, deep levels were observed in both structures, the measured capacitance–voltage characteristics show a negative differential capacitance (NDC) for the (311)A diodes, while the (211)A devices display a usual behaviour. The NDC is related to the nature and spatial distribution of the deep levels, which are characterized by the Deep Level Transient Spectroscopy (DLTS) technique. In the (311)A structure only majority deep levels (hole traps) were observed while both majority and minority deep levels were present in the (211)A diodes. The simulation, which calculates the capacitance–voltage characteristics in the absence and presence of different types of deep levels, agrees well with the experimentally observed behaviour.     

Electrochemical growth and characterization of iron doped cadmium sulfide thin films

Cadmium Sulfide and Ferrous doped Cadmium Sulfide thin films have been prepared on different substrates using an electrodeposition technique. Linear sweep voltammetric analysis has been carried out to determine deposition potential of the prepared films. X-ray diffraction analysis showed that the prepared films possess polycrystalline nature with hexagonal structure. Surface morphology and film composition have been analyzed using Scanning electron microscopy and Energy dispersive analysis by X-rays. Optical absorption analysis showed that the prepared films are found to exhibit Band gap value in the range between 2.3, 2.8 eV for Cadmium Sulfide and Ferrous doped Cadmium Sulfide.     

Development of a computer input device for patients with tetraplegia

It is necessary for medical staff members to evaluate the computer input ability of patients with spinal cord injury (SCI) during the patients' rehabilitation. In this paper, we describe a system for measuring and evaluating the computer input ability of SCI patients. We measured the position locus of the mouse cursor when a patient operates a computer using a ball mouse. After this measurement, we calculated three time parameters to evaluate the computer input ability of the patient. In addition, we developed a new computer input device for patients, and showed by means of the three time parameters that this device was effective for some patients.     

Radio resource management for a mobile network with TD-CDMA

In the paper, we proposed a resource allocation method employing maximal compatible cliques to make use of channel bandwidth as efficiently as possible in a TD-CDMA system. Furthermore, the strength of beacon signals was also measured to decide whether or not to reserve resources for hand-off users, in order to reduce their dropping probabilities. Finally, we conducted several experiments to validate that our method could make use of the finite resources efficiently, thereby revealing better blocking probabilities and dropping probabilities than other methods.     

Favorable influence of ssDNA-functionalized SWCNT on the navigation pattern of C. elegans

Microsystem Technologies - Single-Walled Carbon Nanotubes (SWCNTs) are widely used as potential carriers in drug delivery systems. The objective of this work was to observe the effects of pristine,...     

Human language technology and communicative disabilities: requirements and possibilities for the future

For some years now, the Nederlandse Taalunie (Dutch Language Union) has been active in promoting the development of human language technology (HLT) applications for speakers of Dutch with communicative disabilities. The reason is that HLT products and services may enable them to improve their communication skills and verbal autonomy. We sought to identify a minimum common set of HLT resources that is required to develop tools for a wide range of communication disabilities. In order to reach this goal, we investigated the specific needs of communicatively disabled people and related these needs to the underlying HLT software components. By analysing the availability and quality of these essential HLT resources, we were able to identify which of the crucial elements need further research and development to become usable for developing applications for communicatively disabled speakers of Dutch. The results obtained in the current survey can be used to inform policy institutions on how they can stimulate the development of HLT resources for this target group. In the current survey results were obtained for Dutch, but a similar approach can also be applied to other languages.     

Speaker adaptive voice source modeling with applications to speech coding and processing

We discuss the use of low-dimensional physical models of the voice source for speech coding and processing applications. A class of waveform-adaptive dynamic glottal models and parameter identification procedures are illustrated. The model and the identification procedures are assessed by addressing signal transformations on recorded speech, achievable by fitting the model to the data, and then acting on the physically oriented parameters of the voice source. The class of models proposed provides in principle a tool for both the estimation of glottal source signals, and the encoding of the speech signal for transformation purposes. The application of this model to time stretching and to fundamental frequency control (pitch shifting) is also illustrated. The experiments show that copy synthesis is perceptually very similar to the target, and that time stretching and “pitch extrapolation” effects can be obtained by simple control strategies.     

Ellipsoidal neighbourhood outlier factor for distributed anomaly detection in resource constrained networks

Anomaly detection in resource constrained wireless networks is an important challenge for tasks such as intrusion detection, quality assurance and event monitoring applications. The challenge is to detect these interesting events or anomalies in a timely manner, while minimising energy consumption in the network. We propose a distributed anomaly detection architecture, which uses multiple hyperellipsoidal clusters to model the data at each sensor node, and identify global and local anomalies in the network. In particular, a novel anomaly scoring method is proposed to provide a score for each hyperellipsoidal model, based on how remote the ellipsoid is relative to their neighbours. We demonstrate using several synthetic and real datasets that our proposed scheme achieves a higher detection performance with a significant reduction in communication overhead in the network compared to centralised and existing schemes.