Miracle-dz/UniFAR-FTUs huggingface dataset:
GEO-ENGINEERING MODELING THROUGH INTERNET INFORMATICS (GEMINI)

GEMINI (Geo-Engineering Modeling through Internet Informatics) is a public-domain web application focused on analysis and modeling of petroleum reservoirs and plays (http://www.kgs.ukans.edu/Gemini/index.html). GEMINI creates a virtual project by ''on-the-fly'' assembly and analysis of on-line data either from the Kansas Geological Survey or uploaded from the user. GEMINI's suite of geological and engineering web applications for reservoir analysis include: (1) petrofacies-based core and log modeling using an interactive relational rock catalog and log analysis modules; (2) a well profile module; (3) interactive cross sections to display ''marked'' wireline logs; (4) deterministic gridding and mapping of petrophysical data; (5) calculation and mapping of layer volumetrics; (6) material balance calculations; (7) PVT calculator; (8) DST analyst, (9) automated hydrocarbon association navigator (KHAN) for database mining, and (10) tutorial and help functions. The Kansas Hydrocarbon Association Navigator (KHAN) utilizes petrophysical databases to estimate hydrocarbon pay or other constituent at a play- or field-scale. Databases analyzed and displayed include digital logs, core analysis and photos, DST, and production data. GEMINI accommodates distant collaborations using secure password protection and authorized access. Assembled data, analyses, charts, and maps can readily be moved to other applications. GEMINI's target audience includes small independents and consultants seeking to find, quantitatively characterize, and develop subtle and bypassed pays by leveraging the growing base of digital data resources. Participating companies involved in the testing and evaluation of GEMINI included Anadarko, BP, Conoco-Phillips, Lario, Mull, Murfin, and Pioneer Resources.
Coupled Generation

Abstract Instance generation creates representative examples to interpret a learning model, as in regression and classification. For example, representative sentences of a topic of interest describe the topic specifically for sentence categorization. In such a situation, a large number of unlabeled observations may be available in addition to labeled data, for example, many unclassified text corpora (unlabeled instances) are available with only a few classified sentences (labeled instances). In this article, we introduce a novel generative method, called a coupled generator, producing instances given a specific learning outcome, based on indirect and direct generators. The indirect generator uses the inverse principle to yield the corresponding inverse probability, enabling to generate instances by leveraging an unlabeled data. The direct generator learns the distribution of an instance given its learning outcome. Then, the coupled generator seeks the best one from the indirect and direct generators, which is designed to enjoy the benefits of both and deliver higher generation accuracy. For sentence generation given a topic, we develop an embedding-based regression/classification in conjuncture with an unconditional recurrent neural network for the indirect generator, whereas a conditional recurrent neural network is natural for the corresponding direct generator. Moreover, we derive finite-sample generation error bounds for the indirect and direct generators to reveal the generative aspects of both methods thus explaining the benefits of the coupled generator. Finally, we apply the proposed methods to a real benchmark of abstract classification and demonstrate that the coupled generator composes reasonably good sentences from a dictionary to describe a specific topic of interest. Supplementary materials for this article are available online.
Flexible Sensors for Minimally Invasive Medical Instruments

Being able to measure medical parameters directly inside the body in a minimally invasive way allows for a more accurate, faster, safer and cheaper diagnosis. A typical example can be found in the diagnosis of coronary artery diseases, where simultaneous measurement of intracoronary blood flow and pressure is needed. The aim of this Thesis is to provide the technological means to implement diverse sensing functionalities, such as pressure and flow sensing, at the tip of minimally invasive medical instruments. Because of the cylindrical shape and the small diameter of catheters and guidewires (O = 1 mm and 360 µm, respectively), it is almost unavoidable that complex sensing/and or electronics systems must include flexible or foldable parts. FleXss, a Matlab-based graphical user interface was created. It allows a quick and easy analytical modeling of the stress-strain distribution in multilayered devices during and after fabrication, with the possibility to apply external bending. A generic technological platform allowing for the design, fabrication and assembly of partially flexible sensor systems at the tip of minimally invasive medical instruments was also developed. The Flex-to-Rigid (F2R) technology specifically addresses the handling and mounting issues arising when working with small, ultra-flexible devices. Moreover, the fabrication of ultra-flexible sensors requires the opening of high density vias in polyimide coatings. A two-step plasma etching recipe combining both isotropic and anisotropic profiles, resulting in residue-free wine glass shaped vias, was developed. The design of a polyimide-based 5 mm diameter flexible calorimetric flow sensor was optimized in order to fit around a medical guidewire. It was possible to successfully bend the improved flow sensor around a 360 µm wire, by keeping in the tensile plane only structures that are small compared to the bending diameter. All structures that are oriented perpendicular to the bending axis are embedded in the stress neutral plane. Numerical studies showed that the performance of the mechanically improved sensor is similar to the less flexible original device. It was moreover experimentally proven that the constant temperature sensor driving mode is superior to the constant power mode in terms of sensitivity and applicability for in-vivo use.
An analysis of precision, Fly-Through Solder Jet printing for DCA components

