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The user interface, in broad terms, is the medium through which the user and the information come together. The types of searches a public access catalog (PAC) can perform are defined by the indexing strategy and retrieval software. The way the user's interest is communicated to the retrieval software and the way the results are communicated to the user is, by a more narrow definition, the interface software. Both the kinds of searches that can be performed by a variety of CD‐ROM PACs and how their workstations are used to accomplish the searches are considered.

The Middle East and North Africa (MENA) region is known for its extreme weather conditions during Summer. A major determinant of the sustainability of the design of a building is its fenestrations. The purpose of this paper is to explore the problem of designing and locating windows on building facades such that a number of relevant criteria to the MENA region are optimised, including solar heat gain, privacy, daylighting and cost of installation.

A multi-objective optimisation problem is proposed with the focus on capturing the requirements of residential dwellings in the MENA region. Since the problem contains conflicting objectives that need to be optimised, a lexicographic approach is adopted. In order to display the Pareto curve, a bi-objective analysis based on the ε-constraint method is utilised.

The conflicting nature of the proposed problem is indicated via the Pareto optimal solutions yielded. Depending on the preference of criteria adopted in lexicographic optimisation, the location of the windows on the building façade tends to change. The bi-objective analysis indicates the importance of balancing out the daylight factor against each of privacy, solar heat gain and installation cost criteria. Furthermore, an analysis conducted in three major cities in the MENA region highlights the discrepancy in design alternatives generated depending on the local climatic condition.

This work proposes a novel mathematical optimisation model which focuses on producing a sustainable design and layout for windows on the facades of residential dwellings located in the MENA region. The proposed model provides designers with guidance through an automated support tool that yields optimised window designs and layout to ensure the sustainability of their designed buildings.

The purpose of this paper is to constitute an efficient way to improve energy efficiency and occupants comfort in buildings through reduction of direct solar heat gains by exterior shading devices. The shadings orientation and layout depends on the building location and façade orientation, and influence consequently the windows layout. It is still debated which type of window layout is preferable for a specific building location and façade orientation.

The paper presents a method to determine the most efficient windows’ layout, horizontal or vertical, for shading devices optimization by mean of integrating energy simulations and computational design. A parametric model has been built by visual programming language to simulate, iterate and compare the results.

The research shows the most efficient layouts of windows to be shaded for three latitudes and locations, and the 16 cardinal directions, to be used by architects and designers. The results show a significant prevalence of the horizontal window type on the south façades but also on the east and west orientations for all the three locations, while the rules of thumb would suggest the vertical layout for the sunrise and sunset façades.

The task of designing exterior shading devices presents two main issues: the shading period selection and the method of calculating its size and shape. The present research uses the innovative method Shaderade that existing literature demonstrates superior comparing other more dated like the section method and the solar vectors one.

The purpose of this paper is to determine the approximate window-to-wall ratio (WWR), window width-to-height ratio (WHR) and sill level for a room in Rasht–Gilan province and to present an optimal window in each of the WWR ranges providing the minimum energy consumption by integrating artificial lighting and thermal analyses, whilst maintaining internal comfort conditions using dynamic evaluation.

The process of modelling has four main steps: 1 – defining the building's features and requirements, 2 – validating input weather file data by on-site measurement, 3 – determining input parameters for the lighting and thermal analysis and 4 – clarifying variable parameters and fitness function for the optimization algorithm. Also, the survey study is performed in a daylit office room, in which 30 employees are employed to answer the questions in three different times of a day. In this process, the impact of daylight on their visual comfort is surveyed in 1,350 different illuminance levels which are manually recorded.

The range of useful daylight illuminance (UDI) values is determined as 200–1,000 lux. The optimum range of WWRs in the case study is 15%–25%. Also, due to the appropriate window height, electric lighting could be decreased by 40%.

Thermal and lighting performance in buildings is the relation of facade characteristics to environmental sustainability. Recent studies focussed on optimizing WWR and window characteristics considering thermal comfort and energy analyses. However, architects need freedom for designing façade and making decisions in their first sketches. Thus a guideline for optimum window conditions in each WWR is required. Also, considering occupants' behaviour in practical buildings, the visual comfort investigation is a gap in WWR optimization.

Physical gatherings at social events have been found as one of the main causes of COVID-19 transmission all over the world. Smartphone has been used for contact tracing by exchanging messages through Bluetooth signals. However, recent confirmed cases found in venues indicated that indirect transmission of the causative virus occurred, resulting from virus contamination of common objects, virus aerosolization in a confined space or spread from inadequate ventilation environment with no indication of human direct or close contact observed.

