Miracle-dz/UniFAR-FTUs huggingface dataset:
Using Artificial Neural Networks To Forecast Financial Time Series

This thesis investigates the application of artificial neural networks (ANNs) for forecasting financial time series (e.g. stock prices). The theory of technical analysis dictates that there are repeating patterns that occur in the historic prices of stocks, and that identifying these patterns can be of help in forecasting future price developments. A system was therefore developed which contains several ``agents'', each producing recommendations on the stock price based on some aspect of technical analysis theory. It was then tested if ANNs, using these recommendations as inputs, could be trained to forecast stock price fluctuations with some degree of precision and reliability. The predictions of the ANNs were evaluated by calculating the Pearson correlation between the predicted and actual price changes, and the ``hit rate'' (how often the predicted and the actual change had the same sign). Although somewhat mixed overall, the empirical results seem to indicate that at least some of the ANNs were able to learn enough useful features to have significant predictive power. Tests were performed with ANNs forecasting over different time frames, including intraday. The predictive performance was seen to decline on the shorter time scales.
Entrepreneurial Orientation Instrument (EOI): Integrating mixed mode of research in instrument construction

There are quite a few instruments exists in the literature to measure the concepts of entrepreneurial orientation of university students.Meanwhile, the employed variables and their appropriateness to contextualize the topic within industries and the education sectors, have created confusion.These variances evidently may be observed and applicable in the context of western perspective using the existing instruments. However, they cannot apply in the context of eastern perspective when they gain validity and reliability.In this context, an instrument was developed to measure factors of entrepreneurial orientation and particularly focusing on individual factors, in the education sector. The process of instrument development was initially conducted through qualitative method and followed the by quantitative method. The study adopted various techniques including content analysis, and personal interviews with the students, followed by focused group discussion and Delphi technique with expert.After identifying the variables through Delphi technique, the variables were tested to meet the validity and reliability through quantitative method.This study utilized content, construct and face validity to validate sub-factors and items generated in the instrument.It was finalized that there are 39 items under 6 sub-factors of entrepreneurial orientation.
EVALUATION OF SUPPLIERS UNDER UNCERTAINTY: A MULTIPHASE APPROACH BASED ON FUZZY AHP AND FUZZY EDAS

A decision-making process requires a prior definition and fulfilment of certain factors, especially when it refers to complex fields such as supply chain management. One of the most important items in the initial stage of a supply chain, which strongly influences its further flow, is making a decision on the most suitable supplier. In this paper, a model for evaluation and supplier selection has been proposed, which has been considered in more than ten different production areas. The model consists of twenty quantitative and qualitative criteria, which are reduced to a total of nine by the application of the fuzzy AHP and the assessment of managers in production companies. The verification of the model has been presented throughout a selection of suppliers in a company for the production of plastic bags and foils, where the Fuzzy Analytic Hierarchy Process (Fuzzy AHP) method has been used to determine the significance of the criteria, and the Fuzzy Evaluation based on Distance from Average Solution (Fuzzy EDAS) to evaluate and select suppliers. The obtained results have been considered throughout a sensitivity analysis in which a total of 15 different scenarios have been formed and where the stability of the model has been determined, since the supplier one is the best solution in all the cases.
Validation of Distributed Topology Inference of Distribution Networks usingthe IEEE Reliability Test System

Reliability of power system depends on the up to date knowledge of the system state for operation and control. Shifting from large conventional production units to small and/or renewable DG connected in the distribution network means more control and monitoring system require for the Distributed System operator caused by active generation and reactive power consumption by DG. Therefore it is interesting to explore concepts in fast and scalable topology processors for monitoring and controlling applications such as state estimation, OPF and static and dynamic stability assessment in electrical distribution network the need is evident to validate with meshed network to analyze the overall performance of the proposed methodology\Decentralized Topology Inference of Electrical Distribution Networks". The topology inference processor is require minimal prior knowledge of electrical network structure by taking a series of time-stamped process measurements from each bays of each substation in the network and distinguished between connected and unconnected bays. This master thesis project has implemented an IEEE reference electric power distribution network in Simulink platform , integrating the reference electrical network with the Java-based multi agent topology inference application as well as having investigated. This project has included work in the real time simulation of a standard IEEE reference distribution network, OPC server interfacing between reference model and the topology inference application, testing and analysis of the application. The reference model is selected to provide a sucient case to analyses and validate the methodology.
The Sarbanes-Oxley Debacle: What We've Learned; How to Fix it