An analytical model of Fly-Through Solder Jet printing has been used to develop expected operating parameters and geometric configurations for solder jet printing at size scales typical of Direct Chip Attach devices. The modelling incorporates as a reference condition (reality check) the successful Fly-Through printing that has been reported for Chip Scale Package devices by Pham-Van-Diep et. al. Factors considered in the model are; targeting error, droplet in-flight cooling, electrostatic in-flight interactions, droplet aerodynamic drag, maintaining constant volume depositions by preventing impact splashing, and precision directional control of the droplet stream as the scale changes. The important factors become system constraints and are modelled as functions of system geometry and operating parameters. System configurations and operating parameters are found as a function of target size, with all of the important constraints satisfied.
Predicting Stock Market Prices using Fine-Tuned IndRNN

Prediction and analysis of stock market data have a vital role in current time’s economy. The various methods used for the prediction can be classified into 1) Linear Algorithms like Moving Average (MA) and Auto-Regressive Integrated Moving Average (ARIMA). 2) Non-Linear Models like Artificial Neural Networks and Deep Learning. In this work, we are using the results of previous research papers to demonstrate the potential of some models like ARIMA, Multi-Layer Perception (MLP) ), Convolutional Neural Neural Network (CNN), Recurrent Neural Network (RNN), Gated Recurrent Unit (GRU), Long-Short Term Memory (LSTM) for forecasting the stock price of an organization based on its available historical data. Then, implementing some of these methods to check and compare their efficiency within the same issue. We used Independently RNN (IndRNN) to explore a better efficiency for stock prediction and we found that it gives better accuracy prevailing methods in the current time. We also proposed an enhancement to IndRNN by replacing its default activation function with a more effective function called Parametric Rectified Linear Unit (PreLU). Our proposed approach can be used as an alternative method for predicting time series data efficiently other than the typical approaches today
Assessment with Portfolio and Rubric Use.

The use of portfolios and rubrics in assessment developed in part as a reaction to limitations of standardized tests for student evaluation. Portfolios relate directly to what students are learning, but there are many problems in evaluating their contents. These center on: (1) time involved in scoring; (2) lack of validity statistics; (3) relative absence of reliability data in comparison with standardized tests; (4) vagueness in reporting portfolio results; and (5) the necessity of different criteria for different products. To remedy these perceived weaknesses of the portfolio process, rubrics came into being to quantify student achievement. Rubrics, in the form of agreed-upon criteria, guide raters in assessment. Rubrics may be difficult to write and time consuming to use, but they make the portfolio evaluation process more accountable and support objective
Prediction of Best Traffic Route using Supervised Classification Machine Learning

As of now, street transport foundation neglecting to adapt up to the exponential increment in vehicular populace. To registering the quickest driving courses and mishaps within the sight of fluctuating traffic conditions is a basic issue in current route frameworks. To forestall this issue is to examine the vehicle office dataset with AI strategy for finding the best street choice without mishap estimating by forecast consequences of best exactness counts. The examination of dataset by administered AI technique(SMLT) to catch a few data resembles, variable distinguishing proof, uni-variate investigation, bi-variate and multi-variate investigation, missing worth medicines and dissect the information approval, information cleaning/planning and information perception will be done on the whole given dataset. Moreover, to think about and examine the presentation of different AI calculations from the given vehicle office dataset with assessment of GUI based UI air quality forecast by given properties.
Use of Telecom Energy for Smart Grid

