Low-noise properties of dry gate recess etched InP HEMTs

Lattice-matched InAlAs-InGaAs HEMTs with dry etched and wet etched gate recesses have been fabricated and both high-frequency and noise measurements have been carried out. The highly selective dry etching process ensures uniform device parameters. The small signal and noise performance shows only minor differences between the two transistor types. There is no evidence of detrimental effects caused by dry etching that reduce the electrical and noise performance of the device at high frequencies. These results show that dry etched InP HEMT's have suitable characteristics for the fabrication of MM-wave integrated circuits     

Preparation and sintering behaviour of submicronic Bi4Ti3O12 powders

Submicronic powders of Bi₄Ti₃O₁₂ with different morphologies were prepared by both the oxalate coprecipitation and the conventional mixing oxides methods. Compacts of the two calcined powders were sintered at 850–1100 °C in air, and the densification process was studied by non-isothermal and dilatometric experiments. A rapid densification (> 97% theoretical density) below 875 °C took place in the Bi₄Ti₃O₁₂ oxalate powder which was attributed to an extremely uniform pore-size distribution in the green compact. The possible formation of a transient liquid which promotes densification also was taken into account. The development of plate-like morphology in the conventional Bi₄Ti₃O₁₂ powder, broad pore-size distribution, and the plate-like colony formation, hindered rapid densification of the green compacts at low temperature. Microstructural development was studied; preliminary dielectric and electrical results are also reported.     

The modeling of mode choices of intercity freight transportation with the artificial neural networks and adaptive neuro-fuzzy inference system

Mode choice modeling is probably the most important element of transportation planning. It affects the general efficiency of travel and the allocation of resources. The development of mode choice models has recently witnessed significant advances in many fields, such as passenger and freight transport. A large number of mathematical models have been used to model the traveler’s choice of mode and destination and the shipper’s choice of mode, shipment size and supply market, among others. Such models are not only becoming almost intractable but also data intensive, difficult to calibrate and update, and intransferable. These models cover a wide range of mathematical complexity and accuracy. This paper describes a new approach to mode choice of intercity freight transport modeling using artificial neural networks (ANNs) and adaptive neuro-fuzzy inference system (ANFIS) models. The new approach combines the learning ability of artificial neural networks and the transparent nature of fuzzy logic. The approach is found to be highly adaptive and efficient in investigating non-linear relationships among different variables. The adaptive neuro-fuzzy inference system model is tested on the freight transport market in Turkey, Germany, France and Austria by using information on the freight flows and their attributes. The ANNs and ANFIS models are more successful in the representation of the non-linear behavior of mode choice of intercity freight transport compared to the classical models.     

Identification of EMG signals using discriminant analysis and SVM classifier

The electromyography (EMG) signal is a bioelectrical signal variation, generated in muscles during voluntary or involuntary muscle activities. The muscle activities such as contraction or relaxation are always controlled by the nervous system. The EMG signal is a complicated biomedical signal due to anatomical/physiological properties of the muscles and its noisy environment. In this paper, a classification technique is proposed to classify signals required for a prosperous arm prosthesis control by using surface EMG signals. This work uses recorded EMG signals generated by biceps and triceps muscles for four different movements. Each signal has one single pattern and it is essential to separate and classify these patterns properly. Discriminant analysis and support vector machine (SVM) classifier have been used to classify four different arm movement signals. Prior to classification, proper feature vectors are derived from the signal. The feature vectors are generated by using mean absolute value (MAV). These feature vectors are provided as inputs to the identification/classification system. Discriminant analysis using five different approaches, classification accuracy rates achieved from very good (98%) to poor (96%) by using 10-fold cross validation. SVM classifier gives a very good average accuracy rate (99%) for four movements with the classification error rate 1%. Correct classification rates of the applied techniques are very high which can be used to classify EMG signals for prosperous arm prosthesis control studies.     

