Despite the growing emphasis on intelligent buildings as a cornerstone of sustainable urban development, significant energy inefficiencies persist due to suboptimal design, material choices, and user behavior. The applicability of integrated Building Information Modeling (BIM) and solarpowered environmental monitoring systems for energy optimization in low-carbon smart buildings remains underexplored. Can BIM-driven design improvements, combined with photovoltaic systems, achieve substantial energy savings while enabling self-powered environmental monitoring? This study conducts a case analysis on a retrofitted primary school building in Guangdong, China, utilizing BIM-based energy simulations, material optimization, and solar technology integration. The outcomes reveal that the proposed approach reduced annual energy consumption by 40.68%, with lighting energy use decreasing by 36.59%. A rooftop photovoltaic system demonstrated a payback period of 7.46 years while powering environmental sensors autonomously. Hardware system integrates sensors and an ARDUINO-based controller to detect environmental factors like rainfall, temperature, and air quality. It is powered by a 6W solar panel and a 2200 mAh/7.4 V lithium battery to ensure stable operation. This study underscores the potential of BIM and solar energy integration to transform traditional buildings into energy-efficient, self-sustaining smart structures. Further research can expand the scalability of these methods across diverse climates and building typologies.
Designing Zero-Emissions Buildings (ZEBs) involves balancing numerous complex objectives that traditional methods struggle to address. Fenestration, encompassing façade openings and shading systems, plays a critical role in ZEB performance due to its high thermal transmittance and solar radiation admission. This paper presents a novel simulation-based optimization method for fenestration designed for practical application. It uses a hybrid metaheuristic algorithm and relies on rules and an updatable catalog, to fully automate the design process, create a highly diverse search space, minimize biases, and generate detailed solutions ready for architectural prescription. Nineteen fenestration variables, over which architects have design flexibility, were optimized to reduce heating, cooling demand, and thermal discomfort in residential buildings. The method was tested across three Spanish climate zones. Results demonstrate that the considered optimization algorithm significantly outperforms the baseline Genetic Algorithm in both quality and robustness, with these differences proven to be statistically significant. Furthermore, the findings offer valuable insights for ZEB design, highlighting challenges in reducing cooling demand in warm climates, and showcasing the superior efficiency of automated movable shading systems compared to fixed solutions.
Elias Perdomo, Alexander Kropotov, Francelly Cano
et al.
Emulating chip functionality before silicon production is crucial, especially with the increasing prevalence of RISC-V-based designs. FPGAs are promising candidates for such purposes due to their high-speed and reconfigurable architecture. In this paper, we introduce our Makinote, an FPGA-based Cluster platform, hosted at Barcelona Supercomputing Center (BSC-CNS), which is composed of a large number of FPGAs (in total 96 AMD/Xilinx Alveo U55c) to emulate massive size RTL designs (up to 750M ASIC cells). In addition, we introduce our FPGA shell as a powerful tool to facilitate the utilization of such a large FPGA cluster with minimal effort needed by the designers. The proposed FPGA shell provides an easy-to-use interface for the RTL developers to rapidly port such design into several FPGAs by automatically connecting to the necessary ports, e.g., PCIe Gen4, DRAM (DDR4 and HBM), ETH10g/100g. Moreover, specific drivers for exploiting RISC-V based architectures are provided within the set of tools associated with the FPGA shell. We release the tool online for further extensions. We validate the efficiency of our hardware platform (i.e., FPGA cluster) and the software tool (i.e., FPGA Shell) by emulating a RISC-V processor and experimenting HPC Challenge application running on 32 FPGAs. Our results demonstrate that the performance improves by 8 times over the single-FPGA case.
This report details the development of a networked distributed system named Group Communication System (GCS), implemented in Java to exemplify socket programming and communication protocols. GCS facilitates group-based client-server communication through a command-line interface (CLI), enabling seamless group interaction and management. The project emphasizes fault tolerance, design patterns, and version control system (VCS) utilization. The report offers insights into system architecture, implementation, and practical considerations, providing a comprehensive understanding of distributed systems' technical background and operational aspects.
This study aims to present a material based, second order design method that makes the rapid creation of bridging structures in order to connect two or more horizontal planes which are currently separated and three design instances created via such method. The first element of the presented method is a generative system that creates circulation surfaces through the interpolation of the curves defined on the current surfaces, and also creates the structural volumes via rheotomic (minimal) surfaces. The second constituent is the instantiation of the exposed variable, connected to a displacement algorithm inspired by allometry based on user input, contextual data, or simulation results. The method was created with applicability through additive manufacturing in consideration. The design process - similar to manufacturing - proceeds in a vertical manner, in order to reduce the generation of support geometry as much as possible. The system includes a raster data input viable for simulation results, feeding the accumulation variable in order to modify material amount or quality with the aim of improving structural performance where stress is greater. Through the application of the method, three physical models which connect different horizontal planes were obtained. The models can be evaluated with digital of physical simulations, and results can be utilized in an iterative manner, improving the results by each recursion.
Quantum computers allow to solve efficiently certain problems that are intractable for classical computers. For the realization of a quantum computer, a qubit design as the basic building block is a nontrivial starting point. We propose the utilization of nanoscale magnetic domain walls, which are stabilized by achiral energy, as the building blocks for a universal quantum computer made of ferromagnetic racetracks. In contrast to the domain walls stabilized by conventional Dzyaloshinskii-Moriya interactions, these achiral domain walls are bistable and show two degenerate chirality forms. When the domain wall is extremely small, it can be viewed as a quantum mechanical object and the two degenerate chiralities of the domain walls can be used to encode the qubit states $\lvert 0 \rangle$ and $\lvert 1 \rangle$. We show that the single-qubit quantum gates are regulated by magnetic and electric fields, while the Ising exchange coupling facilitates the two-qubit gates. The integration of these quantum gates allows for a universal quantum computation. Our findings demonstrate a promising approach for achieving quantum computing through spin textures that exist in ferromagnetic materials.
