Engineering Commons^™

Led-Based Optical Sensing Platforms For Multi-Analyte Detection, Youngho Shin

LSU Doctoral Dissertations

Real-time monitoring of phytoplankton groups provides important information about aquatic ecological states, nutrient abundance, and water pollution. A rapid and accurate method for monitoring phytoplankton in water is commonly performed by detecting fluorescence emission from the plankton; however, commercially available portable fluorescence sensors are still expensive, bulky, and limited in functions, such as lacking the capability of selectively detecting multiple phytoplankton groups. In this regard, a low-cost and portable fluorometer platform for phytoplankton detection was developed in order to address the issues that current portable fluorometers have.

This dissertation has four main goals: (1) perform a study on fluorescence measurement …

Wavefront-Selective Fano Resonant Metasurfaces, Adam C. Overvig, Andrea Alù

Advanced Science Research Center

Fano resonances are conventionally understood as sharp spectral features with selectivity in the momentum-frequency domain, implying that they can be excited only by plane waves with specific frequencies and incident angles. We demonstrate that Fano resonances can be made generally selective in the space-frequency domain. They can be tailored to resonate only when excited by a frequency, polarization, and wavefront of choice. This generalization reveals that Fano systems are characterized by eigenwaves that scatter to their time-reversed image upon reflection. Although in conventional Fano systems this trivially occurs for normally incident plane waves, we show that, in general, the selected …

Channel Estimation In Multi-User Massive Mimo Systems By Expectation Propagation Based Algorithms, Mohammed Rashid

LSU Doctoral Dissertations

Massive multiple input multiple output (MIMO) technology uses large antenna arrays with tens or hundreds of antennas at the base station (BS) to achieve high spectral efficiency, high diversity, and high capacity. These benefits, however, rely on obtaining accurate channel state information (CSI) at the receiver for both uplink and downlink channels. Traditionally, pilot sequences are transmitted and used at the receiver to estimate the CSI. Since the length of the pilot sequences scale with the number of transmit antennas, for massive MIMO systems downlink channel estimation requires long pilot sequences resulting in reduced spectral efficiency and the so-called pilot …

Color-Compressive Bilateral Filter And Nonlocal Means For High-Dimensional Images, Christina Karam, Kenjiro Sugimoto, Keigo Hirakawa

Electrical and Computer Engineering Faculty Publications

We propose accelerated implementations of bilateral filter (BF) and nonlocal means (NLM) called color-compressive bilateral filter (CCBF) and color-compressive nonlocal means (CCNLM). CCBF and CCNLM are random filters, whose Monte-Carlo averaged output images are identical to the output images of conventional BF and NLM, respectively. However, CCBF and CCNLM are considerably faster because the spatial processing of multiple color channels are combined into a single random filtering process. This implies that the complexity of CCBF and CCNLM is less sensitive to color dimension (e.g., hyperspectral images) relatively to other BF and NLM methods. We experimentally verified that the execution time …

Deep Learning For Anisoplanatic Optical Turbulence Mitigation In Long-Range Imaging, Matthew A. Hoffmire, Russell C. Hardie, Michael A. Rucci, Richard Van Hook, Barry K. Karch

Electrical and Computer Engineering Faculty Publications

We present a deep learning approach for restoring images degraded by atmospheric optical turbulence. We consider the case of terrestrial imaging over long ranges with a wide field-of-view. This produces an anisoplanatic imaging scenario where turbulence warping and blurring vary spatially across the image. The proposed turbulence mitigation (TM) method assumes that a sequence of short-exposure images is acquired. A block matching (BM) registration algorithm is applied to the observed frames for dewarping, and the resulting images are averaged. A convolutional neural network (CNN) is then employed to perform spatially adaptive restoration. We refer to the proposed TM algorithm as …

Controller Modeling And Stability Analysis Of Multiple Input Single Output Dc-Dc Converter, Astha Adhikari

Master's Theses

This thesis entails the stability analysis of the Multiple Input Single Output (MISO) DC-DC converter developed for the DC House Project at Cal Poly. A frequency domain control system model of the MISO converter was designed and constructed using MATLAB Simulink. Transfer functions were derived and modeled for each stage of the converter to best fit the converter circuit system used in the original MISO circuit. Stability metrics such as overshoot, undershoot, rise time, phase margin and gain margin were measured to evaluate and analyze the stability of the converter. These metrics were measured with the original model including the …

