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The purpose of this paper is to present an improved model based on center potential instead of surface potential which is physically more relevant and accurate. Also, additional analytic insights have been provided to make the model independent and robust so that it can be extended to a full range compact model.

The design methodology used is center potential based analytical modeling using Psuedo-2D Poisson equation, with ingeniously developed boundary conditions, which help achieve reasonably accurate results. Also, the depletion width calculation has been suitably remodeled, to account for proper physical insights and accuracy.

The proposed model has considerable accuracy and is able to correctly predict most of the physical phenomena occurring inside the broken gate Tunnel FET structure. Also, a good match has been observed between the modeled data and the simulation results. I_on/I_ambipolar ratio of 10^(−8) has been achieved which is quintessential for low power SOCs.

The modeling approach used is different from the previously used techniques and uses indigenous boundary conditions. Also, the current model developed has been significantly altered, using very simple but intuitive technique instead of complex mathematical approach.

This paper aims to examine accessibility in the built environment and tries to determine the physical and attitudinal barriers affecting Persons with Visual Disabilities' (PWVDs) experience on the University of Jordan (UJ) campus.

This is a descriptive mixed-methods study, based on the following: data collection regarding PWVDs' services at UJ; semi-structured interviews with PWVDs and with some employees at UJ; observations, photographs and direct measurements during campus tours; accompanying one student with poor eyesight when navigating through UJ campus; then, analyzing data in light of the national code's accessibility checklist.

UJ campus suffers from many shortcomings regarding accessibility; these include an insufficient pedestrian environment, limited tactile paths, low illuminance levels in lecture halls and other inadequate services. Besides, there are many infringements on PWVDs' paths, due to either new expansions or unconscious behavior. Moreover, interpersonal barriers prevent PWVDs from using assistive equipment and accommodation. The study concludes that preserving pedestrians' rights, monitoring new expansions, renovating the UJ campus in accordance with national codes and international standards, improving PWVDs services and awareness-raising programs are needed to ensure accessibility for PWVDs.

New legislation has been recently passed regarding accessibility in Jordan, and – on the UJ campus – the first phase of tactile paving has been installed. This paper is believed to be the first of its kind to evaluate PWVDs' services following the new changes. The study's methodology might also be deemed useful to stakeholders when enabling the built environment.

Accurate prediction of the structural condition of urban critical infrastructure is crucial for predictive maintenance. However, the existing prediction methods lack precision due to limitations in utilizing heterogeneous sensing data and domain knowledge as well as insufficient generalizability resulting from limited data samples. This paper integrates implicit and qualitative expert knowledge into quantifiable values in tunnel condition assessment and proposes a tunnel structure prediction algorithm that augments a state-of-the-art attention-based long short-term memory (LSTM) model with expert rating knowledge to achieve robust prediction results to reasonably allocate maintenance resources.

Through formalizing domain experts' knowledge into quantitative tunnel condition index (TCI) with analytic hierarchy process (AHP), a fusion approach using sequence smoothing and sliding time window techniques is applied to the TCI and time-series sensing data. By incorporating both sensing data and expert ratings, an attention-based LSTM model is developed to improve prediction accuracy and reduce the uncertainty of structural influencing factors.

The empirical experiment in Dalian Road Tunnel in Shanghai, China showcases the effectiveness of the proposed method, which can comprehensively evaluate the tunnel structure condition and significantly improve prediction performance.

This study proposes a novel structure condition prediction algorithm that augments a state-of-the-art attention-based LSTM model with expert rating knowledge for robust prediction of structure condition of complex projects.

The purpose of this paper is to design novel tunnel field effect transistor (TFET) using graphene nanoribbons (GNRs).

To design the proposed TFET, the bilayer GNRs (BLGNRs) have been used as the channel material. The BLGNR-TFET is designed in QuantumATK, depending on 2-D Poisson’s equation and non-equilibrium Green’s function (NEGF) formalism.

