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Automatic modulation recognition (AMR) is a challenging problem in intelligent communication systems and has wide application prospects. At present, although many AMR methods based on deep learning have been proposed, the methods proposed by these works cannot be directly applied to the actual wireless communication scenario, because there are usually two kinds of dilemmas when recognizing the real modulated signal, namely, long sequence and noise. This paper aims to effectively process in-phase quadrature (IQ) sequences of very long signals interfered by noise.

This paper proposes a general model for a modulation classifier based on a two-layer nested structure of long short-term memory (LSTM) networks, called a two-layer nested structure (TLN)-LSTM, which exploits the time sensitivity of LSTM and the ability of the nested network structure to extract more features, and can achieve effective processing of ultra-long signal IQ sequences collected from real wireless communication scenarios that are interfered by noise.

Experimental results show that our proposed model has higher recognition accuracy for five types of modulation signals, including amplitude modulation, frequency modulation, gaussian minimum shift keying, quadrature phase shift keying and differential quadrature phase shift keying, collected from real wireless communication scenarios. The overall classification accuracy of the proposed model for these signals can reach 73.11%, compared with 40.84% for the baseline model. Moreover, this model can also achieve high classification performance for analog signals with the same modulation method in the public data set HKDD_AMC36.

At present, although many AMR methods based on deep learning have been proposed, these works are based on the model’s classification results of various modulated signals in the AMR public data set to evaluate the signal recognition performance of the proposed method rather than collecting real modulated signals for identification in actual wireless communication scenarios. The methods proposed in these works cannot be directly applied to actual wireless communication scenarios. Therefore, this paper proposes a new AMR method, dedicated to the effective processing of the collected ultra-long signal IQ sequences that are interfered by noise.

Compared with traditional methods relying on manual teaching or system modeling, data-driven learning methods, such as deep reinforcement learning and imitation learning, show more promising potential to cope with the challenges brought by increasingly complex tasks and environments, which have become the hot research topic in the field of robot skill learning. However, the contradiction between the difficulty of collecting robot–environment interaction data and the low data efficiency causes all these methods to face a serious data dilemma, which has become one of the key issues restricting their development. Therefore, this paper aims to comprehensively sort out and analyze the cause and solutions for the data dilemma in robot skill learning.

First, this review analyzes the causes of the data dilemma based on the classification and comparison of data-driven methods for robot skill learning; Then, the existing methods used to solve the data dilemma are introduced in detail. Finally, this review discusses the remaining open challenges and promising research topics for solving the data dilemma in the future.

This review shows that simulation–reality combination, state representation learning and knowledge sharing are crucial for overcoming the data dilemma of robot skill learning.

To the best of the authors’ knowledge, there are no surveys that systematically and comprehensively sort out and analyze the data dilemma in robot skill learning in the existing literature. It is hoped that this review can be helpful to better address the data dilemma in robot skill learning in the future.

The present work highlights the outstanding properties of Cannabis sativa that can be harnessed for various utilitarian functions and its climate friendly properties.

In this paper, the authors reviewed current research on all possible utilities from household work to manufacturing of various products that are environmentally sustainable. The authors have presented some of their research on this materials and also exploration of hemp as an archaeological material based on the findings from wall paintings of Ellora caves.

There are references of hemp use in mixing with earthen/lime plaster of western Indian monuments. Around 1,500 years of Ellora’s earthen plaster, despite harsh climatic conditions, survived due to the presence of hemp in the plaster that adds durability, fibrosity and its capacity to ward off insects and control humidity. Furthermore, the outstanding quality of Cannabis as carbon sequestrant was harnessed by Indians of ancient times in Ellora mural paintings.

This work discusses some relevant literature on the potential use of hempcrete aligned with Agenda 2030 of sustainable development goals.

There are several research going on in producing sustainable materials using hemp that have the least environmental impact and can provide eco-friendly solutions.

The authors impress upon the readers about multifarious utility of the hemp and advices for exploration of this material to address many environmental issues.

This paper presents both review of the existing papers and some components coming directly from their laboratory investigations.

Previous students' housing studies have neglected the need to study all-inclusive student housing and quality of services delivery among students with disability. This study explores the expectations in students' housing among university students living with disabilities (SWDs) in Ghana.