With increasing electricity demand and environmental concerns, utilities are looking for improved network operations and efficient energy consumption. Telecom sites with their flexible energy storage and controllable power flows have significant potential to improve reliability, efficiency, security and quality of electricity supply in the AC distribution system. Power quality events such as voltage sags, flickers and energization of power devices cause disturbances in the operational grid. Moreover, extensive use of power electronics devices requires additional reactive power from the grid and cause distortion in the source current waveforms. These power quality problems were identified both from the literature studies and measurements obtained from Sintef Energy, a research organization in Norway. Line rectifiers are being used as grid/utility interfaces for the telecom sites. In this master thesis, an idea is proposed to replace rectifiers with bi-directional AC/DC converters. Operational control schemes for up-to three converters have been developed with the help of vector control technique. These converters with the battery banks on DC side; are not only capable of supplying power for telecommunication services but also of providing the possibility of voltage support, harmonics and reactive power compensation. Basic distribution network models were developed in the software package MATLAB/SIMULINK® to analyse the impact of connected telecom converters both for the voltage support and ancillary services. Simulations were performed and it was observed that the Total Harmonic Distortion (THD) was reduced to maximum 3.4%, reactive power drawn from the grid became zero and voltage dip in case of wind distributed generation rises from 83.5% to 97.5% when three Telecom sites started supporting the grid. It was also seen that with proper energy management system, Telecom sites can also support utilities by supplying active power during peak hours load demand and for islanding operation. THD level within the IEEE, IEC, EN power quality standards, compensation of reactive power and provision of voltage support prove that the efficiency of a network can be improved by properly implementing Smart Grid together with the support from distributed telecom sites. Keywords: Smart Grid, power quality issues, Telecom Power Infrastructure, power electronics, voltage source converter, vector oriented control, harmonics, active and reactive power, voltage support.
Herb ontology : maturity-based analysis of lightweight ontology on herb usages

Ontology serves as a basis for denominating objects in a certain domain. A lightweight ontology is built using classes, instances and relationships and does not include any axiomatic definitions such as the ones found in heavyweight ontology.However, the lightweight ontology needs to be matured in order to detail the concepts and relationship that occur in a domain. To date, there is no suitable ontology design that exists in the herb domain and a design that is measured due to the heterogeneity of the ontology structures. In this study, a lightweight ontology specializing in herbal domain known as Herb Ontology (HO) is developed to explore the complete use of herbs based on their profiles. It began with the design of an informal domain modelling followed by an informal HO design that would manipulate the Unified Modelling Language (UML) notations to highlight the functionality, services and procedural strategies. In conjunction with that, eleven ontology metrics covering three maturity principles namely: reuse, extend and evolve are presented in this study. The principles are measured in both class-level and ontology-level so that different aspects of the ontology designs can be evaluated and would aid in controlling the development process of HO. Besides that, the HO design was compared with other types of ontology such as COIN, Gene Ontology and OntoCAPE. It was found that HO has Inheritance Richness = 0.99301 with the potential to be reused and a denser network ontology (Edge Node Ratio = 1.84) indicating the possibility of HO being extended and evolved. The results have proven that this proposed HO design has compiled herb usage for use by conventional and modern herbalists.
Profile of Children Treated for Uncomplicated Intussusception in a Tertiary Hospital in Enugu, Nigeria

Intussusception is the invagination of a segment of the bowel into another segment. The part of the bowel that invaginates is the intussusceptum while the part that receives the invaginating segment is the intussuscipiens [1]. Intussusception is a pediatric abdominal surgical emergency and one of the most common causes of intestinal obstruction in infants [2]. The clinical presentation of intussusception may vary from one patient to another. However, classically, the symptoms of intussusception include abdominal pain, vomiting and passage of red currant jelly stool [3]. However, these classical symptoms are found only in about 20 percent of the patients [4]. Abdominal ultrasound is diagnostic imaging of choice for the diagnosis of intussusception due to its high sensitivity and specificity [5]. Treatment of intussusception in children could be nonoperative or operative. Non-operative treatment is in the form hydrostatic (using normal saline, Hartmann’s solution or barium) or pneumatic reduction (using air) [6]. Operative treatment of intussusception is indicated in the following conditions: failed hydrostatic reduction, features of peritonitis or marked abdominal distension [6]. Children with intussusception who present early are treated non-operatively with little or no complications. However, only a few patients present early most likely due to poverty and low levels of enlightenment. The aim of study was to evaluate our experience in the management of children who presented with uncomplicated intussusception. For the purposes of this study, uncomplicated intussusception refers to intussusception without intestinal gangrene, without perforation and without features of peritonitis. Abstract
Mechanical Ice Release Processes. I. Self-Shedding from High-Speed Rotors,

Abstract : Ice accreted on high-speed rotors operating in supercooled fog can be thrown off by centrifugal force, creating severe unbalance and dangerous projectiles. A simple force balance analysis indicates that the strength of accreted ice and its adhesive strength can be obtained by measuring the thickness of the accretion, the location of the separation, the rotor speed, and the density. Such an analysis was applied to field and laboratory observations of self-shedding events. The results agree reasonably well with other observations. (Author)
Definition and Measures of Individual and Unit Readiness and Family Phenomena Affecting It

