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Content-centric networking (CCN) introduces a paradigm shift from a host centric to an information centric communication model for future Internet architectures. It supports the retrieval of a particular content regardless of the physical location of the content. Content caching and content delivery networks are the most popular approaches to deal with the inherent issues of content delivery on the Internet that are caused by its design. Moreover, intermittently connected mobile environments or disruptive networks present a significant challenge to CCN deployment. In this paper, we consider the possibility of using mobile users in improving the efficiency of content delivery. Mobile users are producing a significant fraction of the total Internet traffic, and modern mobile devices have enough storage to cache the downloaded content that may interest other mobile users for a short period too. We present an analytical model of the CCN framework that integrates a delay tolerant networking architecture into the native CCN, and we present large-scale simulation results. Caching on mobile devices can improve the content retrieval time by more than 50%, while the fraction of the requests that are delivered from other mobile devices can be more than 75% in many cases.

Automated screening is employed to assist skin specialists in accurately detecting skin lesions at an early stage. Multilevel thresholding is a widely popular and efficient technique for enhancing the classification of skin cancer images. This paper proposes improved PSO with a novel visit table and multiple directions search strategies to develop the performance of the multilevel thresholding. A visit table strategy has been developed that prevents unnecessary searches of the original particle swarm optimization (PSO) algorithm by allowing the discovery of new points by making fewer visits to frequently visited points and their neighbors. Besides, a multiple directions search strategy has been introduced for the PSO to increase the diversity of the population and overcome the stuck at the local optimum by enhancing exploration ability. The qualitative, quantitative, and scalability analyzes of the improved PSO (IPSO) method were carried out on 50 benchmark functions and the highest performance was achieved with the proposed method in most of these functions. Secondly, a multilevel image segmentation application is presented on skin cancer images using two-dimensional (2D) non-local means histograms, improved PSO and Renyi’s entropy. In this work, the ISIC 2017 skin cancer image dataset is used for segmentation application and various performance evaluation metrics are used. The obtained results are compared with seven state-of-the-art approaches to show the efficiency of the proposed approach. It can be noted from the obtained results that, the proposed method outperforms the compared method based on the average of evaluation metrics for all skin cancer images. The best results in SSIM value of 0.8285, FSIM value of 0.7332, and PSNR value of 19.0576 are achieved by using the proposed method in skin cancer image segmentation. Hence, our proposed method is ready to be tested with huge databases and can aid skin specialists in making an accurate diagnosis.

In the islanded mode of operation of a DC microgrid, the main objective is to achieve proportional sharing of load power among sources and to maintain the source voltage within the specified limit. The droop control technique is widely used to achieve these objectives. Nevertheless, the performance of the traditional droop control technique becomes poor in the case of DC Microgrid including sources having unequal values of nominal voltages. The difference in nominal voltages arises due to errors in the measurement of the voltage feedback signal. The unequal values of nominal voltages lead to errors in the proportional sharing of the load current among the source converters. The mismatch in nominal voltages leads to a flow of circulating current among sources. To minimize this circulating current flowing among the sources, various distributed secondary controllers are suggested in the literature. However, these controllers require prior information of circulating current flowing among sources or accurate measurement of line parameters. Further, the applicability of these controllers is valid for the radial configuration of the DC microgrid. To resolve these issues, a distributed secondary controller is proposed in this paper which shifts the droop characteristics of the source parallel to the voltage axis. The proposed controller does not require prior information of circulating current and no estimation of line parameters. The proposed controller requires the evaluation of proportional current to minimize the circulating current. The proportional value of current for a given source is calculated using the formation of power ratings of sources and initial values of their droop gains. The proposed controller ensures the accurate sharing of the load current among source converters in case of a microgrid having sources of unequal capacity or communication link failure. Further, the voltage regulation is maintained within the defined limit. A small signal model is derived to show the effect of the variation of parameters of the proposed controller on the stability of the DC microgrid. The efficacy of the proposed controller is validated with the help of results capture using the Controller Hardware-in-Loop (CHIL) approach which includes a Real-Time Digital Simulator (RTDS) and Digital Signal Processor (DSP).

The clinical application of a real-time artificial intelligence (AI) image processing system to diagnose upper gastrointestinal (GI) malignancies remains an experimental research and engineering problem. Understanding these commonly used technical techniques is required to appreciate the scientific quality and novelty of AI studies. Clinicians frequently lack this technical background, and AI experts may be unaware of such clinical relevance and implications in daily practice. As a result, there is a growing need for a multidisciplinary, international assessment of how to conduct high-quality AI research in upper GI malignancy detection. This research will help endoscopists build approaches or models to increase diagnosis accuracy for upper GI malignancies despite variances in experience, education, personnel, and resources, as it offers real-time and retrospective chances to improve upper GI malignancy diagnosis and screening. This comprehensive review sheds light on potential enhancements to computer-aided diagnostic (CAD) systems for GI endoscopy. The survey includes 65 studies on automatic upper GI malignancy diagnosis and evaluation, which are compared by endoscopic modalities, image counts, models, validation methods, and results. The main goal of this research is to assess and compare each AI method’s current stage and potential improvement to boost performance, maturity, and the possibility to open new research areas for the application of a real-time AI image recognition system that diagnoses upper GI malignancies. The findings of this study suggest that Support Vector Machines (SVM) are frequently utilized in gastrointestinal (GI) image processing within the context of machine learning (ML). Moreover, the analysis reveals that CNN-based supervised learning object detection models are widely employed in GI image analysis within the deep learning (DL) context. The results of this study also suggest that RGB is the most commonly used image modality for GI analysis, with color playing a vital role in detecting bleeding locations. Researchers rely on public datasets from 2018–2019 to develop AI systems, but combining them is challenging due to their unique classes. To overcome the problem of insufficient data to train a new DL model, a standardized database is needed to hold different datasets for the development of AI-based GI endoscopy systems.