In this paper, we present an energy-efficient SNN architecture, which can seamlessly run deep spiking neural networks (SNNs) with improved accuracy. First, we propose a conversion aware training (CAT) to reduce ANN-to-SNN conversion loss without hardware implementation overhead. In the proposed CAT, the activation function developed for simulating SNN during ANN training, is efficiently exploited to reduce the data representation error after conversion. Based on the CAT technique, we also present a time-to-first-spike coding that allows lightweight logarithmic computation by utilizing spike time information. The SNN processor design that supports the proposed techniques has been implemented using 28nm CMOS process. The processor achieves the top-1 accuracies of 91.7%, 67.9% and 57.4% with inference energy of 486.7uJ, 503.6uJ, and 1426uJ to process CIFAR-10, CIFAR-100, and Tiny-ImageNet, respectively, when running VGG-16 with 5bit logarithmic weights.
Kasey Jones, Alexander Preiss, Emily Hadley
et al.
This Overview, Design Concepts, and Details (ODD) Protocol is an ODD extension to an agent-based model (ABM) framework built for the North Carolina Modeling Infectious Diseases Program (NC MInD). The model, NC MInD ABM, can be used as a base model for various infectious disease simulations. In this document, we describe a submodel specifically designed to simulate COVID-19 cases and hospitalizations within North Carolina. We describe in detail how each piece of the submodel works and how it was created. We do not discuss specific simulation scenarios or results. This information is reserved for papers related to each use case of the submodel.
We propose a general theoretical framework for both constructing and diagnosing inversion-protected higher-order topological superconductors using Kitaev building blocks, a higher-dimensional generalization of Kitaev's one-dimensional Majorana model. For a given crystalline symmetry, the Kitaev building blocks serve as a complete basis to construct all possible Kitaev superconductors that satisfy the symmetry requirements. We derive a simple yet powerful Majorana counting rule that can unambiguously diagnose the existence of higher-order topology for all Kitaev superconductors. We expect this real-space diagnosis to work for general two-dimensional higher-order topological superconductors within this symmetry class. As proof of concept, we have identified two inequivalent stacking strategies using the Kitaev building blocks, based on which we have constructed minimal tight-binding models with symmetry-protecetd Majorana corner modes. Moreover, we have successfully applied our diagnosis to comprehend the Majorana corner physcis in a superconductor model with a fragile Wannier obstruction, confirming the validity of our theory beyond the Kitaev limit. Our work paves the way for interpreting higher-order topological superconductivity from the real-space perspective.
Why was the $6 billion FAA air traffic control project scrapped? How could the 1977 New York City blackout occur? Why do large scale engineering systems or technology projects fail? How do engineering changes and errors propagate, and how is that related to epidemics and earthquakes? In this paper we demonstrate how the rapidly expanding science of complex design networks could provide answers to these intriguing questions. We review key concepts, focusing on non-trivial topological features that often occur in real-world large-scale product design and development networks; and the remarkable interplay between these structural features and the dynamics of design rework and errors, network robustness and resilience, and design leverage via effective resource allocation. We anticipate that the empirical and theoretical insights gained by modeling real-world large-scale product design and development systems as self-organizing complex networks will turn out to be the standard framework of a genuine science of design.
Imran Hafeez Abbassi, Faiq Khalid, Semeen Rehman
et al.
Conventional Hardware Trojan (HT) detection techniques are based on the validation of integrated circuits to determine changes in their functionality, and on non-invasive side-channel analysis to identify the variations in their physical parameters. In particular, almost all the proposed side-channel power-based detection techniques presume that HTs are detectable because they only add gates to the original circuit with a noticeable increase in power consumption. This paper demonstrates how undetectable HTs can be realized with zero impact on the power and area footprint of the original circuit. Towards this, we propose a novel concept of TrojanZero and a systematic methodology for designing undetectable HTs in the circuits, which conceals their existence by gate-level modifications. The crux is to salvage the cost of the HT from the original circuit without being detected using standard testing techniques. Our methodology leverages the knowledge of transition probabilities of the circuit nodes to identify and safely remove expendable gates, and embeds malicious circuitry at the appropriate locations with zero power and area overheads when compared to the original circuit. We synthesize these designs and then embed in multiple ISCAS85 benchmarks using a 65nm technology library, and perform a comprehensive power and area characterization. Our experimental results demonstrate that the proposed TrojanZero designs are undetectable by the state-of-the-art power-based detection methods.
New ways to treat electron correlation in electronic structure problems are discussed in the context of many-electron theory. The present work focuses primarily on static correlation. In related work, a method for including dynamical correlation effects is described. The overlap density of two basis functions i, j and the associated density matrix is a signature of bond formation and can be used to define a local molecular orbital, i + j. The total electron density \r{ho} can be written in terms of densities derived from these two-center orbitals and residual one-center terms. In the interaction of total densities, the self-energy terms resulting from an average field (Hartree-Fock) Hamiltonian are allowed to respond to an explicit inclusion of electron repulsion by mixing (i + j)1(i + j)2 +λ(i - j)1(i - j)2 . The energy lowering weighted by the density matrix ij approximates this contribution to the correlation energy of the system. Numerical calculations for a set of 20 molecules representing different bonding environments are reported and results are compared with configuration interaction calculations using the same molecular orbital basis. Calculations on chlorin, N4C20H16, are reported as an example of how the method could be used in an embedding treatment of a large system.