Estimating multiple linear regression parameters using term omission method

In this paper, we introduce a new method to estimate multiple linear regression parameters, namely Multiple Term Omission (MTO). Then, we compare its performance with other three methods: Ordinary Least Square (OLS), Maximum Likelihood (ML) and Bayesian Model using several criteria, such as Mean Average Deviation (MAD), Mean Absolute Percentage Error (MAPE) and Root Mean Square Error standard (RMSE). MTO method has the finest consequences as compared to the other methods for the experimented data

Sequence-Level Reference Frames In Video Coding

The proliferation of low-cost DRAM chipsets now begins to allow for the consideration of substantially-increased decoded picture buffers in advanced video coding standards such as HEVC, VVC, and Google VP9. At the same time, the increasing demand for rapid scene changes and multiple scene repetitions in entertainment or broadcast content indicates that extending the frame referencing interval to tens of minutes or even the entire video sequence may offer coding gains, as long as one is able to identify frame similarity in a computationally- and memory-efficient manner. Motivated by these observations, we propose a “stitching” method that defines a reference buffer and a reference frame selection algorithm. Our proposal extends the referencing interval of inter-frame video coding to the entire length of video sequences. Our reference frame selection algorithm uses well-established feature descriptor methods that describe frame structural elements in a compact and semantically-rich manner. We propose to combine such compact descriptors with a similarity scoring mechanism in order to select the frames to be “stitched” to reference picture buffers of advanced inter-frame encoders like HEVC, VVC, and VP9 without breaking standard compliance. Our evaluation on synthetic and real-world video sequences with the HEVC and VVC reference encoders shows that our method offers significant rate gains, with complexity and memory requirements that remain manageable for practical encoders and decoders

Evaluating of Population Transition and Economic Dimensions Recovering from COVID-19 in Jordan

The study evaluates the population shift towards decreased growth rates in Jordan, considering factors such as migration and the COVID-19 pandemic, since the announcement of the population opportunity in 2009. Economic measurement methods were used to identify the factors and their role in slowing down population growth over time. The study found that an increase in the children category by 1% leads to a 1.05% increase in the dependency rate, indicating a variation in the effect of demographics on dependency rates. The study also found that the COVID-19 crisis had a 0.05% impact on the actual dependency rate, which is declining slowly over time

Magnetic Resonance-Guided Laser Interstitial Thermal Therapy for Management of Low-Grade Gliomas and Radiation Necrosis: A Single-Institution Case Series

Background: Laser interstitial thermal therapy (LITT) has emerged as a minimally invasive treatment modality for ablation of low-grade glioma (LGG) and radiation necrosis (RN). Objective: To evaluate the efficacy, safety, and survival outcomes of patients with radiographically presumed recurrent or newly diagnosed LGG and RN treated with LITT. Methods: The neuro-oncological database of a quaternary center was reviewed for all patients who underwent LITT for management of LGG between 1 January 2013 and 31 December 2020. Clinical data including demographics, lesion characteristics, and clinical and radiographic outcomes were collected. Kaplan-Meier analyses comprised overall survival (OS) and progression-free survival (PFS). Results: Nine patients (7 men, 2 women; mean [SD] age 50 [16] years) were included. Patients underwent LITT at a mean (SD) of 11.6 (8.5) years after diagnosis. Two (22%) patients had new lesions on radiographic imaging without prior treatment. In the other 7 patients, all (78%) had surgical resection, 6 (67%) had intensity-modulated radiation therapy and chemotherapy, respectively, and 4 (44%) had stereotactic radiosurgery. Two (22%) patients had lesions that were wild-type IDH1 status. Volumetric assessment of preoperative T1-weighted contrast-enhancing and T2-weighted fluid-attenuated inversion recovery (FLAIR) sequences yielded mean (SD) lesion volumes of 4.1 (6.5) cm(3) and 26.7 (27.9) cm(3), respectively. Three (33%) patients had evidence of radiographic progression after LITT. The pooled median (IQR) PFS for the cohort was 52 (56) months, median (IQR) OS after diagnosis was 183 (72) months, and median (IQR) OS after LITT was 52 (60) months. At the time of the study, 2 (22%) patients were deceased. Conclusions: LITT is a safe and effective treatment option for management of LGG and RN, however, there may be increased risk of permanent complications with treatment of deep-seated subcortical lesions

Toxic chemical pollution of water resources as a threat to the sustainable development

Water pollution by oil and oil products is an additional source in stress to aquatic organism and it has a great impact on wetlands. Oil pollution of water resources has transformed today into a problem of global proportions. Pollutants such as oil are the greatest dangers because it doing a toxic effect on organisms of neuston, pleuston, plankton and benthos. When you are citing the document, use the following link http://essuir.sumdu.edu.ua/handle/123456789/3608

Rate-Accuracy Trade-Off In Video Classification With Deep Convolutional Neural Networks

Advanced video classification systems decode video frames to derive the necessary texture and motion representations for ingestion and analysis by spatio-temporal deep convolutional neural networks (CNNs). However, when considering visual Internet-of-Things applications, surveillance systems and semantic crawlers of large video repositories, the video capture and the CNN-based semantic analysis parts do not tend to be colocated. This necessitates the transport of compressed video over networks and incurs significant overhead in bandwidth and energy consumption, thereby significantly undermining the deployment potential of such systems. In this paper, we investigate the trade-off between the encoding bitrate and the achievable accuracy of CNN-based video classification models that directly ingest AVC/H.264 and HEVC encoded videos. Instead of retaining entire compressed video bitstreams and applying complex optical flow calculations prior to CNN processing, we only retain motion vector and select texture information at significantly-reduced bitrates and apply no additional processing prior to CNN ingestion. Based on three CNN architectures and two action recognition datasets, we achieve 11%–94% saving in bitrate with marginal effect on classification accuracy. A model-based selection between multiple CNNs increases these savings further, to the point where, if up to 7% loss of accuracy can be tolerated, video classification can take place with as little as 3 kbps for the transport of the required compressed video information to the system implementing the CNN models