This Abstract introduces the authors' new book, The Sarbanes-Oxley Debacle: What We've Learned; How to Fix It (The AEI Press 2006). The Sarbanes-Oxley Act of 2002 ("SOX") is a colossal failure, poorly conceived and hastily enacted during a regulatory panic. Everyone now concedes that the direct compliance costs of SOX have been much greater than anticipated. While that alone should give any serious policy analyst pause, the Act's defenders press the case that SOX was worth its problems. This book demonstrates that the supporters are wrong in their assessment: Both logic and evidence make it clear that SOX was a costly mistake.
Multivariate statistical analysis for damage and delamination in composite structures

The article is devoted to the analysis of the vibration response of composite laminates . Our aim is to develop a method for analysis of the vibration response of structures made of composites which will also be used to develop a vibration-based health monitoring procedure for such structures. Composite materials and composite laminates in particular, exhibit complex dynamic behaviour which on most occasions cannot be modelled linearly. Delamination introduces additional nonlinearities in the vibration behaviour of the structure as a result of the interrupted contact between the layers or the opening and closing of the delamination. Thus conventional linear structural dynamics methods like modal analysis cannot be applied. In this study, the vibration response signals are recorded from damaged and non-damaged (healthy) laminated composite beams. The frequency domain signals are subjected to a special type of Principal Component Analysis, known as Multichannel Singular Spectrum Analysis (MSSA). This type of analysis is known to uncover oscillation patterns and was suggested in the investigation in place of modal analysis. The idea is to establish a new feature based state-space for the vibration response signal. The response of the healthy structure is used as a baseline to which all the responses are compared. MSSA decomposes the signal into new components which are lineal combinations of the original frequency series components. The first several components are responsible for most of the variance of the original signal. The new space is with a much smaller dimension as compared to the original data and creates new variables which can be used as damage features. The results demonstrate strong potential for using MSSA for the purpose of structural health monitoring.
Impressionable Voters

We propose a model of impressionable voters. Impressionable voters vote based on impressions rather than maximizing expected utility. We apply our model to elections with multiple candidates and solve for the stationary distributions of the implied stochastic process. In elections with two candidates, we find that impressionable voters select the candidate that maximizes utilitarian welfare. In multi-candidate elections, Condorcet winners are elected provided that a majority of voters is able to sufficiently distinguish competing candidates. In such cases, models with impressionable voters may have better normative properties than models with rational voters. (JEL D71, D72, D91)
BRI-STARS (BRIDGE STREAM TUBE MODEL FOR ALLUVIAL RIVER SIMULATION)

This NCHRP digest describes the BRIdge Stream Tube model for Alluvial River Simulation (BRI-STARS), Version 3.3, an innovative, operational computer program developed for NCHRP Project 15-11, "Computer-aided Analysis of Highway Encroachments on Mobile Boundary Streams". It is a semi-two-dimensional model capable of computing alluvial scour/deposition through subcritical, supercritical, and a combination of both flow conditions involving hydraulic jumps. This model, unlike conventional water and sediment routing computer models, is capable of simulating channel widening/narrowing phenomenon as well as local scour due to highway encroachments. It couples a fixed-width stream tube computer model, which simulates the scour/deposition process taking place in the vertical direction across the channel, with a total stream power minimization algorithm. The decision making algorithm, using rate of energy dissipation or total stream power minimization, determines whether the simulated sediment erosion satisfying the sediment continuity equation should take place in the lateral or vertical direction. It is this second component that allows the lateral changes in channel geometries. Finally, the bridge component allows computation of the hydraulic flow variables and the resulting scour due to highway encroachments. The model also contains a rule-based expert system program for classifying streams by size, bed and bank material stability, platform geometry, and other hydraulic and morphological features.
Simulation based characterization and performance enhancement of heterogeneous polymer solar cells

Low cost per watt and mechanical flexibility of organic solar cells (OSC) make it a promising alternative to traditional inorganic solar cells. Recently, conjugated polymer based organic solar cells with efficiency of 8.13% [16] have been reported. Experimental results suggest that the distribution of the donor and acceptor constituents in the morphology is a key factor in determining the efficiency of such devices. A computational framework that can effectively explore that correlation between morphology and performance would greatly accelerate the development of high efficiency organic photovoltaic devices. In this paper, we develop a scalable computational framework to understand the correlation between nanoscale morphology and performance of OSC. We focus on the charge transport mechanism while considering one-stage interfacial charge generation process. Steady state driftdiffusion equations are used for modeling these devices. We discuss the numerical challenges associated with a finite element based simulation of OSC with spatial variation in material properties and large charge density gradients. The effect of microstructure on the distribution of charge densities and electrostatic potential is investigated. The prominent effect of feature size and interface area on the current-voltage characteristics is illustrated using realistic microstructures. We showcase the framework by interrogating fully 3D heterogeneous
Study of Warm, Pre-Wetted Sanding Method at Airports in Norway

