PLATOP: a novel planarized trench isolation and field oxideformation using poly-silicon

A novel isolation scheme named planarized trench isolation and field oxide formation using poly-silicon (PLATOP) Is described. PLATOP is applicable to high-performance submicron VLSI since it results in encroachment-free shallow trenches, and planarized field oxide. The process offers poly silicon-filled deep trenches. The process also relies on noncritical lithography and novel etch processes to planarize the deposited poly-silicon from the top of the active areas, and oxidation to consume the poly-silicon in the field regions. Electrical results are presented proving the viability of the isolation scheme     

A simplified method for modelling the effect of blinds on window thermal performance

An approximate method is presented for predicting the effect of a louvered blind on the centre‐glass thermal performance of a fenestration. The method combines a one‐dimensional heat transfer model with data from a numerical simulation of the window and blind. Sample results for a blind mounted on the indoor surface of a window show the effect of blind slat angle on heat transmission. Both summer and winter conditions are considered. The results show that a louvered blind can improve the U‐value of a standard double‐glazed window by up to 37%. Also, the radiation heat exchange with the room can be dramatically reduced (by up to 60%), which will improve the level of occupant comfort. However, there was found to be a trade‐off between U‐value and occupant comfort; placing the blind closer to the window improves the U‐value, but increases the radiation heat exchange with the room. The predictions from the present simplified method compare well with results from a full two‐dimensional computational fluid dynamics solution of the conjugate blind/window interaction. Copyright © 2005 John Wiley & Sons, Ltd.     

Pivotal Role of Phytohormones and Their Responsive Genes in Plant Growth and Their Signaling and Transduction Pathway under Salt Stress in Cotton

The presence of phyto-hormones in plants at relatively low concentrations plays an indispensable role in regulating crop growth and yield. Salt stress is one of the major abiotic stresses limiting cotton production. It has been reported that exogenous phyto-hormones are involved in various plant defense systems against salt stress. Recently, different studies revealed the pivotal performance of hormones in regulating cotton growth and yield. However, a comprehensive understanding of these exogenous hormones, which regulate cotton growth and yield under salt stress, is lacking. In this review, we focused on new advances in elucidating the roles of exogenous hormones (gibberellin (GA) and salicylic acid (SA)) and their signaling and transduction pathways and the cross-talk between GA and SA in regulating crop growth and development under salt stress. In this review, we not only focused on the role of phyto-hormones but also identified the roles of GA and SA responsive genes to salt stress. Our aim is to provide a comprehensive review of the performance of GA and SA and their responsive genes under salt stress, assisting in the further elucidation of the mechanism that plant hormones use to regulate growth and yield under salt stress.     

Spectroscopic studies of sol–gel grown CdS nanocrystalline thin films for optoelectronic devices

CdS is one of the highly photosensitive candidate of II–VI group semiconductor material. Therefore CdS has variety of applications in optoelectronic devices. In this paper, we have fabricated CdS nanocrystalline thin film on ultrasonically cleaned glass substrates using the sol–gel spin coating method. The structural and surface morphologies of the CdS thin film were investigated by X-ray Diffraction (XRD) and Field Emission Scanning Electron Microscopy (FESEM) respectively. The surface morphology of thin films showed that the well covered substrate is without cracks, voids and hole. The round shape particle has been observed in SEM micrographs. The particles sizes of CdS nanocrystals from SEM were estimated to be～10–12 nm. Spectroscopic properties of thin films were investigated using the UV–vis spectroscopy, Photoluminescence and Raman spectroscopy. The optical band gap of the CdS thin film was estimated by UV–vis spectroscopy. The average transmittance of CdS thin film in the visible region of solar spectrum found to be～85%. Optical band gap of CdS thin film was calculated from transmittance spectrum ～2.71 eV which is higher than bulk CdS (2.40 eV) material. This confirms the blue shifting in band edge of CdS nanocrystalline thin films. PL spectrum of thin films showed that the fundamental band edge emission peak centred at 459 nm also recall as green band emission.     

Interference Mitigation Based on Radio Aware Channel Assignment for Wireless Mesh Networks

An intricate network deployment for high demand users leads to simultaneous transmission in wireless mesh networks. Multiple radios are adapted to individual nodes for improving network performance and Quality of Service (QoS). However, whenever multiple radios are assigned to the same channel, co-located radio interference occurs, which poses a major drawback. This paper proposes a Radio aware Channel Assignment (Ra-CA) mechanism based on a direct graphical model for mitigation of interference in multi-radio multi-channel networks. Initially, the co-located radio interference is identified by classifying non-interfering links for simultaneous transmission in the network. Proposed channel assignment mechanism helps in allocating the minimal number of channels to the network that mitigate co-located radio interference. Performance analysis of the proposed Ra-CA strategy is carried out compared with other existing techniques, like Breadth First Search-Channel Assignment (BFS-CA) and Maximal Independent Set Channel Assignment (MaIS-CA), in multi-radio networks. Simulation results demonstrate that the proposed channel assignment scheme is more efficient compared to the existing ones, in terms of QoS parameters like, packet drop rate, packet delivery ratio, transmission delay and throughput.     