Surface Defect Detection In Aircraft Skin & Visual Navigation Based On Forced Feature Selection Through Segmentation, Tyler B. Hussey

Theses and Dissertations

Visual inspection of aircraft skin for surface defects is an area of maintenance that is particularly intensive for time and manpower. One novel way to combat this problem is through the use of computer vision and the advent of Artificial Neural Networks (ANN), or more specifically, semantic segmentation via Convolutional Neural Networks (CNN). The research in the paper explores the use of semantic segmentation of aerial imagery as a way to force feature selection onto key areas of an image that might be more likely to correspond under seasonal variations. Utilizing feature selection and matching on the masked aerial image …

Supporting Space Domain Awareness Through The Development And Analysis Of Space Object Detection Algorithms Employed By Ground-Based Telescopes, Connor A. Paw

Theses and Dissertations

Detection algorithms are instrumental in maintaining space domain awareness, specifically in the observation, monitoring, and categorization of unknown space objects. State of the art detection algorithms utilize a matched filter or a spatial correlator on long exposure image data to make pixel-wise detection decisions. This thesis investigates the advantages and practical potential of two different post-processing detection algorithms that can be employed by ground-based telescopes. The first algorithm explored is based on a long exposure Fourier domain processing technique, while the second is centered around frame selection from a series of short exposure images. The results of the experiments performed …

Commuting Compositions For Quantum Circuit Reduction, Brenna R. Cole

Theses and Dissertations

Quantum circuit simplification improves program execution on quantum hardware by reducing error from prolonged environmental interaction and noisy gate operations. One simplification technique is template matching, which repeatedly conducts local optimization by replacing small sequences of gates within a circuit by optimized versions. Underlying this method is the problem of identifying sequences matching templates. This is challenging because some, but not all, gates can commute within a circuit. This means there may not be a subcircuit that matches a template in the original circuit specification, but a match may exist in an equivalent rearrangement of gates. In such cases, certain …

Robust Scandium Aluminum Nitride Mems Resonators For L Band Operation In Orbital Environments, Israel W. Dunk

Theses and Dissertations

This thesis investigates AlN alloyed with scandium in a variety of resonator architectures including WEM, overtone WEM, LEM, and SAW that have the potential to achieve high levels of electrical performance and environmental robustness. SAW resonators operating near 370 MHz are fabricated on polycrystalline Sc_.37Al_.63N, and AlN with the resulting devices compared and conclusions drawn as to the merits of each material. The design and fabrication of SAW devices is discussed in detail, with the operating characteristics of these resonators then tested both electrically and mechanically. Mechanical characterisation includes analysis of vibration and shock effects on …

Charge Mitigation Technologies For Aircraft Platforms, Mitchell L. Rudy

Theses and Dissertations

Research into ion-based advanced propulsion systems, such as air-breathing Hall effect thrusters on high-velocity aircraft and ion-propelled thrusters on spacecraft, necessitates addressing accompanying residual electric charge accumulation on the ungrounded flight platform. An experimental testbed was constructed to assess charge mitigation technologies and their effectiveness on aircraft. A Van de Graaff generator provided static charge accumulation levels exceeding a megavolt when combined with a high voltage direct current source generator. This research attached an isolated airfoil structure to the Van de Graaff generator's lower terminal to measure the induced leakage current under various applied environmental conditions, including up to three …

Early Wildfire Detection With Line Sensors, Virginia Yan

Master's Theses

Over the last few years, wildfires have become more devastating to communities as the fires are inevitably destructive to many homes, businesses, and ecosystems. Frequent wildfires also pose a significant threat to power grids and nearby residents as they can damage transmission lines and other electrical equipment, which in turn can cause major power shutdowns. Especially in western U.S., severe drought conditions and weather variability cause residents to become more vulnerable to wildfire disasters as their safety is threatened. We are incompetent to control the wildfires effectively despite existing advanced technologies. Hence, an algorithm based on energy conservation and heat …

A Feedback-Based Pneumatic Compression System For Effective Lymphedema Management, Mohammad Imrul Kayes

