FPGA Implementation of Channel Mismatch Calibration in TIADCs for Signals in Any Nyquist Bands

This paper presents a fully digital background calibration technique of the gain and timing mismatches in undersampling Time-Interleaved Analog-to-Digital Converters for the wideband bandlimited input signal at any Nyquist bands. The proposed technique does not require an additional reference channel nor a pilot input. The channel mismatch parameters are estimated based on the mismatch frequency band. The experimental results shows the efficiency of the proposed mitigation technique with the SNDR improvement of 16dB for 4-channel 60dB SNR TIADC clocked at 2.7GHz given a multi-tone input occupied at the third Nyquist band. The hardware architecture of the proposed technique is designed and validated on Altera FPGA DE4 board. The synthesized design utilizes a very little amount of the hardware resource in the FPGA chip and works correctly on a Hardware-In-the-Loop emulation framework

A long range, energy efficient internet of things based drought monitoring system

The climate change and global warning have been appeared as an emerging issue in recent decades. In which, the drought problem has been influenced on economics and life condition in Vietnam. In order to solve this problem, in this paper, we have designed and deployed a long range and energy efficient drought monitoring based on IoT (Internet of Things) for real time applications. After being tested in the real condition, the proposed system has proved its high dependability and effectiveness. The system is promising to become a potential candidate to solve the drought problem in Vietnam

Data Partitioning and Asynchronous Processing to Improve the Embedded Software Performance on Multicore Processors

Nowadays, ensuring information security is extremely inevitable and urgent. We are also witnessing the strong development of embedded systems, IoT. As a result, research to ensure information security for embedded software is being focused. However, studies on optimizing embedded software on multi-core processors to ensure information security and increase the performance of embedded software have not received much attention. The paper proposes and develops the embedded software performance improvement method on multi-core processors based on data partitioning and asynchronous processing. Data are used globally to be retrieved by any threads. The data are divided into different partitions, and the program is also installed according to the multi-threaded model. Each thread handles a partition of the divided data. The size of each data portion is proportional to the processing speed and the cache size of the core in the multi-core processor. Threads run in parallel and do not need synchronization, but it is necessary to share a general global variable to check the executing status of the system. Our research on embedded software is based on data security, so we have tested and assessed the method with several block ciphers like AES, DES, etc., on Raspberry PI3. The average performance improvement rate achieved was 59.09%

Policy Response, Social Media and Science Journalism for the Sustainability of the Public Health System Amid the COVID-19 Outbreak: The Vietnam Lessons

Vietnam, with a geographical proximity and a high volume of trade with China, was the first country to record an outbreak of the new Coronavirus disease (COVID-19), caused by the Severe Acute Respiratory Syndrome Coronavirus 2 or SARS-CoV-2. While the country was expected to have a high risk of transmission, as of April 4, 2020—in comparison to attempts to contain the disease around the world—responses from Vietnam are being seen as prompt and effective in protecting the interests of its citizens, with 239 confirmed cases and no fatalities. This study analyzes the situation in terms of Vietnam’s policy response, social media and science journalism. A self-made web crawl engine was used to scan and collect official media news related to COVID-19 between the beginning of January and April 4, yielding a comprehensive dataset of 14,952 news items. The findings shed light on how Vietnam—despite being under-resourced—has demonstrated political readiness to combat the emerging pandemic since the earliest days. Timely communication on any developments of the outbreak from the government and the media, combined with up-to-date research on the new virus by the Vietnamese science community, have altogether provided reliable sources of information. By emphasizing the need for immediate and genuine cooperation between government, civil society and private individuals, the case study offers valuable lessons for other nations concerning not only the concurrent fight against the COVID-19 pandemic but also the overall responses to a public health crisis

Genomic serotyping, clinical manifestations, and antimicrobial resistance of non-typhoidal Salmonella gastroenteritis in hospitalized children in Ho Chi Minh City, Vietnam

Nontyphoidal Salmonella (NTS) are among the most common etiological agents of diarrheal diseases worldwide and have become the most commonly detected bacterial pathogen in children hospitalized with diarrhea in Vietnam. Aiming to better understand the epidemiology, serovar distribution, antimicrobial resistance (AMR), and clinical manifestation of NTS gastroenteritis in Vietnam, we conducted a clinical genomics investigation of NTS isolated from diarrheal children admitted to one of three tertiary hospitals in Ho Chi Minh City. Between May 2014 and April 2016, 3,166 children hospitalized with dysentery were recruited into the study; 478 (∼15%) children were found to be infected with NTS by stool culture. Molecular serotyping of the 450 generated genomes identified a diverse collection of serogroups (B, C1, C2 to C3, D1, E1, G, I, K, N, O, and Q); however, Salmonella enterica serovar Typhimurium was the most predominant serovar, accounting for 41.8% (188/450) of NTS isolates. We observed a high prevalence of AMR to first-line treatments recommended by WHO, and more than half (53.8%; 242/450) of NTS isolates were multidrug resistant (MDR; resistant to ≥3 antimicrobial classes). AMR gene detection positively correlated with phenotypic AMR testing, and resistance to empirical antimicrobials was associated with a significantly longer hospitalization (0.91 days; P = 0.04). Our work shows that genome sequencing is a powerful epidemiological tool to characterize the serovar diversity and AMR profiles in NTS. We propose a revaluation of empirical antimicrobials for dysenteric diarrhea and endorse the use of whole-genome sequencing for sustained surveillance of NTS internationally

