Miracle-dz/UniFAR-FTUs huggingface dataset:
ELLIPTICAL GATE MOSFETS A MODELING APPROACH

The demand for higher current drives, better short channel characteristics has led to the evolution of multiple gate mosfets from classical single gate devices. Silicon gate all around mosfets(GAA) offers maximum gate control over the channel which makes them an excellent choice among non classical MOS devises. However GAA mosfets with circular cross sections are not common in real fabrication. Elliptical Cross sections have been reported. In this paper new modeling approach for elliptical GAA have been investigated, dependence of physical properties of a device on the behavior of multiple gate devices have been discussed.
DETECTING HEAD MOVEMENT USING GYROSCOPE DATA COLLECTED VIA IN-EAR WEARABLES Islam A. (2021) Detecting Head Movement Using Gyroscope Data Collected via In-Ear Wearables. University of Oulu, Degree Programme in Computer Science and Engineering, 71 p. TABLE OF LIST OF ABBREVIATIONS

Head movement is considered as an effective, natural, and simple method to determine the pointing towards an object. Head movement detection technology has signiﬁcant potentiality in diverse ﬁeld of applications and studies in this ﬁeld verify such claim. The application includes ﬁelds like users interaction with computers, controlling many devices externally, power wheelchair operation, detecting drivers’ drowsiness while they drive, video surveillance system, and many more. Due to the diversity in application, the method of detecting head movement is also wide-ranging. A number of approaches such as acoustic-based, video-based, computer-vision based, inertial sensor data based head movement detection methods have been introduced by researchers over the years. In order to generate inertial sensor data, various types of wearables are available for example wrist band, smart watch, head-mounted device, and so on. For this thesis, eSense - a representative earable device - that has built-in inertial sensor to generate gyroscope data is employed. This eSense device is a True Wireless Stereo (TWS) earbud. It is augmented with some key equipment such as a 6-axis inertial motion unit, a microphone, and dual mode Bluetooth (Bluetooth Classic and Bluetooth Low Energy). Features are extracted from gyroscope data collected via eSense device. Subsequently, four machine learning models - Random Forest (RF), Support Vector Machine (SVM), Naïve Bayes, and Perceptron - are applied aiming to detect head movement. The performance of these models is evaluated by four different evaluation metrics such as Accuracy, Precision, Recall, and F1 score. Result shows that machine learning models that have been applied in this thesis are able to detect head movement. Comparing the performance of all these machine learning models, Random Forest performs better than others, it is able to detect head movement with approximately 77% accuracy. The accuracy rate of other three models such as Support Vector Machine, Naïve Bayes, and Perceptron is close to each other, where these models detect head movement with about 42%, 40%, and 39% accuracy, respectively. Besides, the result of other evaluation metrics like Precision, Recall, and F1 score veriﬁes that using these machine learning models, different head direction such as left, right, or straight can be detected.
Creative Adaptation through Learning

Robots have transformed many industries, most notably manufacturing, and have the power to deliver tremendous benefits to society, for example in search and rescue, disaster response, health care, and transportation. They are also invaluable tools for scientific exploration of distant planets or deep oceans. A major obstacle to their widespread adoption in more complex environments and outside of factories is their fragility. While animals can quickly adapt to injuries, current robots cannot “think outside the box” to find a compensatory behavior when they are damaged: they are limited to their pre-specified self-sensing abilities, which can diagnose only anticipated failure modes and strongly increase the overall complexity of the robot. In this thesis, we propose a different approach that considers having robots learn appropriate behaviors in response to damage. However, current learning techniques are slow even with small, constrained search spaces. To allow fast and creative adaptation, we combine the creativity of evolutionary algorithms with the learning speed of policy search algorithms through three contributions: the behavioral repertoires, the damage recovery using these repertoires and the transfer of knowledge across tasks. Globally, this work aims to provide the algorithmic foundations that will allow physical robots to be more robust, effective and autonomous.
A completely unique account of enumeration

How can we enumerate the inhabitants of an algebraic datatype? This paper explores a datatype generic solution that works for all regular types and indexed families. The enumerators presented here are provably both complete and unique—they will eventually produce every value exactly once—and fair—they avoid bias when composing enumerators. Finally, these enumerators memoise previously enumerated values whenever possible, thereby avoiding repeatedly recomputing recursive results.
Vibration Control of Flexible Structures Based on Impedance Matching Index

Abstract This paper is concerned with a new feedback control design methodology for vibration control of flexible structures by the wave control. In the wave control, controllers are usually designed to minimize the reflection coefficient based on the wave analysis. However, because the method utilizes the wave analysis directly, it has been mainly applied to simple uniform structures, and control design method with some other control objectives has not been established yet. In this paper, aiming to establish a control design method for more complex systems and more complex control design, we propose a method based on the impedance matching index, which represents the difference of the transfer functions between the closed system and the controller. The index is motivated by the wave analysis and control for the uniformly varying ladder networks, an electric circuit analogy of a class of mechanical systems. As a design example for vibration control of mechanical systems, optimal tuning of the passive damper and the dynamic absorber by the index is conducted in the numerical example.
PERFORMANCE ASSESSMENT OF A FLOATING PLATFORM SURROUNDED BY ELASTIC ICE PLATES