Rate-accuracy trade-off in video classification with deep convolutional neural networks

Advanced video classification systems decode video frames to derive the necessary texture and motion representations for ingestion and analysis by spatio-temporal deep convolutional neural networks (CNNs). However, when considering visual Internet -of- Things applications, surveillance systems and semantic crawlers of large video repositories, the compressed video content and the CNN-based semantic analysis parts do not tend to be co-located. This necessitates the transport of compressed video over networks and incurs significant overhead in bandwidth and energy consumption, thereby significantly undermining the deployment potential of such systems. In this paper, we investigate the trade-off between the encoding bitrate and the achievable accuracy of CNN-based video classification that ingests AVC/H.264 encoded videos. Instead of entire compressed video bitstreams, we only retain motion vector and selected texture information at significantly reduced bitrates. Based on two CNN architectures and two action recognition datasets, we achieve 38%-59% saving in bitrate with marginal impact in classification accuracy. A simple rate-based selection between the two CNNs shows that even further bitrate savings are possible with graceful degradation in accuracy. This may allow for rate/accuracy-optimized CNN-based video classification over networks

No tempo de migrar

Resultante do contato com a alteridade inglesa, o texto de Tayeb Salih, Tempo de migrar para o norte, publicado há mais de meio século, continua a suscitar reflexões de uma questão que causa conflitos no mundo hodierno, a migração dos povos. Retratando de maneira intensa a intrincada relação Colônia versus Metrópole, o autor nos apresenta uma outra versão da história que, por tanto tempo, esteve sob controle do colonizador. Considerada uma das mais importantes obras árabes do século XX, foi traduzida ao português pela primeira vez no ano de 2004, e é o único texto árabe, com exceção de As mil e uma noites, a ser reeditado no Brasil.  Dada a importância da novela tanto para o sistema literário árabe como para os estudos pós-coloniais, no presente trabalho propomos uma abordagem do texto que não só o apresente como uma obra que denuncia a exploração colonial inglesa, mas também se posta como um contradiscurso no processo dialógico nas relações Oriente-Ocidente. Por fim, analisaremos alguns excertos do texto que julgamos expressivos e que o distingue como uma obra vanguardista.Resulting from the contact with the English otherness, Season of migration to the North, by Tayeb Salih, published more than half a century ago, continues to raise reflections on a subject that causes conflicts in the world today, the migration of peoples. Representing in an intense way the intricate relationship Colony versus Metropolis, the author shows us another version of the story that, for so long, was under control of the colonizer. Considered one of the most important Arab works of the twentieth century, it was translated into Portuguese for the first time in 2004, and it is the only Arabic text, except for the Arabian Nights, to be republished in Brazil. Given the importance of the novel for both the Arabic Literature and the post-colonial studies, in the present work we propose an approach that not only presents the text as a work that denounces the English colonial exploration, but also as an counter-discourse in the dialogical process in the East-West relations. Finally, we will analyze some excerpts of the text that we consider expressive and that distinguishes it as an avant-garde work

The accuracy of pulse oximetry in emergency department patients with severe sepsis and septic shock: a retrospective cohort study

<p>Abstract</p> <p>Background</p> <p>Pulse oximetry is routinely used to continuously and noninvasively monitor arterial oxygen saturation (SaO₂) in critically ill patients. Although pulse oximeter oxygen saturation (SpO₂) has been studied in several patient populations, including the critically ill, its accuracy has never been studied in emergency department (ED) patients with severe sepsis and septic shock. Sepsis results in characteristic microcirculatory derangements that could theoretically affect pulse oximeter accuracy. The purposes of the present study were twofold: 1) to determine the accuracy of pulse oximetry relative to SaO2 obtained from ABG in ED patients with severe sepsis and septic shock, and 2) to assess the impact of specific physiologic factors on this accuracy.</p> <p>Methods</p> <p>This analysis consisted of a retrospective cohort of 88 consecutive ED patients with severe sepsis who had a simultaneous arterial blood gas and an SpO₂value recorded. Adult ICU patients that were admitted from any Calgary Health Region adult ED with a pre-specified, sepsis-related admission diagnosis between October 1, 2005 and September 30, 2006, were identified. Accuracy (SpO₂- SaO₂) was analyzed by the method of Bland and Altman. The effects of hypoxemia, acidosis, hyperlactatemia, anemia, and the use of vasoactive drugs on bias were determined.</p> <p>Results</p> <p>The cohort consisted of 88 subjects, with a mean age of 57 years (19 - 89). The mean difference (SpO₂- SaO₂) was 2.75% and the standard deviation of the differences was 3.1%. Subgroup analysis demonstrated that hypoxemia (SaO₂< 90) significantly affected pulse oximeter accuracy. The mean difference was 4.9% in hypoxemic patients and 1.89% in non-hypoxemic patients (p < 0.004). In 50% (11/22) of cases in which SpO₂was in the 90-93% range the SaO2 was <90%. Though pulse oximeter accuracy was not affected by acidoisis, hyperlactatementa, anemia or vasoactive drugs, these factors worsened precision.</p> <p>Conclusions</p> <p>Pulse oximetry overestimates ABG-determined SaO₂by a mean of 2.75% in emergency department patients with severe sepsis and septic shock. This overestimation is exacerbated by the presence of hypoxemia. When SaO₂needs to be determined with a high degree of accuracy arterial blood gases are recommended.</p