Inferring hybrid transportation modes from sparse GPS data using a moving window SVM classification

Understanding travel behaviour and travel demand is of constant importance to transportation communities and agencies in every country. Nowadays, attempts have been made to automatically infer transportation modes from positional data, such as the data collected by using GPS devices so that the cost in time and budget of conventional travel diary survey could be significantly reduced. Some limitations, however, exist in the literature, in aspects of data collection (sample size selected, duration of study, granularity of data), selection of variables (or combination of variables), and method of inference (the number of transportation modes to be used in the learning). This paper therefore, attempts to fully understand these aspects in the process of inference. We aim to solve a classification problem of GPS data into different transportation modes (car, walk, cycle, underground, train and bus). We first study the variables that could contribute positively to this classification, and statistically quantify their discriminatory power. We then introduce a novel approach to carry out this inference using a framework based on Support Vector Machines (SVMs) classification. The framework was tested using coarse-grained GPS data, which has been avoided in previous studies, achieving a promising accuracy of 88% with a Kappa statistic reflecting almost perfect agreement

Impact of weather conditions on macroscopic urban travel times

Weather conditions may significantly impact a series of everyday human decisions and activities. As a result, engineers seek to integrate weather-related data into traffic operations in order to improve the current state of practice. Travel times and speeds are two of the elements of a transportation system that may be greatly affected by the weather resulting in deterioration of roadway network performance. This study aims to investigate the impact of different intensities of rain, snow and temperature levels on macroscopic travel times in the Greater London area (UK) during the period 1 October–10 December 2009. The analysis was carried out for three 2-h periods on weekdays during the morning, afternoon and evening periods. Automatic Number Plate Recognition (ANPR) data obtained from more than 380 travel links are used in the analysis. The main finding is that the impact of rain and snow is a function of their intensity. Specifically, the ranges of the total travel time increase due to light, moderate and heavy rain are: 0.1–2.1%, 1.5–3.8%, and 4.0–6.0% respectively. Light snow results in travel time increases of 5.5–7.6%, whilst heavy snow causes the highest percentage delays spanning from 7.4% to 11.4%. Temperature has nearly negligible effects on travel times. It was also found that the longer links within outer London generally yield greater travel time decreases than those in inner London, and even higher decreases than the shortest links in central London. This research provides planners with additional information that can be used in traffic management to modify planning decisions and improve the transportation system control on a network scale under different weather conditions. In order to determine whether the weather effects are region-specific, continued research is needed to replicate this study in other areas that exhibit different characteristics

Sample Size Calculation for Studying Transportation Modes from GPS Data

The many advantageous features of GPS-based longitudinal surveys associated with prompt recall surveys make such surveys very attractive for travel behaviour studies. However, the sample size calculation procedure for GPS-based surveys is more complicated compared to well-known and widely applied conventional household one/two-day travel surveys. The higher cost of GPS surveys requires scrutiny at the sample size planning stage to ensure cost effectiveness. The essence of sample size calculations problem is of a trade-off between cost/time taking the precision of the survey into account. Different machine learning-based techniques have been developed to infer the transportation mode based upon speed and acceleration calculated from GPS data. However, none of these studies calculate the sample size required for validating these techniques. Calculating the most effective sample size for this inference mainly depends on the variability of these variables which are normally used. To perform this calculation, we develop an understanding of inter-modal (variation between different transportation modes) and intra-modal variability (variation within each transportation mode). The study demonstrates that the motorised modes reflect the highest variability. We use traffic count data to study this variability across different seasonal divisions. The hourly and daily seasonal divisions are proved to be of the highest variability. Extending the survey length also decreases the sample size significantly. This reduction is applied to the calculated sample sizes defining the survey length to be 2 weeks, taking the weekly-seasonality into account

Constraints to Economic Development and Growth in the Middle East and North Africa

When comparing the speed and extent of economic development in different geographic regions of the world over the past 20 years, the under-average performance of Arab countries in general and Arab Mediterranean countries in particular is striking. This is despite an overall favorable geo-strategic situation at the crossroads of three continents, with excellent connections to sea and waterways and in direct proximity to the European Union, one of the world’s economic hubs. It is also despite the minor importance of negative factors such as a high-burden diseases or high levels of ethnic fractionalization. In this paper, I focus on identifying the most important constraints on Arab Mediterranean economic development. I use state-of-the-art econometric tools to quantify constraints that have been identified through economic theory and studies of the political economy characteristics of the region. The empirical results offer support for the central hypothesis that limited technological capacities and political economy structures are the primary constraints on economic development. With a view to international structural adjustment efforts, my findings imply that the limited success of the Euro-Mediterranean policy to stimulate the economic development of the Arab Mediterranean countries might be because structural adjustment efforts do not tackle—or at least do not sufficiently tackle— these constraints.Vergleicht man Geschwindigkeit und Umfang der wirtschaftlichen Entwicklung der verschiedenen Weltregionen in den vergangenen zwanzig Jahren, so fällt insbesondere das unterdurchschnittliche Abschneiden der arabischen Länder im Allgemeinen und der arabischen Mittlemeerländer im Besonderen ins Auge, und dies trotz einer insgesamt vorteilhaften geographischen Lage im Schnittpunkt dreier Kontinente mit exzellenten Anschlussmöglichkeiten an See- und Wasserwege, trotz der direkten Nachbarschaft zum Weltwirtschaftsdrehkreuz Europäische Union und trotz der relativ geringen Bedeutung wichtiger entwicklungshemmender Faktoren, beispielsweise ethnische Zersplitterung oder massive Ausbreitung von Krankheiten wie AIDS oder Malaria. In diesem Aufsatz wird versucht, von den unterschiedlichen Hemmfaktoren wirtschaftlicher Entwicklung, die in der wirtschaftstheoretischen Literatur und/oder in MENARegionalstudien diskutiert werden, diejenigen herauszuarbeiten, die wirtschaftliche Entwicklung am stärksten behindern oder möglicherweise stärker als andere. Dabei benutze ich modernste ökonometrische Verfahren, um den Einfluss der verschiedenen erklärenden Variablen zu quantifizieren. Die Ergebnisse stützen die Eingangshypothese, dass insbesondere mangelnde technologische Kapazitäten und Fähigkeiten sowie regionalspezifische politökonomische Strukturen die wirtschaftliche Entwicklung in den arabischen Mittelmeerländern behindern

