BIM-Based Risk Identification and Assessment in Building Projects at their design Phase

The complexity and dynamics of construction sites, interwoven with the uncertain behaviour of human factors, may result in severe injuries in the workplace, illness, and may even lead to fatality. Despite the drafting of a strict legislative framework, the statistics in construction industry remain dissatisfactory and worrisome. Therefore, the demand for a thorough risk management process, based on automated safety modelling and preventive strategy, stands out in order to identify and eliminate potential hazards early in the design phase of a construction project, resolving thus safety issues in the field by extending traditional safety management practices. The underlying purpose of this study is to investigate whether and how Building Information Modelling (BIM) can be used within the health and safety framework to enhance risk identification and assessment in building projects at their design phase. To this aim, a case study is conducted via a BIM software, namely Revit, to develop an effective Building Information Model of a two-storey building in which safety measures are introduced according to State legislation and field practices at a specific construction phase. In the proposed way, the real-life complexity of the risk management process is simplified, due to the object-oriented approach of BIM, the variety of BIM libraries and the experiential recognition of unsafe conditions with 3D simulations in place of the non-judgmental and merely bureaucratic lawenforcement methods. In conclusion, BIM enhances the communication between engineers and workers, using interactive tools, and facilitates the Safety Officer duties in the direction of preventing potentials hazards from the early planning phases

Ikimokyklinio amžiaus vaikų miego sunkumų, emocinio reaktyvumo ir tėvų taikomos miego bei naudojimosi ekranus turinčiais prietaisais tvarkos sąsajos

