Spectral width reduction using apodized cascaded fiber Bragg grating for post-dispersion compensation in WDM optical networks

This paper proposes a system that aims to reduce the spectral width, Δλ, of the optical signal at transmitter for WDM system over distance 100 km. Also, a chirped fiber Bragg grating (CFBG) at the receiver is used to compensate dispersion. The proposed system consists of four cascaded FBGs connected between light source and optical fiber. Many apodization functions are investigated to enhance the performance of the FBG in the proposed system, and Δλ is obtained at every stage and apodization function. The Q-factor and bit error rate (BER) are obtained at distances 30, 40 and 50 km. It is found that Cauchy apodization function is the best one that reduces the reflective spectral width, Δλ, and achieves a maximum Q-factor and minimum BER at distances 30, 40 and 50 km at the last stage.

     

A novel deep learning framework for copy-moveforgery detection in images

Multimedia Tools and Applications - In this era of technology, digital images turn out to be ubiquitous in a contemporary society and they can be generated and manipulated by a wide variety of...     

In vitro analysis of inflammatory responses following environmental exposure to pharmaceuticals and inland waters

Pharmaceuticals are regularly released into the environment; in particular non-steroidal anti-inflammatory drugs (NSAIDs) and antibiotics. Erythromycin, naproxen, furosemide and atenolol are reported to be stable for up to 1 year in the environment, which increases the risk for accumulation. In the present study we have measured the occurrence and concentration of pharmaceuticals in river Viskan (Jössabron) downstream of a sewage treatment plant in Borås, Sweden. Pharmaceuticals and water samples were tested for potential human risk by evaluating inflammatory responses (NF-κB and AP-1) using human T24 bladder epithelial cells and Jurkat T-cells. NF-κB activity in T24 cells was significantly reduced by all NSAIDs analysed (diclofenac, ketoprofen, naproxen, ibuprophen and dextropropoxyphene), but also by trimethoprim, using environmentally relevant concentrations. NF-κB and AP-1 activation was further analysed in response to water samples collected from different locations in Sweden. Dose-dependent down-regulation of AP-1 activity in Jurkat cells was observed at all locations. At two locations (Jössabron and Almenäs) down-regulation of NF-κB was observed. In contrast, the NF-κB response was potentiated by exposure to water from both locations following activation of NF-κB by treatment with heat-killed Escherichia coli. To determine the involvement of pharmaceuticals in the responses, T24 cells were exposed to the pharmaceutical mixture, based on the determined levels at Jössabron. This resulted in reduction of the NF-κB response following exposure to the pharmaceutical mixture alone while no potentiation was observed when cells were co-exposed to heat killed E. coli and pharmaceuticals. The obtained results demonstrate that the identified pharmaceuticals affect the inflammatory responses and furthermore indicate the presence of unknown substance(s) with the ability to potentiate inflammatory responses.     

Steam reforming of simulated pre-reformed naphtha in a PdAu membrane reactor

Process intensification in a membrane reactor is an efficient and compact way to produce hydrogen. A methane-rich gas mixture that simulated the composition of pre-reformed naphtha (PRN; with a steam-to-carbon ratio of 2.7) was reformed at temperatures of 550 °C–625 °C and pressures up to 40 barg. The reactor contained commercial steam reforming catalyst and a 14.8 cm long, 2.6 μm thick Pd-1.8Au (wt. %) membrane on a porous alumina support. Methane conversions approaching 90% were obtained in the membrane reactor at a gas-hourly space velocity of 676 h^?1, compared to ≤30% conversion at the same conditions in conventional reactor mode (CM) without withdrawing hydrogen through the membrane. The results were compared to steam methane reforming (SMR) in the membrane reactor at similar conditions. The nitrogen leak through the membrane increased slowly during the testing, because of both pinhole formation and some leakage through the end seals.     

Effect of mixing rate on the morphology of primary Al phase in the controlled diffusion solidification (CDS) process

Controlled diffusion solidification is a novel and promising process wherein near-net-shaped cast product of a desired Al wrought alloy is obtained by mixing two precursor alloys at specific individual composition, mass, and temperature each to obtain a non-dendritic morphology of the primary Al phase in the solidified microstructure. This study is devoted to quantify the effect of the rate of mixing of the two precursor alloys on the morphology of the primary Al phase in the cast component. The results show that the lower mixing rate with a higher mixing velocity is more favorable for the CDS process.     

