Development of an Optimization Model for Design and Planning of a Decentralized District Energy System

This dissertation reports the development of a optimization model to help designing a tri-generation system for a given newly-built district with its consumers to satisfy the heating, cooling, and hot water demands featuring 4th generation district energy characteristics. The aim is to find the best way to select the equipment among various candidates (capacities), the pipeline network among the buildings, and their electrical grid connections. The objective function includes the annualized overall capital and operation costs for the district along with the benefits of selling electricity to the grid. The distributed energy supply consists of heating, cooling, and power networks, different CHP technologies, solar array, chillers, auxiliary boilers, and thermal and electrical storage. The performance of the model was evaluated for designing two different case under various scenarios: (i) a combined heat and power design, and (ii) a combined cooling and power design both carried out for the new part of Suurstoffi district situated in Risch Rotkreuz, Switzerland with seven residential and office complexes. For the combined heat and power design, the scenarios are defined based on the existence or non-existence of the distribution network (both heat and electricity) and the effectiveness of the storage systems. Allowing heat exchange among the buildings leads to 25% reduction in the total annualized cost and 5% reduction in emission compared to the conventional districts. Simultaneous heat and electricity exchange results in a higher reduction equal to 40% of the base scenario. Adding storage systems opens up an opportunity to lower both costs and emission even more and turns the district to a net-zero energy and energy plus districts. For the combined cooling and power design, the effectiveness of the network is analyzed together with the potential of feeding absorption chillers using the heat from the solar and non-solar energy sources. More than 67% of CO2 emission reduction is achieved through the hybrid heat and solar-driven arrangement

Persian Keyphrase Generation Using Sequence-to-Sequence Models

Keyphrases are a very short summary of an input text and provide the main subjects discussed in the text. Keyphrase extraction is a useful upstream task and can be used in various natural language processing problems, for example, text summarization and information retrieval, to name a few. However, not all the keyphrases are explicitly mentioned in the body of the text. In real-world examples there are always some topics that are discussed implicitly. Extracting such keyphrases requires a generative approach, which is adopted here. In this paper, we try to tackle the problem of keyphrase generation and extraction from news articles using deep sequence-to-sequence models. These models significantly outperform the conventional methods such as Topic Rank, KPMiner, and KEA in the task of keyphrase extraction

Integration of Distributed Energy Storage into Net-Zero Energy District Systems: Optimum Design and Operation

A net-zero energy district is any neighborhood where the consumption of the buildings is offset by on-building generation on an annual basis. In this study, a net-zero energy district is identified among the set of optimal solutions and the effects of storage on its performance is investigated. It is assumed the model simultaneously optimizes the location of host buildings (energy generators), type of technologies and associated size, and the energy distribution network layout together with the optimal operating strategy. The optimization model addresses all technologies with a special focus on the effect of application of energy storage. Two types of energy storage are considered inside each building: thermal energy storage (hot water tank) and electrical energy storage (battery bank). The model is applied to the new part of a district energy system located in Switzerland. The best integrated district energy systems are presented as a set of Pareto optimal solutions by minimizing both the total annualized cost and equivalent CO2 emission while ensuring the reliable system operation to cover the demand. The results indicated that selection of the proposed optimal district energy system along with the storage brings great economic and environmental benefits in comparison to all other scenarios (conventional energy system, stand-alone system, and net zero-energy without storage)

Imaginations of WALL-E : Reconstructing Experiences with an Imagination-Inspired Module for Advanced AI Systems

In this paper, we introduce a novel Artificial Intelligence (AI) system inspired by the philosophical and psychoanalytical concept of imagination as a ``Re-construction of Experiences". Our AI system is equipped with an imagination-inspired module that bridges the gap between textual inputs and other modalities, enriching the derived information based on previously learned experiences. A unique feature of our system is its ability to formulate independent perceptions of inputs. This leads to unique interpretations of a concept that may differ from human interpretations but are equally valid, a phenomenon we term as ``Interpretable Misunderstanding". We employ large-scale models, specifically a Multimodal Large Language Model (MLLM), enabling our proposed system to extract meaningful information across modalities while primarily remaining unimodal. We evaluated our system against other large language models across multiple tasks, including emotion recognition and question-answering, using a zero-shot methodology to ensure an unbiased scenario that may happen by fine-tuning. Significantly, our system outperformed the best Large Language Models (LLM) on the MELD, IEMOCAP, and CoQA datasets, achieving Weighted F1 (WF1) scores of 46.74%, 25.23%, and Overall F1 (OF1) score of 17%, respectively, compared to 22.89%, 12.28%, and 7% from the well-performing LLM. The goal is to go beyond the statistical view of language processing and tie it to human concepts such as philosophy and psychoanalysis. This work represents a significant advancement in the development of imagination-inspired AI systems, opening new possibilities for AI to generate deep and interpretable information across modalities, thereby enhancing human-AI interaction.Comment: 18 pages