This report describes the study of a new sanding method that has been adopted at different Norwegian airports. The new method is based on wetting the sand with hot water before applying it onto the runway surface. It results in a sanding pattern where the particles are bonded to the surface, creating a sandpaper-like appearance. The aim of the study is to improve general knowledge about this warm, pre-wetted sanding method for airside and road applications. A diversity of aspects are addressed, such as its performance in practice, how and why it works, optimization, possible negative effects, and limitations. Data was collected during a six-week field study at three different airports and during a testing workshop for warm, pre-wetted sand spreaders.
Toward Robust Classifiers for PDF Malware Detection

: Malicious Portable Document Format (PDF) files represent one of the largest threats in the computer security space. Significant research has been done using handwritten signatures and machine learning based on detection via manual feature extraction. These approaches are time consuming, require substantial prior knowledge, and the list of features must be updated with each newly discovered vulnerability individually. In this study, we propose two models for PDF malware detection. The first model is a convolutional neural network (CNN) integrated into a standard deviation based regularization model to detect malicious PDF documents. The second model is a support vector machine (SVM) based ensemble model with three different kernels. The two models were trained and tested on two different datasets.The experimental results show that the accuracy of both models is approximately 100%, and the robustness against evasive samples is excellent. Further, the robustness of the models was evaluated with malicious PDF documents generated using Mimicus. Both models can distinguish the different vulnerabilities exploited in malicious files and achieve excellent performance in terms of generalization ability, accuracy, and robustness.
W-CDMA and cdma2000 for 3G Mobile Networks

From the Publisher: This book gives network managers and 3G workers a select background in spread spectrum technology, empowering them to make real-world design, purchasing, and deployment decisions. Assuming only that W-CDMA is the preferred interface, the authors make a point of grounding 3G technologies in the fundamentals of propagation characteristics, physical layer functionalities, and spectrum requirements, so readers can confidently tackle soft handover, power control, sectorization, and message flows.
Cloth simulation by isogeometric analysis

This thesis aims to develop a design-oriented simulation approach for cloth analysis. Our approach is built on the framework of NURBS-based isogeometric analysis, which utilizes NURBS as the basis functions of analysis. NURBS is a class of parametric geometry to represent curves and surfaces in computer-aided design (CAD) programs. Recently, NURBS geometry has been used directly in analysis. The overall goal of this thesis is to develop a computation infrastructure that enables cloth analysis directly on NURBS geometry. The advantage of NURBS in the context of cloth modeling lies in the geometric smoothness. Using NURBS, it’s easy to construct surfaces with C or higher order of continuity. Compared to C finite element geometry, the NURBS geometry is more effective in capturing wrinkles and folders of cloth, which are characteristics of cloth motion. The NURBS geometry enables the use of rotation-free KirchhoffLove shell. The rotation-free shell model not only saves freedoms, but also makes the contact/impact treatment much easier. The major contribution of this work is the development of a NURBS cloth modeling approach. The mechanical model of cloth and its implementation with NURBS geometry will be presented in detail. Proper constitutive laws are employed for fabric materials. Since NURBS geometry from CAD typically contains multiple patches and trimmed patches, a certain treatment is proposed so that geometry can be used directly in analysis.
COVID 19 RISK ASSESSMENT AS A STRENGTHENING OF EARLY AWARENESS AND RESPONSE SYSTEMS WITH THE PERSONAL INARISK APPLICATION

The limited management of the surveillance system in Trenggalek caused the absence of an early warning alert and response system (EWARS) if the infectious disease situation leads to outbreaks. The current condition in the community, that there were still many confusing issues related to Covid19, which caused paranoia to occur. It will be difficult to do early detection and immediate treatment as a form of prevention of severity. Using the InaRISK Personal application, participants were invited to conduct an independent assessment of Covid19 transmission risks. Providing materials, mentoring, and evaluating, did this method. The results knew that participants feel the use of the application in awareness and preventing the transmission of Covid19. However, there were still complaints about application operations, such as disturbances, errors, and difficulty in determining the location point. Therefore, it is necessary to improve the functions and features of the application, which are used easily and comfortably.
Foster