LSU Master's Theses

Bioimpedance analysis (BIA) is a method of detecting lymphedema- a debilitating medical condition involving swelling of the extremities. Pneumatic compression devices are frequently used in the compression treatment of lymphedema. Although existing compression technology provides relief of symptoms, it has limitations in terms of ease-of-use, portability, and monitoring of treatment progress. Currently, there are no BIA analyzers in the market that run on a low-power microcontroller and a rechargeable battery. Moreover, no such device currently exists that integrate the BIA analysis with pneumatic compression system to offer a feedback-based solution for lymphedema treatment. This work represents the first steps towards …

Research Of Focl Parameters In The Range Of Positive Temperatures, Dilmurod Davronbekov, Zafar Khakimov

Bulletin of TUIT: Management and Communication Technologies

This article studies the parameters of fiber-optic communication lines (FOCL) in the temperature range. For research, a climatic unit has been developed that allows a wide temperature range for testing (from -90°C to + 90°C) and an experimental complex for investigating the stability of optical parameters of a fiber-optic cable with temperature changes in the range from + 18°C to + 76°C. A technology of sequential switching of optical fibers of a fiber-optic cable by means of welding is proposed, thanks to which the constructive problem of placing a long optical fiber in a limited volume of a heat chamber …

Characterization Of Spatial-Mode Properties In Few-Mode Fiber Bragg Gratings And Its Applications, Muhammad Khairol Annuar Zaini

Student Works (2020-2029)

Recently, few-mode fiber (FMF) has gained much research attention compared to single mode fiber (SMF) due to its capability to overcome the capacity limit. FMF based fiber sensors have many distinctive advantages such as cost efficiency, great sensitivity, and have the ability to employ the spatial dimension for multi-parameter sensing with discrimination capability. In this work, an analytical model has been proposed to investigate the relationship of the resonant wavelength shift of a few-mode FBG (FMFBG) to the axial stress of the FMF. By applying the proposed model, the axial stress of an FMFs was determined. Besides, the polariscopic technique …

Deep Learning For Task-Based Image Quality Assessment In Medical Imaging, Weimin Zhou

McKelvey School of Engineering Graduate Student Theses & Dissertations

It has been advocated to use objective measures of image quality (IQ) for assessing and optimizing medical imaging systems. Objective measures of IQ quantify the performance of an observer at a specific diagnostic task. Binary signal detection tasks and joint signal detection and localization (detection-localization) tasks are commonly considered in medical imaging. When optimizing imaging systems for binary signal detection tasks, the performance of the Bayesian Ideal Observer (IO) has been advocated for use as a figure-of-merit (FOM). The IO maximizes the observer performance that is summarized by the receiver operating characteristic (ROC) curve. When signal detection-localization tasks are considered, …

Machine Learning Morphisms: A Framework For Designing And Analyzing Machine Learning Work Ows, Applied To Separability, Error Bounds, And 30-Day Hospital Readmissions, Eric Zenon Cawi

McKelvey School of Engineering Graduate Student Theses & Dissertations

A machine learning workflow is the sequence of tasks necessary to implement a machine learning application, including data collection, preprocessing, feature engineering, exploratory analysis, and model training/selection. In this dissertation we propose the Machine Learning Morphism (MLM) as a mathematical framework to describe the tasks in a workflow. The MLM is a tuple consisting of: Input Space, Output Space, Learning Morphism, Parameter Prior, Empirical Risk Function. This contains the information necessary to learn the parameters of the learning morphism, which represents a workflow task. In chapter 1, we give a short review of typical tasks present in a workflow, as …

Neural Dynamics, Adaptive Computations, And Sensory Invariance In An Olfactory System, Srinath Nizampatnam

McKelvey School of Engineering Graduate Student Theses & Dissertations

Sensory stimuli evoke spiking activities that are patterned across neurons and time in the early processing stages of olfactory systems. What features of these spatiotemporal neural response patterns encode stimulus-specific information (i.e. ‘neural code’), and how they are translated to generate behavioral output are fundamental questions in systems neuroscience. The objective of this dissertation is to examine this issue in the locust olfactory system. In the locust antennal lobe (analogous to the vertebrate olfactory bulb), a neural circuit directly downstream to the olfactory sensory neurons, even simple stimuli evoke neural responses that are complex and dynamic. We found each odorant …

Constructing And Analyzing Neural Network Dynamics For Information Objectives And Working Memory, Elham Ghazizadeh Ahsaei

