Miracle-dz/UniFAR-FTUs huggingface dataset:
Unified Pilot-Induced Oscillation Theory. Volume 1. PIO Analysis with Linear and Nonlinear Effective Vehicle Characteristics, Including Rate Limiting.

Abstract : This work was conducted as part of a USAF initiative to develop a comprehensive theory to predict pilot-induced oscillation (PIO) tendencies due to the combined effect of all influencing elements. A PIO is a very complicated phenomenon stemming from a dynamic interaction between the pilot and the aircraft. When tight control is required from the pilot, an undesired oscillation can result. However, the adaptive nature of the human pilot makes such oscillations difficult to predict. The independent research of STI included: compilation of available PIO time histories and references as an initial step toward a comprehensive PIO database; refinement of the proposed PIO categories defined in NASA CR-4683; development of PIO theories based on these categories; development of methods to handle the higher frequency and nonlinear aspects of PIO analysis with an emphasis on rate limiting; and a review of existing and proposed linear PIO criteria.
Event correlation for detecting advanced multi-stage cyber-attacks

Rapidly evolving IT infrastructures bring beneficial effects to society and promote information sharing and use. However, vulnerabilities create opportunities for hostile users to perform malicious activities and IT security has gradually turned into a critical research area for organizations and governments. Processes of decision making in large organizations are widely influenced by their capability of detecting malicious activities effectively, and by the correctness in analyzing suspicious phenomena, which can be observed by a number of security sensors deployed in such large networks. Several techniques are currently employed to detect incidents starting from captured security-related events within networks and computer systems. However, the large volume of observable events, the continuous sophistication and changes in attack strategies make it challenging to provide effective solutions to detect and reconstruct cyber-security incidents. In particular, advanced multi-stage attacks tend to remain undiscovered because common security mechanisms can generally detect and flag harmful activity – sometimes with unsatisfactory false alert rates – but they are not able to draw a big picture of the incidents. Since such task is usually performed by security experts in full, it may be expensive and prone to errors. Therefore, it is essential to develop procedures for combining large heterogeneous datasets and system’s information in meaningful way, and for supplying detailed information to IT security management. By examining realistic multi-stage incidents, this thesis proposes the design of a model to correlate detectable suspicious events by combining complementary state of the art methods, which perform correlation along different axis. Thus, it aims at providing standard data formats, prioritizing and clustering data, increasing confidence about threats, finding relations of causality between suspicious events and eventually reconstructing multi-stage incidents. In addition, reviewing the most influential scientific papers gives us the chance to categorize the techniques and suggest practices for further implementation.
An experimental investigation of an air cooling scheme for the multichip modules of the multiplicity and vertex detector

This report presents a summary of an experimental investigation of an electronics air cooling system for the multiplicity and vertex detector (MVD), a device used to determine and characterize the collision location of two accelerated heavy ions. Measurements of the flow rates of the cooling air and the temperatures of the air and electronic components were used to assess and optimize the performance of the proposed air cooling system, identify potential assembly problems and system limitations, and provide the necessary information for designing and sizing the final MVD cooling system components.
Road Analytics for Transportation Systems using Smartphone Application

Paper presents the design of a smartphone sensing-based IoT system to collect analytical information about the condition of roads using a smartphone application. The system uses inbuilt sensors in modern smartphones to analyze the condition of roads and to classify roads into three zones - Green zone i.e. good condition road, Yellow Zone i.e. moderate condition road, and Red zone i.e. poor condition road. Green zones are the desired zones, yellow zones are zones that would need maintenance and repairs soon, and red zones are terrible roads with potholes and rough surfaces that need immediate maintenance. This information is then mapped with GPS location and stored on the cloud. This data stored in the cloud can be used by government bodies to plan developmental strategies for transportation systems. This information can also be used for smart driving applications like real-time alerts to drivers and intelligent route recommendations. Paper briefly presents the process of collecting data using smartphone sensors, processing of collected data using various algorithms, mapping of data, the transmission of data on the cloud, and visualizing collected data on GUI. A prototype of the proposed system was developed and results obtained during real-time testing of the system are presented.
Benchmark of High Level Programming : Pilot Case Vibration Control

The advancement of technology of laser pattern generators needs to meet demands of the rapid product development pace in the display and semiconductor markets. A hypothesis is that efficiency in the development process of complex systems can be improved by introducing a higher level programming approach. This will make a model and simulation based development (MBD) strategy more easy to adapt leading to 1) higher technical performance at shorter development time from idea to product introduction phase, 2) lower cost of goods, 3) shorter production-, installations- & upgrade time and 4) possibility of very efficient field support & service, etc. The success of an MBD approach is dependent on the simulation software capability to express the behavior of a real system. Consequently, as a first step towards an MBD approach, the investigation covers a pilot-study where results from simulations are compared to an existing controlled system.
e-mulate: a user-friendly software to calculate optoelectronic properties of quantum well systems