The load frequency control (LFC) in modern power system like microgrid has turned out to be significantly challenging due to the high penetration of renewable energy sources (RESs) and the consequent reduction of overall system inertia. The inverter-equipped RESs like solar and wind power generation units, besides the load variations can prompt sustained frequency fluctuations in microgrid and further lead to system instability, power outages, and even complete system blackout in the worst case. As a solution to the concerns of intermittent power source integration and resulting microgrid frequency instability, in this work, two robust LFC schemes using conventional linear quadratic gaussian (LQG) and modified LQG with linear quadratic integral (LQI) control schemes are proposed for secondary/battery energy storage system (BESS)-based auxiliary (virtual inertia (VI)) control of islanded/non-linear microgrid. The efficacy of the suggested control strategy is confirmed through MATLAB/SIMULINK simulations and by comparing with other different control schemes under various scenarios of distinct load and RES disturbance input profiles. The simulation results exhibited superior frequency regulation performance for the proposed control mechanisms over other types of control schemes. The proposed control schemes also ensure fast settling of frequency transients and help improve frequency stability under stochastic loads and random RES output power. In addition to the development of an effective robust controller, the vulnerability of the microgrid LFC system towards the denial of service (DoS) attack is analyzed for different control schemes. The vulnerability analysis is performed in the presence and absence of local auxiliary control loop and the remote secondary measurement communication channel is considered as the DoS attack point. The simulation results indicate that the local auxiliary control mechanism can not only help to improve frequency stability but also helps to add cyber-attack resilience to an extent when the secondary control loop is under attack.

In this article, Pr–Mn substituted X-type hexagonal ferrite Sr1–xPrxCu2MnyFe28–yO46 with concentrations of $x =0$ , 0.02, 0.06, 0.1 and $y =0$ , 0.1, 0.3, 0.5 were prepared by using cotton soaked method. The main intention of this article was to explain the microwave absorption phenomenon theoretically and to perceive the effect of Pr–Mn substitution on structural, magnetic, thermal, and microwave absorption properties of X-type hexagonal ferrites. Moreover, the fabrication of material suitable for microwave absorption devices, permanent magnets, and for recording media applications was also aimed in present investigation. The XRD patterns reveal that all the prepared samples possess X-type hexagonal structure. A gradual and slight increase in both lattice parameters “ $a$ ” and “ $c$ ” values was observed with Pr–Mn substitution. The metal–oxygen stretching (M–O) vibrations in the FTIR spectrum at a low frequency indicates the presence of single phase in synthesized material. The enhancement in magnetic properties (saturation magnetization, retentivity, and coercivity) has been observed with the substitution of Pr–Mn contents in pure ferrites. A maximum reflection loss (RL) of −27.21 dB at 11.891 GHz was attained by Pr–Mn-substituted ferrites and reflectivity results agree well with RL results. Microwave absorption property of this substituted material made it a potential candidate to be used in super high frequency (SHF) devices. [ABSTRACT FROM AUTHOR]

We present a secure transmission method for orthogonal frequency division multiplexing (OFDM) signaling between legitimate nodes (Alice and Bob) communicating in time-division duplex (TDD) mode under an active attack. An active eavesdropper carries out pilot contamination attack in pilot phase by transmitting the pilot signal of the legitimate user and jamming attack in data phase. In the proposed method, Alice estimates the reciprocal channel between Alice and Bob by employing successive cancellation of the pilot contamination and interference from an active eavesdropper in pilot and data phases, respectively. We estimate reciprocal channels of legitimate users and eavesdropper. The precoder design at Alice from the estimated channels steers information towards Bob and artificial noise towards Eve in order to enhance the secrecy capacity of channel of the legitimate nodes. The simulation results show that the proposed method effectively estimates the channels of legitimate users and eavesdropper by removing the impact of contamination attack. Consequently, legitimate channel achieves higher secrecy capacity.

Shannon’s Index of Difficulty ( $ID$ ), reputable for quantifying the perceived difficulty of pointing tasks as a logarithmic relationship between movement-amplitude ( $A$ ) and target-width ( $W$ ), is used for modeling the corresponding observed movement-times ( $MT_{O}$ ) in such tasks in controlled experimental setup. However, real-life pointing tasks are both spatially and temporally uncontrolled, being influenced by factors, such as – human aspects, subjective behavior, the context of interaction, the inherent speed-accuracy trade-off, where, emphasizing accuracy compromises speed of interaction and vice versa. Effective target-width ( $W_{e}$ ) is considered as spatial adjustment for compensating accuracy. However, no significant adjustment exists in the literature for compensating speed in different contexts of interaction in these tasks. As a result, without any temporal adjustment, the true difficulty of an uncontrolled pointing task may be inaccurately quantified using Shannon’s $ID$ . To verify this, we propose ANTASID (A Novel Temporal Adjustment to Shannon’s ID) formulation with detailed performance analysis. We hypothesized a temporal adjustment factor ( $t$ ) as a binary logarithm of $MT_{O}$ , compensating for speed due to contextual differences and minimizing the non-linearity between movement-amplitude and target-width. Considering spatial and/or temporal adjustments to $ID$ , we conducted regression analysis using our own and Benchmark datasets in both controlled and uncontrolled scenarios of pointing tasks with a generic mouse. ANTASID formulation showed significantly superior fitness values and throughput in all the scenarios while reducing the standard error. Furthermore, the quantification of $ID$ with ANTASID varied significantly compared to the classical formulations of Shannon’s $ID$ , validating the purpose of this study.

