Формування вантажного плану контейнеровоза згідно з логічними правилами завантаження-вивантаження

Бень, А. П. Формування вантажного плану контейнеровоза згідно з логічними правилами завантаження-вивантаження = Assessment of the navigation situation in the decision support system for navigator / А. П. Бень, А. І. Федоров // Зб. наук. пр. НУК. – Миколаїв : НУК, 2019. – № 1 (475). – С. 129–134.Анотація. Мета. У статті розглянуті питання створення автоматизованих систем управління вантажними операціями контейнеровозів. Методика. Головною ідеєю наукового дослідження є вивчення особливостей процесу завантаженнявивантаження контейнеровоза під час виконання ним мультипортових рейсів (послідовних заходів до кількох портів під час виконання одного рейсу). При цьому виникає проблема «шифтінгу», тобто необхідності переміщення одних контейнерів на борту судна з метою розміщення інших. Пропонована методика розміщення контейнерів на основі логічних правил завантаження-вивантаження дає змогу скоротити час знаходження судна в порту за рахунок зменшення кількості операцій «шифтінгу», що позитивно впливає на економічні показники виконання рейсу контейнеровозом. Результати. Визначено ключові напрями досліджень у цій галузі. Показано, що створення автоматизованої системи управління вантажними операціями контейнеровозів дасть змогу одночасно вирішувати комплекс задач з управління вантажними операціями, що, своєю чергою, дасть змогу скоротити час, необхідний для їх виконання, та підвищити економічну ефективність рейсу судна. Особливо ефективним є застосування пропонованого підходу під час мультипортових перевезень, які здійснюються контейнеровозами з невеликою кількістю контейнерів (фідерні перевезення). Наукова новизна. Розроблено математичну модель завантаження контейнеровоза на основі логічних правил, що дає змогу одночасно враховувати мультипортовість виконання рейсу судна й технологічні обмеження формування вантажного плану, зумовлені особливостями їх розміщення на судні. Запропоновано модель формування оптимального вантажного плану судна, що враховує послідовність заходу в порти під час виконання рейсу. Практична значимість. У прикладному плані ця робота спрямована на створення програмного продукту, використання якого дасть змогу вирішити важливе науково-прикладне завдання в галузі застосування інформаційних технологій у судноводінні – підвищення ефективності та безпечності контейнерних перевезень за рахунок упровадження автоматизованих систем управління вантажними операціями контейнеровозів.Abstract. Purpose. The article deals with the creation of automated systems for managing cargo operations of container ships. Method. The main idea of the scientific research is to study the features of the process of loading-unloading of a container ship during its multi-port going’s (sequential enter to several ports during the same trip). This raises the problem of "shifting", i.e. the need to move some containers on board a vessel to accommodate others. The proposed method of placing containers on the basis of logical rules of loading and unloading allows to reduce the time of stay of the vessel in port by reducing the number of "shifting" operations, which has a positive effect on the economic performance of a container ship. Results. Key areas of research in this field are identified. It has been shown that the creation of an automated containerized cargo operations management system (ACCOMS) will simultaneously solve a complex of cargo operations management tasks, which will reduce the time required to perform them and increase the economic efficiency of a vessel’s trip. Particularly effective is the application of the proposed approach when it is applied to multi-port transportations carried out by container ships with a small number of containers (feeder transportation). Scientific novelty. The mathematical model of loading of a container ship on the basis of logical rules is developed that allows to take into account simultaneously the multiportity of execution of trip of the vessel and technological limitations of formation of cargo plan due to the peculiarities of their placement on the ship. The model of formation of the optimal cargo plan of the ship, taking into account the sequence of approach to the ports during the trip, is proposed. Practical importance. In the practical side, this work is aimed at creating a software product, the use of which will allow to solve an important scientific and applied task in the field of application of information technologies in navigation –to increase the efficiency and safety of container transportation due to the introduction of ACCOMS

Assessment of the navigation situation in the decision support system for navigator