We present e-mulate, an user-friendly software developed to calculate the electronic states of quantum well heterostructures. e-mulate was designed with a graphical user interface for users without previous coding skills. The unidimensional Schrödinger equation is numerically solved using transfer matrix and Numerov algorithms in the back-end. Essential figures of merit of optoelectronic devices, such as photodetectors are provided by the software: optical transition energies with their respective oscillator strengths, the absorption and the electronic transmission spectra. A comparison between the calculated absorption and experimental results of an In0.53Ga0. 47As/In0.52Al0. 48As quantum Bragg mirror photodetectors is presented as validation of the software.
The Psychology of Thinking in Creating AI

The broad-scale emergence of AI in industry calls forth basic questions in terms of the knowledge bases and approaches relevant for its design. Engineering design has been mainly developed for electromechanical artifacts. In practice, this has meant that the scientific knowledge required for creating technical artifacts such as engines, cars, ships, cranes, telephones, radios, TVs, and simple data processing units has been natural science. However, one cannot find intelligent processes by means of physics and chemistry. Natural scientific phenomena follow their deterministic laws, but intelligence is based on selection and decision processes. The conceptual landscape of natural science is optimized for different kinds of phenomena than intelligent information processing. Consequently, the basic research under technology design should be rethought in light of the emergence of AI. To grasp intelligent information processing, we need concepts and approaches suited for the task. To create intelligent technologies on this basis, we need concepts and approaches that afford the operationalization of such information in artificial systems. We suggest that psychology of thinking and cognitive modeling provide a logical basis for future AI design.
Designing of Trans-radial Prosthetic Hand for Amputee Person

Peoples with lost body parts are increasing in today's world, resulting in considerable hikes in health-care costs. Amputations are most commonly caused by severe traumas such as those caused by accidents or war, congenital deformities, cancers, and other medical conditions like as diabetes and peripheral artery disease. In this paper, a new design of trans-radial prosthetic hand is proposed to replace a functionality and/or appearance of the missing body part. The developed design of the prosthetic hand is based on the anatomy of a human hand. The dimensions and link length ratio which were taken for designing the proposed prosthetic hand is referenced from a biological human hand. The given joint angles ensure the maximum degree of freedom of the prosthetic hand. The joint between two links is a two-point contact joint, which significantly reduces the chances of fatigue and failure of the hand. The actuation of the distal, proximal phalanx of the thumb and the metacarpal phalanx of the thumb are independent from each other. The design of the prosthetic hand is also printed with the help of a 3D printer for better analysis of the proposed work. The material used to 3D print the design is PLA material which makes the design lightweight, economic, eco-friendly and can be more beneficial to amputee person.
Electric Mobility Hosting Capacity assessment in Terni distribution network

Electric Mobility (EM) penetration consists of a challenge that Distribution System Operators (DSOs) are starting to face. The unpredictable load increase, due to EVs charging sessions, can be dangerous from the grid point of view, due to voltage violations or lines congestions. The Hosting Capacity (HC) evaluation is a fundamental need for DSO to monitor the Electric Vehicle (EVs) penetration and maintaining the secure and stable operation of the Distribution Network (DN). This paper suggests a model of end users consumption and production, necessary to make in comparison EVs requests and load/production variability. A simplified HC evaluation is proposed, through an algorithm implemented in Octave environment, to allows DSOs to easily calculate the HC with the current available dataset. The real case study of the city of Terni is analyzed, characterized by almost 40 % of the annual energy request derived from renewable sources. The total number of Charging Stations (CSs), each consisting of a pair of 22 kW charging point, results as 118, with a total installed power of about 5.2 MW. The conservative framework elaborated in the article ensure DSO the feasibility of implementation of CSs in the DN, showing the inner potential of the grid to host a relevant number of EVs in the Terni community.
Phase Shift and Amplitude Array Measurement System Based on 360° Switched Dual Multiplier Phase Detector

