Design and Evaluation of a Network-Monitoring System

Effective design of network monitoring dashboard plays a crucial role in maintaining and managing the network operations infrastructure. An efficiently designed dashboard can communicate key information to network administrators, which would help them to solve network issues as quickly as possible. We argue that dashboard design impacts network monitoring performance. We design and evaluate two visualization designs: (i) Author Driven (AD) and (ii) Reader Driven (RD) in the context of network monitoring dashboards. Further, we also propose to evaluate the effect of Augmented Reality (AR) when it is added to the two designs (RD and AD) on network monitoring performance, namely, perceived effort and perceived learning performance. The initial results from the study show that, reader-driven dashboard design performed relatively better than author-driven design in terms of lower perceived effort and higher perceived performance

Numerical Vibration Analysis of Rectangular Beams for Different End Conditions

In this study the vibration behaviour of rectangular beams with different end conditions i.e. for simply supported and cantilever type is determined. This behaviour is estimated for two different materials namely aluminum (Al6063L) and mild steel (304L). Initially five natural frequencies for simply supported and cantilevered conditions are found out using Rayleigh-Ritz method for both aluminum and mild steel. Vibrational behaviour of rectangular beam under different end conditions and different material properties are carried out experimentally and results are validated

Internal combustion engine gearbox bearing fault prediction using J48 and random forest classifier

Defective bearings in four-stroke engines can compromise performance and efficiency. Early detection of bearing difficulties in 4-stroke engines is critical. Four-stroke gasoline engines that vibrate or make noise can be used to diagnose issues. Using time, frequency, and time-frequency domain approaches, the vibrational features of healthy and diseased tissues are examined. Problems are only detectable by vibration or sound. The fault is identified through statistical analysis of seismic and audio data using frequency and time-frequency analysis. Vibration must be minimized prior to examination. Adaptive noise cancellation removes unwanted noise from recorded vibration signals, boosting the signal-to-noise ratio (SNR). In the first of the experiment's three phases, vibrational data are collected. To reduce noise and boost SNR, adaptive noise cancellation (ANC) is applied to vibration data from the first stage. In the second stage, ANC-filtered vibration data is subjected to three studies to detect bearing failure using J48 and random forest classifiers for online, real-time monitoring. In this experiment, one healthy and two faulty bearings are used. According to a current study, the internet of things (IoT) is a promising alternative for online monitoring of remote body health

Quantitative analysis of heart type fatty acid binding protein in early detection of acute coronary syndrome

Background: Coronary heart disease is a major cause of mortality, morbidity and disability in developed countries. Even though coronary heart disease mortality rates worldwide have reduced over the past five decades, coronary heart disease is the major cause of death in one-third of people more than 35 years of age.Many risk factors and biomarkers have been studied in the past and research is on in detecting the acute coronary syndrome at the earliest so that reperfusion therapy can be undertaken as early as possible to save the life of patients. Heart-type fatty acid binding protein is a newer modality of investigation developed for the above purpose.Methods: Single centre cross-sectional observational study was conducted from 1 September 2017 to May 2019 with an aim to study novel cardiac biomarker h-FABP in patients with acute coronary syndrome and compare sensitivity and specificity of the same with that of troponin -T in the early detection of acute coronary events after fulfilling inclusion and exclusion criteria .The data of 80 patients were collected after getting informed consent. The clinical, demographic and investigations were performed as per the hospital protocol and such patients were recorded in the proforma. The additional test heart-type fatty acid binding protein is performed in the triage by collecting patient’s serum and by using point of care analysis machine. Statistical analysis was performed using SPSS version 20.0 and results were obtainedResults: Out of 80 patients selected males were 35 and female are 45. Chest pain was present in 58 people, dyspnoea was in 28, sweating in 40 people, 35 had anterior wall MI, 30 had Inferior wall MI and 15 had global hypokinesia. Median values of h-FABP values were 82 ng/dl, 53.2 ng/dl, 35.3 ng/dl at 0-6 hours, 6-12 hours, and 12-24 hours respectively after the onset of symptoms with a significant p< 0.001. There were major differences between median values between different time groups of symptoms onset. Median troponin T values were 0.061 ng/ml, 0.350 ng/ml, 1.56 ng/ml after 0-6 hours, 6-12 hours and 12-24 hours of onset of symptoms respectively. There was no correlation between h-FABP and troponin-T values.Conclusions: h-FABP rises early in coronary events in first 6 hrs of onset of symptoms of ACS serum levels of h-FABP decreases as time progresses in 24 hours. In comparison troponin-t levels continue to rise as time progresses. h-FABP serum levels can be used as novel marker for early detection of ACS