The study adopted a mixed-methods approach, involving 423 SWD selected from five public and three private universities across Ghana. Grounded on the Gap Model, the study employed exploratory factor analysis to extract factors of service quality delivery and universal building design for SWD living in off-campus students' housing.

The study uncovered that, expectations of SWD regarding building design specifications hinges more on inbuilt universal design than external building environment designs. SWD are more interested in safety, health, managerial assurances and security. In all, five factors provided a huge gap in services quality delivered by off-campus students' housing.

The Gap Model technique offers a framework that provides an insight for students' housing investors, managers, researchers and local authorities that provides an insight on the needs of SWD in student housing, thus making it possible to attain satisfactions amongst SWD.

Unlike health-related studies that deals with expectations of all-inclusive buildings for persons with disability in hospitals, this study uniquely uncovered the expectations of services delivery and building design support to SWD in the Ghanaian context.

This paper aims to provide an exemplary application of an indicative post-occupancy evaluation (POE) on an organizational multistorey residential apartment building.

This research comprises of mixed qualitative and quantitative approaches. The methodology commences with a review of the recent literature, identification of performance elements, conduct of walk-through, distribution and collection of users' surveys and the development of short and long-term recommendations, where an adequate sample of users were approached for conducting a focus group interview session.

The research identifies 74 performance elements that were clustered into technical, namely (thermal, acoustic and visual comforts, indoor air quality and safety and security), functional, namely (design adequacy, finishing, furnishing, fittings and equipment and building surroundings) dimensions and behavioral, namely (apartment building attributes and managerial and logistical support). The questionnaire survey aimed to solicit users' opinions upon the occupied case study residential facility.

The research identifies areas of occupants' satisfaction and dissatisfaction in a typical multistorey residential building, as a part of a community housings for a mega organization, located in Saudi Arabia. The identification of these areas serves as a lesson learned for future developments, design considerations and implications. Hence, improving the well-being and comfort of its employees.

Near-fault pulse-like ground motions have distinct and very severe effects on reinforced concrete (RC) structures. However, there is a paucity of recorded data from Near-Fault Ground Motions (NFGMs), and thus forecasting the dynamic seismic response of structures, using conventional techniques, under such intense ground motions has remained a challenge.

The present study utilizes a 2D finite element model of an RC structure subjected to near-fault pulse-like ground motions with a focus on the storey drift ratio (SDR) as the key demand parameter. Five machine learning classifiers (MLCs), namely decision tree, k-nearest neighbor, random forest, support vector machine and Naïve Bayes classifier , were evaluated to classify the damage states of the RC structure.

The results such as confusion matrix, accuracy and mean square error indicate that the Naïve Bayes classifier model outperforms other MLCs with 80.0% accuracy. Furthermore, three MLC models with accuracy greater than 75% were trained using a voting classifier to enhance the performance score of the models. Finally, a sensitivity analysis was performed to evaluate the model's resilience and dependability.

The objective of the current study is to predict the nonlinear storey drift demand for low-rise RC structures using machine learning techniques, instead of labor-intensive nonlinear dynamic analysis.

The proposed use of unlatched, reverse swing flappy doors is becoming widespread in the design of residential common corridor smoke control systems. This article explores the conceptual arguments for and against the use of these systems.

This article relies on industry experience, with reference to relevant building design practices, standards and research literature, to categorise arguments. These are collated into four common areas of concern relating to compartmentation, reliability, depressurisation and modelling practices. A final comparison is made between different common corridor smoke control system types for these four areas.

The article highlights several concerns around the use of flappy door systems, including the enforced breaches in stair compartmentation, uncertainties around system reliability, the reliance on door closers as a single point of failure, the impact of day-to-day building use on the system performance and the false confidence that modelling assessments can provide in demonstrating adequacy. The article concludes in suggesting that alternative smoke control options be considered in place of flappy door systems.

Discussion on the use of flappy door smoke control systems has been ongoing within the fire engineering community for several years, but there is limited public literature available on the topic. By collating the common arguments relating to these systems into a single article, a better understanding of their benefits and pitfalls has been provided for consideration by building design and construction professionals.

