An intelligent routing approach for multimedia traffic transmission over SDN

Nowadays, multimedia applications such as video streaming services have become significantly popular, especially with the rapid growth of users, various devices, and the increased availability and diversity of these services over the internet. In this case, service providers and network administrators have difficulties ensuring end-user satisfaction because the traffic generated by such services is more exposed to multiple network quality of service impairments, including bandwidth, delay, jitter, and loss ratio. This paper proposes an intelligent-based multimedia traffic routing framework that exploits the integration of a reinforcement learning technique with software-defined networking to explore, learn and find potential routes for video streaming traffic. Simulation results through a realistic network and under various traffic loads demonstrate the proposed scheme's effectiveness in providing a better end-user viewing quality, higher throughput and lower video quality switches when compared to the existing techniques

Deep learning approach for real-time video streaming traffic classification

Video streaming services such as Amazon Prime Video, Netflix and YouTube, continue to be of enormous demands in everyday peoples’ lives. This enticed research in new mechanisms to provide a clear image of network usage and ensure better Quality of Service (QoS) for these applications. This paper proposes an accurate video streaming traffic classification model based on deep learning (DL). We first collected a set of video traffic data from a real network. Video streaming services such as Amazon Prime Video, Netflix and YouTube, continue to be of enormous demands in everyday peoples’ lives. This enticed research in new mechanisms to provide a clear image of network usage and ensure better Quality of Service (QoS) for these applications. This paper proposes an accurate video streaming traffic classification model based on deep learning (DL). We first collected a set of video traffic data from a real network. Then, data was pre-processed to select the desired features for video traffic classification. Based on the performance evaluation, the model produces an overall accuracy of 99.3% when classifying video streaming traffic using a multi-layer feedforward neural network. This paper also evaluates the DL approach’s effectiveness compared to the Gaussian Naive Bayes algorithm (GNB), one of the most well-known machine learning techniques used in Internet traffic classification. The model is promising to be applied in a real-time scenario as it showed its ability to predict new unseen data with 98.4% overall accuracy

Pengaruh Fraksi Penipisan (P) Air Tanah Tersedia Pada Berbagai Fase Tumbuh Terhadap Pertumbuhan, Hasil Dan Efisiensi Penggunaan Air Tanaman Kedelai (Glycine Max [L] Merr.)

Penelitian bertujuan untuk mengetahui pengaruh fraksi penipisan (p) air tanah tersedia pada berbagai fase tumbuh terhadap pertumbuhan dan efisiensi penggunaan air tanaman kedelai. Penelitian ini dilaksanakan di dalam rumah plastik, laboratorium lapang terpadu, Universitas Lampung pada bulan Oktober 2015 sampai dengan Januari 2016. Penelitian ini menggunakan rancangan Faktorial dalam Acak Lengkap (RAL) dengan 2 faktor perlakuan, yaitu faktor I (Fraksi penipisan air tanah tersedia, p) dan faktor II (fase tumbuh, F). Masing-masing perlakuan terdiri dari 3 taraf, yaitu faktor I terdiri dari P1(0,2), P2(0,4) dan P3(0,6) dari penipisan air tanah tersedia, dan faktor II terdiri dari fase vegetatif aktif (F1), fase pembungaan (F2), dan fase pembentukan polong (F3), dengan ulangan sebanyak 3 kali. Pengukuran evapotranspirasi tanaman acuan dilakukan pada fraksi penipisan 0,2 dari air tanah tersedia dengan menggunakan tanaman rumput. Hasil penelitian menunjukkan bahwa, perlakuan fraksi penipisan (p) air tanah tersedia pada berbagai fase tumbuhtidak berpengaruh terhadap pertumbuhan dan efisiensi penggunaan air tanaman kedelai.Tanaman kedelai pada perlakuan fraksi penipisan (p) air tanah tersedia tidak mengalami cekaman air pada semua perlakuan, karena tanaman sebelum mendekati batas bawah perlakuan segera diberi irigasi dan dikembalikan ke kondisi kapasitas lapang. Produksi tertinggi dengan nilai efisiensi penggunaan air tertinggi dicapai oleh perlakuan fraksi penipisan (0-0,2) air tanah tersedia pada perlakuan fase pembungaan (F2). Tanaman kedelai menghasilkan produksi yang tinggi pada fraksi penipisan 0,4 untuk perlakuan fase pertumbuhan aktif dan fraksi penipisan 0,2 untuk perlakuan fase pembungaan dan fase pengisian polong

