Towards Practical Plug-and-Play Diffusion Models

Diffusion-based generative models have achieved remarkable success in image generation. Their guidance formulation allows an external model to plug-and-play control the generation process for various tasks without fine-tuning the diffusion model. However, the direct use of publicly available off-the-shelf models for guidance fails due to their poor performance on noisy inputs. For that, the existing practice is to fine-tune the guidance models with labeled data corrupted with noises. In this paper, we argue that this practice has limitations in two aspects: (1) performing on inputs with extremely various noises is too hard for a single model; (2) collecting labeled datasets hinders scaling up for various tasks. To tackle the limitations, we propose a novel strategy that leverages multiple experts where each expert is specialized in a particular noise range and guides the reverse process at its corresponding timesteps. However, as it is infeasible to manage multiple networks and utilize labeled data, we present a practical guidance framework termed Practical Plug-And-Play (PPAP), which leverages parameter-efficient fine-tuning and data-free knowledge transfer. We exhaustively conduct ImageNet class conditional generation experiments to show that our method can successfully guide diffusion with small trainable parameters and no labeled data. Finally, we show that image classifiers, depth estimators, and semantic segmentation models can guide publicly available GLIDE through our framework in a plug-and-play manner

Addressing Negative Transfer in Diffusion Models

Diffusion-based generative models have achieved remarkable success in various domains. It trains a model on denoising tasks that encompass different noise levels simultaneously, representing a form of multi-task learning (MTL). However, analyzing and improving diffusion models from an MTL perspective remains under-explored. In particular, MTL can sometimes lead to the well-known phenomenon of $\textit{negative transfer}$, which results in the performance degradation of certain tasks due to conflicts between tasks. In this paper, we aim to analyze diffusion training from an MTL standpoint, presenting two key observations: $\textbf{(O1)}$ the task affinity between denoising tasks diminishes as the gap between noise levels widens, and $\textbf{(O2)}$ negative transfer can arise even in the context of diffusion training. Building upon these observations, our objective is to enhance diffusion training by mitigating negative transfer. To achieve this, we propose leveraging existing MTL methods, but the presence of a huge number of denoising tasks makes this computationally expensive to calculate the necessary per-task loss or gradient. To address this challenge, we propose clustering the denoising tasks into small task clusters and applying MTL methods to them. Specifically, based on $\textbf{(O2)}$, we employ interval clustering to enforce temporal proximity among denoising tasks within clusters. We show that interval clustering can be solved with dynamic programming and utilize signal-to-noise ratio, timestep, and task affinity for clustering objectives. Through this, our approach addresses the issue of negative transfer in diffusion models by allowing for efficient computation of MTL methods. We validate the proposed clustering and its integration with MTL methods through various experiments, demonstrating improved sample quality of diffusion models.Comment: 22 pages, 12 figures, under revie

Steel Module-to-Concrete Core Connection Methods in High Rise Modular Buildings: A Critical Review

Modularization in a high-rise building is different from a small building, as it is exposed to more lateral forces like wind and earthquakes. The integrity, robustness, and overall stability of the modules and their performance is based on the joining techniques and strong structural systems. High lateral stiff construction structures like concrete shear walls and frames, braced steel frames, and steel moment frames are used for the stability of high-rise modular buildings. Similarly, high-rise stick-built buildings have concrete cores and perimeter frames for lateral load strength and stiffness. Methods for general steel-concrete connections are available in many works of literature. However, there are few modular-related papers describing this connection system in modular buildings. This paper aims to review the various research and practice adopted for steel-to-concrete connections in construction and compare the methods between stick-built buildings and modular buildings. The literature review shows that the practice of steel module-to-concrete core connection in high-rise modular buildings is like outrigger beams-to-concrete core connection in stick-built framed buildings. This paper concludes that further studies are needed in developing proper guidelines for a steel module-to-concrete core connection system in high-rise modular buildings

Lessons Learned during the Early Phases of a Modular Project: A Case Study of UNLV\u27s Solar Decathlon 2020 Project

The U.S. Department of Energy conducts the Solar Decathlon competition as a student-based achievement that encourages sustainable design with energy efficiency and solar energy technologies. In the 2020 competition, the University of Nevada, Las Vegas (UNLV) team designed, fabricated, and constructed a net-zero modular house that applies innovative and highly efficient building technologies. This paper focused on the lessons learned during the early phases of this ongoing modular project. The research methodology included obtaining feedback from key project participants using a well-structured questionnaire. The results showed that the major items/challenges in the project’s planning phase included selecting the modular size, planning the construction system, planning the materials and procurement, estimating costs and duration, selecting a fabricator, collaboration and communication, safety, and planning module transportation. These findings will help modular practitioners and future Solar Decathlon competition participants better understand how and what factors they should consider most during the early phases through the lessons learned

Cutting-edge Technologies to Achieve a Higher Level of Modular Construction – Literature Review

Cost overruns, schedule delays, and a shortage of skilled labor are common problems the construction industry is currently experiencing. Modularization and standardization strategies have the potential to resolve the various problems mentioned above and have been applied for various construction applications for a long time. However, the level of modularization remains low, and modular construction projects have not been getting the full benefits. Thus, this review investigated the cutting-edge technologies currently being utilized to develop the modular construction field. For this paper, qualified research papers were identified using predetermined keywords from previous related research papers. Identified literature was then filtered and analyzed. According to the included reviews, several technologies are being developed for modular construction. For example, automated design and monitoring systems for modularization were developed. In addition, research labs are utilizing robotic arms for modular construction to achieve a high level of completion in the construction industry, as is seen in the manufacturing industry. Despite these efforts, more research and development are necessary because some automation technologies still require manual activities. Thus, there is great potential for further development of modularization techniques, and further research is recommended to achieve high levels of modularization

