Time interleaved counter analog to digital converters

The work explores extending time interleaving in A/D converters, by applying a high-level of parallelism to one of the slowest and simplest types of data-converters, the counter ADC. The motivation for the work is to realise high-performance re-configurable A/D converters for use in multi-standard and multi-PHY communication receivers with signal bandwidths in the 10s to 100s of MHz. The counter ADC requires only a comparator, a ramp signal, and a digital counter, where the comparator compares the sampled input against all possible quantisation levels sequentially. This work explores arranging counter ADCs in large time-interleaved arrays, building a Time Interleaved Counter (TIC) ADC. The key to realising a TIC ADC is distributed sampling and a global multi-phase ramp generator realised with a novel figure-of-8 rotating resistor ring. Furthermore Counter ADCs allow for re-configurability between effective sampling rate and resolution due to their sequential comparison of reference levels in conversion. A prototype TIC ADC of 128-channels was fabricated and measured in 0.13μm CMOS technology, where the same block can be configured to operate as a 7-bit 1GS/s, 8-bit 500MS/s, or 9-bit 250MS/s dataconverter. The ADC achieves a sub 400fJ/step FOM in all modes of configuration

Evaluation of Diagnostic Values in NCCT and MRI of the Patients With Cerebral Venous or Sinus Thrombosis in Loghman Hakim Hospital in Tehran 2014-2018

Background: Cerebral venous and sinus thrombosis (CVT) is the rare type of stroke, which can be fatal or causes significant morbidity. CVT could cause by multiple etiologies and risk factors and could present with many signs and symptoms such as a headache, seizure or altered mental status. The gold standard for diagnosing CVT is magnetic resonance venography (MRV) or computed tomographic venography (CTV), as these modalities are not available in many health centers and the early diagnosis of this disease improves significantly the outcome of treatment, we evaluated the diagnostic values of CT and magnetic resonance imaging (MRI) in CVT patients.Methods: We compiled and investigated the radiological and clinical records of 92 patients with the final diagnosis of CVT; we observed the sign of thrombosis in 74 patients who had either the non-contrast CT or MRI plus MRV. We statistically analyzed the sensitivity, specificity, positive predictive value, negative predictive value, accuracy, the positive and negative likelihood ratio of these modalities.Results: Our results demonstrated that the sensitivity of CT scan is 60.5%, and its specificity is 66.7%. The positive predictive value of CT is 85%, and its negative predictive value is 34%. Our study demonstrated that the accuracy of CT in diagnosing CVT patients is 62%.Besides our results showed that the sensitivity of MRI in diagnosing CVT is 87%, and the specificity of MRI is 76.9%. Hence the positive predictive value of MRI is 94%, and the negative predictive value is 58%, and the accuracy of this modality is 85%Conclusion: In the absence of gold standard modalities, MRI and CT scan have relatively good diagnostic values, besides MRI is more beneficial between the two, moreover we found that CVT is more prevalent among women and in warm seasons

Paranasal sinuses malignancies : a 12-year review of clinical characteristics

Inadequate epidemiologic investigations of the paranasal sinuses malignancies prompted this retrospective study with special emphasis on a major group of 111 tumors. Clinical records of 111 patients with histologically confirmed malignant tumors of the paranasal sinuses were investigated retrospectively from April 2000 to January 2012. Collection of data included demographic information, clinical manifestations, treatment plans, and histopathology of the tumor. There were 69 (62.16%) male and 42 (37.83%) female patients (male-to-female ratio of 1.6:1), with a median age of 49±12.2 years (range 21 to 88 years). A high level of occurrence was noticed in the fifth (26.3%) decade of life. The most frequent histological types were squamous cell carcinoma (43.5%) and adenoid cystic carcinoma (19%). Among clinical manifestations, nasal obstruction was the most frequent followed by diplopia, and facial swelling. Fifty three patients (47.74%) were treated with combined approach of surgery and radiation therapy. Paranasal sinuses malignancies are rare conditions with nonspecific symptoms which make early diagnosis of the lesions more challenging. The optimal therapeutic protocol for patients suffering from these tumors is still a somewhat controversial entity and requires further studies

Predicting and Mapping of Soil Organic Carbon Using Machine Learning Algorithms in Northern Iran

