Proposed system for data security in distributed computing in using ‎triple data encryption standard and ‎Rivest Shamir ‎Adlemen

Cloud computing is considered a distributed computing paradigm in which resources ‎are ‎provided as services. In cloud computing, the ‎applications do not run ‎from a user’s personal computer but are run and stored on distributed ‎servers on the Internet. The ‎resources of the cloud infrastructures are shared on cloud ‎computing on the Internet in the open ‎environment. This increases the security problems in ‎security such as data confidentiality, data ‎integrity and data availability, so the solution of such ‎problems are conducted by adopting data ‎encryption is very important for securing users data. ‎In this paper, a comparative ‎study is done between the two security algorithms on a cloud ‎platform called eyeOS. From the ‎comparative study it was found that the Rivest Shamir ‎Adlemen ‎(3kRSA) algorithm ‎outperforms that triple data encryption standard (3DES) algorithm with ‎respect to the complexity, and output bytes. The main ‎drawback of the 3kRSA algorithm is its ‎computation time, while 3DES is faster than that ‎‎3kRSA. This is useful for storing large amounts of ‎data used in the cloud computing, the key ‎distribution and authentication of the asymmetric ‎encryption, speed, data integrity and data ‎confidentiality of the symmetric encryption are also ‎important also it enables to execute ‎required computations on this encrypted data.

Optimization of capacity in non-Gaussian noise models with and without fading channels for sustainable communication systems

The highest rate at which information may be reliably sent via a communication link is known as its capacity. In the case of non-Gaussian noise, the capacity of the channel depends on the specific characteristics of the noise, which can cause severe errors and reduce the reliability of communication systems over a fading channel. The Gaussian mixture impulsive noise model (GMINM), which is a more general and flexible non-Gaussian model for impulsive noise, has been compared in this paper with the Middleton Class-A impulsive noise model (MCAINM) in terms of derived channel capacity normalized by channel bandwidth (C/BW) with and without Rayleigh fading (Rf) channels. It also investigated the trade-off between complexity and accuracy in modeling the impulsive noise using two simplified Middleton Class-A impulsive noise models based on derived C/BW. The derived C/BW of these models under various conditions, such as different signal-to-noise ratios and impulsive noise parameters and models, have been performed and evaluated using two different scenarios: the exact method and the semi-analytical method. When the impulsive noise parameters  and A are both near 0 in GMINM and MCAINM, respectively, the capacity of the impulsive noise channel is found to be equivalent to that of the Gaussian channel sustainable, as shown by the findings based on Monte-Carlo simulations. We have shown that when the impulsive noise decreases, the capacity increases in all models; however, the capacity of Gaussian noise is higher than the capacity of non-Gaussian noise, which in turn is higher than the capacity of non-Gaussian noise over the Rf channel overall values of SNR in dB. Moreover, multi-channel configuration introduces spatial diversity and multiplexing gains that have been proposed to sustainably optimize the ergodic capacity for the challenge case when the channel state information (CSI) is unknown at the transmitter in non-Gaussian noise over Rf channel. In today's rapidly evolving world, sustainable communication systems play a crucial role in ensuring efficient and responsible utilization of resources. As the demand for wireless communication continues to rise, it becomes imperative to optimize the capacity of communication channels, especially in scenarios involving non-Gaussian noise models and fading channels.

Efficacy of entomopathogenic nematodes for control of large pine weevil, Hylobius abietis: effects of soil type, pest density and spatial distribution

The large pine weevil Hylobius abietis (L.), LPW, is a major pest of trees in replanted coniferous forests in northern Europe. The use of entomopathogenic nematodes (EPNs) applied against developing stages for population suppression is increasingly recognized as an effective alternative to plant protection using chemical pesticides. Here, we report results from a series of trials we conducted over 2 years using two species of EPN, Steinernema carpocapsae (Weiser) and Heterorhabitis downesi (Stock, Griffin, and Burnell) with different foraging strategies. Trials were conducted at lodgepole pine sites in Ireland on both mineral and peat soil type. EPN suspension was applied to the stumps of felled pine trees, and EPN efficacy was determined afterwards by directly assessing parasitism rates after debarking one quarter of the stumps and by collecting emerging adult weevils from traps erected over other treated and control stumps. Our results suggest that both species of EPN are equally effective in suppressing LPW populations to below the current, informal thresholds of economic damage. EPN were equally efficient in controlling LPW in peat and in mineral (lithosols/regosols and acid brown earth/brown podzolics) soils. Weevil density and distribution within pine stumps in peat versus mineral sites can explain patterns of LPW parasitism and suppression. Our results also suggest that infestation level (number of weevils per stump) can be an important factor in forecasting EPN application success as there is evidence of negative density-dependent parasitism when weevil densities were high. © 2016 Springer-Verlag Berlin Heidelber

Efficacy of entomopathogenic fungi against large pine weevil, Hylobius abietis, and their additive effects when combined with entomopathogenic nematodes