How the other half lives: CRISPR-Cas's influence on bacteriophages

CRISPR-Cas is a genetic adaptive immune system unique to prokaryotic cells used to combat phage and plasmid threats. The host cell adapts by incorporating DNA sequences from invading phages or plasmids into its CRISPR locus as spacers. These spacers are expressed as mobile surveillance RNAs that direct CRISPR-associated (Cas) proteins to protect against subsequent attack by the same phages or plasmids. The threat from mobile genetic elements inevitably shapes the CRISPR loci of archaea and bacteria, and simultaneously the CRISPR-Cas immune system drives evolution of these invaders. Here we highlight our recent work, as well as that of others, that seeks to understand phage mechanisms of CRISPR-Cas evasion and conditions for population coexistence of phages with CRISPR-protected prokaryotes.Comment: 24 pages, 8 figure

Re-reading in Stylistics

Cognitive stylistics is primarily concerned with the cognitive processes – mental simulations – experienced by readers. Most cognitive stylisticians agree that experiences of reading texts are dynamic and flexible. Changes in the context of reading, our attentional focus on a given day, our extra background knowledge about the text, and so on, are all factors that contribute to our experience of a fictional world. A second reading of a text is a different experience to a first reading. As researchers begin to systematically distinguish between the ‘solitary’ and ‘social’ readings that constitute reading as a phenomenon (Peplow et al., 2016), the relationship between multiple readings and the nature of their processing become increasingly pertinent. In order to explore this relationship, firstly we examine the different ways in which re-reading has previously been discussed in stylistics, grounding our claims in an empirical analysis of articles published in key stylistics journals over the past two decades. Next, we draw on reader response data from an online questionnaire in order to assess the role of re-reading and the motivations that underpin it. Finally, we describe an exercise for the teaching of cognitive stylistics, specifically applying schema theory in literary linguistic analysis (Cook, 1994), which illustrates the need to distinguish between readings as part of an analysis. Through these three sections we argue that our experiences of texts should be considered diachronically, and propose that the different readings that make up an analysis of a text should be given greater attention in stylistic research and teaching

Identification of Substrain-Specific Mutations by Massively Parallel Whole-Genome Resequencing of Synechocystis sp. PCC 6803

The cyanobacterium, Synechocystis sp. PCC 6803, was the first photosynthetic organism whose genome sequence was determined in 1996 (Kazusa strain). It thus plays an important role in basic research on the mechanism, evolution, and molecular genetics of the photosynthetic machinery. There are many substrains or laboratory strains derived from the original Berkeley strain including glucose-tolerant (GT) strains. To establish reliable genomic sequence data of this cyanobacterium, we performed resequencing of the genomes of three substrains (GT-I, PCC-P, and PCC-N) and compared the data obtained with those of the original Kazusa strain stored in the public database. We found that each substrain has sequence differences some of which are likely to reflect specific mutations that may contribute to its altered phenotype. Our resequence data of the PCC substrains along with the proposed corrections/refinements of the sequence data for the Kazusa strain and its derivatives are expected to contribute to investigations of the evolutionary events in the photosynthetic and related systems that have occurred in Synechocystis as well as in other cyanobacteria