Estimation of the soil organic carbon content is of utmost importance in understanding the chemical, physical, and biological functions of the soil. This study proposes machine learning algorithms of support vector machines, artificial neural networks, regression tree, random forest, extreme gradient boosting, and conventional deep neural network for advancing prediction models of SOC. Models are trained with 1879 composite surface soil samples, and 105 auxiliary data as predictors. The genetic algorithm is used as a feature selection approach to identify effective variables. The results indicate that precipitation is the most important predictor driving 15 percent of SOC spatial variability followed by the normalized difference vegetation index, day temperature index of moderate resolution imaging spectroradiometer, multiresolution valley bottom flatness and land use, respectively. Based on 10 fold cross validation, the DNN model reported as a superior algorithm with the lowest prediction error and uncertainty. In terms of accuracy, DNN yielded a mean absolute error of 59 percent, a root mean squared error of 75 percent, a coefficient of determination of 0.65, and Lins concordance correlation coefficient of 0.83. The SOC content was the highest in udic soil moisture regime class with mean values of 4 percent, followed by the aquic and xeric classes, respectively. Soils in dense forestlands had the highest SOC contents, whereas soils of younger geological age and alluvial fans had lower SOC. The proposed DNN is a promising algorithm for handling large numbers of auxiliary data at a province scale, and due to its flexible structure and the ability to extract more information from the auxiliary data surrounding the sampled observations, it had high accuracy for the prediction of the SOC baseline map and minimal uncertainty.Comment: 30pages, 9 figure

Towards a highly customizable framework for release planning process

U razvoju softvera, planiranjem puštanja u promet izabiru se važna svojstva i zahtjevi temeljeni na tehničkim ograničenjima i ograničenjima sredstava te odnosima između zahtjeva. Planiranje puštanja u promet usmjereno je na pronalaženje optimalnog rješenja traženjem raznih stanja. Takav način traženja rješenja otkriva dvije stvari. Prvo, pokazuje da postoje različiti nejasni i nesigurni parametri koji utječu na rješenje. Drugo, da ne postoji samo jedno rješenja za neki problem. Mogu postojati različita rješenja koja se razlikuju po svojim karakteristikama (na pr. u odnosu na trajanje, složenost itd.). Stoga su mnoge metode planiranja puštanja u promet često specifične za samo neke aspekte problema. U ovom se radu istražuju razne postojeće metode za planiranje pokretanja u svrhu pronalaženja nekih općih razmišljanja i aktivnosti za uspostavljanje prilagodljivog okvira za planiranje puštanja u promet. Prilagodba se postiže identificiranjem učinkovitih parametara ili primjera parametara i njihovih odnosa tako da se može izabrati pravi algoritam ili metoda za svaku aktivnost. Karakteristike projekta mogu se odrediti na osnovu primjera parametara te se oni tada primjenjuju za određivanje odgovarajuće metode za izvršavanje pojedine aktivnosti u okviru čitavog postupka planiranja puštanja u promet, a čiji se rezultati bilježe. Taj predloženi okvir vrlo prilagodljivog postupka sa svojim mogućim obilježjima prilagođavanja zatim se ocjenjuje u nekoliko softverskih poduzeća. U 85 % slučajeva predloženi okvir za svaku aktivnost u skladu je s uvjetima poduzeća i pomaže u ubrzanju postupka planiranja puštanja u promet.In software development, release planning is performed to select important features and requirements based on resource and technical constraints and the relationships between requirements. Release planning focuses on finding an optimal solution by seeking various states. This kind of solution finding reveals two remarks. First, it shows that there are various, ambiguous and uncertain parameters that influence the solution. Second, there is not only one solution to any problem. Various solutions can be found that differ in their performance (e.g. time performance, complexity performance, etc.). Consequently, many methods for release planning are often specific to only certain problem domains. This paper examines various current release planning methods to extract the common activities and thoughts in order to establish a customizable framework for release planning. Customization is done by identifying effective parameters, parameter instances and their relationships so that they can affect the selection of the right algorithm or method for each activity. Project characteristics can be specified based on the parameter instances and they are then used to determine the suitable method for achieving each activity within the whole release planning process and the results of which are recorded. This proposed highly customizable process framework with its possible customization features is then validated in several software companies. In 85 % of the cases, the suggested framework for every activity of the process fits the companies’ circumstances and helps to hasten the process of release planning

Bicycle Anti-Lock Braking System

Bicycling can be a very dangerous activity, largely because bicyclists have little to no protection relative to other vehicles on the road. In 2001, Transport Canada recorded 60 bicyclist fatalities and thousands of bicyclist injuries [1]. Governments have mandated safety equipment like helmets to protect cyclists in the event of an accident, but as any experienced bicyclist will tell you, keeping safe on a bike is largely about avoiding accidents in the first place. To meet this need for better bicycling safety, Cyclic Technologies is developing an antilock braking system (ABS) for bicycles that will help cyclists to avoid accidents by enabling them to stop faster and with more control