Confidence assessment (CA), in which students state alongside each of their answers a confidence level expressing how certain they are, has been employed successfully within higher education. However, it has not been widely explored with school pupils. This study examined how school mathematics pupils (N = 345) in five different secondary schools in England responded to the use of a CA instrument designed to incentivise the eliciting of truthful confidence ratings in the topic of directed (positive and negative) numbers. Pupils readily understood the negative marking aspect of the CA process and their facility correlated with their mean confidence with r = . 546, N = 336, p < . 001, indicating that pupils were generally well calibrated. Pupils’ comments indicated that the vast majority were positive about the CA approach, despite its dramatic differences from more usual assessment practices in UK schools. Some pupils felt that CA promoted deeper thinking, increased their confidence and had a potential role to play in classroom formative assessment.
Determinants of Small Holder Rural Farm Households’ Participation in Small Scale Irrigation in Western Ethiopia, in Case of Assosa District in Assosa Zone (Heckman Two-Stage Model)

Increasing technology adoption including irrigation among smallholder farmers has a big potential to uplift living standards of poor through increasing production and consumption pattern. The objective of this study was analyzing determinant of smallholder farmer participation in small scale irrigation and its intensification in western Ethiopia, in case of Assosa district in Assosa Zone. The study used data from 329 respondents from six selected kebeles of Assosa woreda in Assosa zone, through structured questioner. The descriptive statistics and Heckman two stage econometric methods were employed to analyze data collected from sampled household. The significance of coefficient of inverse Mill’s ratio (  ) indicates the presence of selection bias and the effectiveness of applying Heckman two stage model. In the first stage of probit regression results of study show that the adoption decision of small scale irrigation use were driven by factors such as sex of the head, education, farm size, attend training at farmer training center, distance to irrigation, credit use, total livestock unit, ethnicity, active labor and development agent advice significantly determine participation in small scale irrigation. In the second stage, the intensification of small scale irrigation use was influenced by family size, credit use, ethnicity of farm household head and lambda. The policies which expand the accessibility of credit service, dissemination of productive agricultural technology information, and creating opportunity of education for farm household has potential to increase the chance of small scale irrigation adoption decision and strengthen the level of adoption among smallholder farmers.
Efficient Layout Analysis of Ancient Manuscripts Using Local Features

Layout analysis is the first step in the process of document understanding; it identifies regions of interest and hence, serves as input for other algorithms such as Optical Character Recognition (Ocr). A binarization-free layout analysis method for ancient manuscripts is proposed, which identifies and localizes layout entities exploiting their structural similarities on a local level. The dataset, the method is evaluated on, is an ancient manuscript originating from the 11 century, discovered at St. Catherine’s monastery on Mt. Sinai, Egypt, in 1975 and digitized in the course of The Sinaitic Glagolitic Sacramentary (Euchologium) Fragments Project. It is written Glagolica, the oldest known Slavonic alphabet. The document layout computed allows scholars to establish the spatio-temporal origin, authenticate, or index a document. The layout entities considered in this approach include body text, embellished initials, plain initials and headings. These textual elements are disassembled into segments, and a part-based detection is done which employs local gradient features known from the field of object recognition, the Scale Invariant Feature Transform (Sift). These features describe the structures in a scale-, rotationand illumination invariant manner. Hence, this approach does not rely on a binarization step but is directly applied to the gray scale image, and furthermore it is robust to variations in shape, illumination, writing orientation and (background) noise. Thus, it is suitable for ancient handwritten documents with varying layouts and degradation effects. As the whole entity cannot directly be inferred from the mere positions of the interest points, a localization algorithm is needed that expands the interest points according to their scales and the classification score to regions that encapsulate the whole entity. Hence, a cascading algorithm is proposed that successively rejects weak candidates applying voting schemes. The evaluation shows that the method is able to locate main body text in ancient manuscripts. The detection rate of decorative entities is not as high as for main body text but already yields to promising results.
Survival at Sea for Mariners, Aviators and Search and Rescue Personnel (RTO-AG-HFM-152)

This AGARDograph summarizes the current scientific knowledge of sea survival for mariners, aviators, search and rescue technicians and medical staff. The text discusses key issues such as drowning through cold shock and swimming failure induced by immersion in water particularly below 15 Celsius, survival prediction curves and non-freezing cold injuries. It emphasizes the importance of integrating good human engineering practices at the beginning of a project involving survival equipment such as lifejackets, life rafts and lifeboats. Manikin testing to evaluate survival suit insulation is described. The latest helicopter ditching statistics and helicopter underwater escape protocols are presented. Practical advice is given on the causes and treatment of seasickness. Finally a discussion is had on the importance of understanding how humans mentally process information under stress and why this should be included in every survival school curriculum.