Post COVID-19 Guillain Barre syndrome with syndrome of inappropriate secretion of antidiuretic hormone

Guillain Barre syndrome (GBS) is a rare but potentially fatal immune mediated disorder of peripheral nerves and nerve roots usually triggered by infections characterized by ascending paralysis with or without sensory symptoms, hyporeflexia to areflexia. Usually preceded by gastrointestinal or respiratory infection. Post COVID-19 neurological manifestation include GBS, transverse myelitis etc., occur at varying incidence rates at various places. Here we report a 42-year-old lady who had COVID-19 recovered presented with quadriparesis with absent deep tendon reflexes with electro-diagnostically proven AMSAN variety of GBS treated successfully with IVIg. Patient was having hyponatremia which was diagnosed to be due to SIADH and was successfully treated with fluid restriction and tolvaptan. This case is being reported due to combination of COVID-19, COVID vaccination shortly before GBS and hyponatremia due to syndrome of inappropriate secretion of antidiuretic hormone (SIADH) which is quite rare combination

Discrete Audio Representation as an Alternative to Mel-Spectrograms for Speaker and Speech Recognition

Discrete audio representation, aka audio tokenization, has seen renewed interest driven by its potential to facilitate the application of text language modeling approaches in audio domain. To this end, various compression and representation-learning based tokenization schemes have been proposed. However, there is limited investigation into the performance of compression-based audio tokens compared to well-established mel-spectrogram features across various speaker and speech related tasks. In this paper, we evaluate compression based audio tokens on three tasks: Speaker Verification, Diarization and (Multi-lingual) Speech Recognition. Our findings indicate that (i) the models trained on audio tokens perform competitively, on average within $1\%$ of mel-spectrogram features for all the tasks considered, and do not surpass them yet. (ii) these models exhibit robustness for out-of-domain narrowband data, particularly in speaker tasks. (iii) audio tokens allow for compression to 20x compared to mel-spectrogram features with minimal loss of performance in speech and speaker related tasks, which is crucial for low bit-rate applications, and (iv) the examined Residual Vector Quantization (RVQ) based audio tokenizer exhibits a low-pass frequency response characteristic, offering a plausible explanation for the observed results, and providing insight for future tokenizer designs.Comment: Preprint. Submitted to ICASSP 202

Management Of Extracranial Schwannomas In Head And Neck Region - An Observational Study

ABSTRACT Background: Schwannomas, benign tumors arising from Schwann cells, often manifest as slow-growing lesions in the peripheral nerve sheath. While typically asymptomatic, they can affect cranial and peripheral nerves. Surgical excision is the primary treatment, but preserving nerve function poses challenges. Methods: This retrospective study analyzed 12 cases of benign head and neck schwannomas diagnosed at Department of ENT, SCB Medical College, Orissa, India between 2021 and 2023. Data encompassed patient demographics, tumor characteristics, diagnostic methods, surgical approaches, histopathology, and follow-up outcomes. Pre-operative investigations included Fine Needle Aspiration Cytology, Ultrasonography, and imaging. Results: Predominantly middle-aged and male patients presented with painless swelling, commonly in the cervical region, tongue, nose, and hard palate. Mean symptom duration was 8.5 months. Imaging depicted characteristic features, guiding surgical planning. Various approaches ensured complete excision, preserving nerve function. Histopathology confirmed the diagnosis, with positive S-100 staining. No cases showed malignancy or recurrence during follow-up. Conclusions: Head and neck schwannomas, though rare, present diagnostic and management challenges. Pre-operative diagnosis relies on imaging and biopsy, with surgical excision essential for treatment. Nerve preservation minimizes post-operative complications. Despite diagnostic difficulties, maintaining a high index of suspicion for schwannomas in patients with painless, slow-growing swellings is crucial

The CHiME-7 Challenge: System Description and Performance of NeMo Team's DASR System

We present the NVIDIA NeMo team's multi-channel speech recognition system for the 7th CHiME Challenge Distant Automatic Speech Recognition (DASR) Task, focusing on the development of a multi-channel, multi-speaker speech recognition system tailored to transcribe speech from distributed microphones and microphone arrays. The system predominantly comprises of the following integral modules: the Speaker Diarization Module, Multi-channel Audio Front-End Processing Module, and the ASR Module. These components collectively establish a cascading system, meticulously processing multi-channel and multi-speaker audio input. Moreover, this paper highlights the comprehensive optimization process that significantly enhanced our system's performance. Our team's submission is largely based on NeMo toolkits and will be publicly available

