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The paper aims to examine the concept of architectural design communication (ADC) for updating design studio dynamics in architectural education during the Covid-19 pandemic. Within this perspective, the changing and transforming contents of architectural education, the thinking, representation and production mediums are examined through the determined components of ADC. There are five components in the study, which are (1) Effective Language Use, (2) Effective use of Handcrafts, (3) Effective Technical Drawing Knowledge, (4) Effective Architectural Software Knowledge and (5) Outputs.

The research method is based on qualitative and quantitative methods; a survey study is applied and the comparative results are evaluated with the path analysis method. The students in the Department of Architecture of two universities have been selected as the target audience. Case study 1 survey is applied to Altinbas University (AU) and Case study 2 survey is applied to Universitat Politecnica de Valencia (UPV) students during the COVID-19 pandemic; ‘19-‘20 spring term, online education.

As a result, two-path analysis diagrams are produced for two universities, and a comparative analysis is presented to reveal the relationships of the selected ADC components.

This paper fulfills an identified need to study how ADC can be developed in online education platforms.

The impact of the coronavirus disease 2019 (COVID-19) pandemic on architectural education (AE) was investigated, and a framework was proposed to reduce the impacts' negative consequences.

Systematic literature review, bibliometric and content analyses were combined to gain an in-depth understanding of the effects of the pandemic on AE and projections for its future. Relevant documents were extracted from the Web of Science (WoS) database. Bibliometric connections in the context of AE and COVID-19 pandemic were explored using text-mining and content analysis was performed.

The challenges, development tendencies and collaboration networks in AE during the pandemic were quantitatively and qualitatively analyzed. The most influential articles, journals, authors and countries/regions were highlighted using a bibliometric analysis. The analysis of keyword tendencies and clusters indicates that new concepts have emerged in AE research during the pandemic involving online, in-person and hybrid education. Using content analysis of 57 subtopics, 39 (18) were categorized as having negative (positive) effects. A comprehensive mitigation framework was designed to reduce the impact of the pandemic on AE.

The study findings can enable practitioners to construct effective solutions to COVID-19- and other disaster-related problems regarding AE. The implications, obstacles and mitigation framework presented can help identify gaps in the literature and guide further research.

This paper presents the first bibliometric and content analysis of AE and COVID-19 pandemic-related studies published from January 2020 to June 2022 to highlight several research directions and academic development within the field.

The paper aims to understand and assess architecture students' experiences of online teaching during the initial lockdown caused by the coronavirus disease-2019 (COVID-19) pandemic between March–June 2020. The exploratory study was conducted across two architectural engineering departments of two separate campuses of the same not-for-profit, non-governmental higher education institution in Cairo, Egypt, focusing on two course streams within their architectural curriculum; design-studio-based courses (DC) and technology courses (TC).

A mixed-methods approach was used, where a questionnaire-based survey was developed to gather qualitative and quantitative data based on perceptions of a sample of 245 students. The survey quantitatively queried five dimensions related to students' learning experiences and qualitatively sought to evaluate both the positive experiences and challenges the students experienced.

Findings outline that students' experiences were neutral but veered toward the positive end of the scale. Three factors appear to have affected students' learning experiences; students' reliance on educational technologies, the stage of architectural education students were enrolled in when they went into lockdown, and finally, quality and timing of feedback received. While challenges were faced during transition to the digital realm, these may have compelled students to take ownership of the students' own knowledge construction.

Results provide a nuanced understanding of how students dealt with this critical transformation in architectural pedagogy at a unique moment in history, highlighting merits that could have an everlasting impact on design education during and after times of pandemic.

As technology advances the demand for an analog-to digital converter has increased, as every application demands a converter as per its parameters. Currently, work is done on improvement of data converters at three levels of design – architectural, circuit and physical level. This paper aims to review the work done in the field of analog-to-digital converters (ADCs) at architectural and circuit level and discusses the achievements in this field. Furthermore, a new architecture is proposed, which works at higher resolution and provides optimum design parameters at low power consumption.

A hybrid architecture combining the features of synthetic approximation register and sigma-delta ADC is presented. The validity of the proposed design at architectural level is verified using MATLAB SIMULINK simulations.

The design simulation was tested for a sinusoidal wave of 1 V at the test frequency of 60 Hz. The design consumes least power, and is found to yield an error of the order less than 10–3 V, thus providing highly accurate digital output.

The design is applicable in many applications including biomedical systems, Internet-of-Things and earthquake engineering. This architecture can be further optimized to obtain better performance parameters.