Human intention is an internal, mental characterization for acquiring desired information. From interactive interfaces containing either textual or graphical information, intention to perceive desired information is subjective and strongly connected with eye gaze. In this work, we determine such intention by analyzing real-time eye gaze data with a low-cost regular webcam. We extracted unique features (e.g., Fixation Count, Eye Movement Ratio) from the eye gaze data of 31 participants to generate a dataset containing 124 samples of visual intention for perceiving textual or graphical information, labeled as either TEXT or IMAGE, having 48.39% and 51.61% distribution, respectively. Using this dataset, we analyzed 5 classifiers, including Support Vector Machine (SVM) (Accuracy: 92.19%). Using the trained SVM, we investigated the variation of visual intention among 30 participants, distributed in 3 age groups, and found out that young users were more leaned towards graphical contents whereas older adults felt more interested in textual ones. This finding suggests that real-time eye gaze data can be a potential source of identifying visual intention, analyzing which intention aware interactive interfaces can be designed and developed to facilitate human cognition.

In this paper, an adaptive N-path filter design technique is presented. The filter designed by this method can be reconfigured to different shapes, e.g., Butterworth or Chebyshev with variable bandwidth (BW), based on the user requirements. In addition, an analytical synthesis procedure is introduced to realize high-order bandpass filters (BPFs) based on N-path architecture with a prescribed set of specifications. A proof-of-concept BPF is fabricated and measured in a 65-nm CMOS process. The filter can be reconfigured to realize different filter shapes by changing coupling capacitors. The BW of the proposed filter is also tunable. The passband of the filter is tunable from 0.2 to 1.2 GHz with a gain of 14.5–18 dB, a noise figure of 3.7–5.5 dB, and a total power consumption of 37.5–52.7 mW. The channel BW can be varied from 20 to 40 MHz and the filter out-of-band third-order intercept point ( $\Delta f=50$ MHz) is 25 dBm. [ABSTRACT FROM AUTHOR]

The concept of introducing hybrid off-grid systems has made electricity accessible to areas that are far or have no access to grid network. This paper evaluates the techno-economic and environmental characteristics of a hybrid renewable energy system considering three different scheduling approaches, four different solar tracking systems, two different PV modules and eight scheduling scenarios to supply sustainable electricity to a rural community in Sierra Leone. Each scenario consists of a solar tracking system, a specific type of PV module and a scheduling approach. The aim is to find the most efficient and cost-effective scenario that meets the electrical demands of the village. Results revealed that the ‘Two axis tracking system’ generated the highest PV power, 28.8% additional power compared to the ‘No tracking system’ confirming the superiority of using a tracking system though it comes with initial cost repercussions. Also, systems that employed the use of Canadiasolar Dymond CS6K-285M-FG PV module tend to be more efficient and cost-effective than those that employed Sharp ND-250QCS PV module even with the same solar tracking technology and scheduling approach. From the best scheduling approach (third scheduling), Scenario 7 (SC#7) gives the lowest net present cost (NPC) of $ \$ $ 1.53M with $ \$ $ 0.173/kWh cost of energy (COE) and CO2 emission of 8.54 kg/yr making it the optimum scenario. A daily operation of the optimum scenario on both a sunny and rainy day confirms that the system is capable of supplying the required electricity for both rainy and dry seasons. Sensitivity analyses explain the high reliance of the system cost on the erratic inflation rate, discount rate and PV derating factor. Maintaining a healthy and sustainable environment depends on the minimum load ratio of both the biogas and diesel generators.

This paper presents a comprehensive evaluation of the effect of quasi oppositional - based learning method utilization in output tracking control through a swarm-based multivariable Proportional-Integral-Derivative (SMPID) controller, which is tuned by a novel performance index based on the step response characteristics in multi-input multi-output (MIMO) system. The role of the proposed quasi oppositional based SMPID controller is to modify the tracking strategy on AC/HVDC interconnected systems while reducing the related cost function. The proposed analysis is established considering the most highly cited, well-known tested and newly expanded swarm-based optimization algorithms (SBOAs), such as Grasshopper Optimization Algorithm (GOA), Grey Wolf Optimization (GWO), Artificial Fish Swarm Algorithm (AFSA), Artificial Bee Colony (ABC) and Particle Swarm Optimization (PSO). These methods are used in the tuning process of multivariable PID (MPID) controller for output tracking control of an interconnected AC/DC system with virtual inertia emulation-based HVDC capabilities. The virtual inertia-based HVDC model, which is using a derivative technique, is attached for enhancing the system frequency dynamics with fast power injection during the contingency. The potential possibility for achieving a suitable assessment about the velocity reaction, the flexibility response, and the accuracy of the tracking process is provided by four different scenarios which are operated by step load changes as essential inputs in AC/HVDC interconnected MIMO system. Also the proposed fitness function, as deviation characteristics of the step response in MIMO transfer function in virtual inertia emulation based HVDC model, is compared with integral time absolute error (ITAE), as the standard performance index in the optimization process. The results are compared with the conventional tuned MPID (C - MPID) controller using MATLAB software. The obtained analysis emphasizes how the tuned SMPID can significantly increase the capability of tracking control on the proposed AC/HVDC interconnected model.

