nils-herrmann/clean_scirepeval huggingface dataset:
Small-signal modeling of In2O5Sn based transparent gate recessed channel MOSFET for microwave/RF applications

In this paper, modeling of the small signal equivalent circuit of Transparent Gate Recessed Channel (TGRC) MOSFET in terms of Z (impedance) parameters and Y (admittance) parameters is presented. The modeled and simulated results are compared with Conventional Recessed Channel (CRC) MOSFET having metal gate electrode at THz frequency range, using ATLAS-3D device simulator. Instead of metal gate, In2O5Sn (Indium Tin Oxide) ITO as a transparent conducting oxide (TCO) is amalgamated. The input impedance of TGRC-MOSFET enhances by 99.4% as compared to CRC-MOSFET, and input admittance improves by 32.9% in the proposed device as compared to its counterpart. Simulation results reveal that the proposed device design improves the small signal behavior thus, providing the detailed insight to RF engineers for microwave applications/ RFIC design.
Economic load dispatch of wind thermal integrated system using dragonfly algorithm

Majority of electricity produced across world is from thermal power plants and they causes environmental pollution. With the increased awareness regarding environmental protection several countries has allotted share for electricity generation from wind power. As wind power is a clean energy, wind thermal integrated systems reduce emission. Wind integrated system are considered in this study along with valve point effect. The economic dispatch problem becomes highly nonlinear while considering valve point effect. The situation becomes more stringent when intermittent wind power is integrated with thermal system. In this paper Dragonfly Algorithm is implemented to solve the economic load dispatch problem with valve point effect. This dispatch model includes both Thermal and Wind farm. The stochastic nature of wind is modeled using weibull distribution function and over estimation/under estimation cost is analyzed using closed integral function. The model is tested on a modified IEEE-30 bus system comprising 6 thermal generating units and one wind farm. The performance of Dragonfly Algorithm is validated by comparing with other metaheuristic algorithm on the test systems. The proposed dispatch model can minimize the generating cost and enhance the renewable power consumption capacity. The MATLAB software 2010b has been used to simulate the model. The simulation demonstrates that Dragonfly Algorithm is capable of finding global optimum solution and is free from local optima problem as compare to other traditional and metaheuristic optimization techniques.
Combining Algorithm Exploration with Instruction Set Design: A Case Study in Elliptic Curve Cryptography

In recent years, processor customization has matured to become a trusted way of achieving high performance with limited cost/energy in embedded applications. In particular, instruction set extensions (ISEs) have been proven very effective in many cases. A large body of work exists today on creating tools that can select efficient ISEs given an application source code: ISE automation is crucial for increasing the productivity of design teams. In this paper, we show that an additional motivation for automating the ISE process is to facilitate algorithm exploration: the availability of ISE can have a dramatic impact on the performance of different algorithmic choices to implement identical or equivalent functionality. System designers need fast feedbacks on the ISE-ability of various algorithmic flavors. We use a case study in elliptic curve (EC) cryptography to exemplify the following contributions: (I) ISE can reverse the relative performance of different algorithms for one and the same operation, and (2) automatic ISE, even without predicting speed-ups as precisely as detailed simulation can, is able to show exactly the trends that the designer should follow
Analysis of modified impedance-network half-bridge converter

This paper presents a modified Z-network half-bridge converter for applications that requires different kinds of load voltages such as varied positive or negative load voltage and varied time ratio between positive and negative load voltage. Compared to traditional Z-source half-bridge converter, the proposed converter reduces the Z-network capacitor voltage stress remarkably to realize the same load voltage characteristics, with same switch voltage stress. The operating principle, steady-state analysis, small-signal analysis, parameters design and comparison with conventional Z-source half-bridge converter is presented. Simulation results validates the effectiveness of theoretical analysis of proposed converter.
Human Identification Using Finger Images

This paper presents a new approach to improve the performance of finger-vein identification systems presented in the literature. The proposed system simultaneously acquires the finger-vein and low-resolution fingerprint images and combines these two evidences using a novel score-level combination strategy. We examine the previously proposed finger-vein identification approaches and develop a new approach that illustrates it superiority over prior published efforts. The utility of low-resolution fingerprint images acquired from a webcam is examined to ascertain the matching performance from such images. We develop and investigate two new score-level combinations, i.e., holistic and nonlinear fusion, and comparatively evaluate them with more popular score-level fusion approaches to ascertain their effectiveness in the proposed system. The rigorous experimental results presented on the database of 6264 images from 156 subjects illustrate significant improvement in the performance, i.e., both from the authentication and recognition experiments.
Learning Robot Manipulation Tasks With Task-Parameterized Semitied Hidden Semi-Markov Model

