Salt-and-pepper noise removal by adaptive median-based lifting filter using second-generation wavelets

In this paper, we propose a novel adaptive median-based lifting filter for image de-noising which has been corrupted by homogeneous salt and pepper noise. The median-based lifting filter removes the noise of the input image by calculating the median of the neighboring significant pixels. The algorithm for image noise removal uses the lifting scheme of the second-generation wavelets in conjunction with the proposed adaptive median-based lifting filter. The experimental results demonstrate the efficiency of the proposed method. The proposed algorithm is compared with all the basic filters, and it is found that our method outperforms many other algorithms and it can remove salt and pepper noise with a noise level as high as 90%. The algorithm works exceedingly well for all levels of noise, as illustrated in terms of peak signal-to-noise ratio (PSNR) and structural similarity index (SSIM) measures.     

A low-power up-conversion CMOS mixer for 22-29-GHz ultra-wideband applications

A double-balanced, low-power, and low-voltage dual-gate up-conversion mixer working at K-band is designed and fabricated in the UMC 130-nm logic CMOS process. The mixer achieves a 3-dB conversion-gain bandwidth of 1.8 GHz at the input IF port and a 3-dB conversion-gain bandwidth of 10 GHz at the output RF port. The mixer achieves an output referred 1-dB compression point as high as -5.8 dBm and an output referred third-order intercept point as high as 5.8 dBm, while consuming 8.0 mW from a 1.2-V supply. This study demonstrates that the implementation of low-power mixers operating in the 22-29-GHz band for ultra-wideband automotive radar applications is possible in low-cost and low-voltage logic CMOS technology.     

Design of efficient lightweight strategies to combat DoS attack in delay tolerant network routing

Delay tolerant networks (DTNs) are characterized by delay and intermittent connectivity. Satisfactory network functioning in a DTN relies heavily on co-ordination among participating nodes. However, in practice, such co-ordination cannot be taken for granted due to possible misbehaviour by relay nodes. Routing in a DTN is, therefore, vulnerable to various attacks, which adversely affect network performance. Several strategies have been proposed in the literature to alleviate such vulnerabilities—they vary widely in terms of throughput, detection time, overhead etc. One key challenge is to arrive at a tradeoff between detection time and overhead. We observe that the existing table-based reactive strategies to combat Denial-of-service (DoS) attacks in DTN suffer from two major drawbacks: high overhead and slow detection. In this paper, we propose three secure, light-weight and time-efficient routing algorithms for detecting DoS attacks (Blackhole and Grey-hole attacks) in the Spray & Focus routing protocol. The proposed algorithms are based on use of a small fraction of privileged (trusted) nodes. The first strategy, called TN, outperforms the existing table-based strategy with 20–30 % lesser detection time, 20–25 % higher malicious node detection and negligible overhead. The other two strategies, CTN_MI and CTN_RF explore the novel idea that trusted nodes are able to utilize each others’ information/experience using their long range connectivity as and when available. Simulations performed using an enhanced ONE simulator reveals that investing in enabling connectivity among trusted nodes (as in CTN_RF) can have significant performance benefits.     

C60 Concentration Influence on MEH-PPV:C60 Bulk Heterojunction-Based Schottky Devices

We have investigated the effect of C60 concentration on the performance of poly[2-methoxy-5-(2′-ethylhexoxy-p-phenylene vinylene] (MEH-PPV):C60 blend-based Schottky barrier-based devices. Incorporation of C60 in MEH-PPV leads to a red shift and the reduction of intensity in MEH-PPV absorption spectra. The appearance of a C60 characteristic band in the Raman spectra of the composites indicates the presence of C60 in the blends. A FESEM study reveals that the addition of C60 significantly modifies the surface morphology of the blend films. However, higher concentrations (>?5 wt.%) results in agglomeration of C60 particles. Dark I–V measurements allow us to extract various diode parameters including barrier height, ideality factor, and saturation current. Profound variations have been observed in the dominant charge carrier transport mechanism for different C60 concentrations. A photoresponse study demonstrates the enhancement in the photocurrent with the increase in the C60 concentration up to 5 wt.%. Beyond this concentration, agglomeration impedes exciton dissociation and charge transport, which results in a decrease in the photocurrent. Finally, an impedance spectroscopy analysis has been extensively carried out to estimate the internal device parameters, such as junction resistance, capacitance and carrier lifetime. The correlation between these parameters and I–V curves has been established.     

Enhanced ground bounce noise reduction in a low-leakage CMOS multiplier

In this paper, various parameters are used to reduce leakage power, leakage current and noise margin of circuits to enhance their performance. A multiplier is proposed with low-leakage current and low ground bounce noise for the microprocessor, digital signal processors (DSP) and graphics engines. The ground bounce noise problem appears when a conventional power-gating circuit transits from sleep-to-active mode. This paper discusses a reduction in leakage current in the stacking power-gating technique by three modes – sleep, active and sleep-to-active. The simulation results are performed on a 4 × 4 carry-save multiplier for leakage current, active power, leakage power and ground bounce noise, and comparison made for different nanoscales. Ground bounce noise is limited to 90%. The leakage current of the circuit is decimated up to 80% and the active power is reduced to 31%. We performed simulations using cadence virtuoso 180 and 45 nm at room temperature at various supply voltages.     

Comprehensive review for energy efficient hierarchical routing protocols on wireless sensor networks

Wireless Networks - In recent years, wireless sensor networks (WSNs) have played a major role in applications such as tracking and monitoring in remote environments. Designing energy efficient...     

Smart City Healthcare Cyber Physical System: Characteristics,Technologies and Challenges

Wireless Personal Communications - The recent pandemic has demanded a strong and smart healthcare system which can monitor the patients efficiently and handle the situation that arises from the...     

Semantic Information Extraction from Multi-Corpora Using Deep Learning

Information extraction plays a vital role in natural language processing, to extract named entities and events from unstructured data. Due to the exponential data growth in the agricultural sector, extracting significant information has become a challenging task. Though existing deep learning-based techniques have been applied in smart agriculture for crop cultivation, crop disease detection, weed removal, and yield production, still it is difficult to find the semantics between extracted information due to unswerving effects of weather, soil, pest, and fertilizer data. This paper consists of two parts. An initial phase, which proposes a data preprocessing technique for removal of ambiguity in input corpora, and the second phase proposes a novel deep learning-based long short-term memory with rectification in Adam optimizer and multilayer perceptron to find agricultural-based named entity recognition, events, and relations between them. The proposed algorithm has been trained and tested on four input corpora i.e., agriculture, weather, soil, and pest & fertilizers. The experimental results have been compared with existing techniques and it was observed that the proposed algorithm outperforms Weighted-SOM, LSTM+RAO, PLR-DBN, KNN, and Naïve Bayes on standard parameters like accuracy, sensitivity, and specificity.     

Sensitivity Optimization of MEMS Based Piezoresistive Pressure Sensor for Harsh Environment

Silicon - Silicon carbide piezoresistive pressure sensor is more suitable for harsh environment due to its wide bandgap, corrosion tolerance, excellent chemical inertness, high Young’s...     

Microbiological quality of sausages containing chickpea flour (Cicer arietinum)

English-type fresh skinless pork sausages in which 30% of the protein was replaced by unheated chickpea flour or by chickpea flour heated at 80°C for 1 h were evaluated microbiologically. During storage at 0°C, but not 22°C, incorporation of unheated chickpea flour lowered the microbiological quality of the sausages, but incorporation of chickpea flour previously heated at 80°C for 1 h led to no less of microbiological quality.