When Intervention Becomes Imperative: A Case Report of Spontaneous Vulvar Edema During Pregnancy

Spontaneous idiopathic vulvar edema during the second trimester is a rare condition. The approach to managing this condition involves relieving symptoms, identifying underlying causes, and implementing appropriate treatment. Managing such cases during pregnancy is challenging because of concerns for potential adverse fetal outcomes. Conservative management expects the condition to be relieved spontaneously postpartum, whereas invasive treatment offers a more rapid resolution. Treatment choices are controversial because each method has its pros and cons and influences the delivery process to a certain extent. Surgical drainage becomes a viable option when patients are not responsive to medications. We report a case of spontaneous massive vulvar edema in a 22-year-old primigravida in her 23rd week of pregnancy. After ruling out other notable causes of vulvar edema, we decided to intervene using an invasive procedure because she complained of progressive symptoms and discomfort. Subsequently, the edema subsided postprocedure, and the patient experienced successful labor with no complications. This report aims to alert clinicians that drainage attempts should be considered in pregnant patients with worsening symptoms

The impact of environmental and climatic variation on the spatiotemporal trends of hospitalized pediatric diarrhea in Ho Chi Minh City, Vietnam.

It is predicted that the integration of climate-based early warning systems into existing action plans will facilitate the timely provision of interventions to diarrheal disease epidemics in resource-poor settings. Diarrhea remains a considerable public health problem in Ho Chi Minh City (HCMC), Vietnam and we aimed to quantify variation in the impact of environmental conditions on diarrheal disease risk across the city. Using all inpatient diarrheal admissions data from three large hospitals within HCMC, we developed a mixed effects regression model to differentiate district-level variation in risk due to environmental conditions from the overarching seasonality of diarrheal disease hospitalization in HCMC. We identified considerable spatial heterogeneity in the risk of all-cause diarrhea across districts of HCMC with low elevation and differential responses to flooding, air temperature, and humidity driving further spatial heterogeneity in diarrheal disease risk. The incorporation of these results into predictive forecasting algorithms will provide a powerful resource to aid diarrheal disease prevention and control practices in HCMC and other similar settings

TextANIMAR: Text-based 3D Animal Fine-Grained Retrieval

3D object retrieval is an important yet challenging task, which has drawn more and more attention in recent years. While existing approaches have made strides in addressing this issue, they are often limited to restricted settings such as image and sketch queries, which are often unfriendly interactions for common users. In order to overcome these limitations, this paper presents a novel SHREC challenge track focusing on text-based fine-grained retrieval of 3D animal models. Unlike previous SHREC challenge tracks, the proposed task is considerably more challenging, requiring participants to develop innovative approaches to tackle the problem of text-based retrieval. Despite the increased difficulty, we believe that this task has the potential to drive useful applications in practice and facilitate more intuitive interactions with 3D objects. Five groups participated in our competition, submitting a total of 114 runs. While the results obtained in our competition are satisfactory, we note that the challenges presented by this task are far from being fully solved. As such, we provide insights into potential areas for future research and improvements. We believe that we can help push the boundaries of 3D object retrieval and facilitate more user-friendly interactions via vision-language technologies.Comment: arXiv admin note: text overlap with arXiv:2304.0573

Flexible interactive retrieval SysTem 3.0 for visual lifelog exploration at LSC 2022

Building a retrieval system with lifelogging data is more complicated than with ordinary data due to the redundancies, blurriness, massive amount of data, various sources of information accompanying lifelogging data, and especially the ad-hoc nature of queries. The Lifelog Search Challenge (LSC) is a benchmarking challenge that encourages researchers and developers to push the boundaries in lifelog retrieval. For LSC'22, we develop FIRST 3.0, a novel and flexible system that leverages expressive cross-domain embeddings to enhance the searching process. Our system aims to adaptively capture the semantics of an image at different levels of detail. We also propose to augment our system with an external search engine to help our system with initial visual examples for unfamiliar concepts. Finally, we organize image data in hierarchical clusters based on their visual similarity and location to assist users in data exploration. Experiments show that our system is both fast and effective in handling various retrieval scenarios