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This strategy significantly reduces the computational overhead and storage overhead required when using the kernel density estimation method to calculate the abnormal evaluation value of the test sample.

To effectively deal with the security threats of botnets to the home and personal Internet of Things (IoT), especially for the objective problem of insufficient resources for anomaly detection in the home environment, a novel kernel density estimation-based federated learning-based lightweight Internet of Things anomaly traffic detection based on nuclear density estimation (KDE-LIATD) method. First, the KDE-LIATD method uses Gaussian kernel density estimation method to estimate every normal sample in the training set. The eigenvalue probability density function of the dimensional feature and the corresponding probability density; then, a feature selection algorithm based on kernel density estimation, obtained features that make outstanding contributions to anomaly detection, thereby reducing the feature dimension while improving the accuracy of anomaly detection; finally, the anomaly evaluation value of the test sample is calculated by the cubic spine interpolation method and anomaly detection is performed.

The simulation experiment results show that the proposed KDE-LIATD method is relatively strong in the detection of abnormal traffic for heterogeneous IoT devices.

With its robustness and compatibility, it can effectively detect abnormal traffic of household and personal IoT botnets.

Urban mobility has substantially evolved in several western countries, shifting from interest in road expansion strategies to cater motorized movement to the emphasis on sustainable mobility. This is, however, not the case in several developing countries that still try to accommodate vehicular flows in inner historic cities. This paper aims at providing an assessment framework that helps in evaluating the effect of streetscape development on the walking and cycling environment in historic contexts.

This research follows a two-phase methodology. Phase 1 is the investigation of the literature review including the streetscape design, Sustainable Development Goals (SDGs) and indicators for the assessment of walking and cycling environment. This phase results in developing a set of indicators for the assessment. Phase 2 is the case study including, methods, steps and results of the assessment based on the output of Phase 1. This phase concludes with a discussion on the challenges and recommendations for the enhancement.

The streetscape development in Afrang was insufficient and negatively affected the walking and cycling environment. It was motorized-oriented, instead of enhancing green mobility. The interventions led to more crowds, safety risks and less pleasant experience. Moreover, the car users' experience was enhanced initially; however, the traffic situation did not persist. A sustainable urban mobility approach is necessary to be implemented with consideration to the global level and the relation to SDGs.

There is a gap in tackling the research problem both within the context of Port Said in particular and Egyptian context in general. Local authorities need a clear structured methodology to follow in the development of the streetscape. The assessment indicators gathered can be the basis for evaluating future plans.

Public spaces, which offer opportunities for social, cultural and recreational activities, enhance urban life quality (ULQ). Thus, this study aims to investigate the impact of public spaces and physical-environmental criteria affecting the usability of ULQ in Adana city, Turkey.

The study method consists of three stages. Firstly, public spaces and physical-environmental criteria that can be effective in ULQ were determined. Secondly, the effect of the determining criteria on ULQ was evaluated through a 5-point Likert scale questionnaire (1 = very negative, 5 = very positive). The survey was conducted with 601 people in the four central districts of Adana, including Çukurova, Seyhan, Sariçam and Yüregir. Participants evaluated ULQ for both the residence district and Adana city. Lastly, factors affecting ULQ were determined using exploratory factor analysis (EFA). In addition, MANOVA was used to determine the changes in factors according to socio-demographic characteristics.

Based on the EFA, the results show that the criteria affecting the ULQ are grouped into four factors, including (1) open spaces, (2) cultural, sports and recreation, (3) environmental and (4) transportation. In evaluating these factors, while gender does not affect the perception of ULQ, residence districts show a statistically significant difference in the perception of ULQ. Cultural and transportation factors show statistical differences according to education and age.

This study has a limitation in that it relies solely on the quantitative perceptions of residents with varying demographics, such as age, gender and educational level, to evaluate public spaces and physical environment criteria. While these perspectives are valuable, they may not necessarily reflect the qualitative reality of the urban environment. Therefore, future studies combining quantitative and qualitative data could provide a more comprehensive understanding of the factors affecting ULQ in urban areas.

The implementation of the survey showed the subjective perception of ULQ in Adana city. Urban green spaces, including cultural, sports and recreational areas, should be improved in areas with insufficient facilities that affect the quality of urban life. Additionally, the impact of climate conditions on the quality of life should be taken into account when designing the city to ensure maximum utilization of public spaces. Furthermore, safe cycling transportation networks should be developed.