McKelvey School of Engineering Graduate Student Theses & Dissertations

Creation of quantitative models of neural functions and discovery of underlying principles of how neural circuits learn and compute are long-standing challenges in the field of neuroscience. In this work, we blend ideas from computational neuroscience, information and control theories with machine learning to shed light on how certain key functions are encoded through the dynamics of neural circuits. In this regard, we pursue the ‘top-down’ modeling approach of engineering neuroscience to relate brain functions to basic generative dynamical mechanisms. Our approach encapsulates two distinct paradigms in which ‘function’ is understood. In the first part of this research, we explore …

Holistic Control For Cyber-Physical Systems, Yehan Ma

McKelvey School of Engineering Graduate Student Theses & Dissertations

The Industrial Internet of Things (IIoT) are transforming industries through emerging technologies such as wireless networks, edge computing, and machine learning. However, IIoT technologies are not ready for control systems for industrial automation that demands control performance of physical processes, resiliency to both cyber and physical disturbances, and energy efficiency. To meet the challenges of IIoT-driven control, we propose holistic control as a cyber-physical system (CPS) approach to next-generation industrial automation systems. In contrast to traditional industrial automation systems where computing, communication, and control are managed in isolation, holistic control orchestrates the management of cyber platforms (networks and computing platforms) …

Theory, Design And Implementation Of Energy-Efficient Biotelemetry Using Ultrasound Imaging, Sri Harsha Kondapalli

McKelvey School of Engineering Graduate Student Theses & Dissertations

This dissertation investigates the fundamental limits of energy dissipation in establishing a communication link with implantable medical devices using ultrasound imaging-based biotelemetry.

Ultrasound imaging technology has undergone a revolution during the last decade due to two primary innovations: advances in ultrasonic transducers that can operate over a broad range of frequencies and progresses in high-speed, high-resolution analog-to-digital converters and signal processors. Existing clinical and FDA approved bench-top ultrasound systems cangenerate real-time high-resolution images at frame rates as high as 10000 frames per second. On the other end of the spectrum, portable and hand-held ultrasound systems can generate high-speed real-time scans, …

Ultrafast Thermal Modification Of Strong Coupling In An Organic Microcavity, Bin Liu, Vinod M. Menon, Matthew Y. Sfeir

Advanced Science Research Center

There is growing interest in using strongly coupled organic microcavities to tune molecular dynamics, including the electronic and vibrational properties of molecules. However, very little attention has been paid to the utility of cavity polaritons as sensors for out-of-equilibrium phenomena, including thermal excitations. Here, we demonstrate that non-resonant infrared excitation of an organic microcavity system induces a transient response in the visible spectral range near the cavity polariton resonances. We show how these optical responses can be understood in terms of ultrafast heating of electrons in the metal cavity mirror, which modifies the effective refractive index and subsequently the strong …

Asset Management Framework For The United States Army Corps Of Engineers Lock And Dam Electrical Equipment, Megan Elizabeth Bates

Theses, Dissertations and Capstones

The focus of this thesis is to design an efficient and effective preventative maintenance program for the electrical equipment that the United States Army Corps of Engineers (USACE) operates at the locks and dams. This thesis presents the concept of asset management and designs a framework to manage the electrical assets at USACE. The methodology was tested, and the results validated the framework proposed in this thesis. The framework was tested on two separate projects and the results were the same optimized strategies, which shows that the framework is robust and can be implemented into each project and can give …

A Zugunruhe Data Collection System Using Passive Infrared Sensors, Ryan Terry, Luis E. Ramirez, Carol Carrera, Abigail Kimmitt, Kira Delmore, Ana Goulart

Pursue: Undergraduate Research Journal

When engineers and biologists work together, there is a lot to learn on both sides. For instance, our work introduced us to zugunruhe, which is a German word that means “unrest”. It is used in the context of migratory birds, as they become restless at night, inside their cages, during their migratory period. When does zugunruhe start? It usually starts when the weather becomes cold and the days shorter, but it varies for different bird species. Moreover, global warming has caused changes in zungunruhe’s timing, which made it even harder to predict. Another question is about genetics: is …

Distributed Control, Optimization, And State Estimation For Renewable Power System, Qiao Li