Security and key management in IoT‐based wireless sensor networks: An authentication protocol using symmetric key

Wireless sensor networks (WSN) consist of hundreds of miniature sensor nodes to sense various events in the surrounding environment and report back to the base station. Sensor networks are at the base of internet of things (IoT) and smart computing applications where a function is performed as a result of sensed event or information. However, in resource‐limited WSN authenticating a remote user is a vital security concern. Recently, researchers put forth various authentication protocols to address different security issues. Gope et al presented a protocol claiming resistance against known attacks. A thorough analysis of their protocol shows that it is vulnerable to user traceability, stolen verifier, and denial of service (DoS) attacks. In this article, an enhanced symmetric key‐based authentication protocol for IoT‐based WSN has been presented. The proposed protocol has the ability to counter user traceability, stolen verifier, and DoS attacks. Furthermore, the proposed protocol has been simulated and verified using Proverif and BAN logic. The proposed protocol has the same communication cost as the baseline protocol; however, in computation cost, it has 52.63% efficiency as compared with the baseline protocol.     

MIMO iterative receiver SNR estimation strategies for link to system interfacing

This paper presents link to system (L2S) interfacing technique for multiple input and multiple output (MIMO) iterative receivers. In L2S interfacing, usually the post detection signal to noise ratio (SNR)‐based frame error rate lookup tables (LUT) are used to predict the link level performance of receivers. While L2S interfacing for linear MIMO receivers can be conveniently implemented, it is more challenging for MIMO iterative receivers due to unavailability of the closed form SNR expressions. In this paper, we propose three methods for post detection SNR estimation for MIMO iterative receivers. The first is based on the QR decomposition of the channel matrix, the second relies on the residual noise calculation based on the soft symbols, and the third exploits the closed form SNR expressions for linear receivers. A link to system interface model for iterative receivers is developed for evaluating the reference curves for different modulation and coding schemes, and results are validated by comparing the simulated and predicted frame error rates. It is shown that linear and residual noise‐based SNR approximations result in a very good prediction performance whereas the performance of QR decomposition‐based method degrades for higher order modulations and coding schemes. This paper presents link to system interfacing technique for MIMO iterative receivers. A link to system interface model for iterative receivers is developed for evaluating the reference curves for different modulation and coding schemes, and results are validated by comparing the simulated and predicted frame error rates. Three post detection SNR evaluation schemes have been proposed for link to system interfacing all of which give good prediction performance especially at lower order modulation.     

Exploring network-level performances of wireless nanonetworks utilizing gains of different types of nano-antennas with different materials

Wireless nanonetworks are not a simple extension of traditional communication networks at the nano-scale. Owing to being a completely new communication paradigm, existing research in this field is still at an embryonic stage. Furthermore, most of the existing studies focus on performance enhancement of nanonetworks via designing new channel models and routing protocols. However, the impacts of different types of nano-antennas on the network-level performances of the wireless nanonetworks remain still unexplored in the literature. Therefore, in this paper, we explore the impacts of different well-known types of antennas such as patch, dipole, and loop nano-antennas on the network-level performances of wireless nanonetworks. We also investigate the performances of nanonetworks for different types of traditional materials (e.g., copper) and for nanomaterials (e.g., carbon nanotubes and graphene). We perform rigorous simulation using our customized ns-2 simulation to evaluate the network-level performances of nanonetworks exploiting different types of nano-antennas using different materials. Our evaluation reveals a number of novel findings pertinent to finding an efficient nano-antenna from its several alternatives for enhancing network-level performances of nanonetworks. Our evaluation demonstrates that a dipole nano-antenna using copper material exhibits around 51% better throughput and about 33% better end-to-end delay compared to other alternatives for large-size nanonetworks. Furthermore, our results are expected to exhibit high impacts on the future design of wireless nanonetworks through facilitating the process of finding the suitable type of nano-antenna and suitable material for the nano-antennas.

     

Femtojoule-Power-Consuming Synaptic Memtransistor Based on Mott Transition of Multiphasic Vanadium Oxides

To realize the potential of Mott transition of multiphasic vanadium oxides (VO_x) for memory applications, the development of VO_x memtransistors on SiO₂ wafer is introduced. Through electrical characterizations, the volatile memory behaviors of the VO_x memtransistors are observed in both two- and three-terminal measurements. Their capacitive memory and resistive switching mechanisms are strongly related to the mixed VO_x/SiO₂ interface (called VSiO_x). VSiO_x supports the Mott transition in VO_x at low bias voltages (<0.5 V), leading to the low power consumption of the memtransistor. Moreover, the fast switching time (≈35 ns) and tunable memory retention with the synaptic functions (potentiation and depression) of the memtransistors (by using the gate and drain biases) are demonstrated. Overall, the findings open up major opportunities for constructing ultrafast and femto-joule power-consuming neuromorphic devices.     

A classification-based privacy-preserving decision-making for secure data sharing in Internet of Things assisted applications

The introduction of the Internet of Things (IoT) paradigm serves as pervasive resource access and sharing platform for different real-time applications. Decentralized resource availability, access, and allocation provide a better quality of user experience regardless of the application type and scenario. However, privacy remains an open issue in this ubiquitous sharing platform due to massive and replicated data availability. In this paper, privacy-preserving decision-making for the data-sharing scheme is introduced. This scheme is responsible for improving the security in data sharing without the impact of replicated resources on communicating users. In this scheme, classification learning is used for identifying replicas and accessing granted resources independently. Based on the trust score of the available resources, this classification is recurrently performed to improve the reliability of information sharing. The user-level decisions for information sharing and access are made using the classification of the resources at the time of availability. This proposed scheme is verified using the metrics access delay, success ratio, computation complexity, and sharing loss.