The novelty of this study lies in its unique approach to investigating the effects of public spaces and physical environmental criteria on ULQ based on combining residents' perceptions, literature review and data analysis. The study provides a valuable perspective often overlooked in urban planning research, especially in developing countries like Turkey. Additionally, the study's findings can inform the development of strategies to enhance ULQ.

This paper presents the Edge Load Management and Optimization through Pseudoflow Prediction (ELMOPP) algorithm, which aims to solve problems detailed in previous algorithms; through machine learning with nested long short-term memory (NLSTM) modules and graph theory, the algorithm attempts to predict the near future using past data and traffic patterns to inform its real-time decisions and better mitigate traffic by predicting future traffic flow based on past flow and using those predictions to both maximize present traffic flow and decrease future traffic congestion.

ELMOPP was tested against the ITLC and OAF traffic management algorithms using a simulation modeled after the one presented in the ITLC paper, a single-intersection simulation.

The collected data supports the conclusion that ELMOPP statistically significantly outperforms both algorithms in throughput rate, a measure of how many vehicles are able to exit inroads every second.

Furthermore, while ITLC and OAF require the use of GPS transponders and GPS, speed sensors and radio, respectively, ELMOPP only uses traffic light camera footage, something that is almost always readily available in contrast to GPS and speed sensors.

This study presents a systematic literature review (SLR) of the interdisciplinary literature on drones in last-mile delivery (LMD) to extrapolate pertinent insights from and into the logistics management field.

Rooting their analytical categories in the LMD literature, the authors performed a deductive, theory refinement SLR on 307 interdisciplinary journal articles published during 2015–2022 to integrate this emergent phenomenon into the field.

The authors derived the potentials, challenges and solutions of drone deliveries in relation to 12 LMD criteria dispersed across four stakeholder groups: senders, receivers, regulators and societies. Relationships between these criteria were also identified.

This review contributes to logistics management by offering a current, nuanced and multifaceted discussion of drones' potential to improve the LMD process together with the challenges and solutions involved.

The authors provide logistics managers with a holistic roadmap to help them make informed decisions about adopting drones in their delivery systems. Regulators and society members also gain insights into the prospects, requirements and repercussions of drone deliveries.

This is one of the first SLRs on drone applications in LMD from a logistics management perspective.

With the rise in demand and adoption of smart city initiatives, it is imperative to plan the railway infrastructure, as it will have a huge positive impact if adequately integrated into the planning process. Given the complexities involved, a whole systems thinking framework provides a useful platform for rail transport planners.

This paper proposes a simple, adoptable framework utilising systems thinking concepts and techniques taking into cognisance the key stakeholders. Milton Keynes in the United Kingdom is the adopted case study.

Selected systems thinking tools and techniques are adopted to develop a framework for mapping stakeholders and attributes when developing sustainable rail transport systems, taking note of their core functionalities and the complex systems wherein they exist.

The desire to build future (smart) cities is to effectively match infrastructural resources with a rapidly growing population, and the railway sector can play a strategic role in building a much more competitive low-carbon-emission transport system, which is a driving force for sustainable development.

The urban rail service has become vital to urban development as railway stations serve as hubs for sustainable mobility to meet local requirements. Moreover, it takes extra effort to input railway development into smart city plans, as it is a herculean task to get governments to focus on it with clarity of purpose in passing legislation.

The developed framework reduces complexities when planning and designing rail transport systems compared to many of the existing reductionist planning approaches. The simplicity of the framework would also make it easily adoptable by a wide range of users.

Although extensive research has been conducted on precast production, irregular component loading constraints have received little attention, resulting in limitations for transportation cost optimization. Traditional irregular component loading methods are based on past performance, which frequently wastes vehicle space. Additionally, real-time road conditions, precast component assembly times, and delivery vehicle waiting times due to equipment constraints at the construction site affect transportation time and overall transportation costs. Therefore, this paper aims to provide an optimization model for Just-In-Time (JIT) delivery of precast components considering 3D loading constraints, real-time road conditions and assembly time.