Background. Children’s sleep problems are associated with temperament. One of the dimensions of temperament – higher emotional reactivity – is defined as a risk factor for children’s emotional, behavioral, and sleep problems. Screen-based media use is a very common phenomenon among children that relates to sleep problems. Still there is a gap of research explaining the interactions between children’s sleep problems, temperament, and parental discipline (sleep regime and rules for screen-based media use). The aim of this study is to evaluate the relations between preschool children’s sleep problems and parents’ discipline (sleep regime and rules for screen-based media use), and the role of children’s emotional reactivity. Methods. This research is a part of the longitudinal study “Electronic Media Use and Young Children’s Health” conducted in the year 2017–2018 and funded by the Research Council of Lithuanian (agreement no. GER-006/2017). Participants are 876 children aged 2 to 5 years old and their parents. Children’s sleep problems and emotional reactivity were assessed using the Child Behavior Checklist (CBCL/1½-5). Information about rules for screen-based media use and sleep regime was obtained using the parent-report questionnaire. Results. Sleep problems are related to emotional reactivity, sleep regime, and rules for screen media use. Children without regular sleep regime and without constant rules for screen-based media use have higher sleep problems and emotional reactivity. The results of the regression analysis show that emotional reactivity, together with sleep regime and rules for screen-based media use, significantly explain one-fifth to one-third of children’s sleep problems at different ages of the preschool period. However, the prognostic value of emotional reactivity and parental discipline varies according to a child’s age, as they are significant predictors of sleep problems among two, three and four-year-olds, but no longer explain sleep problems of five-year-olds. The path analysis confirmed that emotional reactivity, directly and through mediating variables, e.g., parental reported child’s sleep regime and rules for screen-based media use, is significantly associated with children’s sleep problems. Conclusions. Emotional reactivity should be considered as a significant risk factor in the relation between children’s sleep problems, sleep regime and parental applied rules for screen-based media use. These results are important while identifying children at higher risk for sleep problems. The results also support that parental discipline, such as sleep regime and rules for screen-based media use, are significant for preventing sleep problems in children with higher emotional reactivity.Įvadas. Vaikų emocinis reaktyvumas, viena iš temperamento dimensijų, išskiriamas kaip rizikos veiksnys emocinių, elgesio ir miego sunkumų raiškai. Vaikų naudojimasis ekranus turinčiais išmaniaisiais prietaisais yra labai paplitęs reiškinys ir taip pat siejamas su vaikų miego sunkumais. Siekiant labiau suprasti vaikų miego sunkumų priežastis dar trūksta tyrimų, kurie aiškintųsi miego sunkumų, temperamento ir tėvų taikomos tvarkos (miego ir naudojimosi ekranais) tarpusavio sąveikas. Šio tyrimo tikslas – įvertinti ikimokyklinio amžiaus vaikų miego sunkumų ir tėvų taikomos tvarkos (miego ir naudojimosi ekranus turinčiais prietaisais) sąsajas, atsižvelgiant į emocinio reaktyvumo, kaip temperamento dimensijos, vaidmenį šiose sąsajose. Metodai. Šis tyrimas yra mokslinio tyrimo „Šiuolaikinės informacinės technologijos ir mažų vaikų sveikata“, vykdyto 2017–2018 m., dalis. Tyrime naudojami duomenys apie 876 vaikus nuo 2 iki 5 metų, šiuos duomenis apklausos būdu pateikė jų tėvai. Vaikų miego sunkumai ir emocinis reaktyvumas buvo vertinti naudojant Vaiko elgesio aprašą (CBCL/1½-5). Informaciją apie miego ir naudojimosi ekranus turinčiais prietaisais tvarką teikė tėvai, atsakydami į anketos klausimus. Rezultatai. Miego sunkumai siejasi su emociniu reaktyvumu ir miego bei ekranus turinčių prietaisų naudojimo tvarka. Vaikai, kurie neturi pastovios miego ir naudojimosi ekranus turinčiais prietaisais tvarkos, patiria didesnių miego sunkumų ir jų emocinis reaktyvumas yra labiau išreikštas. Regresinės analizės rezultatai rodo, kad emocinis reaktyvumas kartu su miego bei naudojimosi ekranus turinčiais prietaisais tvarka reikšmingai paaiškina nuo penktadalio iki trečdalio dvejų–penkerių metų vaikų miego sunkumų. Vis dėlto, atsižvelgiant į vaiko amžių, emocinio reaktyvumo ir tėvų taikomos tvarkos prognostinė reikšmė kinta – jie yra reikšmingi dvejų, trejų ir ketverių metų vaikų miego sunkumus nuspėjantys veiksniai, tačiau nepaaiškina penkerių metų vaikų miego sunkumų. Struktūrinių lygčių modeliavimas atskleidė, kad emocinis reaktyvumas tiesiogiai ir per tarpinius kintamuosius – tėvų taikomą miego ir naudojimosi ekranus turinčiais prietaisais tvarką – reikšmingai siejasi su vaikų miego sunkumais. Apibendrinimas. Analizuojant vaikų miego sunkumų ir tėvų taikomos miego ir naudojimosi ekranus turinčiais prietaisais tvarkos sąsajas, emocinį reaktyvumą galima traktuoti kaip rizikos veiksnį. Šie rezultatai yra reikšmingi siekiant atpažinti vaikus, turinčius didesnę miego sunkumų atsiradimo riziką ir yra svarbūs tuo, kad atskleidžia, jog net ir didesnį emocinį reaktyvumą turintiems vaikams tėvų palaikoma miego ir naudojimosi ekranus turinčiais prietaisais tvarka yra reikšmingas prevencinis vaikų miego sunkumų veiksnys

Development of a multi criteria model for assisting EV user charging decisions

Electric Vehicles offer one of the most efficient solutions towards the direction of providing sustainable transportation systems. However, a broader market uptake of Electric Vehicle--based mobility is still missing. The lack of sufficient infrastructure (Electric Vehicle charging stations) in combination with the lack of information about their availability appears as a major limitation, leading to low user acceptance. Additional, technology based, assistance services provided to Electric Vehicle users is a key solution to unlock the full potential of their utilization. This paper presents a multi-factor dynamic optimization model using multi-criteria analysis to select the best alternatives for Electric Vehicle charging within a smart grid with the goal of supporting a larger uptake of Electric Vehicle -based mobility. The application provides assistance to the Electric Vehicle drivers through functionalities of energy price, cost and travel time of the electric vehicle to the charging station, the specifications of vehicles and stations, the status of the charging stations as well as the user\u27s preferences. The proposed model is developed by incorporating PROMETHEE II and Analytic Hierarchy Process methodologies to provide the best charging solutions after considering all possible options for each Electric Vehicle user. The multi-criteria analysis algorithm is not only limited to comparing alternative charging options at a specific time but also looks at several starting times of charging. A simulated case study is implemented to examine the functionality of the proposed model. From the results, it is evident that by applying the findings of this work entrepreneurial community and industry can develop new services that will improve user satisfaction, electromobility, urban mobility, and sustainability of cities. At the same time, academia, leveraging the methodology and factors that influence the choice of charging station, can conduct further research on digital innovations that will contribute to the consolidation of e-mobility ensuring the sustainability of cities, while accelerating digital transformation in the transport sector