HIV-2 Neutralization Sensitivity in Relation to Co-Receptor Entry Pathways and Env Motifs

HIV-2, compared to HIV-1, elicits potent and broadly neutralizing antibodies, and uses a broad range of co-receptors. However, both sensitivity to neutralization and breadth of co-receptor use varies between HIV-2 isolates, and the molecular background is still not fully understood. Thus, in the current study, we have deciphered relationships between HIV-2 neutralization sensitivity, co-receptor use and viral envelope glycoprotein (Env) molecular motifs. A panel of primary HIV-2 isolates, with predefined use of co-receptors, was assessed for neutralization sensitivity using a set of HIV-2 Env-directed monoclonal antibodies and co-receptor indicator cell lines. Neutralization sensitivity of the isolates was analysed in relation target cell co-receptor expression, in addition to amino acid motifs and predicted structures of Env regions. Results showed that HIV-2 isolates were more resistant to neutralizing antibodies when entering target cells via the alternative co-receptor GPR15, as compared to CCR5. A similar pattern was noted for isolates using the alternative co-receptor CXCR6. Sensitivity to neutralizing antibodies appeared also to be linked to specific Env motifs in V1/V2 and C3 regions. Our findings suggest that HIV-2 sensitivity to neutralization depends both on which co-receptor is used for cell entry and on specific Env motifs. This study highlights the multifactorial mechanisms behind HIV-2 neutralization sensitivity.     

Synthesis and electrochemical,in situ spectroelectrochemical,electrical and gas sensing properties of ball-type homo- and hetero-dinuclear phthalocyanines with four [1a,8b-dihydronaphtho[b]naphthofuro[3,2-d]furan-7,10-diyl] bridges

The new mono-nuclear Fe^II 2 and ball-type homo-dinuclear Fe^II–Fe^II 3 phthalocyanines have been synthesized from the corresponding 4,4′-(1a,8b-dihydronaphtho[b]naphthofuro[3,2-d]-furan-7,10-diyl)bis(oxy)diphthalonitrile 1 while ball-type hetero-dinuclear Fe^II–Co^II phthalocyanine 4 was synthesized from 2. The compounds have been characterized by elemental analysis, UV–vis, IR and MALDI-TOF-mass spectroscopies. The redox behaviours of the complexes were identified by controlled-potential coulometry, cyclic voltammetry and differential pulse voltammetry measurements on Pt in dimethylsulfoxide containing tetrabutylammonium perchlorate. The assignments of the redox processes and the understanding of the interactions between the metal phthalocyanine units in 3 and 4 were achieved by the combined evaluation of the voltammetric and in situ spectroelectrochemical outcomes. Complex 3 showed ring-based mixed-valence behaviour as a result of the considerable interaction between the phthalocyanine rings. On the other hand, the interactions between the two metal phthalocyanine units of 4 were found to be much weaker than those in 3. The potential application of molecular organic semiconductors needs the control adjustment of conductivity. Ac and dc conductivity measurements were performed with the applied external electric filed. At high frequency, the conduction follows the universal power law and conduction mechanism can be explained by classical hopping barriers mechanism for the system.     