Genomic Structure of the Cyanobacterium Synechocystis sp. PCC 6803 Strain GT-S

Synechocystis sp. PCC 6803 is the most popular cyanobacterial strain, serving as a standard in the research fields of photosynthesis, stress response, metabolism and so on. A glucose-tolerant (GT) derivative of this strain was used for genome sequencing at Kazusa DNA Research Institute in 1996, which established a hallmark in the study of cyanobacteria. However, apparent differences in sequences deviating from the database have been noticed among different strain stocks. For this reason, we analysed the genomic sequence of another GT strain (GT-S) by 454 and partial Sanger sequencing. We found 22 putative single nucleotide polymorphisms (SNPs) in comparison to the published sequence of the Kazusa strain. However, Sanger sequencing of 36 direct PCR products of the Kazusa strains stored in small aliquots resulted in their identity with the GT-S sequence at 21 of the 22 sites, excluding the possibility of their being SNPs. In addition, we were able to combine five split open reading frames present in the database sequence, and to remove the C-terminus of an ORF. Aside from these, two of the Insertion Sequence elements were not present in the GT-S strain. We have thus become able to provide an accurate genomic sequence of Synechocystis sp. PCC 6803 for future studies on this important cyanobacterial strain

Functional Connectivity Evaluation for Infant EEG Signals based on Artificial Neural Network

The employment of the brain signals electroencephalography (EEG) could supply a deep intuitive understanding for infants behaviour and their alertness level within the living environment. The study of human brain through a computer-based approach has increased significantly as it aiming at the understanding of infants’ mind and measure their attention towards the surrounding activities. The artificial neural network achieved a significant level of success in different fields such as pattern classification, decision making, prediction, and adaptive control by learning from a set of data and construct weight matrices to represent the learning patterns. This research study proposes an artificial neural network based approach to predict the rightward asymmetry or leftward asymmetry which reflects higher frontal functional connectivity in the frontal right and frontal left, respectively within infant’s brain. In the traditional methods, the value of asymmetry of the frontal (FA) functional connectivity is used to determine the rightward or the leftward asymmetry. While the proposed approach is trying to predict that without going through all the levels of the calculation complexity. The achieved work will supply a deep understanding into the deployment of the functional connectivity to provide information on the interactions between different brain regions

Germ Warfare in a Microbial Mat Community: CRISPRs Provide Insights into the Co-Evolution of Host and Viral Genomes

CRISPR arrays and associated cas genes are widespread in bacteria and archaea and confer acquired resistance to viruses. To examine viral immunity in the context of naturally evolving microbial populations we analyzed genomic data from two thermophilic Synechococcus isolates (Syn OS-A and Syn OS-B′) as well as a prokaryotic metagenome and viral metagenome derived from microbial mats in hotsprings at Yellowstone National Park. Two distinct CRISPR types, distinguished by the repeat sequence, are found in both the Syn OS-A and Syn OS-B′ genomes. The genome of Syn OS-A contains a third CRISPR type with a distinct repeat sequence, which is not found in Syn OS-B′, but appears to be shared with other microorganisms that inhabit the mat. The CRISPR repeats identified in the microbial metagenome are highly conserved, while the spacer sequences (hereafter referred to as “viritopes” to emphasize their critical role in viral immunity) were mostly unique and had no high identity matches when searched against GenBank. Searching the viritopes against the viral metagenome, however, yielded several matches with high similarity some of which were within a gene identified as a likely viral lysozyme/lysin protein. Analysis of viral metagenome sequences corresponding to this lysozyme/lysin protein revealed several mutations all of which translate into silent or conservative mutations which are unlikely to affect protein function, but may help the virus evade the host CRISPR resistance mechanism. These results demonstrate the varied challenges presented by a natural virus population, and support the notion that the CRISPR/viritope system must be able to adapt quickly to provide host immunity. The ability of metagenomics to track population-level variation in viritope sequences allows for a culture-independent method for evaluating the fast co-evolution of host and viral genomes and its consequence on the structuring of complex microbial communities