Seawater desalination is one of the prominent solutions to cope with the water crisis. Suppling demanded energy and high investment and operation costs have been the most critical challenges facing the sustainable development of these plants. Previous studies have shown that renewable resources can be used as an alternative for sustainable desalination. Wind energy is a renewable resource with good potential, especially in coastal areas with a severe water crisis. In previous studies of wind-powered desalination units, typical values have been used for turbines, and also, the desalination unit’s capacity is considered equal to the peak water demand. In this paper, a new optimization model for wind-powered desalination is presented wherein the optimal number of turbines will be defined based on the technical specifications of different commercially available turbine types. Also, simultaneous selection of several different turbines is modeled and optimized. The proposed mathematical model is implemented on a test case to evaluate its effectiveness. The simulation results show the proposed model’s functionality to obtain optimal results while considering available commercial turbine types. The study demonstrates a 2.38 to 35.28 reduction in the net planning cost resulting from multiple turbine technology selections and optimization concerning the various single turbine installation cases.

The sensitivity analysis becomes particularly critical for voltage stability analysis due to the fluctuation in power outputs of renewable energy resources. Besides, impacts of different load modeling and the operation mode of Distributed Generations (DGs) are not addressed in the well-known sensitivity analysis methods. Therefore, this work presents a new sensitivity analysis approach to find the relation between the Voltage Stability Margin (VSM) and the control variables of power systems, considering the voltage dependent characteristics of loads and DGs. The sensitivity analysis is performed on VSM, defined from equivalent nodal analysis, via its differential equation. To include the voltage dependent characteristics, loads are modeled as polynomial function (ZIP model) and DGs are considered to be operated with constant current and constant power modes. Based on this analysis, the sensitivity of VSM can be directly obtained by taking the derivatives of nodal voltages with respect to control variables. The validity of the developed approach is demonstrated on the IEEE 118 bus system.

Faults in the power system need appropriate maintenance actions at the fault point to fix the problem immediately. A high percentage of the short circuit faults in power systems occur on the transmission system where the lines pass through different harsh climates and experience outdoor environmental conditions. The repairing procedure of the faulty line requires determining the accurate fault location. Fast and accurate fault location of transmission networks play an important role in modern power systems to improve the system reliability and stability. A fault locator is an apparatus that determines the location of the fault in the transmission system by acquiring the proper measured quantities, i.e. the voltages and currents at the lines terminals. As such, the utilities can repair and fix the problem rapidly after determining the location of the fault using the analytical and numerical methods provided in fault locators. This research explores various fault location techniques of transmission networks in detail as a vital requirement for operating the modern power system more secure and reliable. In this survey, different new methods of fault location such as i) distance relay algorithm, ii) traveling wave, iii) artificial intelligence, iv) wide-area, v) time reversal theory, vi) differential equations, and vii) impedance calculation methods are reviewed and investigated to illustrate their pros and cons inaccurate fault location for complex modern power networks. In addition, these methods are assessed to compare their requirements, abilities and shortcomings. Moreover, using the provided extensive analysis in the paper, and based on the useful experiences of the authors, some beneficial topics and suggestions are proposed for future works and improved algorithms in the field of fault location.

This paper presents a tunable active bandpass filter (BPF) with adjustable transmission zeros (TZs) close to the passband for software-defined radio (SDR) applications. The RF front-end frequency selectivity is enhanced by the creation of TZs that also improve the out-of-band (OOB) input-referred third-order intercept point (IIP3). The filter is based on two-path signal cancellation and consists of a tunable BPF in parallel with two tunable bandstop filters. This combination ensures the correct amplitude and phase relationships across a wide tuning range to create adjustable TZs without sacrificing the gain of the passband. This paper presents in detail the design considerations and guidelines, as well as analysis of the filter performance in the presence of nonidealities such as parasitics and imperfect clock signal shape. The proposed filter is implemented with high- $Q~N$ -path filter blocks in a 65-nm CMOS process. The passband of the filter is tunable from 0.1 to 1.4 GHz with a 3-dB bandwidth of 9.8–10.2 MHz, a gain of 21.5–24 dB, a noise figure of 3–4.2 dB, and a total power consumption of 50–73 mW. TZs are created on both sides of the passband with a minimal offset of 25 MHz and are tunable across a 20-MHz range with up to a 60-dB rejection. The measured blocker 1-dB compression point is 8 dBm and the OOB IIP3 is 23 dBm. The reported filter provides a promising on-chip filtering solution for multistandard multifrequency SDR applications with improved interference mitigation capabilities. [ABSTRACT FROM AUTHOR]

In this paper, novel Doherty Power Amplifier (DPA) models are presented. The motivation behind the proposed models is to accurately predict static nonlinearities in the compression regions of the carrier and peaking amplifiers. DPAs suffer from a nonlinearity that originates from the carrier amplifier, and a second more pronounced nonlinearity generated at the full compression region following the turn-on of the peaking amplifier. Moreover, these distortions are often observed at different input power levels depending on whether the AM-AM or the AM-PM characteristic is considered. Therefore, the proposed static model is based on independent modeling of the memoryless gain in the polar domain. The static model of the memoryless AM-AM and AM-PM characteristics is augmented with either memory polynomials or deep neural network functions for memory effects modeling. The methodology of building the proposed models and the achieved results are discussed in this paper. The MP based proposed model achieves an NMSE as low as -45.3dB with only 78 model parameters, while the DNN based model achieves an NMSE as low as -46.1dB with only 156 model parameters. However, the DNN based model achieves the best model resilience to changes in the identification data.