The large pine weevil Hylobius abietis is an important pest of reforestation in northern Europe. In field trials, we assessed the efficacy of entomopathogenic fungi (EPF) alone and in combination with entomopathogenic nematodes (EPN) against immature stages. We used commercial strains of Metarhizium brunneum and Beauveria bassiana and a strain of Beauveria caledonica isolated from the pest’s habitat. The EPN used were Steinernema carpocapsae and Heterorhabditis downesi. Efficacy was assessed by weevil infection in stumps and by numbers of adult weevils emerging in traps above the stumps. EPF infected up to 23% of pine weevils, at depths up to 25 cm below ground. Three EPF application methods were compared, but application method did not affect infection rates. When applied at half doses, EPF and EPN had additive effects: M. brunneum and S. carpocapsae caused a reduction in emergence of 58% relative to control, M. brunneum and H. downesi 93%, B. caledonica and H. downesi 86%. EPN alone offered good suppression of H. abietis populations and suppression by the mixture did not surpass suppression afforded by EPN alone. Our trials show B. caledonica is a promising species, rivalling the success of the other two species. Applied EPF, especially M. brunneum, can persist for at least 2 years in the forest setting. Additionally, different fungi can have differential action against weevils above versus below ground; therefore, EPF combinations may be beneficial. Based on our trials, further development of strains and application methods are required before EPF can be recommended for suppression of pine weevil. © 2018 Springer-Verlag GmbH Germany, part of Springer Natur

Recent advances of data compression in wireless sensor network

Wireless Sensor Networks (WSNs) have emerged as one of the most promising wireless communication systems supporting wide variety of applications ranging from military tasks, healthcare, disaster prediction and indoor positioning. The low complexity and cost of the nodes result in constraints such as computational power, communication bandwidth and battery power. Energy consumption is one of the most critical to WSN. In WSN communication, data transmission is considered the largest contributor to total energy exhaustion and apparently, it is influenced by the size of the data. Favorably, data compression can be used to reduce the amount of data that requires to be transmitted and hence prolongs sensor's lifetime. In this study, we survey various approaches, issues and challenges to WSN efficiency related to data compression discuss the effect of the data size on the sensor efficiency and how data compression algorithms can be used to address small size data transmission. Finally, recent approaches are reviewed with highlighting of advantages and disadvantages of each solution

The roles and contributions of Biodiversity Observation Networks (BONs) in better tracking progress to 2020 biodiversity targets: a European case study

The Aichi Biodiversity Targets of the United Nations’ Strategic Plan for Biodiversity set ambitious goals for protecting biodiversity from further decline. Increased efforts are urgently needed to achieve these targets by 2020. The availability of comprehensive, sound and up-to-date biodiversity data is a key requirement to implement policies, strategies and actions to address biodiversity loss, monitor progress towards biodiversity targets, as well as to assess the current status and future trends of biodiversity. Key gaps, however, remain in our knowledge of biodiversity and associated ecosystem services. These are mostly a result of barriers preventing existing data from being discoverable, accessible and digestible. In this paper, we describe what regional Biodiversity Observation Networks (BONs) can do to address these barriers using the European Biodiversity Observation Network (EU BON) as an example. We conclude that there is an urgent need for a paradigm shift in how biodiversity data are collected, stored, shared and streamlined in order to tackle the many sustainable development challenges ahead. We need a shift towards an integrative biodiversity information framework, starting from collection to the final interpretation and packaging of data. This is a major objective of the EU BON project, towards which progress is being made

Performance analysis of MPI approaches and PThread in multi-core system

Comparison among the HPC techniques has been made in order to address the highest and lowest performance of each in terms of execution time, speedup and efficiency when it is used with the HPc multicore system. The matrix multiplication in a variant size is used as a common complex task to examine the performance of each approach. FSKTM server has been used as an HPC multicore system to perform the approaches and tasks. Based on the results, it shows that Hybrid MPI/OpenMP approach is the best in terms of execution time, speed up and efficiency than other approaches when the matrix size is very high (>1024×1024 size). Furthermore, the results show that the compiler version has a significant impact over the performance of Pthread. With a new compiler, the performance becomes much better due to the improvement in code translation

Conditional Adversarial Camera Model Anonymization

The model of camera that was used to capture a particular photographic image (model attribution) is typically inferred from high-frequency model-specific artifacts present within the image. Model anonymization is the process of transforming these artifacts such that the apparent capture model is changed. We propose a conditional adversarial approach for learning such transformations. In contrast to previous works, we cast model anonymization as the process of transforming both high and low spatial frequency information. We augment the objective with the loss from a pre-trained dual-stream model attribution classifier, which constrains the generative network to transform the full range of artifacts. Quantitative comparisons demonstrate the efficacy of our framework in a restrictive non-interactive black-box setting.Comment: ECCV 2020 - Advances in Image Manipulation workshop (AIM 2020

A decadal view of biodiversity informatics: challenges and priorities

Biodiversity informatics plays a central enabling role in the research community's efforts to address scientific conservation and sustainability issues. Great strides have been made in the past decade establishing a framework for sharing data, where taxonomy and systematics has been perceived as the most prominent discipline involved. To some extent this is inevitable, given the use of species names as the pivot around which information is organised. To address the urgent questions around conservation, land-use, environmental change, sustainability, food security and ecosystem services that are facing Governments worldwide, we need to understand how the ecosystem works. So, we need a systems approach to understanding biodiversity that moves significantly beyond taxonomy and species observations. Such an approach needs to look at the whole system to address species interactions, both with their environment and with other species. It is clear that some barriers to progress are sociological, basically persuading people to use the technological solutions that are already available. This is best addressed by developing more effective systems that deliver immediate benefit to the user, hiding the majority of the technology behind simple user interfaces. An infrastructure should be a space in which activities take place and, as such, should be effectively invisible. This community consultation paper positions the role of biodiversity informatics, for the next decade, presenting the actions needed to link the various biodiversity infrastructures invisibly and to facilitate understanding that can support both business and policy-makers. The community considers the goal in biodiversity informatics to be full integration of the biodiversity research community, including citizens’ science, through a commonly-shared, sustainable e-infrastructure across all sub-disciplines that reliably serves science and society alike