Abstract : The Army Family Research Program (AFRP) is a 5-year integrated research program that supports the Chief of Staff of the Army (CSA) White Paper 1983: The Army Family and The Army Family Action Plans (1984-1990) by developing databases, models, program evaluation technologies, and policy options that assist the Army to retain quality soldiers, improve soldier and unit readiness, and increase family adaptation to Army life. This report documents the development of operational definitions and measurement instruments to assess individual and unit readiness. The developmental process included a review of literature, soldier readiness workshops to identify the dimensions, and spouse workshops.
A Computationally Efficient Free Energy Model for Shape Memory Alloys - Experiments and Theory

HEINTZE, OLAF. A Computationally Efficient Free Energy Model for Shape Memory Alloys Experiments and Theory. (Under the direction of Dr. Stefan Seelecke.) Shape memory alloys (SMA) belong to the class of active materials and have recently been considered as novel actuation and damping mechanisms in microand macro-scale applications. Combined with their advantageous lightweight and high work output characteristics is a complex, highly non-linear and hysteretic material behavior, which is also thermo-mechanically coupled. Due to this complexity, model development for SMAmaterial behavior is a challenging task, and experimental data in particular about the inner hysteresis loops is necessary to gain further understanding and successfully design applications. In this thesis, a single crystal material model is presented and subsequently extended to the more realistic polycrystalline case considering material inhomogeneities, grain impurities and lattice imperfections. A first implementation, based on a stochastic homogenization procedure, provides a very accurate description of the observed phenomena, but also requires very high computation times. A reformulation of the underlying concept leads to a parameterization method, which preserves the advantages of the original method, but dramatically reduces the computation times. It is shown that the material behavior prediction of both models are identical, and the parameterization method is compared extensively to data from tensile experiments with a pseudoelastic SMA wire. Remarkably, the model is able to capture all facets of the material behavior including rate-dependence and minor loops. The versatility of the model also allows for the simulation of SMA actuator behavior including the electrical resistance. Finally, a MEMS device using polycrystalline SMA thin film actuators is experimentally investigated. As a first step, the material behavior of the SMA thin films is presented using strain-temperature and resistance-temperature measurements. Secondly, the performance of the MEMS device was determined for different driving frequencies. A COMPUTATIONALLY EFFICIENT FREE ENERGY MODEL FOR SHAPE MEMORY ALLOYS EXPERIMENTS AND THEORY
Total Engagement: Using Games and Virtual Worlds to Change the Way People Work and Businesses Compete

Can the workplace be more productive by including avatars, three-dimensional environments, and participant-driven outcomes? This grounded and thought-provoking book by Byron Reeves and Leighton Read proves that it is not only possible, it is inevitable. Implementing components of multiplayer computer games in the workplace will address a host of age-old problems. Games can not only stem boredom and decrease turnover, but also enhancee collaboration and encourage creative leadership. Games require extraordinary teamwork, elaborate data analysis and strategy, recruitment and retention of top players, and quick decision making. Recreating some elements of games - such as positioning tasks within stories, creating internal economies, and implementing participant-driven communication systems - can not only boost employee engagement but overall productivity. Of course, the strong psychological power of games can have both positive and negative consequences for the workplace. That's why it's important to put them into practice correctly from the beginning - and Reeves and Read explain how by showing which good design principles are a powerful antidote to the addictive and stress-inducing potential of games. Supported by specific case studies and years of research, Total Engagement will completely change the way you view both work and play.
The Movement Characteristics of Suspended Solid(SS) in Harbor Construction(I) - In a Riprap Work -

This paper intends to analyze the movement characteristics of the suspended solid(SS) generated in a riprap work which is the most widespread process in harbor construction. The generation and movement behaviors of SS are investigated when 1) basic ripraps (0.001~0.03㎥) are cast for breakwater construction, 2) ripraps are loaded on carrier for riprap casting in the sea-wall construction of dredged material pocket, and 3) ripraps for inner filling are cast. The result of the present study shows that the SS generation is considerable when basic ripraps are cast for breakwater construction and the SS diffusion reaches up to 500m in high tide period. When ripraps are loaded on carrier, the SS is generated by the ripraps running down into sea from carrier, thereby showing a high concentration of SS in the vicinity of carrier. In the surface layer, SS distribution is confined in the vicinity of the carrier due to the prompt sinking of the SS. However the SS in the bottom layer is diffused approximately up to loom and then the SS concentration reaches to the background one. In the riprap (less than 0.03㎥) casting for inner filling using pork crane, SS is diffused approximately up to 300m in the surface layer and more than 300m in the bottom layer. It is quite interesting that the movement of the SS generated in harbor construction is mainly controlled by wind drift in the surface layer and tidal current in the bottom layer, and also the diffusion range of SS in the bottom layer is much larger than that in the surface layer.