The global burden of adolescent and young adult cancer in 2019 : a systematic analysis for the Global Burden of Disease Study 2019

Background In estimating the global burden of cancer, adolescents and young adults with cancer are often overlooked, despite being a distinct subgroup with unique epidemiology, clinical care needs, and societal impact. Comprehensive estimates of the global cancer burden in adolescents and young adults (aged 15-39 years) are lacking. To address this gap, we analysed results from the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2019, with a focus on the outcome of disability-adjusted life-years (DALYs), to inform global cancer control measures in adolescents and young adults. Methods Using the GBD 2019 methodology, international mortality data were collected from vital registration systems, verbal autopsies, and population-based cancer registry inputs modelled with mortality-to-incidence ratios (MIRs). Incidence was computed with mortality estimates and corresponding MIRs. Prevalence estimates were calculated using modelled survival and multiplied by disability weights to obtain years lived with disability (YLDs). Years of life lost (YLLs) were calculated as age-specific cancer deaths multiplied by the standard life expectancy at the age of death. The main outcome was DALYs (the sum of YLLs and YLDs). Estimates were presented globally and by Socio-demographic Index (SDI) quintiles (countries ranked and divided into five equal SDI groups), and all estimates were presented with corresponding 95% uncertainty intervals (UIs). For this analysis, we used the age range of 15-39 years to define adolescents and young adults. Findings There were 1.19 million (95% UI 1.11-1.28) incident cancer cases and 396 000 (370 000-425 000) deaths due to cancer among people aged 15-39 years worldwide in 2019. The highest age-standardised incidence rates occurred in high SDI (59.6 [54.5-65.7] per 100 000 person-years) and high-middle SDI countries (53.2 [48.8-57.9] per 100 000 person-years), while the highest age-standardised mortality rates were in low-middle SDI (14.2 [12.9-15.6] per 100 000 person-years) and middle SDI (13.6 [12.6-14.8] per 100 000 person-years) countries. In 2019, adolescent and young adult cancers contributed 23.5 million (21.9-25.2) DALYs to the global burden of disease, of which 2.7% (1.9-3.6) came from YLDs and 97.3% (96.4-98.1) from YLLs. Cancer was the fourth leading cause of death and tenth leading cause of DALYs in adolescents and young adults globally. Interpretation Adolescent and young adult cancers contributed substantially to the overall adolescent and young adult disease burden globally in 2019. These results provide new insights into the distribution and magnitude of the adolescent and young adult cancer burden around the world. With notable differences observed across SDI settings, these estimates can inform global and country-level cancer control efforts. Copyright (C) 2021 The Author(s). Published by Elsevier Ltd.Peer reviewe

Burden of disease scenarios for 204 countries and territories, 2022–2050: a forecasting analysis for the Global Burden of Disease Study 2021