Many economic, political and socio-cultural events in the 2020s have been strong headwinds for architecture, engineering and construction (AEC). Nevertheless, technological advancements (e.g. artificial intelligence (AI), big data and robotics) provide promising avenues for the development of AEC. This study aims to map the state of the literature on automation in AEC and thereby be of value not only to those researching automation and its composition of a variety of distinct technological and system classes within AEC, but also to practitioners and policymakers in shaping the future of AEC.

This review adopts scientometric methods, which have been effective in the research of large intra and interdisciplinary domains in the past decades. The full dataset consists of 1,871 articles on automation in AEC.

This overarching scientometric review offers three interdisciplinary streams of research: technological frontiers, project monitoring and applied research in AEC. To support the scientometric analysis, the authors offer a critical integrative review of the literature to proffer a multilevel, multistage framework of automation in AEC, which demonstrates an abundance of technological paradigm discussions and the inherent need for a holistic managerial approach to automation in AEC.

The authors underline employee well-being, business sustainability and social growth outcomes of automation and provide several managerial implications, such as the strategic management approach, ethical management view and human resource management perspective. In doing so, the authors seek to respond to the Sustainable Development Goals proposed by the United Nations as this becomes more prevalent for the industry and all levels of society in general.

Ergonomics usually reciprocate the study about people fitness toward working environment. In addition, financial distress refers a condition of organizations incompetency in generating sufficient revenues or incomes, which thereby refrain them to pay their financial obligations. This study aims to evaluate two independent organizational fields named as ergonomics in first phase and financial distress in manufacturing organization behavior in the second phase. The study presented a resiliency framework for operations and strategic management in the third phase based on various facts received from the distress organizations.

A questionnaire survey based on plant-visit is presented. The study embedded two segments to explicate its novelty. In the first segment, the plant-visit case study is presented and in the second segment, an exploratory data related to financial distress is presented. The study tried to communicate observations related to multiple decision-making fields in single umbrella, where multiple concepts like ergonomics and financial distress of organizations as well as employees are presented. DEMATEL-ANP integrated approach is used to represent the critical financial distress dimensions of employees and their ranking.

The study provided insights toward connecting two independent fields named as ergonomics and financial distress in single umbrella. The study can benefit practitioners in designing policies and procedures in their planning model to effectively achieve organizational goals. The study presented 14 financial distress drivers of employees and advocated the aggregation of ergonomics and financial distress toward developing a holistic framework for attaining organization goals for sustainability.

The study presented a comprehensive understanding about multiple organization decision-making fields toward developing a holistic approach from different aspects for attaining organizational sustainability. The study can be fruitful in stimulating cross-pollination of ideas between researchers and provides a good understandability of ergonomics and financial distress in single roof.

The objective of this research is to evaluate the influence of mineral additions on the mechanical performances of polymer concrete. This study aims to propose a novel approach formulation of polymer concrete based on reduction in the quantity of the binder and disposal of large quantities of industrial by-products and household waste such as the marble, the brick and silica fume whose valuation in polymer concrete could be an interesting ecological and economical alternative. The incorporation of a rate of 10% brick powder affects the distribution of pores inside polymer concrete, that is, the pore diameters become thinner and decrease and the porosity becomes evenly distributed. The recycled mineral brick powder addition in polymer concrete mix improved the mechanical properties.

This polymer concrete was prepared by using polyester resin and two different types of sand, following a new formulation based on an empirical method. Furthermore, the optimal binder percentage was of 20% resin and a mixture of 52% dune sand and 48% quarry sand according to the Abrams method. To achieve our objective, five rates (from 2% to 10%) of brick powder, marble powder and silica fume were examined. Afterwards, its mechanical characteristics were evaluated via a three-point flexural with compressive resistance. The findings indicated that the addition of brick, marble and silica fume to polymer concrete increases the flexural strength with 21.84%, 12.76% and 9.07%, respectively.

Concerning the compressive strength, the best resistance is that of polymer concretes based on brick powder, and this economic formulation of polymer concrete serves the optimal cost/resistance ratio criteria. It allows an improvement in the mechanical resistance of concrete are obtained by adding brick powder that exceed that of the reference concrete.

In the past few decades, there has been several contribution concerning the subject of the reduction of the binder quantity in polymer concretes and adding the industrial and household wastes. However, previous studies revolving around the same area disregarded the effect of the brick powder, which appears scientifically of great importance for enriching the literature.