Fully Point-wise Convolutional Neural Network for Modeling Statistical Regularities in Natural Images

Modeling statistical regularity plays an essential role in ill-posed image processing problems. Recently, deep learning based methods have been presented to implicitly learn statistical representation of pixel distributions in natural images and leverage it as a constraint to facilitate subsequent tasks, such as color constancy and image dehazing. However, the existing CNN architecture is prone to variability and diversity of pixel intensity within and between local regions, which may result in inaccurate statistical representation. To address this problem, this paper presents a novel fully point-wise CNN architecture for modeling statistical regularities in natural images. Specifically, we propose to randomly shuffle the pixels in the origin images and leverage the shuffled image as input to make CNN more concerned with the statistical properties. Moreover, since the pixels in the shuffled image are independent identically distributed, we can replace all the large convolution kernels in CNN with point-wise ($1*1$) convolution kernels while maintaining the representation ability. Experimental results on two applications: color constancy and image dehazing, demonstrate the superiority of our proposed network over the existing architectures, i.e., using 1/10$\sim$1/100 network parameters and computational cost while achieving comparable performance.Comment: 9 pages, 7 figures. To appear in ACM MM 201

Ультрафлокуляция – как метод повышения эффективности процесса извлечения тонкодисперсного угля из хвостов обогащения

На прикладі хвостів вуглезбагачення ОФ "Распадська" (р. Междуріченськ Кемеровської області, РФ) встановлено, що використання ультрафлокулярної обробки дає нижче-наступні переваги при витяганні тонкодисперсного вугілля методом седиментації в радіальному згущувачі: • зниження витрати флокулянтів – в 2,5-3,5 разу. • збільшення витягання вугільного концентрату з хвостів на 23…26%. • зменшення зольності концентрату, вилученого з хвостів з 18 до 12%. • зменшення вологості прес-фільтраційного кека концентрату, вилученого з хвостів з 40 до 35%.На примере хвостов углеобогащения ОФ "Распадская" (г. Междуреченск Кемеровской области, РФ) установлено, что использование ультрафлокулярной обработки дает нижеследующие преимущества при извлечении тонкодисперсного угля методом седиментации в радиальном сгустителе: • снижение расхода флокулянтов – в 2,5-3,5 раза. • увеличение извлечения угольного концентрата из хвостов на 23…26%. • уменьшение зольности концентрата, извлекаемого из хвостов с 18 до 12%. • уменьшение влажности пресс-фильтрационного кека концентрата, извлекаемого из хвостов с 40 до 35%

Federated mmWave Beam Selection Utilizing LIDAR Data

Efficient link configuration in millimeter wave (mmWave) communication systems is a crucial yet challenging task due to the overhead imposed by beam selection. For vehicle-to-infrastructure (V2I) networks, side information from LIDAR sensors mounted on the vehicles has been leveraged to reduce the beam search overhead. In this letter, we propose a federated LIDAR aided beam selection method for V2I mmWave communication systems. In the proposed scheme, connected vehicles collaborate to train a shared neural network (NN) on their locally available LIDAR data during normal operation of the system. We also propose a reduced-complexity convolutional NN (CNN) classifier architecture and LIDAR preprocessing, which significantly outperforms previous works in terms of both the performance and the complexity

Influential factors impacting leadership effectiveness: A case study at a public university

As a result of increased globalisation and rapid changes in the technological, social, economic and political spheres, the environment in which businesses and organisations function has become increasingly volatile, uncertain, complex and ambiguous (VUCA). This has created a unique set of challenges for the leaders of these organisations, including higher education (HE) in South Africa. This study aimed to identify potential influential factors that have impact on leader effectiveness in a HE VUCA environment

Population and antenatal-based HIV prevalence estimates in a high contracepting female population in rural South Africa.

BACKGROUND: To present and compare population-based and antenatal-care (ANC) sentinel surveillance HIV prevalence estimates among women in a rural South African population where both provision of ANC services and family planning is prevalent and fertility is declining. With a need, in such settings, to understand how to appropriately adjust ANC sentinel surveillance estimates to represent HIV prevalence in general populations, and with evidence of possible biases inherent to both surveillance systems, we explore differences between the two systems. There is particular emphasis on unrepresentative selection of ANC clinics and unrepresentative testing in the population. METHODS: HIV sero-prevalence amongst blood samples collected from women consenting to test during the 2005 annual longitudinal population-based serological survey was compared to anonymous unlinked HIV sero-prevalence amongst women attending antenatal care (ANC) first visits in six clinics (January to May 2005). Both surveillance systems were conducted as part of the Africa Centre Demographic Information System. RESULTS: Population-based HIV prevalence estimates for all women (25.2%) and pregnant women (23.7%) were significantly lower than that for ANC attendees (37.7%). A large proportion of women attending urban or peri-urban clinics would be predicted to be resident within rural areas. Although overall estimates remained significantly different, presenting and standardising estimates by age and location (clinic for ANC-based estimates and individual-residence for population-based estimates) made some group-specific estimates from the two surveillance systems more predictive of one another. CONCLUSION: It is likely that where ANC coverage and contraceptive use is widespread and fertility is low, population-based surveillance under-estimates HIV prevalence due to unrepresentative testing by age, residence and also probably by HIV status, and that ANC sentinel surveillance over-estimates prevalence due to selection bias in terms of age of sexual debut and contraceptive use. The results presented highlight the importance of accounting for unrepresentative testing, particularly by individual residence and age, through system design and statistical analyses