In this letter, we investigate the semitied Gaussian mixture models for robust learning and adaptation of robot manipulation tasks. We make use of the spatial and temporal correlation in the data by tying the covariance matrices of the mixture model with common synergistic directions/basis vectors, instead of estimating full covariance matrices for each cluster in the mixture. This allows the reuse of the discovered synergies in different parts of the task having similar coordination patterns. We extend the approach to task-parameterized and hidden semi-Markov models for autonomous adaptation to changing environmental situations. The planned movement sequence from the model is smoothly followed with a finite horizon linear quadratic tracking controller. Experiments to encode whole body motion data in simulation, followed by valve opening and pick-and-place via obstacle avoidance tasks with the Baxter robot, show improvement over standard Gaussian mixture models with much less parameters and better generalization ability.
Managing software product line using an ontological rule-based framework

Feature model is amongst the widely used approach to manage variability and commonality in software product lines for enabling software reuse. Modeling variability and developing variable software products from feature model is an arduous task. Due to the growing complexity and size of feature models, defects such as false-optional and dead features can arise which lead to the development of low-quality erroneous software products. We propose an ontological rule-based framework that improves software product line by identifying feature model defects due to false-optional and dead features with their causes. This information further suggest corrections to the modelers for resolving defects. The evaluation results show the applicability of proposed framework to handle false-optional and dead features, and indicate its accuracy and scalability for huge size feature models with 21, 050 features. Thereby, improving the quality and reusability of software product line.
Day-Ahead Zonal Reactive Power Market Clearing Model for Competitive Markets: A Multi-objective Approach

In this paper, a multi-zone/localized reactive power market clearing model namely MZ-RPMC model is proposed for day-ahead competitive markets. In proposed model, two objective functions such as total payment function (TPF) for reactive power support from generators/synchronous condensers and total real transmission loss (TRTL) are optimized simultaneously while satisfying various system equality and inequality constraints. A well known elitist non-dominated sorting genetic algorithm called as NSGA-II is used to solve the multi-objective reactive power clearing models. The proposed multi-zone model is compared with single-zone model to explore its superiority.
Challenges in Automatic Optimization of Arithmetic Circuits

Despite the impressive progress of logic synthesis in the past decade, finding the best architecture for a given circuit still remains an open and largely unsolved problem, especially for arithmetic circuits. In many cases, the outcome of even the most advanced synthesis techniques is highly dependent on the input description of the circuit, and the optimizations themselves barely modify the architecture of the circuit itself. Once the input description is converted to an appropriate architecture, logic synthesis performs local optimizations quite effectively; however, finding the best architecture up front is a nontrivial problem. This paper reviews recent results in arithmetic logic synthesis that the authors have published in recent years. Progress has clearly been made, but much further work is still needed to narrow the gap between the effectiveness of logic synthesis techniques for arithmetic and control-oriented circuits.
Online personal identification in night using multiple face representations

This paper details a fully automated face authentication system using low-cost near infrared imaging. The image normalization step consists of eye center localization, scale correction and orientation correction. This paper investigates the comparison and combination of four face matchers on the automatically normalized face images: elastic bunch graph matching (EBGM), trace transform, PCA, and LDA. The performance evaluation is presented on the near infrared images acquired from the 102 users in two sessions with different pose and expressions. Our experimental results achieve the best results with the EER of 3.92% from the EBGM matcher while the combination of results from the different matchers can significantly improve the performance and achieve the EER of 2.28 %. The near infrared face database developed in this work is also made publicly available to foster further research.
A survey on techniques to achive energy efficiency in cloud computing

Due to the increased usage of Information and Communication Technology, together with increasing energy costs and the need to reduce greenhouse gas emissions the energy consumption required for cloud computing system need to be reduced. Hence, the energy-efficient technologies that decrease the overall energy consumption of computation, storage and communications in cloud computing have become more important. The researchers have so far focused on hardware aspects, scheduling, virtualization and clustering for saving energy. The major techniques available in the literature for energy saving in cloud computing such as energy efficient hardware, energy efficient scheduling, consolidation, energy efficient network and clustering servers have also been discussed in the present exposition.
Improved palmprint authentication using contactless imaging