This article presents an amplitude and 360° phase shift array measurement system. The basic cell of the measurement system uses a novel amplitude and phase detector based on switched dual multipliers. The phase shift measurement is characterized using an analog phase detector (mixer), detecting a maximum range of ±90°, and a double multiplication of the input signals, in phase and phase shifted. This method broadens the frequency and amplitude range beyond other solutions that require fulfilling the quadrature condition. This method broadens the frequency and amplitude beyond other solutions requiring fulfilling the quadrature condition or phase and amplitude balance. Thus, it enables to compensate significant phase imbalance in the 90° hybrid or use amplitudes out of the range that ensures the switching operation of mixer diodes. The circuit calibration that allows compensation for errors (amplitude, phase shift, mismatching, etc.) is detailed, and its relation to the required measurement accuracy is discussed. The design can be easily extrapolated to other frequency ranges because it uses commercial RF devices available in a wide frequency range and avoids the need of crossing lines or complex 90° hybrid. A prototype with $3 \times 3$ cells has been built to evaluate various test conditions on $1 \times 3$ cell configurations that show the advantages of the procedure. It should be highlighted that the cell prototype uses devices that will be operating outside the frequency and amplitude ranges recommended by their manufacturers. A calibration from 2.6 to 6 GHz and −15 to −3 dBm was performed to evaluate the measurement errors. An analysis of the isolation between cells and different calibration configurations is performed to analyze the measurement errors. Measurements show compensation of +30°/−25° phase imbalance and 13-dB power lower than mixer manufacturer recommendation.
Trends of Accuracy on Diabetic Retinopathy Considering Epoch Effect and Bayes Error

Diabetes is the major cause of severe blindness among adults and the increasing diabetic population further increases the impaired vision in several people. Early detection of this disorder is important as it is incurable at an advanced stage. In this paper authors had proposed a model that uses the Transfer Learning Technique utilizing VGG-16 Network Architecture and Adam Optimization (AO) to classify the Diabetic Retinopathy and to show the nature of model accuracy considering epochs and Bayes error. Transfer learning is a technique that uses a pre-trained network before modeling. The initial layers of the Network learn the lower-level features which can be used in any other problem statement. AO results in an optimal value of parameters as it is much faster, and is a combination of two optimization algorithms namely RMS ProP and Gradient Descent with Momentum. The performance of the model is calculated using hyper parameters like activation functions, number of layers, epochs, etc. During the training of the Diabetic Retinopathy model to classify the severity of the disease, it was observed that for a constant size of CNN, with the increase of epochs the training accuracy first increases and then starts becoming constant and lastly decreases.
Energy Management of PV-Grid-Integrated Microgrid with Hybrid Energy Storage System

The short-term variability in power produced by grid-integrated photovoltaic (PV) plants can adversely affect the power quality and reliability of the system. Hence, the variability of the generated power is one of the major challenges to integrating this solar resource into the electricity grid. The irregular nature of renewable sources and unpredictable load changes require high-energy and high-power density storage devices in the current microgrid (MG) environment. In this paper, an energy management scheme (EMS) is proposed for the control of solar PV fluctuations using ramp-rate control with a hybrid energy storage system (HESS). The ramp-rate control in the system mitigates fluctuating PV power and improves system reliability. The proposed EMS has the following key advantages: effective power-sharing between energy storage devices (ESSs), faster regulation of DC-link voltage to generation and load uncertainties, effective power distribution between battery and grid-based on the battery charge state, and reduced charging/discharging rate for battery current during steady and transient state power fluctuations. The performance of the system was validated using the MATLAB/Simulink environment.
Stock Trend Prediction Using News Headlines

A stock market is a gathering of stock buyers and sellers. It displays ownership claims on firms, such as securities traded on a public stock exchange and privately traded equities. These private company shares are then sold to investors via equity crowdfunding platforms. The future movement of the stocks can be predicted by analyzing the trend based on past and current data. Without delving extensively into the basic reasons of a particular currency, technical analysis makes it simple to grasp the market's sentiments (psychology) and predict prices. By analysing share market trends, we may try to predict if a market sector that is currently growing will continue to grow in the future, or whether a market trend in one sector will start a trend in another, and so on. A lot of data is involved in the process of share market trend analysis and most technical analysts use combinations of tools such as random forest, adaboost classifier, gradient boosting, neural network, xgboost etc. to recognize the trade's potential entry and exit points. Technical analysis is frequently utilised by forex, equities, and commodities traders to determine market patterns in the short and long term. The use of technical analysis in stock market prediction is growing by the day, as more people strive to gain technical analysis abilities in order to make big money.
NAM6: Batch Code for the Navy Aerosol Model