Electronic Theses and Dissertations

The traditional power systems are usually centralized systems, in which the control, operation and monitoring are performed by the centralized control center, e.g., SCADA. However, with the development of renewable energy, power systems are getting more and more distributed. So, it becomes necessary to establish the distributed power system operation methods for these power systems. In this research, the distributed techniques for the renewable power systems are proposed based on the consensus protocol technique from graph theory. These techniques cover the three important problems in power systems, i.e., economic dispatch, state estimation, and optimal power flow. First, the Distributed Economic …

Design, Manufacture, And Test Of A Hybrid Aerial-Ground Robotic Platform, William Garrett Willmon

Electronic Theses and Dissertations

A hybrid aerial-ground robotic platform allows for enhanced functionality combining most of the operational profiles of an aerial and ground vehicle with applications to intelligence, surveillance, reconnaissance (ISR), infrastructure inspection, emergency response, photography, etc. Motivated by this challenge, we designed, developed, and tested a prototype hybrid aerial-ground robotic vehicle capable of guidance, navigation, and control in the air and on the ground. The thesis focus is on the system design. As such, at first, we designed and analyzed the mechanical component to ensure durability. We then designed the electrical component to reduce overall weight and maximize battery life. We developed …

Analog & Digital Remote Synthesizer, Adam Brunner, Andrew Cihon-Scott, Scott Grisso, Linus Wright

Williams Honors College, Honors Research Projects

The purpose of this project is to develop and design an analog synthesizer musical instrument that integrates embedded digital hardware into the design to enable control from a remote source. The use of digital hardware enables the potential for a wide range of convenient features such as sound profile saving and loading, output recording functionality, and the ability to accept digital input from another musical instrument utilizing the Musical Instrument Digital Interface (MIDI). In addition to the synthesizer itself, this project also includes the design of a companion application that can be hosted on a wide variety of consumer computing …

การจัดสรรแหล่งผลิตไฟฟ้าแบบกระจายหลายตำแหน่งในระบบจำหน่ายไฟฟ้าแบบเรเดียลโดยพิจารณาการลดการสูญเสียกำลังไฟฟ้าและการจำกัดปริมาณการรับซื้อไฟฟ้า, กฤตภาส เพียรวิบูลย์

Chulalongkorn University Theses and Dissertations (Chula ETD)