Battery energy storage system (BESS) has already been studied to deal with uncertain parameters of the electrical systems such as loads and renewable energies. However, the BESS have not been properly studied under unbalanced operation of power grids. This paper aims to study the modelling and operation of BESS under unbalanced-uncertain conditions in the power grids. The proposed model manages the BESS to optimize energy cost, deal with load uncertainties, and settle the unbalanced loading at the same time. The three-phase unbalanced-uncertain loads are modelled and the BESSs are utilized to produce separate charging/discharging pattern on each phase to remove the unbalanced condition. The IEEE 69-bus grid is considered as case study. The load uncertainty is developed by Gaussian probability function and the stochastic programming is adopted to tackle the uncertainties. The model is formulated as mixed-integer linear programming and solved by GAMS/CPLEX. The results demonstrate that the model is able to deal with the unbalanced-uncertain conditions at the same time. The model also minimizes the operation cost and satisfies all security constraints of power grid.

The realm of cloud computing has revolutionized access to cloud resources and their utilization and applications over the Internet. However, deploying cloud computing for delay critical applications and reducing the delay in access to the resources are challenging. The Mobile Edge Computing (MEC) paradigm is one of the effective solutions, which brings the cloud computing services to the proximity of the edge network and leverages the available resources. This paper presents a survey of the latest and state-of-the-art algorithms, techniques, and concepts of MEC. The proposed work is unique in that the most novel algorithms are considered, which are not considered by the existing surveys. Moreover, the chosen novel literature of the existing researchers is classified in terms of performance metrics by describing the realms of promising performance and the regions where the margin of improvement exists for future investigation for the future researchers. This also eases the choice of a particular algorithm for a particular application. As compared to the existing surveys, the bibliometric overview is provided, which is further helpful for the researchers, engineers, and scientists for a thorough insight, application selection, and future consideration for improvement. In addition, applications related to the MEC platform are presented. Open research challenges, future directions, and lessons learned in area of the MEC are provided for further future investigation.

In this paper, we present a method to improve emotion recognition based on the fusion of local cortical activations and dynamic functional network patterns. We estimate the cortical activations using power spectral density (PSD) with the Burg autoregressive model. On the other hand, we estimate the functional connectivity networks by utilizing the phase locking value (PLV). The results of cortical activations and connectivity networks show different patterns across three emotions at all frequency bands. Similarly, the results of fusion significantly improve the classification rate in terms of accuracy, sensitivity, specificity and the area under the receiver operator characteristics curve (AROC), p

In this paper we present efficient algorithms to take advantage of the double-base number system in the context of elliptic curve scalar multiplication. We propose a generalized version of Yao’s exponentiation algorithm allowing the use of general double-base expansions instead of the popular double base chains. We introduce a class of constrained double base expansions and prove that the average density of non-zero terms in such expansions is O(\frac\log\, k\log\, \log\, k) for any large integer $k$ . We also propose an efficient algorithm for computing constrained expansions and finally provide a comprehensive comparison to double-base chain expansions, including a large variety of curve shapes and various key sizes. [ABSTRACT FROM AUTHOR]

In this paper, nFET-to-pFET (n-to-p) tracking characteristics in 14-nm silicon-on-insulator (SOI) FinFET technology are studied by technology computer-aided design-based statistical modeling. Compared with planar SOI high- $k$ metal gate CMOS technologies, 14-nm SOI FinFET technology shows better n-to-p tracking mainly due to the strong influence of correlated Fin geometrical variation, as well as reduced uncorrelated variation from an innovative work function process. The impact of the n-to-p tracking characteristics on setup and hold (guard time) of latch circuits is evaluated by corner and Monte Carlo simulation using compact models. It is found that the guard time is significantly modulated by slow/fast and fast/slow corners in certain conditions and, therefore should be considered in guard time design. [ABSTRACT FROM AUTHOR]

This paper presents a wide linear output range biopotential amplifier for physiological measurement frontend. The proposed amplifier consists of an open-loop rail-to-rail differential pair in the first stage and a closed-loop common source amplifier in the second stage, which extends the linear output range by maintaining a constant voltage gain with amplifier output level variation. The nMOS and pMOS gain enhancement switches provide additional compensation for the voltage gain degradation as the amplifier output level moves toward the supply rails. In addition, voltage buffers are used after the first and second stages to alleviate the loading effect. This enables using small-sized feedback resistors, where the amplifier performance is relatively insensitive to resistor mismatch. Aside from the wide linear output range, this approach leads to small silicon area, low power, and relatively high common mode rejection ratio and power supply rejection ratio, which are highly demanding for portable and implantable biomedical instrumentation frontend. The proposed amplifier is implemented using CMOS 0.35- \mu m technology (3.3 V supply) with core area of 0.063 mm ^{2} . Measurement results show a stable voltage gain of 46.3 dB for amplifier output range from 0.15 to 3.12 V, and a 0.04% total harmonic distortion with input amplitude of 15 mV _{\rm pp}$ . Furthermore, the amplifier operation is demonstrated with an actual ECG measurement setup. [ABSTRACT FROM PUBLISHER]

