Statistical Measures of Generic Noise Distributions for Molecular Communication

Author(s):  
Srishti Kumari ◽  
Swati Singh ◽  
Rajneesh Kumar Singh ◽  
S. Pratap Singh ◽  
Laksh manan M ◽  
...  
Author(s):  
Revati Kadu ◽  
U. A. Belorkar

One of the most common and augmenting health problems in the world are related to skin. The most  unpredictable and one of the most difficult entities to automatically detect and evaluate is the human skin disease because of complexities of texture, tone, presence of hair and other distinctive features. Many cases of skin diseases in the world have triggered a need to develop an effective automated screening method for detection and diagnosis of the area of disease. Therefore the objective of this work is to develop a new technique for automated detection and analysis of the skin disease images based on color and texture information for skin disease screening. In this paper, system is proposed which detects the skin diseases using Wavelet Techniques and Artificial Neural Network. This paper presents a wavelet-based texture analysis method for classification of five types of skin diseases. The method applies tree-structured wavelet transform on different color channels of red, green and blue dermoscopy images, and employs various statistical measures and ratios on wavelet coefficients. In all 99 unique features are extracted from the image. By using Artificial Neural Network, the system successfully detects different types of dermatological skin diseases. It consists of mainly three phases image processing, training phase, detection  and classification phase.


2018 ◽  
Vol 31 (1) ◽  
pp. 277 ◽  
Author(s):  
Methaq Talib Gaata

  With the fast progress of information technology and the computer networks, it becomes very easy to reproduce and share the geospatial data due to its digital styles. Therefore, the usage of geospatial data suffers from various problems such as data authentication, ownership proffering, and illegal copying ,etc. These problems can represent the big challenge to future uses of the geospatial data. This paper introduces a new watermarking scheme to ensure the copyright protection of the digital vector map. The main idea of proposed scheme is based on transforming  the digital map to frequently domain using the Singular Value Decomposition (SVD) in order to determine suitable areas to insert the watermark data. The digital map is separated into the isolated parts.Watermark data are embedded within the nominated magnitudes in each part when satisfied the definite criteria. The efficiency of proposed watermarking scheme is assessed within statistical measures based on two factors which are fidelity and robustness. Experimental results demonstrate the proposed watermarking scheme representing ideal trade off for disagreement issue between distortion amount and robustness. Also, the proposed scheme shows  robust resistance for many kinds of attacks.


2019 ◽  
Vol 20 (8) ◽  
pp. 800-807 ◽  
Author(s):  
Jose Luis Marzo ◽  
Josep Miquel Jornet ◽  
Massimiliano Pierobon

By interconnecting nanomachines and forming nanonetworks, the capacities of single nanomachines are expected to be enhanced, as the ensuing information exchange will allow them to cooperate towards a common goal. Nowadays, systems normally use electromagnetic signals to encode, send and receive information, however, in a novel communication paradigm, molecular transceivers, channel models or protocols use molecules. This article presents the current developments in nanomachines along with their future architecture to better understand nanonetwork scenarios in biomedical applications. Furthermore, to highlight the communication needs between nanomachines, two applications for nanonetworks are also presented: i) a new networking paradigm, called the Internet of NanoThings, that allows nanoscale devices to interconnect with existing communication networks, and ii) Molecular Communication, where the propagation of chemical compounds like drug particles, carry out the information exchange.


2020 ◽  
Vol 16 (2) ◽  
pp. 280-289
Author(s):  
Ghalib H. Alshammri ◽  
Walid K. M. Ahmed ◽  
Victor B. Lawrence

Background: The architecture and sequential learning rule-based underlying ARFIS (adaptive-receiver-based fuzzy inference system) are proposed to estimate and predict the adaptive threshold-based detection scheme for diffusion-based molecular communication (DMC). Method: The proposed system forwards an estimate of the received bits based on the current molecular cumulative concentration, which is derived using sequential training-based principle with weight and bias and an input-output mapping based on both human knowledge in the form of fuzzy IFTHEN rules. The ARFIS architecture is employed to model nonlinear molecular communication to predict the received bits over time series. Result: This procedure is suitable for binary On-OFF-Keying (Book signaling), where the receiver bio-nanomachine (Rx Bio-NM) adapts the 1/0-bit detection threshold based on all previous received molecular cumulative concentrations to alleviate the inter-symbol interference (ISI) problem and reception noise. Conclusion: Theoretical and simulation results show the improvement in diffusion-based molecular throughput and the optimal number of molecules in transmission. Furthermore, the performance evaluation in various noisy channel sources shows promising improvement in the un-coded bit error rate (BER) compared with other threshold-based detection schemes in the literature.


Author(s):  
Kyle Hoegh ◽  
Trevor Steiner ◽  
Eyoab Zegeye Teshale ◽  
Shongtao Dai

Available methods for assessing hot-mix-asphalt pavements are typically restricted to destructive methods such as coring that damage the pavement and are limited in coverage. Recently, density profiling systems (DPS) have become available with the capability of measuring asphalt compaction continuously, giving instantaneous measurements a few hundred feet behind the final roller of the freshly placed pavement. Further developments of the methods involved with DPS processing have allowed for coreless calibration by correlating dielectric measurements with asphalt specimens fabricated at variable air void contents using superpave gyratory compaction. These developments make DPS technology an attractive potential tool for quality control because of the real-time nature of the results, and quality assurance because of the ability to measure a more statistically significant amount of data as compared with current quality assurance methods such as coring. To test the viability of these recently developed methods for implementation, multiple projects were selected for field trials. Each field trial was used to assess the coreless calibration prediction by comparing with field cores where dielectric measurements were made. Ground truth core validation on each project showed the reasonableness of the coreless calibration method. The validated dielectric to air void prediction curves allowed for assessment of the tested pavements in relation to as-built characteristics, with the DPS providing the equivalent of approximately 100,000 cores per mile. Statistical measures were used to demonstrate how DPS can provide a comprehensive asphalt compaction evaluation that can be used to inform construction-related decisions and has potential as a future quality assurance tool.


Author(s):  
Yansha Deng ◽  
Adam Noel ◽  
Maged Elkashlan ◽  
Arumugam Nallanathan ◽  
Karen C. Cheung

Science ◽  
2021 ◽  
Vol 372 (6539) ◽  
pp. eabf1941
Author(s):  
Sandipan Ray ◽  
Utham K. Valekunja ◽  
Alessandra Stangherlin ◽  
Steven A. Howell ◽  
Ambrosius P. Snijders ◽  
...  

Abruzzi et al. argue that transcriptome oscillations found in our study in the absence of Bmal1 are of low amplitude, statistical significance, and consistency. However, their conclusions rely solely on a different statistical algorithm than we used. We provide statistical measures and additional analyses showing that our original analyses and observations are accurate. Further, we highlight independent lines of evidence indicating Bmal1-independent 24-hour molecular oscillations.


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