Air-drying temperature changes the content of the phenolic acids and flavonols in white mulberry (Morus alba l.) leaves

The white mulberry leaves are typically available on the market in dried or encapsulated form. It was assumed in the study that appropriate drying of leaves of the white mulberry is significant for obtaining intermediate products with high content of compounds having anti-oxidative activity. The purpose of the study was to determine the influence of the temperature of mulberry leaves air drying on the content of phenolic acids and flavonols. It has been determined that the content of these compounds in the leaves depended on the drying temperature. Drying at 60 \ub0C favored release of phenolic acids and flavonols from complexes and/or formation of new compounds. Their total content was 22% higher than in leaves dried at 30 \ub0C. Drying at 90 \ub0C reduced the phenolic acid and flavonol content by 24%. The most favorable drying temperature was 60 \ub0C

COVID-19 vaccine uptake, confidence and hesitancy in rural KwaZulu-Natal, South Africa between April 2021 and April 2022: A continuous cross-sectional surveillance study

High COVID-19 vaccine hesitancy in South Africa limits protection against future epidemic waves. We evaluated how vaccine hesitancy and its correlates evolved April 2021-April 2022 in a well-characterized rural KwaZulu-Natal setting. All residents aged >15 in the Africa Health Research Institute's surveillance area were invited to complete a home-based, in-person interview. We described vaccine uptake and hesitancy trends, then evaluated associations with pre-existing personal factors, dynamic environmental context, and cues to action using ordinal logistic regression. Among 10,011 respondents, vaccine uptake rose as age-cohorts became vaccine-eligible before levelling off three months post-eligibility; younger age-groups had slower uptake and plateaued faster. Lifetime receipt of any COVID-19 vaccine rose from 3.0% in April-July 2021 to 32.9% in January-April 2022. Among 7,445 unvaccinated respondents, 47.7% said they would definitely take a free vaccine today in the first quarter of the study time period, falling to 32.0% in the last. By March/April 2022 only 48.0% of respondents were vaccinated or said they would definitely would take a vaccine. Predictors of lower vaccine hesitancy included being male (adjusted odds ratio [aOR]: 0.70, 95% confidence interval [CI]: 0.65-0.76), living with vaccinated household members (aOR:0.65, 95%CI: 0.59-0.71) and knowing someone who had had COVID-19 (aOR: 0.69, 95%CI: 0.59-0.80). Mistrust in government predicted greater hesitancy (aOR: 1.47, 95%CI: 1.42-1.53). Despite several COVID-19 waves, vaccine hesitancy was common in rural South Africa, rising over time and closely tied to mistrust in government. However, interpersonal experiences countered hesitancy and may be entry-points for interventions

Federated mmWave beam selection utilizing LIDAR data

Efficient link configuration in millimeter wave (mmWave) communication systems is a crucial yet challenging task due to the overhead imposed by beam selection. For vehicle-to-infrastructure (V2I) networks, side information from LIDAR sensors mounted on the vehicles has been leveraged to reduce the beam search overhead. In this letter, we propose a federated LIDAR aided beam selection method for V2I mmWave communication systems. In the proposed scheme, connected vehicles collaborate to train a shared neural network (NN) on their locally available LIDAR data during normal operation of the system. We also propose a reduced-complexity convolutional NN (CNN) classifier architecture and LIDAR preprocessing, which significantly outperforms previous works in terms of both the performance and the complexity

Recurrence relation for relativistic atomic matrix elements

Recurrence formulae for arbitrary hydrogenic radial matrix elements are obtained in the Dirac form of relativistic quantum mechanics. Our approach is inspired on the relativistic extension of the second hypervirial method that has been succesfully employed to deduce an analogous relationship in non relativistic quantum mechanics. We obtain first the relativistic extension of the second hypervirial and then the relativistic recurrence relation. Furthermore, we use such relation to deduce relativistic versions of the Pasternack-Sternheimer rule and of the virial theorem.Comment: 10 pages, no figure