This paper presents a novel cyber-physical architecture for spatial temporal analytics (iGather for short). Locations with time windows are modeled as digital chromosomes in cyberspace to represent human activity instances in the physical world.

Results show that the high spatial temporal correlated but indirect tracing can be realized through the deployment of physical hardware and spatial temporal analytics including mobility and traceability analytics. iGather is tested and verified in different spatial temporal correlated cases. From a management perspective of mobilizing social capacity, the venue plays not only a promotion role in boosting the utilization rates but also a supervision-assisted role for keeping the venue in a safe and healthy situation.

This research is of particular significance when physical distancing measures are being relaxed with situations gradually become contained. iGather is able to help the general public to ease open questions: Is a venue safe enough? Is there anyone at a gathering at risk? What should one do when someone gets infected without raising privacy issues?

This study contributes to the existing literature by cyber-physical spatial temporal analytics to trace COVID-19 indirect contacts through digital chromosome, a representation of digital twin technology. Also, the authors have proposed a venue-oriented management perspective to resolve privacy-preserving and unitization rate concerns.

The challenge of truckload routing is increased in complexity by the introduction of stochastic demand. Typically, this demand is generalized to follow a Poisson distribution. In this chapter, we cluster the demand data using data mining techniques to establish the more acceptable distribution to predict demand. We then examine this stochastic truckload demand using an econometric discrete choice model known as a count data model. Using actual truckload demand data and data from the bureau of transportation statistics, we perform count data regressions. Two outcomes are produced from every regression run, the predicted demand between every origin and destination, and the likelihood that that demand will occur. The two allow us to generate an expected value forecast of truckload demand as input to a truckload routing formulation. The negative binomial distribution produces an improved forecast over the Poisson distribution.

FOR some time it has been recognized that the greater part of all passenger fatalities in air transportation were the result of impact in crash landings. Since in the majority of cases the crash landing was followed by fire, it was popularly believed that the majority of the deaths were occasioned by incineration. This Command, anxious to better an already excellent safety record, was fully aware of this problem, as were all other operators of transport aircraft.

Predictive analytics is the science of decision-making that eliminates guesswork out of the decision-making process and applies proven scientific procedures to find right solutions. Predictive analytics provides ideas on the occurrences of future downtimes and rejections thereby aids in taking preventive actions before abnormalities occur. Considering these advantages, predictive analytics is adopted in various diverse fields such as health care, finance, education, marketing, automotive, etc. Predictive analytics tools can be used to predict various behaviors and patterns, thereby saving the time and money of its users. Many open-source predictive analysis tools namely R, scikit-learn, Konstanz Information Miner (KNIME), Orange, RapidMiner, Waikato Environment for Knowledge Analysis (WEKA), etc. are freely available for the users. This chapter aims to reveal the best accurate tools and techniques for the classification task that aid in decision-making. Our experimental results show that no specific tool provides the best results in all scenarios; rather it depends upon the datasets and the classifier.

Truckload routing has always been a challenge. This paper explores the development of continuous flow truckload routes, which resemble less than truckload routes, and a new way to formulate the truckload routing problem (TRP). Rather than view the problem as a succession of origin/destination pairs, we look at the problem as a series of routing triplets. This enables us to use alternate solution methods, which may result in greater efficiency and improved solutions.

This paper aims to raise awareness on how a simple action by the occupant can significantly influence building energy efficiency, cost and CO₂ emissions to the environment. Classrooms in schools are the primary energy consumers (45.4%) due to the use of artificial lighting, despite Malaysia's tropical climate being ideal for daylight exploitation. This paper focuses on assessing the workplane daylight distribution quality and quantity in baseline and existing conditions of a typical pre-school classroom in Kuala Lumpur as a model-based exploration strategy towards nearly Zero Energy Buildings.

The adopted method is based on the calculation of average daylight factor (DF), daylight illuminance level (IL) and uniformity ratio (UR) parameters affected by the internal fixed drapes through computational and in situ measurements according to the requirements of the law and respective standards comprising the MS1525:2019, GBI and BREEAM.

The results show how user behaviour can turn a well-daylit area (Net Lettable Area>90%) into a poor-daylit area (NLA<5%) by sacrificing natural daylight. All the parameters' values were significantly decreased from 10% (UR) up to 88% (ADF). Full dependency on artificial lighting has imposed a total of RM18858.90 and CO₂ emissions of 25,362 kg for all pre-schools' classrooms in the country per day.

The paper develops the occupants' awareness on their contribution to climate change and global warming through the information and transparency provided.

The evidence indicates that a simple action by the occupant can significantly influence visual comfort, EE, cost and CO₂ emissions to the environment.