A fully integrated low-IF CMOS GPS radio with on-chip analog image rejection

A fully integrated Global Positioning System (GPS) radio is presented. Low-IF architecture was used for a high level of integration and low power consumption. An on-chip analog image-reject filter provides 18 dB of image-noise rejection to prevent noise figure (NF) degradation. With image rejection performed in the analog radio, a single-path (nonquadrature) output was used. The integrated synthesizer only requires an off-chip phase-locked loop-filter to function. Implemented in a 0.35-/spl mu/m 2P4M CMOS process, the integrated radio has a chip area of 9.5 mm/sup 2/. The radio operates over a wide range of voltage and temperature, from 2.2 to 3.6 V and from -40/spl deg/C to +85/spl deg/C and consumes 27 mW from a 2.2-V supply. The receiver has 4 dB NF.     

Improved Cloud Storage Encryption Using Block Cipher-Based DNA Anti-Codify Model

When it comes to data storage, cloud computing and cloud storage providers play a critical role. The cloud data can be accessed from any location with an internet connection. Additionally, the risk of losing privacy when data is stored in a cloud environment is also increased. A variety of security techniques are employed in the cloud to enhance security. In this paper, we aim at maintaining the privacy of stored data in cloud environment by implementing block-based modelling to boost the privacy level with Anti-Codify Technique (ACoT) and block cipher-based algorithms. Initially, the cipher text is generated using Deoxyribo Nucleic Acid (DNA) model. Block-cipher-based encryption is used by ACoT, but the original encrypted file and its extension are broken up into separate blocks. When the original file is broken up into two separate blocks, it raises the security level and makes it more difficult for outsiders to cloud data access. ACoT improves the security and privacy of cloud storage data. Finally, the fuzzy-based classification is used that stores various access types in servers. The simulation results shows that the ACoT-DNA method achieves higher entropy against various block size with reduced computational cost than existing methods.     

Performance analysis of 2 level DWT-SVD based non blind and blind video watermarking using range conversion method

Microsystem Technologies - The recent availability of inexpensive digital recording and storage devices have created an environment to obtain, replicate and distribute digital content without any...     

Bioactive Chemical Constituents from the Brown Alga Homoeostrichus formosana

A new chromene derivative, 2-(4'',8''-dimethylnona-3''E,7''-dienyl)-8-hydroxy-2,6-dimethyl-2H-chromene (1) together with four known natural products, methylfarnesylquinone (2), isololiolide (3), pheophytin a (4), and β-carotene (5) were isolated from the brown alga Homoeostrichus formosana. The structure of 1 was determined by extensive 1D and 2D spectroscopic analyses. Acetylation of 1 yielded the monoacetylated derivative 2-(4'',8''-dimethylnona-3''E,7''-dienyl)-8-acetyl-2,6-dimethyl-2H-chromene (6). Compounds 1–6 exhibited various levels of cytotoxic, antibacterial, and anti-inflammatory activities. Compound 2 was found to display potent in vitro anti-inflammatory activity by inhibiting the generation of superoxide anion (IC₅₀ 0.22 ± 0.03 μg/mL) and elastase release (IC₅₀ 0.48 ± 0.11 μg/mL) in FMLP/CB-induced human neutrophils.     

Highly basic CaO nanoparticles in mesoporous carbon materials and their excellent catalytic activity

Highly basic CaO nanoparticles immobilized mesoporous carbon materials (CaO-CMK-3) with different pore diameters have been successfully prepared by using wet-impregnation method. The prepared materials were subjected to extensive characterization studies using sophisticated techniques such as XRD, nitrogen adsorption, HRSEM-EDX, HRTEM and temperature programmed desorption of CO2 (TPD of CO2). The physico-chemical characterization results revealed that these materials possess highly dispersed CaO nanoparticles, excellent nanopores with well-ordered structure, high specific surface area, large specific pore volume, pore diameter and very high basicity. We have also demonstrated that the basicity of the CaO-CMK-3 samples can be controlled by simply varying the amount of CaO loading and pore diameter of the carbon support. The basic catalytic performance of the samples was investigated in the base-catalyzed transesterification of ethylacetoacetate by aryl, aliphatic and cyclic primary alcohols. CMK-3 catalyst with higher CaO loading and larger pore diameter was found to be highly active with higher conversion within a very short reaction time. The activity of 30% CaO-CMK3-150 catalyst for transesterification of ethylacetoacetate using different alcohols increases in the following order: octanol > butanol > cyclohexanol > benzyl alcohol > furfuryl alcohol.     

A proportional fair scheduling strategy using multiobjective gradient-based African buffalo optimization algorithm for effective resource allocation and interference minimization

The increased usage of Internet of Things (IoT) applications in several areas, like healthcare, agriculture, and business, has aggravated mobile traffic issues to a large extent. The deployment of 5G technology has resulted in increased traffic globally. These coherent devices, on the other hand, use the internet to fine-tune the quality of service in order to provide scalability, anonymity, and accessibility. Despite its numerous virtues, it is bound to encounter issues with interference management, fairness, throughput, and computational complexities. In this paper, a novel Multi-Objective Gradient-based African Buffalo Optimization (MOGABO) algorithm is developed to handle proportional fairness scheduling, improve interference management, increase throughput, and reduce computational complexities in cellular communication systems, particularly device-to-device (D2D) communication. The simulation analysis is done against other approaches such as the Hungarian technique, DDDPG technique, heuristic technique, and SC-FDMA technique demonstrates that this method has improved system fairness over the existing approaches. Our method maximizes throughput, and for 500 UE, the throughput is 10.4 Mbps, with an average queuing delay of 24 ms. As a result, when compared to the existing method, MOGABO method offers a 1.2% increase in throughput. Thus, our method offers better coverage and throughput for D2D cellular communication with the reduction of computational complexities.     