Бень, А. П. Оцінка навігаційної ситуації в системі підтримки прийняття рішень судноводія = Assessment of the navigation situation in the decision support system for navigator / А. П. Бень, І. В. Паламарчук // Shipbuilding & Marine Infrastructure. – 2019. – № 1 (11). – C. 105–109.Анотація. У статті розглянуті питання створення систем підтримки прийняття рішень судноводія з оцінкою навігаційної ситуації. Методика. Головною ідеєю дослідження є вивчення особливостей перебігу процесів формування і прийняття рішень судноводієм із метою вдосконалення процесу взаємодії судноводія з інформаційною навігаційною системою, підвищення якості рішень, які ним приймаються, та розроблення новітніх підходів допобудови високоточної системи підтримки прийняття рішень судноводія. Результати. Визначено ключові напрямки досліджень у даній галузі, показано вплив людського фактора на процеси прийняття рішень із керування судном. Показано, що створення системи підтримки прийняття рішень судноводія дозволить одночасно вирішувати комплекс задач із оперативного керування рухом судна з позицій досягнення заданого рівня безпечності та економічної ефективності. Запропоновано алгоритм функціонування такої системи. Визначено набір критеріїв для оцінки рівня небезпеки суден, що перебувають у ситуації зближення.Abstract. Purpose. The article consider with the creation of decision support systems of the navigator with the estimation of navigation situation. Method. The main idea of the research is to study the peculiarities of the process of formation and decision-making of the navigator in order to improve the process of interaction of the navigator with the information navigation system, to improve the quality of the decisions they make, and to develop new approaches to the construction of a high-precision decision support systems of the navigator. Results. The key areas of research in this field are identified; the influence of the human factor on the ship management decision-making processes is shown. It is shown that the creation of a decision support systems of the navigator will simultaneously solve a complex of problems in operational management of the ship's movement from the standpoint of achieving the set level of safety and economic efficiency.An algorithm for the operation of such a system is proposed. A set of criteria for assessing the level of danger of vessels in a convergence situation has been identified. Scientific novelty. An important area of further research is the study of the influence of maneuverability of ships on the processes of formation of control effects in intelligent decision support systems of the navigator. The proposed approaches to the creation of decision support systems of the navigator reduce the risks of collision of ships and increase the economic efficiency of navigation. Practical importance. An important problem today is to improve the accuracy of the ships' planned trajectory. The presence of a large number of recent marine casualties, including the large number of human casualties and severe man-made consequences, the major cause of which is the «human factor» clearly demonstrates the need to create modern decision support systems of the navigatorwhich include the process of human interaction with the technical means of navigation and making decisions in difficult navigational conditions and critical situations.The development of such systems requires taking into account the peculiarities of human interaction with the technical means of control of the ship

Early Indicators of COVID-19 Infection Prevention Behaviors:Machine Learning Identifies Personal and Country-Level Factors

The Coronavirus is highly infectious and potentially deadly. In the absence of a cure or a vaccine, the infection prevention behaviors recommended by the World Health Organization constitute the only measure that is presently available to combat the pandemic. The unprecedented impact of this pandemic calls for swift identification of factors most important for predicting infection prevention behavior. In this paper, we used a machine learning approach to assess the relative importance of potential indicators of personal infection prevention behavior in a global psychological survey we conducted between March-May 2020 (N = 56,072 across 28 countries). The survey data were enriched with society-level variables relevant to the pandemic. Results indicated that the two most important indicators of self-reported infection prevention behavior were individual-level injunctive norms—beliefs that people in the community should engage in social distancing and self-isolation, followed by endorsement of restrictive containment measures (e.g., mandatory vaccination). Society-level factors (e.g., national healthcare infrastructure, confirmed infections) also emerged as important indicators. Social attitudes and norms were more important than personal factors considered most important by theories of health behavior. The model accounted for 52% of the variance in infection prevention behavior in a separate test sample—above the performance of psychological models of health behavior. These results suggest that individuals are intuitively aware that this pandemic constitutes a social dilemma situation, where their own infection risk is partly dependent on the behaviors of others. If everybody engaged in infection prevention behavior, the virus could be defeated even without a vaccine

Review of quantitative empirical evaluations of technology for people with visual impairments

Addressing the needs of visually impaired people is of continued interest in Human Computer Interaction (HCI) research. Yet, one of the major challenges facing researchers in this field continues to be how to design adequate quantitative empirical evaluation for these users in HCI. In this paper, we analyse a corpus of 178 papers on technologies designed for people with visual impairments, published since 1988, and including at least one quantitative empirical evaluation (243 evaluations in total). To inform future research in this area, we provide an overview, historic trends and a unified terminology to design and report quantitative empirical evaluations. We identify open issues and propose a set of guidelines to address them. Our analysis aims to facilitate and stimulate future research on this topic

Using machine learning to identify important predictors of COVID-19 infection prevention behaviors during the early phase of the pandemic

Before vaccines for coronavirus disease 2019 (COVID-19) became available, a set of infection-prevention behaviors constituted the primary means to mitigate the virus spread. Our study aimed to identify important predictors of this set of behaviors. Whereas social and health psychological theories suggest a limited set of predictors, machine-learning analyses can identify correlates from a larger pool of candidate predictors. We used random forests to rank 115 candidate correlates of infection-prevention behavior in 56,072 participants across 28 countries, administered in March to May 2020. The machine-learning model predicted 52% of the variance in infection-prevention behavior in a separate test sample—exceeding the performance of psychological models of health behavior. Results indicated the two most important predictors related to individual-level injunctive norms. Illustrating how data-driven methods can complement theory, some of the most important predictors were not derived from theories of health behavior—and some theoretically derived predictors were relatively unimportant