วิทยานิพนธ์ฉบับนี้ได้ศึกษาการหาขนาดที่เหมาะสมของแหล่งผลิตไฟฟ้าแบบกระจายหลายตัวในระบบจำหน่ายไฟฟ้าแบบเรเดียล และ ศึกษาผลกระทบของการลดการสูญเสียกำลังไฟฟ้าและการจำกัดปริมาณรับซื้อไฟฟ้าของระบบที่มีแหล่งผลิตไฟฟ้าแบบกระจายหลายตัว นอกจากนี้วิทยานิพนธ์ได้ศึกษาผลกระทบของการลดการสูญเสียกำลังไฟฟ้าและการจำกัดปริมาณรับซื้อไฟฟ้าของระบบที่มีแหล่งผลิตไฟฟ้าแบบกระจายหลายตัวร่วมกับเทคโนโลยีระบบกักเก็บพลังงาน กรณีศึกษาถูกแบ่งเป็น 3 ส่วน ดังนี้ กรณีศึกษาที่ 1 การเปรียบเทียบวิธีการจัดสรรแหล่งผลิตไฟฟ้า กรณีศึกษาที่ 2 ผลกระทบของวิธีการจัดสรรแหล่งผลิตไฟฟ้าเมื่อมีจำนวนแหล่งผลิตไฟฟ้าเพิ่มขึ้น และ กรณีศึกษาที่ 3 ผลการจำลองเวลาจริงของการหาค่าขนาดที่เหมาะสมของการจัดสรรแหล่งผลิตไฟฟ้า วิทยานิพนธ์ใช้ข้อมูลการผลิตไฟฟ้าของแหล่งผลิตไฟฟ้าแบบกระจายตัวจากการไฟฟ้าฝ่ายผลิตแห่งประเทศไทย ข้อมูลความต้องการโหลดแบบผู้อยู่อาศัยและแบบเชิงอุตสาหกรรมจากการไฟฟ้าส่วนภูมิภาค และ ระบบทดสอบ IEEE-33 บัส การจำลองหาขนาดที่เหมาะสมของแหล่งผลิตไฟฟ้า ใช้โปรแกรม Power Factory – DIgSILENT และ MATLAB ผลการศึกษาแสดงให้เห็นว่าวิธีที่นำเสนอของวิทยานิพนธ์สามารถใช้แก้ปัญหาของการจัดสรรแหล่งผลิตไฟฟ้าแบบกระจายตัวเมื่อพิจารณาดรรชนีความอ่อนไหวที่มีค่ามากที่สุดในระบบ ผลการทดลองของกรณีศึกษาที่ 2 แสดงให้เห็นว่า ระบบไฟฟ้ามีจุดอิ่มตัวของค่าการลดลงของกำลังไฟฟ้าเมื่อมีการเพิ่มจำนวนการติดตั้งแหล่งผลิตไฟฟ้า โดยค่าการลดลงของกำลังไฟฟ้าไม่มีความแตกต่างทางนัยสำคัญที่จุดอิ่มตัว ผลการทดลองสำหรับกรณีศึกษาที่ 3 แสดงให้เห็นว่าการจัดสรรขนาดแหล่งผลิตไฟฟ้าแบบกระจายตัวเมื่อมีการพิจารณาการลดการสูญเสียกำลังไฟฟ้าและการจำกัดปริมาณการรับซื้อไฟฟ้า สามารถลดปริมาณเฉลี่ยการจำกัดปริมาณรับซื้อไฟฟ้าของระบบได้อย่างมีนัยสำคัญ โดยที่มีพลังงานไฟฟ้าสูญเสียไม่แตกต่างกันระหว่างการพิจารณาการจำกัดปริมาณการรับซื้อไฟฟ้ากับไม่พิจารณาการจำกัดปริมาณการรับซื้อไฟฟ้า สำหรับการจัดสรรแหล่งผลิตไฟฟ้าแบบกระจายตัวเมี่อมีการใช้แหล่งผลิตไฟฟ้าแบบกระจายตัวและระบบกักเก็บพลังงาน ผลลัพธ์แสดงให้เห็นว่าการจัดสรรขนาดแหล่งผลิตไฟฟ้าแบบกระจายตัวเมื่อมีการพิจารณาการลดการสูญเสียกำลังไฟฟ้าและการจำกัดปริมาณการรับซื้อไฟฟ้า สามารถลดปริมาณเฉลี่ยการจำกัดปริมาณรับซื้อไฟฟ้าของระบบได้อย่างมีนัยสำคัญ อย่างไรก็ตาม วิธีนี้ไม่สามารถทำให้ระบบมีพลังงานไฟฟ้าสูญเสียต่ำกว่ากรณีการจัดสรรแหล่งผลิตไฟฟ้าแบบกระจายตัวเมื่อพิจารณาเฉพาะการลดการสูญเสียกำลังไฟฟ้าได้

Adaptive Uplink Data Rate Prediction And Networkselection In A Vehicular Mobile Channel, Georgi Nikolov

Theses

The rapid acceleration into the digital age brings a worldwide interconnectedness of an unprecedented level. This interconnectedness transforms the modern transportation network by linking its infrastructure components (e.g., signaling systems, traffic control systems, maintenance systems) together. Intelligent transportation systems (ITS) can utilize this newly emerged network infrastructure, improving traffic safety, traffic control, and reducing transportation-related environmental impacts, changing the way drivers, businesses and governments deal with road transport. It is expected that in the near future self-aware vehicles (e.g., trains, cars or trucks) will constitute the majority of the transportation infrastructure. Vehicles need to be able to reliably communicate critical …

Dales Objects: A Large Scale Benchmark Dataset For Instance Segmentation In Aerial Lidar, Nina M. Singer, Vijayan K. Asari

Electrical and Computer Engineering Faculty Publications

We present DALES Objects, a large-scale instance segmentation benchmark dataset for aerial lidar. DALES Objects contains close to half a billion hand-labeled points, including semantic and instance segmentation labels. DALES Objects is an extension of the DALES (Varney et al., 2020) dataset, adding additional intensity and instance segmentation annotation. This paper provides an overview of the data collection, preprocessing, hand-labeling strategy, and final data format. We propose relevant evaluation metrics and provide insights into potential challenges when evaluating this benchmark dataset. Finally, we provide information about how researchers can access the dataset for their use at go.udayton.edu/dales3d.