A nonviral DNA delivery system based on surface modified silica-nanoparticles can efficiently transfect cells in vitro

Diverse polycationic polymers have been used as nonviral transfection agents. Here we report the ability of colloidal silica particles with covalently attached cationic surface modifications to transfect plasmid DNA in vitro and make an attempt to describe the structure of the resulting transfection complexes. In analogy to the terms lipoplex and polyplex, we propose to describe the nanoparticle-DNA complexes by the term 'nanoplex'. Three batches, Si10E, Si100E, and Si26H, sized between 10 and 100 nm and with ζ potentials ranging from +7 to +31 mV at pH 7.4 were evaluated. The galactosidase expression plasmid DNA pCMVβ was immobilized on the particle surface and efficiently transfected Cos-1 cells. The transfection activity was accompanied by very low cytotoxicity, with LD50 values in the milligrams per milliliter range. The most active batch, Si26H, was produced by modification of commercially available silica particles with N-(6-aminohexyl)-3-aminopropyltrimethoxysilane, yielding spherical nanoparticles with a mean diameter of 26 nm and a ζ potential of +31 mV at pH 7.4. Complexes of Si26H and pCMVβ plasmid DNA formed at w/w ratios of 10 were most effective in promoting transfection of Cos-1 cells in the absence of serum. At this ratio, >90% of the DNA was associated with the particles, yielding nanoplexes with a net negative surface charge. When the transfection medium was supplemented with 10% serum, maximum gene expression was observed at a w/w ratio of 30, at which the resulting particle-DNA complexes possessed a positive surface charge. Transfection was strongly increased in the presence of 100 µM chloroquine in the incubation medium and reached approximately 30% of the efficiency of a 60 kDa polyethylenimine. In contrast to polyethylenimine, no toxicity was observed at the concentrations required. Atomic force microscopy of Si26H-DNA complexes revealed a spaghetti-meatball-like structure. The surface of complexes prepared at a w/w ratio of 30 was dominated by particles half-spheres. Complex sizes correlated well with those determined previously by dynamic light scattering

City of Hitchcock Comprehensive Plan 2020-2040

Hitchcock is a small town located in Galveston County (Figure 1.1), nestled up on the Texas Gulf Coast. It lies about 40 miles south-east of Houston. The boundaries of the city encloses an area of land of 60.46 sq. miles, an area of water of 31.64 sq. miles at an elevation just 16 feet above sea level. Hitchcock has more undeveloped land (~90% of total area) than the county combined. Its strategic location gives it a driving force of opportunities in the Houston-Galveston Region.The guiding principles for this planning process were Hitchcock’s vision statement and its corresponding goals, which were crafted by the task force. The goals focus on factors of growth and development including public participation, development considerations, transportation, community facilities, economic development, parks, and housing and social vulnerabilityTexas Target Communitie

Detection of soft tissue abnormalities in mammographic images for early diagnosis of breast cancer

Treatment of breast cancer is currently effective only if it is detected at an early stage. X-ray mammography is the most effective method for early detection, however, mammographic images are complex. Researchers have been utilizing image processing and image analysis techniques to assist radiologists in their difficult task of detecting tumors in mammographic images. To aid radiologists in earlier detection of breast cancer, a retrospective study of mammograms was conducted. In this pioneer study, screening mammograms taken prior to the detection of a malignant mass were analyzed. The aim is to determine if there exists any signs of cancer development in the screening mammograms prior to the detection of a mass by the radiologist. For 58 biopsy proven breast cancer patients who were diagnosed by identifying a malignant mass in their mammograms, 224 previous screening mammograms were collected. These mammograms were reviewed by an expert radiologist and three regions were marked on each of the two mammographic projections of each case: 1) the region which corresponds to the site in which the malignant mass subsequently developed, 2) a similar normal region on the same mammogram, and 3) the normal region on the previous screening mammogram of the opposite breast which corresponds to region 1. Sixty-two texture and photometric image features were calculated for all the marked areas. A stepwise discriminant analysis found that six of these features best distinguish between the normal and abnormal regions. The best linear classification function resulted in 72% average classification. A t its current stage, the system can be used by a radiologist to examine suspicious patterns in a mammogram. The regions which are flagged by the system have a 72% chance of developing a malignant mass by the time of the next screening. Therefore, further evaluation of these patients (e.g., a screening examination sooner than the usual one year interval) can result in earlier detection of breast cancer. A novel segmentation algorithm for mammogram partitioning based on fuzzy sets theory was also devised. This algorithm considers the fact that malignant masses and parenchymal patterns have unclear and fuzzy boundaries in a mammogram. It also takes into account the effects of neighboring pixels for this segmentation. This algorithm was evaluated in combination with a texture feature extraction step for detection of malignant masses in mammograms. The mass detection scheme resulted in 94.3% true-positive detection rate and 0.24 false-positives per image on a set of 35 mammograms.Applied Science, Faculty ofElectrical and Computer Engineering, Department ofGraduat