Some applications like cryptography involve a large number of multiplications of binary polynomial. In this paper, we consider two-, three-, and four-way methods for parallel implementation of binary polynomial multiplication. We propose optimized three- and four-way split formulas which reduce the space and time complexity of the best known methods. Moreover, we present a block recombination method which provides some further reduction in the space complexity of the considered two-, three-, and four-way split multipliers. [ABSTRACT FROM PUBLISHER]

Cooperative routing mitigates the adverse channel effects in the harsh underwater environment and ensures reliable delivery of packets from the bottom to the surface of water. Cooperative routing is analogous to sparse recovery in that faded copies of data packets are processed by the destination node to extract the desired information. However, it usually requires information about the two or three position coordinates of the nodes. It also requires the synchronization of the source, relay, and destination nodes. These features make the cooperative routing a challenging task as sensor nodes move with water currents. Moreover, the data packets are simply discarded if the acceptable threshold is not met at the destination. This threatens the reliable delivery of data to the final destination. To cope with these challenges, this paper proposes a cooperative energy-efficient optimal relay selection protocol for underwater wireless sensor networks. Unlike the existing routing protocols involving cooperation, the proposed scheme combines location and depth of the sensor nodes to select the destination nodes. Combination of these two parameters does not involve knowing the position coordinates of the nodes and results in selection of the destination nodes closest to the water surface. As a result, data packets are less affected by the channel properties. In addition, a source node chooses a relay node and a destination node. Data packets are sent to the destination node by the relay node as soon as the relay node receives them. This eliminates the need for synchronization among the source, relay, and destination nodes. Moreover, the destination node acknowledges the source node about the successful reception or retransmission of the data packets. This overcomes the packets drop. Based on simulation results, the proposed scheme is superior in delivering packets to the final destination than some existing techniques.

Wireless multimedia sensor network has been renewed to the distributed model by incorporating the single board computer (i.e., camera nodes and mobile beacons). The redesigned camera nodes, such as unmanned aerial vehicle and mobile beacon nodes are limited in terms of memory, computation power, bandwidth, and node power while the real-time processing requires the multimedia contents transmission over the wireless interface in the presence of all these constraints. To tackle this problem, advanced video compression schemes have been adopted by which bit rate overhead over the network is greatly improved. H.264/moving picture experts group (MPEG)-4 is a state-of-the-art video compression standard developed jointly by International Telecommunication Union Telecommunication Standardization Sector video coding experts group and ISO/Joint Technical Committee of International Electrotechnical Commission MPEG. The H.264 provides a number of tunable parameters (e.g., quantization parameter (QP) and number of reference frames (NoRF)) for tailoring the encoding process as per requirements. In this paper, we propose a framework consisting of a joint parameter cost function to find the best trade-off between QP and NoRF with the policy of controlling the bit-rate (BR) while maintaining reasonably good video quality without compromising on processing delay (PD) and nodal power consumption (NPC). The framework has been proposed by transforming the multi-objective problem into a convex optimization problem. It is shown that an optimal trade-off between these conflicting objectives can be achieved by choosing appropriate values for QP and NoRF. Results for optimal values of QP and NoRF with corresponding trade-off between BR, quality of multimedia contents, low PD and low NPC are presented.

Computing the product of a Toeplitz matrix and a vector arises in various applications including cryptography. In this paper, we consider Toeplitz matrices and vectors with entries in (\\rlapI\kern 2.0pt\F_2). For improved efficiency in such computations, large Toeplitz matrices and vectors are recursively split and special formulas with subquadratic arithmetic complexity are applied. To this end, we first present a formula for the five-way splitting and then provide a generalization for the (k)-way splitting, where (k) is an arbitrary integer. These formulas can be used to compute a Toeplitz matrix-vector product (TMVP) of size (n) with an arithmetic complexity of (O(n^\log_k(k(k+1)/2))). [ABSTRACT FROM PUBLISHER]

In this paper, we consider three-way split formulas for binary polynomial multiplication and Toeplitz matrix vector product (TMVP). We first recall the best known three-way split formulas for polynomial multiplication: the formulas with six recursive multiplications given by Sunar in a 2006 IEEE Transactions on Computers paper and the formula with five recursive multiplications proposed by Bernstein at CRYPTO 2009. Second, we propose a new set of three-way split formulas for polynomial multiplication that are an optimization of Sunar's formulas. Then, we present formulas with five recursive multiplications based on field extension. In addition, we extend the latter formulas to TMVP. We evaluate the space and delay complexities when computations are performed in parallel and provide a comparison with best known methods. [ABSTRACT FROM PUBLISHER]

This paper presents a technique for designing a low-power and variability-aware SRAM cell. The cell achieves low power dissipation due to its series-connected tail transistor and read buffers, which offer a stacking effect. This paper studies the impact of process, voltage, and temperature (PVT) variations on most of the design metrics of the SRAM cell and compares the results with standard 6T, 9T, and ST10T (Schmitt trigger based) SRAM cells. [ABSTRACT FROM AUTHOR]