Palmprint identification has emerged as one of the popular and promising biométrie modalities for forensic and commercial applications. In recent years the contactless system emerges as a viable option to address hygienic issues and improve the user acceptance. The presence of significant scale, rotation, occlusion and translation variations in the contactless palmprint images requires the feature extraction approaches which are tolerant to such changes. Therefore the usage of traditional palmprint feature extraction methods on contactless imaging schemes remains questionable and hence all/popular palmprint feature extraction methods may not be useful in contactless frameworks. This paper we systematically examine the issues related to the contactless palmprint authentication and presents performance evaluation on the two public databases. Our experimental results on more than 4300 images from two contactless databases suggests that the Scale Invariant Feature Transform (SIFT) features perform significantly better for the contactless palmprint images than the (most) promising Orthogonal Line Ordinal Features (OLOF) approach employed earlier on the more conventional palmprint imaging. Our experimental results further suggests that the combination of robust SIFT matching scores along with those from OLOF can be employed to achieve more reliable performance improvement. The achieved error rates show a good performance of these features in controlled and uncontrolled environments conditions with the error rates similar to other contact based approaches.
Power Deduction in Digital Signal Processing Circuit using Inventive CPL Subtractor Circuit

The proposed 4 bit subtracter circuit is designed by using bit slice method of complementary pass transistor logic (CPL), which is suitable for applications like fast shifting; multiplier/adder in the loop cycle of DSP data processing device. The circuit can perform real time computational tasks at high speed. The designed circuit is performing efficiently in filtering signal at 100-520 MHz sampling rate in real time. We have analyzed the proposed circuit for submicron regime, whose layout is designed by using microwind III VLSI CAD tools, in terms of propagation delay, power consumption, power dissipation and area. In 50 nm analysis, the proposed circuit is found to dissipate less power (~0.46 muW) and possess less overall area of order of 423 mum2. The propagation delay is 9.5206 times 10-12 sec. In DSP architecture, time and area are the critical components which are responsible for the efficient execution of arithmetic and logical operation. Our proposed circuit is enhancing, complete set of instruction cycle, passing at speed of 9.0 GHz, which is higher than reported results.
Tongue line extraction

Tongue line refers to the surface of the tongue covered with fissures or lines in deep or shallow shape and is one type of important features in clinical practice of Traditional Chinese Tongue Diagnosis (TCTD). However, it is hard to extract tongue lines completely due to the large variation of the widths of tongue lines and the strong noise caused by the rough surface of tongue and uneven illumination. In this paper, an improved wide line detector (WLD) is presented for tongue line extraction. Based on the characteristics of tongue lines, the original WLD is improved to avoid the undesired separation of a wide line and the influence of uneven lighting conditions. The proposed method has been tested on a total of 286 tongue line images and our experimental results demonstrate that the improved WLD significantly outperforms the original WLD for tongue line extraction by improving the TPR 16.5%, FPR 44.6% and PM 33.4%, respectively.
A review on applied machine learning in wearable technology and its applications

Wearable technology has added a whole new dimension to already rich field of personal gadgets. It was the mobile phone which truly made gadgets personal. With so many services built around mobile phones, the market has opened up for a whole new personalization experience involving wearable technology. The fabric sensors that sense stretch, pressure, bend and even the direction of bracing on the body are now combined with wearable microcontrollers such as flora and lily pad. The connections between them are being made from conductive threads which curves along with the fabric. In this paper we will take a peek as to how different teams have applied the rich knowledge of wearable technologies to achieve their goals.
Identification and localization of series and shunt faults along a transformer winding using a rough set classifier aided with S-transform

In this paper, a Rough Set based approach aided with S-Transform features have been proposed for classification of short circuit faults during impulse test of a transformer. The required winding current waveforms are acquired by emulating short circuit faults across different disc positions in the analog model of a 33 kV winding of a 3 MVA transformer using developed analog fault simulator. Significant features are extracted for identification of various fault characteristics. It was found that the features extracted from S-transform data were sufficient for efficient classification of different fault cases and also application of Rough sets with a minor modification helps in improving the classification accuracy percentage.
Multiband circularly polarized symmetrical fractal boundary microstrip antenna for microwave applications

A new fractal antenna is designed for multi band operation. The designed antenna is single layered symmetrical fractal boundary microstrip antenna. By the alteration in the geometry of fractal boundary of the square patch multiband operation is attained. The proposed antenna worked nearly in ten bands of frequency. Four antennas were intended by having a square slot at the middle for circular polarization (CP) operation. Antennas proposed worked at frequencies 3-5 GHz, 6.9 GHz, 11-19.5 GHz and at 6.9 GHz the invented antenna shown excellent gain and 10-dB return loss.
A low complex adaptive algorithm for antenna beam steering