Krempfielins Q and R,Two New Eunicellin-Based Diterpenoids from the Soft Coral Cladiella krempfi

Two new eunicellin-based diterpenoids, krempfielins Q and R (1 and 2), and one known compound cladieunicellin K (3) have been isolated from a Formosan soft coral Cladiella krempfi. The structures of these two new metabolites were elucidated by extensive spectroscopic analysis. Anti-inflammatory activity of new metabolites to inhibit the superoxide anion generation and elastase release in N-formyl-methionyl-leucyl phenylalanine/cytochalasin B (FMLP/CB)-induced human neutrophil cells and cytotoxicity of both new compounds toward five cancer cell lines were reported.     

Intrusion Detection System for Big Data Analytics in IoT Environment

In the digital area, Internet of Things (IoT) and connected objects generate a huge quantity of data traffic which feeds big data analytic models to discover hidden patterns and detect abnormal traffic. Though IoT networks are popular and widely employed in real world applications, security in IoT networks remains a challenging problem. Conventional intrusion detection systems (IDS) cannot be employed in IoT networks owing to the limitations in resources and complexity. Therefore, this paper concentrates on the design of intelligent metaheuristic optimization based feature selection with deep learning (IMFSDL) based classification model, called IMFSDL-IDS for IoT networks. The proposed IMFSDL-IDS model involves data collection as the primary process utilizing the IoT devices and is preprocessed in two stages: data transformation and data normalization. To manage big data, Hadoop ecosystem is employed. Besides, the IMFSDL-IDS model includes a hill climbing with moth flame optimization (HCMFO) for feature subset selection to reduce the complexity and increase the overall detection efficiency. Moreover, the beetle antenna search (BAS) with variational autoencoder (VAE), called BAS-VAE technique is applied for the detection of intrusions in the feature reduced data. The BAS algorithm is integrated into the VAE to properly tune the parameters involved in it and thereby raises the classification performance. To validate the intrusion detection performance of the IMFSDL-IDS system, a set of experimentations were carried out on the standard IDS dataset and the results are investigated under distinct aspects. The resultant experimental values pointed out the betterment of the IMFSDL-IDS model over the compared models with the maximum accuracy 95.25% and 97.39% on the applied NSL-KDD and UNSW-NB15 dataset correspondingly.     

Investigation and Comparative Analysis of Advanced PWM Techniques for Three-Phase Three-Level NPC-MLI Drives

The Multilevel inverter topologies (MLIs) are increasingly being used, which is the preferred choice in many industrial Medium-voltage (MV) applications. The inherent low switching frequency in medium voltage neutral point clamped MLI (NPC-MLI) fed industrial drives represent the power quality issues and filter-design challenges. In this paper, two multilevel pulse width modulation (PWM) methods; multi-carrier sine PWM (MCSPWM) and space vector PWM (SVPWM) has been considered for NPC-MLI. Both the methods are compared and analyzed based on different constraints such as voltage profile, total harmonic distortion (THD), common mode voltage (CMV) and neutral point fluctuation (NPF). The results convey that the SVPWM method is superior when compared with the MCSPWM algorithms. Analytical and simulation results achieved by using the MATLAB/Simulink for control systems are experimentally verified using FPGA-SPARTAN – III generation – 3AN –XC3S400 with a 2KW NPC-MLI fed adjustable speed – drive system.     

Preparation of Highly Ordered Nitrogen‐Containing Mesoporous Carbon from a Gelatin Biomolecule and its Excellent Sensing of Acetic Acid

Novel nitrogen‐containing mesoporous carbon with well‐ordered pores (NMC‐G) and high basicity is synthesized using a low‐cost single‐molecule precursor, gelatin biomolecule, and SBA‐15 as a template via nanocasting method. The obtained materials are thoroughly characterized. It is found that the prepared materials have excellent textural properties such as high specific surface areas, huge pore volumes, and large pore diameters. The pore diameter of the materials can also be controlled with a simple adjustment of the pore diameter of the hard templates. The C/N ratio of the samples is calculated to be ≈6.01, which is slightly higher than that observed for mesoporous carbon nitride samples. X‐ray photoelectron spectroscopy (XPS) reveals the presence of sp² hybridized carbon in aromatic ring structure attached to amino groups. The materials could adsorb a huge quantity of CO₂. The sensing capability of the materials with different pore diameters for different adsorbates including ethanol, acetic acid, aniline, toluene, and ammonia is also investigated. Among the materials with different pore diameters studied, the material with the highest basicity and the largest pore diameter (NMC‐G‐150) showed excellent sensing performance with a high selectivity of adsorption for acetic acid molecule.