Lateral asymmetric channel doping is applied to 45-nm technology NFET devices. The measured effective drain-current enhancement over coprocessed symmetric control devices is 10%. Analysis reveals that the dominant physical mechanism, which accounts for two-third of the total enhanced drain current, is an 8% increase in the source-side injection velocity. The remaining one-third is attributed to the decreased drain-induced barrier lowering. This paper concludes with an analysis of the switching characteristics of CMOS inverters composed of an asymmetric NFET and a companion symmetric PFET and shows a 5% improvement in the delay. The improvement is explained in terms of the increased velocity and 30% reduction in drain junction capacitance. [ABSTRACT FROM AUTHOR]

In this work, we consider detection of errors in polynomial, dual, and normal bases arithmetic operations. Error detection is performed by recomputing with the shifted operand method, while the operation unit is in use. This scheme is efficient for pipelined architectures, particularly systolic arrays. Additionally, one semisystolic multiplier for each of the polynomial, dual, type I, and type II optimal normal bases is presented. The results show that for having better or similar space and time overheads compared to a number of related previous work, the multipliers have generally a higher error-detection capability, e.g., the error-detection capability of the RESO-based scheme for single and multiple stuck-at faults in a polynomial basis multiplier is 100 percent. Finally, we also comment on how RESO can be used for concurrent error correction to deal with transient faults. [ABSTRACT FROM AUTHOR]

A high-performance architecture of elliptic curve scalar multiplication based on the Montgomery ladder method over finite field CF(2m) is proposed. A pseudopipelined word-serial finite field multiplier, with word size w, suitable for the scalar multiplication is also developed, Implemented in hardware, this system performs a scalar multiplication in approximately 6[m/w](m - 1) clock cycles, and the gate delay in the critical path is equal to TAND + log2(w/k)]TXOR, where TAND and TXOR are delays due to two-input AND and XOR gates, respectively, and 1 ≤ k ⪡ w is used to shorten the critical path. [ABSTRACT FROM AUTHOR]

In many manufacturing studies, longitudinal failure time data comprise repeated exponential responses, and a set of multi-dimensional covariates for a large number of independent components or objects. When the covariates collected along with exponential failure times are time dependent, the responses of an object exhibit non-stationary correlations. We examine the effects of the covariates by taking this non-stationary correlation structure into account. First, we develop Gaussian type non-stationary AR(1), MA(1), and exchangeable correlation structures for the repeated exponential failure times; and then exploit the suitable auto-correlation structure to obtain consistent, efficient estimates for the effects of the covariates by using a generalized quasi-likelihood (GQL) estimating equation approach. The finite sample estimation performance of the GQL approach is examined through a simulation study. [ABSTRACT FROM AUTHOR]

We have calculated the levitation force and the inter- action energy between a thin monolayer of super-paramagnetic fine ferromagnetic particles system and a large flat superconductor in the Meissner state. Both energy and force depend on the temperature and the levitation height of the monolayer. Our results show that the interaction energy and the levitation force increases as the temperature of the momolayer increases. In the limit of zero Kelvin temperature, we found that our results for the levitation force goes over to the case where all the moments of the fine-particle system are parallel to the superconductor surface, which has the lowest interaction energy. [ABSTRACT FROM AUTHOR]

The interaction force between a small magnet and a superconducting ring in assumptions of the Meissner state was analyzed using the dipole-dipole interaction model. Two configurations were evaluated: the vertical configuration when the magnetic moment lies parallel to the symmetry axis of the ring and the horizontal when it is perpendicular. The levitation force on the magnet increases by decreasing the distance from the center of the ring up to a maximum value and then decreases down to zero when the magnet is exactly at the center of the ring. The levitation force when the magnet is in the horizontal configuration is mostly higher than that when it is in the vertical configuration. Simulation results were compared with experimental results reported in literature. [ABSTRACT FROM AUTHOR]

Based on Toeplitz matrix-vector products and coordinate transformation techniques, we present a new scheme for subquadratic space complexity parallel multiplication in GF(2n) using the shifted polynomial basis. Both the space complexity and the asymptotic gate delay of the proposed multiplier are better than those of the best existing subquadratic space complexity parallel multipliers. For example, with n being a power of 2, the space complexity is about 8 percent better, while the asymptotic gate delay is about 33 percent better, respectively. Another advantage of the proposed matrix-vector product approach is that it can also be used to design subquadratic space complexity polynomial, dual, weakly dual, and triangular basis parallel multipliers. To the best of our knowledge, this is the first time that subquadratic space complexity parallel multipliers are proposed for dual, weakly dual, and triangular bases. A recursive design algorithm is also proposed for efficient construction of the proposed subquadratic space complexity multipliers. This design algorithm can be modified for the construction of most of the subquadratic space complexity multipliers previously reported in the literature. [ABSTRACT FROM AUTHOR]