Effectiveness of the use of the anti-virus drug in children with COVID - 19

В роботі описується ефективність противірусних препаратів у дітей з COVID-19. Для педіатрів, сімейних лікарів, інфекціоністів, лікарів-інтернів.Перша згадка про коронавірусну інфекцію (COVID - 19) виявлена в Ухані, Китай, у 2019 році. Людство неодноразово страждало від епідемій. 2019 - 2021 роки називаються пандемією, яка називається COVID - 19. COVID-19 — сучасний вірус, який асоціюється з тим же сімейством вірусів, що й гостра респіраторна вірусна інфекція (ГРВІ). У більшості випадків хвороба у дітей протікає нешкідливо. В основному дітей госпіталізують через високий ризик ускладнень вірусної пневмонії. Стан здоров’я дітей і людства при цій інфекції в цілому характеризується зниженням імунологічної реактивності, особливо при ГРВІ, таких як COVID-19. Мета роботи Метою даного дослідження було визначити вплив препарату «ГРОПРИНОСИН» на перебіг коронавірусної інфекції у дітей та його специфічність по відношенню до клітин, які беруть участь в імунних процесах. Матеріали та методи В інфекційному відділенні міської дитячої лікарні м. Суми за період Жовтень, листопад, грудень 2020 року під нашим спостереженням перебувало 20 хворих дітей, яким призначали противірусні препарати в комплексному лікуванні даного захворювання та 23 хворих дитини, які лікувались іншими лікарськими засобами. Результати. Це діти, у яких клінічні прояви COVID-19 були типовими, такими як синдром тяжкої інтоксикації, гіпертермія, бронхообструкція. Діти, які отримували цей препарат 2-3 рази на добу у вікових дозах, скоротили час перебування в стаціонарі на 10-12 днів, а інша частина дітей перебувала в лікарні на 12-16 днів. Температура нормалізувалася на 2-3 добу від початку застосування противірусних препаратів. Тоді як у дітей з COVID-19, які не отримували препарат, температура трималася більше 3-5 днів. Основні симптоми вірусної інфекції стали менш вираженими. Таким чином, можна сказати, що лікування противірусними препаратами є високим при ГРВІ, а особливо при COVID-19. І особливо важливо розпочати комплексну терапію якомога раніше, щоб уникнути можливих ускладнень основного захворювання. Препарат перешкоджає ослабленню синтезу РНК і білка в інфікованих клітинах і тим самим прискорює одужання пацієнта. Також препарат підсилює противірусні механізми за рахунок активації системи інтерферону, який є важливим компонентом при вірусних захворюваннях.The first mention of coronavirus infection (COVID - 19) detected in Wuhan, China in 2019. Mankind has repeatedly suffered from epidemics. 2019 - 2021 is referred to as pandemic, called COVID - 19. COVID-19 is a modern virus that is associated with the same family of viruses as acute respiratory viral infection (ARI). In most cases, the disease in children is innocuous. In general, children are hospitalized due to the high risk of complications of viral pneumonia. The state of health of children and humanity in this infection is generally characterized by a decrease in immunological reactivity, especially in acute respiratory viral infections such as COVID-19. The aim of this study was to determine the effect of the drug “GROPRINOSIN” on the course of coronavirus infection in children and its specificity in relation to cells involved in immune processes. Materials and methods In the infectious department of the city children’s hospital of Sumy for the period of October, November, December 2020 under our supervision there were 20 sick children who were prescribed the antiviral drugs in the complex treatment of this disease and 23 sick children who were treated by using other medicines. These were children in whom the clinical manifestations of COVID-19 were typical, such as severe intoxication syndrome, hyperthermia, bronchoobstruction. Children who received this drug 2-3 times a day in age-related doses reduced their hospital stay for 10-12 days, while another part of kids were staying at hospital for 12-16 days. The temperature normalized for 2-3 days from the start of using the antiviral drugs. Whereas in children with COVID-19 who did not receive the drug, the temperature lasted more than 3-5 days. The main symptoms of viral infection became less determined. Conclusions Thus, we can say that the treatment with the antiviral drugs is high in SARS, and especially in COVID - 19. And it is especially important to start complex therapy as early as possible to avoid possible compli- cations of the underlying disease. The medicine prevents the weakening of RNA and protein synthesis in infected cells and thus accelerates the patient’s recovery. Also, this drug enhances antiviral mechanisms through the acti- vation of the interferon system, which is an important component in viral diseases