Abstract : This report describes the operation of a computer program that calculates optical extinction according to the Navy Aerosol Model (NAM). The Navy Aerosol Model is an empirical model describing the size distribution of aerosol particles close to the surface of the open ocean. The model depends on four parameters: (1) p, the dimensionless air mass parameter; (2) W, the average wind speed (m s(-1) during the previous 24 hours; (3) w, the current wind speed (m s(-1); and (4) U, the relative humidity (%). These parameters completely specify dN/dr, the particle size distribution in the Navy Aerosol Model. The information in this report refers solely to the sixth version of the Navy Aerosol Model (NAM6), the version that is the kernel of the Navy Oceanic Vertical Aerosol Model. When NAM6 runs on a 333 MHz Pentium II computer, an input file containing a thousand lines will execute in slightly less than 1 minute. This speed is obtained with default precision settings for which the absolute accuracy is measured as approximately 5% for extinction and 10% for phase. Program precision is under the control of the user, however, and accuracy may be increased, up to a point, by increasing precision and sacrificing speed.
Relationship of SBS-symptoms and ventilation system type in office buildings

LBNL - 50046 RELATIONSHIP OF SBS-SYMPTOMS AND VENTILATION SYSTEM TYPE IN OFFICE BUILDINGS O Seppanen 1 and WJ Fisk 2 Helsinki University of Technology Helsinki, Finland Environmental Energy Technologies Division Indoor Environment Department Lawrence Berkeley National Laboratory Berkeley, CA, USA March 2002 This review was supported with a grant from the Academy of Finland and by the Assistant Secretary for Energy Efficiency and Renewable Energy, Office of Building Technology, State and Community Programs, Office of Building Research and Standards of the U.S. Department of Energy under contract No. AC03-76SF00098.
Design, Fabrication and Testing of Two Dimensional Radio-Frequency Metamaterials

Abstract : This project focused on radio frequency (RF) metamaterials (MTM) structures using two different methods: wet etching copper (Cu) on insulating glass reinforced epoxy resin (FR4) and silver nano-particle ink printed SRR meta-atoms on photo paper (Ag on paper). Once the MTMs were fabricated, RF properties were measured using a 0-4 GHz stripline and the 2-18 GHz broad antenna near-field test and measurement range two dimensional focus beam system. Through electromagnetic (EM) material property extraction of these RF measurements, the EM properties of the MTM were also shown. Three tests were employed: scattering parameter measurements, near-field testing, and empty PPWG application testing. Results from the RF testing showed that the highest performing MTM was the Ag on paper with FR4 backing. These devices performed closest to analytic modeling and showing resonance within . 4% of simulations (2.56 GHz to 2.57 GHz). This sample also displayed the best null at -21 dB, which was 3 dB lower than the Cu on FR4. These results could be used in a number of applications, including RF absorbers or RF cloaking devices. We have successfully shown a fully capable metamaterial testing system including material property extraction.
Nudging social media sharing towards accuracy

Recent work indicates that a meaningful portion of online misinformation sharing can be attributed to users merely failing to consider accuracy when deciding what to share. As a result, simply redirecting attention to the concept of accuracy can increase sharing discernment. Here we discuss the relevance of accuracy, and outline a limited-attention utility model that formalizes a theory about inattention to accuracy on social media. Research showing how a simple nudge or prompt that shifts attention to accuracy increases the quality of news that people share (typically by decreasing the sharing of false content) is reviewed. We then discuss outstanding questions relating to accuracy nudges, including the need for more work relating to persistence and habituation, as well as a dearth of cross-cultural research. We also make several recommendations for policy makers and social media companies on how to implement accuracy nudges.
Utilizing Raman Microscopy to Identify Sources of PM10 Downwind of Agricultural Operations

Title of Thesis: UTILIZING RAMAN MICROSCOPY TO IDENTIFY SOURCES OF PM10 DOWNWIND OF AGRICULTURAL OPERATIONS Qiang Huang, Master of Science, 2011 Directed By: Professor Alba Torrents Department of Civil and Environmental Engineering Emission of particulate matter (PM) from animal feeding operations (AFOs) poses a potential threat to the health of human and livestock. Current efforts to characterize PM emissions from AFOs generally examine variations in mass concentration and particle size distributions over time and space, but these methods do not provide information on the sources of the PM. Raman microscopy was employed in an innovative manner to quantify the contributions of source materials to PM10 emitted from a large cattle feedlot. Raman spectra from potential source materials were first compiled to create a spectral library. Multivariate statistical analysis model was developed to identify the source of particles collected on PM10 sample filters. Cross validation of the model resulted in 99.76% correct classification of the model spectra. Source characterization results from samples collected over a two-day period indicate that pen surface dominated in PM10 emission with unpaved road as the second biggest contributor.