In 1999, Solinas introduced families of moduli called the generalized Mersenne numbers (GMN5), which are expressed in low-weight polynomial form, p = f(t), where is limited to a power of 2. GMNs are very useful in elliptic curve cryptosystems over prime fields since modular reduction by a GMN requires only integer additions and subtractions. However, since there are not many GMNs and each GMN requires a dedicated implementation, GMNs are hardly useful for other cryptosystems. Here, we modify GMN by removing restriction on the choice oft. and restricting the coefficients of f(t) to 0 and ±1. We call such families of moduli low-weight polynomial form integers (LWPFIs). We show an efficient modular multiplication method using LWPFI moduli. LWPFI5 allow general implementation and there exist many LWPFI moduli. One may consider LWPFIs as a trade-oft between general integers and GMNs. [ABSTRACT FROM AUTHOR]

Applying the matrix-vector product idea of the Mastrovito multiplier to the GF(2m) Montgomery multiplication algorithm, we present a new parallel multiplier for irreducible trinomiats. This multiplier and the corresponding shifted polynomial basis (SPB) multiplier have the same circuit structure for the same set of parameters. Furthermore, by establishing isomorphisms between the Montgomery and the SPB constructions of GF(2m), we show that the Montgomery algorithm can be used to perform the SPB multiplication without any changes and vice versa. [ABSTRACT FROM AUTHOR]

In many cryptographic schemes, the most time consuming basic arithmetic operation is the finite field multiplication and its hardware implementation for bit parallel operation may require millions of logic gates. Some of these gates may become faulty in the field due to natural causes or malicious attacks, which may lead to the generation of erroneous outputs by the multiplier. In this paper, we propose new architectures to detect erroneous outputs caused by certain types of faults in bit-parallel and bit-serial polynomial basis multipliers over finite fields of characteristic two. In particular, parity prediction schemes are developed for detecting errors due to single and certain multiple stuck-at faults. Although the issue of detecting soft errors in registers is not considered, the proposed schemes have the advantage that they can be used with any irreducible binary polynomial chosen to define the finite field. [ABSTRACT FROM AUTHOR]

A class of universal unidirectional bit serial systolic architectures for multiplicative inversion and division over Galois field GF(2m) is presented. The field elements are represented with polynomial (standard) basis. These systolic architectures have no carry propagation structures and are suitable for hardware implementations where the dimension of the field is large and may vary. This is the typical case for cryptographic applications, these architectures are independent of any defining irreducible polynomial of a given degree as well. The time compIexity is constant and area complexity is linear (w.r.t. field dimension) and these measures are equivalent to or exceed similar proposed designs. [ABSTRACT FROM AUTHOR]

A class of universal unidirectional bit serial systolic architectures for multiplicative inversion and division over Galois field GF(2m) is presented. The field elements are represented with polynomial (standard) basis. These systolic architectures have no carry propagation structures and are suitable for hardware implementations where the dimension of the field is large and may vary. This is the typical case for cryptographic applications, these architectures are independent of any defining irreducible polynomial of a given degree as well. The time compIexity is constant and area complexity is linear (w.r.t. field dimension) and these measures are equivalent to or exceed similar proposed designs. [ABSTRACT FROM AUTHOR]

For efficient hardware implementation of finite field arithmetic units, the use of a normal basis is advantageous. In this paper, two classes of architectures for multipliers over the finite field GF(2m) are proposed. These multipliers are of sequential type, i.e., after receiving the coordinates of the two input field elements, they go through k, 1 ≤ k ≤ in, iterations (i.e., clock cycles) to finally yield all the coordinates of the product in parallel. The value of k depends on the word size to For ω=[m/k] 1, these multipliers are highly area efficient and require fewer number of logic gates even when compared with the most area efficient multipliers available in the open literature. This makes the proposed multipliers suitable for applications where the value of m is large but space is of concern, e.g., resource constrained cryptographic systems. Additionally, if the field dimension in is composite, i.e., m = kn, then the extension of one class of the architectures yields a highly efficient multiplier over composite fields. [ABSTRACT FROM AUTHOR]

The impact of processing factors such as ion implantation and rapid thermal annealing on mobility enhancement in strained-Si n-channel metal-oxide-semiconductor field-effect transistors (n-MOSFETS) has been investigated. Long-channel strained-Si and bulk n-MOSFETs were fabricated with various channel-region implant doses and thermal budgets. Neutral Si and Ge species were used to study the impact of the implant damage on mobility separately from ionized impurity scattering effects. Electron mobility enhancement is shown to degrade considerably when the implant dose is above a critical dose for a given thermal budget. Transmission electron microscopy, secondary ion mass spectrometry and Raman spectroscopy were used to investigate the mobility degradation mechanisms. Residual implant damage and implant damage enhanced Ge up-diffusion into the Si are shown to be responsible for the mobility degradation. Two-dimensional damage simulations of 30-nm scale MOSFETs are used to examine potential technological implications of these findings. [ABSTRACT FROM AUTHOR]

A physically based analytic model for the threshold voltage Vt of long-channel strained-Si-Si1-∞ Ge ∞MOSFETs is presented and confirmed using numerical simulations for a wide range of channel doping concentration, gate-oxide thicknesses, and strained-Si layer thicknesses. The threshold voltage is sensitive to both the electron affinity and bandgap of the strained-Si cap material and the relaxed-Si1-∞Ge∞ substrate. It is shown that the threshold, voltage difference between strained- and unstrained-Si devices increases with channel doping, but that the increase is mitigated by gate oxide thickness reduction. Strained Si devices with constant, high channel doping have a threshold voltage difference that is sensitive to Si cap thickness, for thicknesses below the equilibrium critical thickness for strain relaxation. [ABSTRACT FROM AUTHOR]