The Forest Observation System, building a global reference dataset for remote sensing of forest biomass

International audienceForest biomass is an essential indicator for monitoring the Earth's ecosystems and climate. It is a critical input to greenhouse gas accounting, estimation of carbon losses and forest degradation, assessment of renewable energy potential, and for developing climate change mitigation policies such as REDD+, among others. Wall-to-wall mapping of aboveground biomass (aGB) is now possible with satellite remote sensing (RS). However, RS methods require extant, up-to-date, reliable, representative and comparable in situ data for calibration and validation. Here, we present the Forest Observation System (FOS) initiative, an international cooperation to establish and maintain a global in situ forest biomass database. aGB and canopy height estimates with their associated uncertainties are derived at a 0.25 ha scale from field measurements made in permanent research plots across the world's forests. all plot estimates are geolocated and have a size that allows for direct comparison with many RS measurements. The FOS offers the potential to improve the accuracy of RS-based biomass products while developing new synergies between the RS and ground-based ecosystem research communities

Optimasi Portofolio Resiko Menggunakan Model Markowitz MVO Dikaitkan dengan Keterbatasan Manusia dalam Memprediksi Masa Depan dalam Perspektif Al-Qur`an

Risk portfolio on modern finance has become increasingly technical, requiring the use of sophisticated mathematical tools in both research and practice. Since companies cannot insure themselves completely against risk, as human incompetence in predicting the future precisely that written in Al-Quran surah Luqman verse 34, they have to manage it to yield an optimal portfolio. The objective here is to minimize the variance among all portfolios, or alternatively, to maximize expected return among all portfolios that has at least a certain expected return. Furthermore, this study focuses on optimizing risk portfolio so called Markowitz MVO (Mean-Variance Optimization). Some theoretical frameworks for analysis are arithmetic mean, geometric mean, variance, covariance, linear programming, and quadratic programming. Moreover, finding a minimum variance portfolio produces a convex quadratic programming, that is minimizing the objective function ðð¥with constraintsð ð 𥠥 ðandð´ð¥ = ð. The outcome of this research is the solution of optimal risk portofolio in some investments that could be finished smoothly using MATLAB R2007b software together with its graphic analysis

Search for heavy resonances decaying to two Higgs bosons in final states containing four b quarks

A search is presented for narrow heavy resonances X decaying into pairs of Higgs bosons (H) in proton-proton collisions collected by the CMS experiment at the LHC at root s = 8 TeV. The data correspond to an integrated luminosity of 19.7 fb(-1). The search considers HH resonances with masses between 1 and 3 TeV, having final states of two b quark pairs. Each Higgs boson is produced with large momentum, and the hadronization products of the pair of b quarks can usually be reconstructed as single large jets. The background from multijet and t (t) over bar events is significantly reduced by applying requirements related to the flavor of the jet, its mass, and its substructure. The signal would be identified as a peak on top of the dijet invariant mass spectrum of the remaining background events. No evidence is observed for such a signal. Upper limits obtained at 95 confidence level for the product of the production cross section and branching fraction sigma(gg -> X) B(X -> HH -> b (b) over barb (b) over bar) range from 10 to 1.5 fb for the mass of X from 1.15 to 2.0 TeV, significantly extending previous searches. For a warped extra dimension theory with amass scale Lambda(R) = 1 TeV, the data exclude radion scalar masses between 1.15 and 1.55 TeV

Multidifferential study of identified charged hadron distributions in ZZ-tagged jets in proton-proton collisions at s=\sqrt{s}=13 TeV

Jet fragmentation functions are measured for the first time in proton-proton collisions for charged pions, kaons, and protons within jets recoiling against a $Z$ boson. The charged-hadron distributions are studied longitudinally and transversely to the jet direction for jets with transverse momentum 20 $< p_{\textrm{T}} < 100$ GeV and in the pseudorapidity range $2.5 < \eta < 4$. The data sample was collected with the LHCb experiment at a center-of-mass energy of 13 TeV, corresponding to an integrated luminosity of 1.64 fb$^{-1}$. Triple differential distributions as a function of the hadron longitudinal momentum fraction, hadron transverse momentum, and jet transverse momentum are also measured for the first time. This helps constrain transverse-momentum-dependent fragmentation functions. Differences in the shapes and magnitudes of the measured distributions for the different hadron species provide insights into the hadronization process for jets predominantly initiated by light quarks.Comment: All figures and tables, along with machine-readable versions and any supplementary material and additional information, are available at https://cern.ch/lhcbproject/Publications/p/LHCb-PAPER-2022-013.html (LHCb public pages