Training Sequence Aided Signature Waveform Estimation

In code division multiple access channels multiuser detection techniques are known to be effective strategies to counter the presence of multiuser interference towards improving spectral efficiency. Generally, multiuser detectors can provide excellent performance only when the signature waveforms of all users are precisely known. Hence, the estimation of signature waveforms is a challenging issue in mobile communication systems. In this paper, we compare the performance of two short training sequence aided signature waveform estimators. One is maximum likelihood type signature waveform estimator that requires the knowledge of spreading sequences and short training sequences. The other estimator is recently proposed based on subspace method and requires the knowledge of training sequences only. Through the simulations, we show the signature waveform estimation performance of both systems and the effect of the estimation error on the performance of a multiuser detector. The complexity comparisons of both systems are also given. We use the term “signature waveform” to refer to the convolution of the channel and the spreading code throughout the paper. Hasan AMCA was born in 1961 in Nicosia-Cyprus. He graduated from the Higher Technological Institute in Magosa – Cyprus (which is renamed later as Eastern Mediterranean University). He joined EMU in 1985 after receiving a M.Sc. (Digital Signal Processing) degree from the University of Essex in England (1985). He took his Ph.D. (Mobile Communications) from the University of Bradford where he was on a Commonwealth scholarship. He has been teaching in the Electrical and Electronic Engineering Department of Eastern Mediterranean University since 1993 where he also served as the Vice Chairman from Spring 1998 to Spring 2000. He has been appointed as the Director of the School of Computing and Technology of the EMU since Spring 2000. His research interests include Multi User Detection of CDMA signals, Adaptive Equalisation, Multi Carrier Systems, Mobile Radio Systems and Networks, Internet and Information Technology Applications in Education. Ahmet Rizaner was born in Larnaca, Cyprus, on January 31, 1974. He received the B.S. and M.S. degrees in Electrical and Electronics Engineering from the Eastern Mediterranean University, Famagusta, North Cyprus, in 1996 and 1998, respectively. He completed his PhD. degree in Electrical and Electronic Engineering in Eastern Mediterranean University and joined Eastern Mediterranean University as a lecturer in 2004. He is lecturing in the School of Computing and Technology. His main research interests include CDMA communications, adaptive channel estimation, and multiuser detection technique. Kadri Hacioğlu was born in Nicosia, Cyprus. He received the B.Sc., M.Sc., and Ph.D. degrees in electrical and electronic engineering from the Middle East Technical University, Ankara, Turkey, in 1980, 1984, and 1990, respectively. After his two-year military service, in 1992, he joined the faculty of Eastern Mediterranean University, Magosa, North Cyprus, as an Assistant Professor, and became an Associate Professor in 1997. While there, he taught several classes on electronics, digital communications, speech processing and neural networks. During this time, he conducted research on applying fuzzy logic, neural networks, and genetic algorithms to signal processing and communications problems. From 1998 to 2000, he was a Visiting Professor in the Department of Computer Science, University of Colorado, Boulder. Here, he taught classes on neural networks and continued his research. Since 2000, he has been a Research Associate at the Center for Spoken Language Research, University of Colorado. He has authored or coauthored numerous papers and supervised a dozen M.Sc./Ph.D. theses. His current research interests are concept-based language modeling, speech understanding, natural language generation, and search methods in speech recognition/understanding. He also does research on multiuser detection and equalization in CDMA systems. Ali Hakan Ulusoy was born in Eskişehir, Turkey, on June 3, 1974. He graduated from the double major program of the department of Electrical and Electronic Engineering and department of Physics in Eastern Mediterranean University as the first rank student of Faculty of Engineering in 1996. He received his M.S. degree in Electrical and Electronic Engineering in Eastern Mediterranean University in 1998. He completed his Ph.D. degree in Electrical and Electronic Engineering in Eastern Mediterranean University and joined Eastern Mediterranean University as a lecturer in 2004. He is lecturing in the School of Computing and Technology. His current research interests include receiver design, multi-user detection techniques, blind and trained channel estimation in Code Division Multiple Access (CDMA).     

Experimental study for high effective mobility with directly deposited HfO2/La2O3 MOSFET

We experimentally examine the effective mobility in nMOSFETs with La₂O₃ gate dielectrics without SiO_x-based interfacial layer. The reduced mobility is mainly caused by fixed charges in High-k gate dielectrics and the contribution of the interface state density is approximately 30% at N_s = 5 × 10¹¹ cm^?2 in the low 10¹¹ cm^?2 eV^?1 order. It is considered that one of the effective methods for improving mobility is to utilize La-silicate layer formed by high temperature annealing. However, there essentially exists trade-off relationship between high temperature annealing and small EOT.