The performance of the proposed BLGNR-TFET is investigated in terms of current and voltage (I-V) characteristics and transconductance. Moreover, the proposed device performance is compared with the monolayer GNR-TFET (MLGNR-TFET). From the simulation results, it is investigated that the BLGNR-TFET shows high current and gain over the MLGNR-TFET.

This paper presents a new technique to design GNR-based TFET for future low power very large-scale integration (VLSI) devices.

Analysis of architectural space is commonly conducted by examining architectural drawings that project spatial information by means of walls and partitions. To capture the lived experience of space, which is richer than what we can see from drawings, a new method is proposed to quantify the cognitive dimension of space and re-present it as an audible format.

Using an urban vernacular house in Seoul as a case study, this research takes a syntactic approach to quantify one's changing perception through their movement from the main gate to the most private reception room. Based on Luigi Moretti's theory of hollow space, a new method is proposed to measure the level of spatial pressure exerted on a navigating body. The numerical data of spatial pressure are then converted to a sound using musical techniques of the chromatic scale and chorale textures.

Building on Moretti's abstract concept, it has been shown that a rule-based quantification of users' spatial perception is possible. In addition, unlike conventional approaches of treating architecture as a static entity, this study showed an alternative approach to represent it as a sequence of sensorial experience that can be readily converted to a sound of music.

This research developed a quantification method to measure the perception of pressure inside buildings by revisiting Luigi Moretti's theory proposed in 1952. It has been also demonstrated that the visual stimuli in space can be translated into an audible experience. This new method is applicable to a wide range of buildings including important historic architecture.

This study aims to replace current multi-layer and coplanar wire crossing methods in QCA technology to avoid fabrication difficulties caused by them.

Quantum-dot cellular automata (QCA) is one of the newly emerging nanoelectronics technology tools that is proposed as a good replacement for complementary metal oxide semiconductor (CMOS) technology. This technology has many challenges, among them being component interconnection and signal routing. This paper will propose a new wire crossing method to enhance layout use in a single layer. The presented method depends on the central cell clock phase to enable two signals to cross over without interference. QCADesigner software is used to simulate a full adder circuit designed with the proposed wire crossing method to be used as a benchmark for further analysis of the presented wire crossing approach. QCAPro software is used for power dissipation analysis of the proposed adder.

A new cost function is presented in this paper to draw attention to the fabrication difficulties of the technology when designing QCA circuits. This function is applied to the selected benchmark circuit, and the results show good performance of the proposed method compared to others. The improvement is around 59, 33 and 75% compared to the best reported multi-layer wire crossing, coplanar wire crossing and logical crossing, respectively. The power dissipation analysis shows that the proposed method does not cause any extra power consumption in the circuit.

In this paper, a new approach is developed to bypass the wire crossing problem in the QCA technique.

The purpose of this paper is to design multiplexers (MUXs) based on ternary half subtractor and full subtractor using carbon nanotube field-effect transistors.

Conventionally, the binary logic functions are developed by using the binary decision diagram (BDD) systems. Each node in BDD is replaced by 2:1 MUX to implement the digital circuits. Similarly, in the ternary decision diagram, each node has to be replaced by 3:1 MUX. In this paper, ternary transformed BDD is used to design the ternary subtractors using 2:1 MUXs.

The performance of the proposed ternary half subtractor and full subtractor using the 2:1 MUX are compared with the 3:1 MUX-based ternary circuits. It has been observed that the delay, power and power delay product values are reduced, respectively, by 67.6%, 84.3%, 94.9% for half subtractor and 67.7%, 70.1%, 90.3% for full subtractor. From the Monte Carlo simulations, it is observed that the propagation delay and power dissipation of the proposed subtractors are increased by increasing the channel length due to process variations. The stability test is also performed and observed that the stability increases as the channel length and diameter are increased.

The proposed half subtractor and full subtractor show better performance over the existing subtractors.