Novel OTEC Cycle Using Efficiency Enhancer

The ocean thermal energy conversion (OTEC) plant is designed to improve the efficiency of the existing plants. Various researches are being conducted to increase the plant’s efficiency and output with the use of an enhancer, and studies for performance improvement are also in progress from the Kalina and Uehara cycles to ejector pump OTEC (EP-OTEC). Their performance can be improved by increasing the evaporation pressure using an unused heat source and reducing the heat consumption using a reheating system and a regenerator. In the case of EP-OTEC, an ejector is installed near the turbine-exit to reduce the pressure and therefore increase the power output. In simulations and experiments conducted in this study, EP-OTEC showed 38% efficiency improvement from the basic cycle, which is due to the power output volume increase. The optimum ratio was derived by adjusting the pressure ratio. The demonstration plant to be developed in the future is expected to be applied to the high-efficiency OTEC demonstration plant with improved performance, and new technologies will be continuously developed considering economics and commercial viability

The Current State and Future Directions of Industrial Robotic Arms in Modular Construction

Industrial robotic arms are widely adopted in numerous industries for manufacturing automation under factory settings, which eliminates the limitations of manual labor and provides significant productivity and quality benefits. The U.S. modular construction industry, despite having similar controlled factory environments, still heavily relies on manual labor. Thus, this study investigates the U.S., Canada, and Europe-based leading modular construction companies and research labs implementing industrial robotic arms for manufacturing automation. The investigation mainly considered the current research scope, industry state, and constraints, as well as identifying the types and specifications of the robotic arms in use. First, the study investigated well-recognized modular building associations, the Modular Building Institute (MBI), and renowned architecture design magazine, Dezeen to gather industry updates. The authors discovered one university lab and a few companies that adopted Switzerland-based robotic arms, ABB. Researching ABB robotics led to the discovery of ABB’s competitor, Germany-based KUKA robotic arms. Consequently, research extended to the companies and labs adopting KUKA models. In total, this study has identified seven modular companies and four research labs. All companies employed robotic arms and gantry robot combinations in a production-line-like system for partial automation, and some adopted design standardization for optimization. The common goal among the labs was to achieve greater flexibility and full automation with robotic arms. This study will help companies better implement robotic arm automation by providing recommendations from investigating its current industry status

Next-generation sequencing analysis of hepatitis C virus resistance–associated substitutions in direct-acting antiviral failure in South Korea

Background/Aims We used next-generation sequencing (NGS) to analyze resistance-associated substitutions (RASs) and retreatment outcomes in patients with chronic hepatitis C virus (HCV) infection who failed direct-acting antiviral agent (DAA) treatment in South Korea. Methods Using prospectively collected data from the Korean HCV cohort study, we recruited 36 patients who failed DAA treatment in 10 centers between 2007 and 2020; 29 blood samples were available from 24 patients. RASs were analyzed using NGS. Results RASs were analyzed for 13 patients with genotype 1b, 10 with genotype 2, and one with genotype 3a. The unsuccessful DAA regimens were daclatasvir+asunaprevir (n=11), sofosbuvir+ribavirin (n=9), ledipasvir/sofosbuvir (n=3), and glecaprevir/pibrentasvir (n=1). In the patients with genotype 1b, NS3, NS5A, and NS5B RASs were detected in eight, seven, and seven of 10 patients at baseline and in four, six, and two of six patients after DAA failure, respectively. Among the 10 patients with genotype 2, the only baseline RAS was NS3 Y56F, which was detected in one patient. NS5A F28C was detected after DAA failure in a patient with genotype 2 infection who was erroneously treated with daclatasvir+asunaprevir. After retreatment, 16 patients had a 100% sustained virological response rate. Conclusions NS3 and NS5A RASs were commonly present at baseline, and there was an increasing trend of NS5A RASs after failed DAA treatment in genotype 1b. However, RASs were rarely present in patients with genotype 2 who were treated with sofosbuvir+ribavirin. Despite baseline or treatment-emergent RASs, retreatment with pan-genotypic DAA was highly successful in Korea, so we encourage active retreatment after unsuccessful DAA treatment

Analysis of Major Temporary Electrical Equipment Consumption and Usage Patterns in Educational Buildings: Case Study

The energy use patterns of electrical appliances are more difficult to predict than energy use for heating, ventilation, and air-conditioning (HVAC) and lighting, as: (1) there are large varieties of electrical equipment (e.g., appliances, vending machines, etc.) in buildings and each serves a different function; thus, their energy consumption patterns are difficult to predict; (2) electrical appliances are scattered across buildings, most are not permanently fixed to a location, and they consume much energy. Appliances are also not centrally controlled, such as HVAC and lighting. Thus, energy consumption patterns are more difficult to predict. In addition, electrical appliances consume significant amounts of energy to influence energy consumption volatility. This case study focuses on understanding the energy consumption patterns of electrical appliances in educational buildings. This research analyzes the electrical appliances and energy consumption data from institutional buildings and the factors that drive energy consumption. The analyses show that: (1) energy consumption patterns are dependent on building characteristics and use; (2) the number of appliances in a building influences the peak electricity consumption; (3) vending machines and fridges consume significant amounts of electricity; it has been proven (by minimum building energy loads) that buildings that have more vending machines have significantly higher minimum loads than no or fewer vending machines; and (4) the energy-saving potential from desktops and monitors rose to 60 kWh during lunchtime and 500 kWh at night