In order to propose a JIT (just-in-time) delivery optimization model, the effects of the sizes of irregular precast components, the assembly time, and the loading methods are considered in the 3D loading constraint model. In addition, for JIT delivery, incorporating real-time road conditions in the transportation process is essential to mitigate delays in the delivery of precast components. The 3D precast component loading problem is solved by using a hybrid genetic algorithm which mixes the genetic algorithm and the simulated annealing algorithm.

A real case study was used to validate the JIT delivery optimization model. The results indicated this study contributes to the optimization of strategies for loading irregular precast components and the reduction of transportation costs by 5.38%.

This study establishes a JIT delivery optimization model with the aim of reducing transportation costs by considering 3D loading constraints, real-time road conditions and assembly time. The irregular precast component is simplified into 3D bounding box and loaded with three-space division heuristic packing algorithm. In addition, the hybrid algorithm mixing the genetic algorithm and the simulated annealing algorithm is to solve the 3D container loading problem, which provides both global search capability and the ability to perform local searching. The JIT delivery optimization model can provide decision-makers with a more comprehensive and economical strategy for loading and transporting irregular precast components.

This study aims to draw a general framework for recreating water-related urban places. It discusses design criteria and processes that will strengthen people's and the city's relationship with the waterfront. It also explores the functional requirements of a participatory process to incorporate social and functional relations into place making.

The study is based on a comprehensive case study of the Kabataş project process. Data collection methods include archive searches, questionnaires, interviews and analysis. The study analyses the architectural decisions, the role and perspectives of the key actors and the current dynamics that shape the process. It points out shortcomings and needs of communication and collaboration with different stakeholders, especially with the users.

The results show that political and power dynamics play an important role in shaping the process. Non-transparent processes increase the gap between the aspects of community and decision makers in current practices. Establishing holistic, waterfront-specific and collaborative approaches is a necessity. The results also show that the success of participation depends on procedural dynamics such as scope, method, timing, representativeness of the community, institutionalisation level, transparency and deliberation.

Despite the intense interest in waterfront regeneration, few studies have focused on the potential of the participatory process. The study examines the intersections of waterfront design decisions and collaborative participation at various scales and emphasises the importance of local actors in the social production of space.

This study aims to investigate the relationships between the perceived neighborhood walkable environment (PNWE), neighborhood interaction (NI) and residents’ mental health, with a focus on examining differences among residents of different age groups.

Using an electronic survey questionnaire, data on PNWE, NI and mental health were collected from 1,159 residents across 205 communities in Shanghai, China. Our study utilized a structural equation modeling (SEM), employing the maximum likelihood estimation method. The structural equation model was fitted using the MPLUS software.

The mental health of young and middle-aged adults is generally poor, and they are at higher risk of depression than children and older adults. The effects of PNWE and NI on the mental health of residents varied among different age groups. As residents get older, their mental health is more affected by the PNWE. In addition, the influence of the PNWE on children and older adults’ mental health is direct and not mediated by NI. For young and middle-aged adults, the influence of the PNWE on their mental health needs to be mediated by NI.

This study marks the first examination of the relationship between PNWE, NI and mental health among different age groups of residents in China. The findings of this research can assist policymakers in gaining a deeper understanding of the underlying mechanisms by which PNWE affects mental health. Furthermore, it can contribute to the development of more targeted walkable environment designs aimed at enhancing mental health among various age groups.

This study aimed to design a user-participatory methodology to investigate the post-occupancy sustainability of reused historical buildings and to apply it to a case study.

This study was designed in four stages. In the first stage, the sustainability parameters and sub-parameters were determined in the reused historical buildings based on the literature. The second stage included a field study in which the current situation of the study area was analysed, and the users were reached using the survey technique. In the third stage, the data obtained from the user participation were analysed with importance performance analysis (IPA) and an IPA matrix was created. The fourth stage included an evaluation of the results of the analysis and the development of recommendations.

IPA is a supportive method for ensuring the sustainable use of historic buildings. According to the data obtained from the IPA, it was seen that the functional sustainability of the building was achieved to a great extent. At the same time, there were deficiencies in technical and environmental sustainability. In terms of aesthetic sustainability, it was observed that the importance and performance values given by the users were generally consistent with each other.

The originality of this study is that the performance of the reused historical buildings in the process of use was monitored with appropriate parameters, and a user-participated method was proposed that allows improvement suggestions to be developed in line with the results obtained.