Optimized convolutional neural network architectures for efficient on-device vision-based object detection

Convolutional neural networks have pushed forward image analysis research and computer vision over the last decade, constituting a state-of-the-art approach in object detection today. The design of increasingly deeper and wider architectures has made it possible to achieve unprecedented levels of detection accuracy, albeit at the cost of both a dramatic computational burden and a large memory footprint. In such a context, cloud systems have become a mainstream technological solution due to their tremendous scalability, providing researchers and practitioners with virtually unlimited resources. However, these resources are typically made available as remote services, requiring communication over the network to be accessed, thus compromising the speed of response, availability, and security of the implemented solution. In view of these limitations, the on-device paradigm has emerged as a recent yet widely explored alternative, pursuing more compact and efficient networks to ultimately enable the execution of the derived models directly on resource-constrained client devices. This study provides an up-to-date review of the more relevant scientific research carried out in this vein, circumscribed to the object detection problem. In particular, the paper contributes to the field with a comprehensive architectural overview of both the existing lightweight object detection frameworks targeted to mobile and embedded devices, and the underlying convolutional neural networks that make up their internal structure. More specifically, it addresses the main structural-level strategies used for conceiving the various components of a detection pipeline (i.e., backbone, neck, and head), as well as the most salient techniques proposed for adapting such structures and the resulting architectures to more austere deployment environments. Finally, the study concludes with a discussion of the specific challenges and next steps to be taken to move toward a more convenient accuracy–speed trade-off.

The Impact of COVID-19 on Adult Day Services' Closures and Programming

Nationally, adult day services (ADS) were forced to closed due to the COVID-19 pandemic. The forced closure of ADS programming consequentially impacted the services provided to clients. Many ADS continued to provide telephonic/remote services to clients, despite limited reimbursement from national and state sources for these services. Using data from ADS sites participating in the ADS-Plus Program (n= 22), this presentation examines the effects of COVID-19 on ADS closures and programming provided during the closure. About 86% (n=19) of the centers reported having to closed due to COVID-19. One-hundred percent of the sites reported offering telephone support to clients. Nearly 45% (n=10) of the centers reported not being reimbursed for this service. As ADS is a vital community-based resource for many families, it is important to demonstrate the crucial services provided by ADS to inform policymakers of the essentiality of day centers.

ESJF Algorithm to Improve Cloud Environment

Nowadays, after the technological development in societies, cloud computing has become one of the most important technologies. It provides users with software, hardware, and platform as remote services over the Internet. The increasing number of cloud users has caused a critical problem in how the clients receive cloud services when the cloud is in a state of instability, as it cannot provide required services and, thus, a delay occurs. Therefore, an algorithm was proposed to provide high efficiency and stability to work, because all existing tasks must operate without delay. The proposed system is an enhancement shortest job first algorithm (ESJF) using a time slice, which works by taking a task in the shortest time first and then the longest first from the queue. Through the experimental results in decreasing the waiting and completion time of the task, as well as taking into account reducing tasks starvation, the result of the proposed ESJF algorithm was compared with the traditional shortest job first (SJF) algorithm. These algorithms were applied when all tasks arrived at the same time, and it proved that the ESJF algorithm works more efficiently compared to SJF.

Remote-Delivered Services on College Campuses Manuscript

Objective: The COVID-19 pandemic has drastically increased use of remote-delivered mental health services. This study identifies advantages and limitations of remote-delivered services on college campuses to inform mental health delivery post-pandemic. Methods: Clinicians (n = 30) were asked to evaluate COVID-19’s impact on their work, environment, and wellness in an online survey. Qualitative data was coded using a thematic analysis approach, while quantitative data was analyzed using descriptive statistics. Results: Many clinicians reported benefits of remote services, including increased accessibility, greater convenience, no change in therapeutic alliance, and decreased stress for clinicians. Clinicians also experienced challenges such as social isolation, technological difficulties, and personal/family concerns. Clinicians envisioned a hybrid service combining online and in-person activities post-pandemic. Conclusions: Overall, remote-delivered mental health services on college campuses have potential in increasing treatment quality while highlighting a necessity for further research in hybrid mental health delivery.

Providing statistical stability of qualimetric studies on the basis of geochronological tracking

Geochronological tracking has received wide recognition as an appropriate scientific and methodological tool and an effective information technology of qualimetric research in the interests of ensuring high quality of transport services, transportation efficiency, analysis of the facts of insufficient meeting the needs of the population with spatially remote services, etc. On the basis of geochronotracking, a procedure has been developed for statistical verification of research hypotheses about stable trends in changes in the quality of various spatio-temporal processes. The reliability and validity of accepting a particular hypothesis in the framework of a qualimetric research is determined by the representativeness of the volume of initial data on geographical movements, considered as a selection from the general population. This article is devoted to the analysis of this dependence and the development of an algorithm for assessing the specified stability (significance).

THE NEED TO DEVELOP PROTECTIVE MEASURES TO MAINTAIN AND SUSTAINABLE FUNCTIONING OF THE BANKING ECOSYSTEM IN RUSSIA

В условиях активного развития экосистем и сближения финансового и нефинансового секторов особую важность приобретает не только качество используемых сервисов, но и контроль за их функционированием на уровне операционных офисов и внутренних структурных подразделений банков. Стратегически важным приоритетом современного банковского сектора выступает поиск новых информационных взаимосвязей, генерирующих не только конкурентные преимущества, но изменение профиля операционных рисков в условиях увеличения объема дистанционных услуг, характера и объемов их предоставления на уровне экосистемы.Развитие глобальных экосистем актуализирует проблемы защиты банковской системы ввиду растущих операционных рисков, оказывающих влияние на капитал. В этой связи целью данной публикации выступает поиск комплексных информационных индикаторов, способных оказать превентивное воздействие на снижение операционных потерь для банков в условиях рисков и неопределенности внешней и внутренней среды. In the context of the active development of ecosystems and the convergence of the financial and non- financial sectors, not only the quality of the services used, but also control over their functioning at the level of operational offices and internal structural divisions of banks, is of particular importance.A strategically important priority of the modern banking sector is the search for new information relationships that generate not only competitive advantages, but also a change in the profile of operational risks in the face of an increase in the volume of remote services, the nature and volume of their provision at the ecosystem level.The development of global ecosystems actualizes the problems of protecting the banking system in view of growing operational risks affecting capital.In this regard, the purpose of this publication is to search for complex information indicators that can have a preventive effect on reducing operating losses for banks in the face of risks and uncertainty in the external and internal environment.

PROSPECTS FOR TRANSFORMATION OF INTERNAL AUDIT SERVICES IN COMMERCIAL BANKS

The article discusses the prospects for improving the activities of internal audit services of commercial banks, transforming their activities through the introduction of modern banking services,digital technologies. The results of previous studies on the topic were reviewed. The regulatory framework for the transformation of the internal audit service has been introduced.Keywords: internal audit, transformation, current control, digital technologies, remote services, bank board, annual plan