Background: Future trends in disease burden and drivers of health are of great interest to policy makers and the public at large. This information can be used for policy and long-term health investment, planning, and prioritisation. We have expanded and improved upon previous forecasts produced as part of the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) and provide a reference forecast (the most likely future), and alternative scenarios assessing disease burden trajectories if selected sets of risk factors were eliminated from current levels by 2050. Methods: Using forecasts of major drivers of health such as the Socio-demographic Index (SDI; a composite measure of lag-distributed income per capita, mean years of education, and total fertility under 25 years of age) and the full set of risk factor exposures captured by GBD, we provide cause-specific forecasts of mortality, years of life lost (YLLs), years lived with disability (YLDs), and disability-adjusted life-years (DALYs) by age and sex from 2022 to 2050 for 204 countries and territories, 21 GBD regions, seven super-regions, and the world. All analyses were done at the cause-specific level so that only risk factors deemed causal by the GBD comparative risk assessment influenced future trajectories of mortality for each disease. Cause-specific mortality was modelled using mixed-effects models with SDI and time as the main covariates, and the combined impact of causal risk factors as an offset in the model. At the all-cause mortality level, we captured unexplained variation by modelling residuals with an autoregressive integrated moving average model with drift attenuation. These all-cause forecasts constrained the cause-specific forecasts at successively deeper levels of the GBD cause hierarchy using cascading mortality models, thus ensuring a robust estimate of cause-specific mortality. For non-fatal measures (eg, low back pain), incidence and prevalence were forecasted from mixed-effects models with SDI as the main covariate, and YLDs were computed from the resulting prevalence forecasts and average disability weights from GBD. Alternative future scenarios were constructed by replacing appropriate reference trajectories for risk factors with hypothetical trajectories of gradual elimination of risk factor exposure from current levels to 2050. The scenarios were constructed from various sets of risk factors: environmental risks (Safer Environment scenario), risks associated with communicable, maternal, neonatal, and nutritional diseases (CMNNs; Improved Childhood Nutrition and Vaccination scenario), risks associated with major non-communicable diseases (NCDs; Improved Behavioural and Metabolic Risks scenario), and the combined effects of these three scenarios. Using the Shared Socioeconomic Pathways climate scenarios SSP2-4.5 as reference and SSP1-1.9 as an optimistic alternative in the Safer Environment scenario, we accounted for climate change impact on health by using the most recent Intergovernmental Panel on Climate Change temperature forecasts and published trajectories of ambient air pollution for the same two scenarios. Life expectancy and healthy life expectancy were computed using standard methods. The forecasting framework includes computing the age-sex-specific future population for each location and separately for each scenario. 95% uncertainty intervals (UIs) for each individual future estimate were derived from the 2·5th and 97·5th percentiles of distributions generated from propagating 500 draws through the multistage computational pipeline. Findings: In the reference scenario forecast, global and super-regional life expectancy increased from 2022 to 2050, but improvement was at a slower pace than in the three decades preceding the COVID-19 pandemic (beginning in 2020). Gains in future life expectancy were forecasted to be greatest in super-regions with comparatively low life expectancies (such as sub-Saharan Africa) compared with super-regions with higher life expectancies (such as the high-income super-region), leading to a trend towards convergence in life expectancy across locations between now and 2050. At the super-region level, forecasted healthy life expectancy patterns were similar to those of life expectancies. Forecasts for the reference scenario found that health will improve in the coming decades, with all-cause age-standardised DALY rates decreasing in every GBD super-region. The total DALY burden measured in counts, however, will increase in every super-region, largely a function of population ageing and growth. We also forecasted that both DALY counts and age-standardised DALY rates will continue to shift from CMNNs to NCDs, with the most pronounced shifts occurring in sub-Saharan Africa (60·1% [95% UI 56·8–63·1] of DALYs were from CMNNs in 2022 compared with 35·8% [31·0–45·0] in 2050) and south Asia (31·7% [29·2–34·1] to 15·5% [13·7–17·5]). This shift is reflected in the leading global causes of DALYs, with the top four causes in 2050 being ischaemic heart disease, stroke, diabetes, and chronic obstructive pulmonary disease, compared with 2022, with ischaemic heart disease, neonatal disorders, stroke, and lower respiratory infections at the top. The global proportion of DALYs due to YLDs likewise increased from 33·8% (27·4–40·3) to 41·1% (33·9–48·1) from 2022 to 2050, demonstrating an important shift in overall disease burden towards morbidity and away from premature death. The largest shift of this kind was forecasted for sub-Saharan Africa, from 20·1% (15·6–25·3) of DALYs due to YLDs in 2022 to 35·6% (26·5–43·0) in 2050. In the assessment of alternative future scenarios, the combined effects of the scenarios (Safer Environment, Improved Childhood Nutrition and Vaccination, and Improved Behavioural and Metabolic Risks scenarios) demonstrated an important decrease in the global burden of DALYs in 2050 of 15·4% (13·5–17·5) compared with the reference scenario, with decreases across super-regions ranging from 10·4% (9·7–11·3) in the high-income super-region to 23·9% (20·7–27·3) in north Africa and the Middle East. The Safer Environment scenario had its largest decrease in sub-Saharan Africa (5·2% [3·5–6·8]), the Improved Behavioural and Metabolic Risks scenario in north Africa and the Middle East (23·2% [20·2–26·5]), and the Improved Nutrition and Vaccination scenario in sub-Saharan Africa (2·0% [–0·6 to 3·6]). Interpretation: Globally, life expectancy and age-standardised disease burden were forecasted to improve between 2022 and 2050, with the majority of the burden continuing to shift from CMNNs to NCDs. That said, continued progress on reducing the CMNN disease burden will be dependent on maintaining investment in and policy emphasis on CMNN disease prevention and treatment. Mostly due to growth and ageing of populations, the number of deaths and DALYs due to all causes combined will generally increase. By constructing alternative future scenarios wherein certain risk exposures are eliminated by 2050, we have shown that opportunities exist to substantially improve health outcomes in the future through concerted efforts to prevent exposure to well established risk factors and to expand access to key health interventions