Safety management plays an important part in coal mine construction. Due to complex data, the implementation of the construction safety knowledge scattered in standards poses a challenge. This paper aims to develop a knowledge extraction model to automatically and efficiently extract domain knowledge from unstructured texts.

Bidirectional encoder representations from transformers (BERT)-bidirectional long short-term memory (BiLSTM)-conditional random field (CRF) method based on a pre-training language model was applied to carry out knowledge entity recognition in the field of coal mine construction safety in this paper. Firstly, 80 safety standards for coal mine construction were collected, sorted out and marked as a descriptive corpus. Then, the BERT pre-training language model was used to obtain dynamic word vectors. Finally, the BiLSTM-CRF model concluded the entity’s optimal tag sequence.

Accordingly, 11,933 entities and 2,051 relationships in the standard specifications texts of this paper were identified and a language model suitable for coal mine construction safety management was proposed. The experiments showed that F1 values were all above 60% in nine types of entities such as security management. F1 value of this model was more than 60% for entity extraction. The model identified and extracted entities more accurately than conventional methods.

This work completed the domain knowledge query and built a Q&A platform via entities and relationships identified by the standard specifications suitable for coal mines. This paper proposed a systematic framework for texts in coal mine construction safety to improve efficiency and accuracy of domain-specific entity extraction. In addition, the pretraining language model was also introduced into the coal mine construction safety to realize dynamic entity recognition, which provides technical support and theoretical reference for the optimization of safety management platforms.

This study aims to assess each of the seven segments of the Akbarieh Garden as the World Heritage Cultural Landscape. First, we wanted to identify the macro elements that dominated one's perception within each area. Then, we wanted to identify the micro elements that support the vista in its entirety.

To acquire data, we used a Participant Observer (PO) method as part of a Continuous/Stop-Motion (CSM) procedure. The identification of macro elements came from retrospective recollections derived from the continuous walk method—the stop-walk method allowed for the identification of micro elements. The data gained from this method is then used to understand how one interprets and responds to large—multi-segmented sites such as the Akbarieh Garden.

The results of this study show the Continuous/Stop-Motion method yielded predictable results with macro elements and elements of interest being easily recalled. However, the use of photographing for the stop-walk method revealed a similar focus on the macro element. We had hypothesized that the micro elements would be the elements of fascination and discovered when the person remained in the area to photograph scenes of interest. However, the PO photographed the macro elements. It wasn't until the post photo analysis that the PO identified some of the micro elements would be the elements of fascination and discovered when the person remained in the area to photograph scenes of interest. However, the PO photographed the macro elements. It wasn't until the post photo analysis that the PO identified some of the micro elements. The post photo discoveries suggest that real-time experience of micro elements is undervalued.

There is no general discussion on this topic yet amongst professionals. The initiative of the Participant Observer (PO) method as a tool for perception the historic gardens and landscapes identified that gap and its related necessity to provide guidance. As is true for exploratory studies, these results provide a foundation for further study. The use of the Continuous/Stop-Motion method was ideal for this study.

The theoretical findings serve as a foundation for further research into understanding sulfide-based solid-state electrolytes, ultimately advancing the progress of all-solid-state batteries.

The electronic properties of Li₇P₃S₁₁ are thoroughly explored through first-principles calculations.

This investigation encompasses the intricate atom-dominated valence and conduction bands, spatial charge density distribution and the breakdown of atom and orbital contributions to van Hove singularities. Additionally, the compound’s wide and discrete energy spectra reflect the substantial variations in bond lengths and its highly anisotropic geometric structure. The complex and nonuniform chemical environment indicates the presence of intricate hopping integrals.

This study provides valuable insights into the critical multiorbital hybridizations occurring in the Li-S and P-S chemical bonds. To validate the theoretical predictions, experimental techniques can be employed. By combining theoretical predictions with experimental data, a comprehensive understanding of the geometric and electronic characteristics of Li₇P₃S₁₁ can be achieved.