An adaptive antenna system consists of a combination of multiple antenna elements with a signal-processing capability to optimize its radiation and/or reception pattern automatically in response to the signal environment. In a telecommunication system, adaptive antenna system is the port through which radio frequency (RF) energy is coupled from the transmitter to the environment and, in reverse, to the receiver from the environment. In this paper, an efficient and simple adaptive beam steering technique is presented. The proposed method is based on Least Mean Square (LMS) algorithm, provides a comprehensive and detailed treatment of the signal model used for beam forming. In order to improve the convergence rate of LMS algorithm in smart antenna system, this paper proposes the Block Based Normalized LMS (BBNLMS) algorithm. The performance of the BNLMS algorithm in the presence of Multi-path effects and multiple users is analyzed using MATLAB simulations. Simulation results confirm that the convergence rate and error reduction of BBNLMS is superior than conventional LMS algorithm.
Biquadratic universal filter based on CCDDCCTA

A voltage mode (VM) biquadratic universal filter using a current controlled differential difference current conveyor transconductance amplifier (CCDDCCTA) is discussed. The proposed filter uses two capacitors and one CCDDCCTA block only. It has following important facets: (i) Low pass (LP), band pass (BP), high pass (HP), notch and all pass (AP) voltage responses using same configuration, (ii) All the responses are electronically tunable, (iii) Uses only two passive components and (iv) Non-ideality effect due to parasitic capacitances may be compensated. The functionality of design is verified using 0.25μm TSMC process technology.
Performance analysis of fuel cell assisted distributed generation system

This paper investigates performance analysis of Solid oxide fuel cell assisted seven-level cascaded flying capacitor multilevel inverter (FCMI) based distributed system. A hybrid modulation technique proposes for generating thyristor gate pulses. This hybrid modulation technique is achieved by combining two well-known modulation techniques: phase disposition (PD) and phase shift (PS). This paper also consist modeling of SOFC. The whole model simulated and tested on MATLAB/ SIMULINK environment to verify the theoretical consideration.
Fast, Nearly Optimal ISE Identification With I/O Serialization Through Maximal Clique Enumeration

The last decade has witnessed the emergence of the application-specific instruction-set processor (ASIP) as a viable platform for embedded systems. Extensible ASIPs allow the user to augment a base processor with instruction set extensions (ISEs) that execute on dedicated hardware application-specific functional units (AFUs). Due to the limited number of read and write ports in the register file of the base processor, the size and complexity of AFUs are generally limited. Recent papers have focused on overcoming these constraints by serializing access to the register file. Exhaustive ISE enumeration methods are not scalable and generally fail for larger applications and register files with a large number of read and write ports. To address this concern, a new approach to ISE identification is proposed. The approach presented in this paper significantly prunes the list of the best possible ISE candidates compared to previous approaches. Experimentally, we observe that the new approach produces optimal results on larger applications where prior approaches either fail or produce inferior results.
Optimal polynomial-time interprocedural register allocation for high-level synthesis and ASIP design

Register allocation, in high-level synthesis and ASIP design, is the process of determining the number of registers to include in the resulting circuit or processor. The goal is to allocate the minimum number of registers such that no scalar variable is spilled to memory. Previously, an optimal polynomial-time algorithm for this problem has been presented for individual procedures represented in Static Single Assignment (SSA) Form. This result is now extended to complete programs (or sub-programs), as long as: (1) each procedure is represented in SSA Form; and (2) at every procedure call, all live variables are split at the call point. With this representation, it is possible to ensure that the interprocedural interference graph (IIG) is chordal, and can therefore be colored optimally in polynomial time. An optimal coloring of the IIG can be achieved by allocating registers for each procedure individually. Previous work has shown that optimal register allocation in SSA Form does not require an interference graph. Optimal interprocedural register allocation, therefore, is achieved without constructing an interference graph, giving the optimal algorithm a significant runtime advantage over prior sub-optimal heuristics.
Robust image watermarking using combined DSR-SVM with PCA based feature reduction

This paper proposes a novel approach for image watermarking using combined dynamic stochastic resonance (DSR) and support vector machine (SVM). The algorithm incorporates lifting wavelet transform (LWT) to decompose the host image into three level frequency sub-bands, and a low-pass frequency sub-band is opted for watermark embedding. Watermark bits are embedded into small blocks of low-pass frequency sub-band using quantization of minimum and maximum coefficients of the corresponding blocks. And, to extract the watermark, DSR based coefficient enhancement process is incorporated. A features set of enhanced block coefficients is generated by employing different statistical parameters, and principal component analysis (PCA) is employed to reduce the dimensions of the features set, which are used for training and testing the learning machine. Training and testing patterns are generated using concatenation of reduced features with enhanced coefficients of the corresponding blocks. Finally, a binary watermark can be extracted using well trained machine (SVM) using binary classification approach. The experimental results show remarkable performance in terms of robustness against various geometrical and signal processing attacks.