Coordination for fragmented loops and scopes in a distributed business process

As partner relationships become more dynamic and global boundaries give way to a more agile and dynamic environment, the ability to distribute one's processes in an agile manner becomes increasingly important. Such processes may need to be split not only along their explicit dependencies but also along more complex behavior such as recovery behavior and loops. The resulting process fragments can be distributed and wired together, recreating the execution semantics of the original process model. In earlier work, we presented BPEL fragmentation covering data and explicit control dependencies. We now extend the approach to handle fragmenting loops and scopes. Maintaining the focus on standards and maximizing extensibility of Web service runtimes and standards, the solution defines and uses two new coordination protocols that plug into the WS-Coordination framework. The approach uses the standards as much as is feasible and addresses the remaining required functionality by providing architected extensions. This results in layered approach that maximizes transparency and interoperability. After defining the fragmentation approach for scopes and loops, an implementation is presented that extends the Active Endpoints BPEL engine and a WS-Coordination system. A detailed example is used to illustrate how the protocols are used at runtime to enable the coordinator and the process fragments to recreate the behavior of the original, unsplit process model.     

Embedded Coded Relay System for Molecular Communications

With the emergence of the COVID-19 pandemic, the World Health Organization (WHO) has urged scientists and industrialists to explore modern information and communication technology (ICT) as a means to reduce or even eliminate it. The World Health Organization recently reported that the virus may infect the organism through any organ in the living body, such as the respiratory, the immunity, the nervous, the digestive, or the cardiovascular system. Targeting the abovementioned goal, we envision an implanted nanosystem embedded in the intra living-body network. The main function of the nanosystem is either to perform diagnosis and mitigation of infectious diseases or to implement a targeted drug delivery system (i.e., delivery of the therapeutic drug to the diseased tissue or targeted cell). The communication among the nanomachines is accomplished via communication-based molecular diffusion. The control/interconnection of the nanosystem is accomplished through the utilization of Internet of bio-nano things (IoBNT). The proposed nanosystem is designed to employ a coded relay nanomachine disciplined by the decode and forward (DF) principle to ensure reliable drug delivery to the targeted cell. Notably, both the sensitivity of the drug dose and the phenomenon of drug molecules loss before delivery to the target cell site in long-distance due to the molecules diffusion process are taken into account. In this paper, a coded relay NM with conventional coding techniques such as RS and Turbo codes is selected to achieve minimum bit error rate (BER) performance and high signal-to-noise ratio (SNR), while the detection process is based on maximum likelihood (ML) probability and minimum error probability (MEP). The performance analysis of the proposed scheme is evaluated in terms of channel capacity and bit error rate by varying system parameters such as relay position, number of released molecules, relay and receiver size. Analysis results are validated through simulation and demonstrate that the proposed scheme can significantly improve delivery performance of the desirable drugs in the molecular communication system.     

A Novel Hybrid Machine Learning Approach for Classification of Brain Tumor Images

Abnormal growth of brain tissues is the real cause of brain tumor. Strategy for the diagnosis of brain tumor at initial stages is one of the key step for saving the life of a patient. The manual segmentation of brain tumor magnetic resonance images (MRIs) takes time and results vary significantly in low-level features. To address this issue, we have proposed a ResNet-50 feature extractor depended on multilevel deep convolutional neural network (CNN) for reliable images segmentation by considering the low-level features of MRI. In this model, we have extracted features through ResNet-50 architecture and fed these feature maps to multi-level CNN model. To handle the classification process, we have collected a total number of 2043 MRI patients of normal, benign, and malignant tumor. Three model CNN, multi-level CNN, and ResNet-50 based multi-level CNN have been used for detection and classification of brain tumors. All the model results are calculated in terms of various numerical values identified as precision (P), recall (R), accuracy (Acc) and f1-score (F1-S). The obtained average results are much better as compared to already existing methods. This modified transfer learning architecture might help the radiologists and doctors as a better significant system for tumor diagnosis.     

Web Application Commercial Design for Financial Entities Based on Business Intelligence

Multiple customer data management has become a focus of attention in big organizations. Although much information is available, it does not translate into significant profitable value-added services. We present a design of a commercial web application based on business intelligence that generates information on social and financial behavior of clients in an organization; with the purpose of obtain additional information that allows to get more profits. This app will provide a broader perspective for making strategic decisions to increase profits and reduce internal investment costs. A case in point is the financial sector, a group of financial entities were used to make measurements and test them. A design to build a web application aimed at achieving a large and ambitious goal by means of defined tools reflecting clients’ business needs is proposed. In this research, different techniques and technologies are explored, such as diagrams, frameworks, design, architecture, model entity-relationship, tables, equations, mental maps and development tools. Through the Personal Software Process methodology and with the help of information extraction, consolidation, and visualization, the implementation can be carried out. This article provides the importance of implementing business intelligence in an organization and expands on the steps needed for the implementation of this valuable technology.