COVID-19 trajectories among 57 million adults in England: a cohort study using electronic health records

BACKGROUND: Updatable estimates of COVID-19 onset, progression, and trajectories underpin pandemic mitigation efforts. To identify and characterise disease trajectories, we aimed to define and validate ten COVID-19 phenotypes from nationwide linked electronic health records (EHR) using an extensible framework. METHODS: In this cohort study, we used eight linked National Health Service (NHS) datasets for people in England alive on Jan 23, 2020. Data on COVID-19 testing, vaccination, primary and secondary care records, and death registrations were collected until Nov 30, 2021. We defined ten COVID-19 phenotypes reflecting clinically relevant stages of disease severity and encompassing five categories: positive SARS-CoV-2 test, primary care diagnosis, hospital admission, ventilation modality (four phenotypes), and death (three phenotypes). We constructed patient trajectories illustrating transition frequency and duration between phenotypes. Analyses were stratified by pandemic waves and vaccination status. FINDINGS: Among 57 032 174 individuals included in the cohort, 13 990 423 COVID-19 events were identified in 7 244 925 individuals, equating to an infection rate of 12·7% during the study period. Of 7 244 925 individuals, 460 737 (6·4%) were admitted to hospital and 158 020 (2·2%) died. Of 460 737 individuals who were admitted to hospital, 48 847 (10·6%) were admitted to the intensive care unit (ICU), 69 090 (15·0%) received non-invasive ventilation, and 25 928 (5·6%) received invasive ventilation. Among 384 135 patients who were admitted to hospital but did not require ventilation, mortality was higher in wave 1 (23 485 [30·4%] of 77 202 patients) than wave 2 (44 220 [23·1%] of 191 528 patients), but remained unchanged for patients admitted to the ICU. Mortality was highest among patients who received ventilatory support outside of the ICU in wave 1 (2569 [50·7%] of 5063 patients). 15 486 (9·8%) of 158 020 COVID-19-related deaths occurred within 28 days of the first COVID-19 event without a COVID-19 diagnoses on the death certificate. 10 884 (6·9%) of 158 020 deaths were identified exclusively from mortality data with no previous COVID-19 phenotype recorded. We observed longer patient trajectories in wave 2 than wave 1. INTERPRETATION: Our analyses illustrate the wide spectrum of disease trajectories as shown by differences in incidence, survival, and clinical pathways. We have provided a modular analytical framework that can be used to monitor the impact of the pandemic and generate evidence of clinical and policy relevance using multiple EHR sources. FUNDING: British Heart Foundation Data Science Centre, led by Health Data Research UK

A pattern-based release planning methodology for market-driven software / Amir Seyed Danesh

In software development, release planning is performed in order to select important features and requirements based on resource and technical constraints and the relationships between requirements. Several methods have been developed for release planning, but the most challenging part of release planning methods is dealing with unique complexities and varying characteristics of problem scope and domain. This has made the existing methods and approaches only applicable to a limited range of software projects. As a result, a more flexible and adaptive approach is required for release planning that can be customized in accordance to different domains and can be employed in a variety of software development projects. Achieving a highly customized release planning methodology requires an effective planning process that covers all release planning tasks and can be customized according to project specifications for each parameter. This study aims to, firstly, assemble a general and comprehensive process for release planning which covers all the important tasks and, secondly, identify parameters which can be used to customize the process for various projects, and thirdly introduce and apply release planning patterns based on process model steps and the identified parameters to facilitate customization. Thus, available release planning approaches have been studied and four common tasks i.e. requirements prioritization, resource estimation, release pre-planning, and trade-off analysis were identified and assembled in the form of a process model. Subsequently, various relevant parameters for each step which are related to project specifications were identified. In order to customize each step of the process model for various projects, each parameter was determined precisely and its current instances were identified. Some of the parameters are shared between process model steps. The notion of "pattern" was employed in order to facilitate the customization of the steps of the process model and several patterns were identified. Every release planning pattern has constraints based upon parameter instances of the step of process model, and suggests a solution as the selected method to apply to the step. Using this notion, the release planner only has to select a release planning pattern based on selected parameters that suit his circumstance. To validate the proposed methodology, two methods are used. At first, five software companies with 31 projects were used to implement method to their projects. The companies were asked to apply the pattern-based methodology to at least two releases and, for each step of the methodology, apply PRP tool suggested method. Secondly, numbers of 13 experts in the software development domain are answered questions in a survey on the results of the methodology and their satisfaction. Results showed that in most cases -more than 87% of the cases, the methodology suggested by the pattern release planner produce better releases and make the release planning process easier and faster than those used previously