Modern, complex control systems for specific application domains often display common system design architectures with similar subsystem functionality and interactions. The similarities between these subsystems in most spacecraft can be exploited to create a model‐driven system development environment and then transformed into software or hardware either manually or automatically. Modifications to software and hardware during operations can be similarly made in the same controlled way. The approach is illustrated using a spacecraft attitude determination and control subsystem, but applies equally to other types of aerospace systems.

A decade and a half after the debut of pervasive computing, a large number of prototypes, applications, and interaction interfaces have emerged. However, there is a lack of consensus about the best approaches to create such systems or how to evaluate them. To address these issues, this paper aims to develop a performance evaluation framework for pervasive computing systems.

Based on the authors' experience in the Gator Tech Smart House – an assistive environment for the elderly, they established a reference scenario that was used to guide the analysis of the large number of systems they studied. An extensive survey of the literature was conducted, and through a thorough analysis, the authors derived and arrived at a broad taxonomy that could form a basic framework for evaluating existing and future pervasive computing systems.

A taxonomy of pervasive systems is instrumental to their successful evaluation and assessment. The process of creating such taxonomy is cumbersome, and as pervasive systems evolve with new technological advances, such taxonomy is bound to change by way of refinement or extension. This paper found that a taxonomy for something so broad as pervasive systems is very complex. It overcomes the complexity by focusing the classifications on key aspects of pervasive systems, decided purely empirically and based on the authors own experience in a real‐life, large‐scale pervasive system project.

There are currently no methods or frameworks for comparing, classifying, or evaluating pervasive systems. The paper establishes a taxonomy – a first step toward a larger evaluation methodology. It also provides a wealth of information, derived from a survey of a broad collection of pervasive systems.

The purpose of this paper is to present a compressed sensing (CS)-based sampling system for ultra-wide-band (UWB) signal. By exploiting the sparsity of signal, this new sampling system can sub-Nyquist sample a multiband UWB signal, whose unknown frequency support occupies only a small portion of a wide spectrum.

A random Rademacher sequence is used to sense the signal in the frequency domain, and a matrix constructed by Hadamard basis is used to compress the signal. The probability of reconstruction is proved mathematically, and the reconstruction matrix is developed in the frequency domain.

Simulation results indicate that, with an ultra-low sampling rate, the proposed system can capture and reconstruct sparse multiband UWB signals with high probability. For sparse multiband UWB signals, the proposed system has potential to break through the Shannon theorem.

Different from the traditional sub-Nyquist techniques, the proposed sampling system not only breaks through the limitation of Shannon theorem but also avoids the barrier of input bandwidth of analog-to-digital converters (ADCs).

Wireless sensor networks (WSNs) will profoundly influence the ubiquitous computing landscape. Their utility derives not from the computational capabilities of any single sensor node, but from the emergent capabilities of many communicating sensor nodes. Consequently, the details of communication within and across single hop neighborhoods is a fundamental component of most WSN applications. But these details are often complex, and popular embedded languages for WSNs provide only low‐level communication primitives. We propose that the absence of suitable communication abstractions contributes to the difficulty of developing large‐scale WSN applications. To address this issue, we present the design and implementation of a Remote Procedure Call (RPC) abstraction for nesC and TinyOS, the emerging standard for developing WSN applications. We present the key language extensions, operating system services, and automation tools that enable the proposed abstraction. We illustrate these contributions in the context of a representative case study, and analyze the overhead introduced when using our approach. We use these results to draw conclusions regarding the suitably of our work to resource‐constrained sensor nodes.

The purpose of this paper is to describe an approach towards code validation of RISC microcontrollers, which helps to automate software debugging. A static machine code analysis which checks the appropriateness of instructions in a sequence to identify any logical mistakes and also to identify redundant codes appearing in a program for the target processor is presented.

Validation is done with the help of rules of inferences formulated for the target processor. The rules govern the occurrence of illegitimate/out of place instructions and code sequences for executing the computational and integrated peripheral functions. The stipulated rules are encoded in propositional logic formulae and their compliance is tested in all possible execution paths of the application programs. An incorrect sequence of machine code pattern is identified using slicing techniques on the control flow graph generated from machine code.

The results explain that the technique is independent of compiler/assembler and contributes to early detection of software bugs that are otherwise hard to detect. Program states are identified mainly with machine code pattern, which drastically reduces the state space creation contributing to an improved state‐of‐the‐art model checking.

Though the technique described is general, the implementation is highly architecture oriented, and hence the feasibility study is conducted only on PIC16F87X microcontrollers.

This validation tool can be integrated to the system development environment resulting in improved software quality and reduced debugging time.

It is a novel and original approach at machine code level applicable to a wide range of processors once appropriate rules are available.