Stochastic Optimization Approaches for Solving Sudoku

In this paper the Sudoku problem is solved using stochastic search techniques and these are: Cultural Genetic Algorithm (CGA), Repulsive Particle Swarm Optimization (RPSO), Quantum Simulated Annealing (QSA) and the Hybrid method that combines Genetic Algorithm with Simulated Annealing (HGASA). The results obtained show that the CGA, QSA and HGASA are able to solve the Sudoku puzzle with CGA finding a solution in 28 seconds, while QSA finding a solution in 65 seconds and HGASA in 1.447 seconds. This is mainly because HGASA combines the parallel searching of GA with the flexibility of SA. The RPSO was found to be unable to solve the puzzle.Comment: 13 page

Using Artificial Intelligence to Improve Traffic flows, with Consideration of Data Privacy

USDOT Grant 69A3551747109This project develops an artificial neural network (ANN), a class of Artificial Intelligence (AI) systems, to accurately model and predict future delays at an intersection. Developing such modeling and prediction systems raises considerable data privacy concerns and it is incumbent upon municipal, state, and federal branches of government to prioritize citizens and their concerns before the implementation of new smart community technologies that are fueled by unprecedented levels of data collection. The technique proposed in this study identifies nonlinear, time-varying mapping between the inputs to the ANN and its output, the predicted delay. The traffic data measured at a Long Beach intersection with heavy truck traffic are used to build a realistic simulation in Vissim, a microscopic traffic flow simulator. The authors designed and performed experiments on the developed Vissim model to train the ANN delay predictor and validate the generalization ability of the predictor. The simulation results agree with the on-site delay measurements. This suggests the ANN predictor can accurately predict the delay at the intersection with heavy-truck penetration. Because smart technologies raise data privacy concerns, the research team led 32 study participants on \u201cdatawalks\u201d designed to gauge comfort levels and attitudes toward devices that collect personally identifiable information. Study participants encountered public WiFi routers, surveillance cameras, automated license plate readers and other surveillance technologies. They used a custom app to respond to prompts related to data collection, sharing and analysis. Study participants\u2019 responses, along qualitative data collected during a \u201cdebriefing\u201d conversation following each walk, provided insights into residents\u2019 attitudes toward smart communities technologies and identified privacy concerns. The quantitative and qualitative findings in this study inform a series of recommendations that research teams can follow to implement real-world test labs at busy truck intersections while fostering public trust, installing these modelling and prediction systems, and ensuring the overall safety and efficiency of the intersection\u2019s traffic flow

System-Theoretic Process Analysis (STPA) for Hazard Analysis in Complex Systems: The Case of “Demand-Side Management in a Smart Grid”

Inelasticity of demand along with the distributed energy sources and energy market democratization pose significant challenges which have considerable negative impacts on overall grid balance. The need for increased capacity and flexibility in the era of energy market digitalization has introduced new requirements in the energy supply network which could not be satisfied without continuous and costly local power network upgrades. Additionally, with the emergence of Smart Homes (SHs) and Home Energy Management (HEM) systems for monitoring and operating household appliances, opportunities have arisen for automated Demand Response (DR). DR is exploited for the modification of the consumer energy demand, in response to the specific conditions within the electricity system (e.g., peak period network congestion). In order to optimally integrate DR in the broader Smart Grid (SG) system, modelling of the system parameters and safety analysis is required. In this paper, the implementation of STPA (System-Theoretic Process Analysis) structured method, as a relatively new hazard analysis technique for complex systems is presented and the feasibility of STPA implementation for loss prevention on a Demand Response system for home energy management, and within the complex SG context, is examined. The applied method delivers a mechanism useful in understanding where gaps in current operational risk structures may exist. The STPA findings in terms of loss scenarios can be used to generate a variety of safeguards to ensure secure operational control and in implementing targeted strategies through standard approaches of risk assessment