Oil and gas resources are abundant in the Arctic. In recent decades, with global warming and the melting of polar ice coverages, the Arctic marginal ice zone (MIZ) has gradually expanded, particularly in summer [1]. It is therefore more accessible to carry out oil and gas exploitation in the region. However, different from open water, the design of floating platforms in a polar sea state must consider the influence of floating ices. Previous studies have shown that the existence of elastic ice floes has complex effects on the water wave characteristics [2], [3]. Thus, for ensuring the structural safety of polar floating platforms, it is essential to assess the hydrodynamic loads combining with sea ice effects. Until now, there is little research on wave-ice-structure interactions. The majority of previous work relied on analytical methods [4], [5], including two-dimensional linear potential flow theory and linear elastic theory. Meanwhile, studies on the interaction between waves and ice floes have made considerable progress [6], [7]. For the last several years, numerical approaches have been significantly developed and show the potential to improve the accuracy by accounting for nonlinear features that are excluded in analytical solutions. In such a context, this study establishes a two-dimensional numerical structure-ice-wave interactive model based on OpenFOAM. The layout of the model is shown in Figure 1. Water waves are generated from the left-hand side and propagate towards the right-hand-side. A two-way fully fluid-structural coupling algorithm is applied to simulate the interaction between elastic floating ice floes and waves [8], [9]. The associated hydrodynamic effects on the floating platform are investigated systematically, considering different distribution modes and stiffness of elastic ice floes and incident wave frequencies. More detailed results will be presented in the full-length paper.
Building robust web-based systems by managing exceptions through logging, reporting and analysis

Software systems will never be free from bugs since dynamic operating environments will introduce operating errors. Deployed Web-based applications could be made more useful and robust by planning exceptions handling during development phase. Under deployment, errors should be log for reporting and analysis. Error messages should make sense to the users and should not expose the system internals. Exception handling needs to be carefully planed.
Facial Expression Recognition Using AI

: The emotions evolved in face have an excellent influence on decisions and arguments about various subjects. In psychological theory, emotional states of an individual are often classified into six main categories: surprise, fear, disgust, anger, happiness and sadness. Automatic extraction of those emotions from the face images can help in human computer interaction also as many other applications. Machine learning algorithms and particularly deep neural network can learn complex features and classify the extracted patterns. In this paper, a deep learning based framework is used for human emotion recognition. The proposed framework uses the feature extraction then a Convolutional Neural Network (CNN) for classification. The experimental results show that the proposed methodology increases both of the speed training process of CNN and therefore the recognition accuracy.
A Study on Emotional Labour among Teaching Professionals in an Indian Context

: Emotional intelligence is one person behaving in accordance with the other person’s emotions. This by itself is in a way Emotional Labour prohibiting display of actually felt emotions. The consequences of this is more significant in the superior subordinate relationship that prevails in the workplace because of contradictions that may arise in day to day workplace issues which demands execution of emotional and intellectual decisions from either sides. The researcher made an attempt to study the emotional aspects of the teaching faculty members in schools and colleges. The researcher choose 112 private school teachers and 112 private college faculty members for the present study using purposive sampling technique by non-probability method. The samples were chosen from a metropolitan city Chennai which has cosmopolitan crowd of people representing all states of the country. Hence, the findings of the study can be generalized to whole of the country as the opinion of academicians. The findings of the study are discussed in detail in the paper.
OCT signal enhancement with deep learning 1

Purpose: To establish whether deep learning methods are able to improve the signal-to-noise 12 ratio of time-domain (TD) optical coherence tomography (OCT) images to approach that of 13 spectral-domain (SD) OCT. Design: Method agreement study and progression-detection in a randomized, double-masked, 15 placebo-controlled, multi-centre trial for open-angle glaucoma (OAG) [UK Glaucoma Treatment 16 Study (UKGTS)]. 17 Participants: Cohort for training and validation: 77 stable OAG participants with TDOCT and 18 SDOCT imaging at up to 11 visits within 3 months. Cohort for testing: 284 newly-diagnosed OAG 19 patients with TDOCT from a cohort of 516 recruited at 10 UK centres between 2007 and 2010. 20 Methods: An ensemble of generative adversarial networks (GANs) was trained on TDOCT and 21 SDOCT image pairs from the training dataset and applied to TDOCT images from the testing 22 dataset. TDOCT were converted to synthesized SDOCT images and segmented via Bayesian fusion 23 on the output of the GANs. Main analysis to assess between TDOCT and synthesized SDOCT average retinal nerve fibre layer
The Determinants of Government Bond Market Development in Asean+3

: This study aims to demonstrate the determinants of government bond market development in ASEAN+3 countries. The data is collected from 3 non-ASEAN countries and 6 ASEAN countries. There are eight factors being considered as the size of the economy, exchange rate fluctuation, the level of financial integration, the fiscal balance, banking size, deposit and lending interest rates spread, the level of monetary freedom and the stage of country’s development. The results show the positive impact of economic size, integration level and stage of development on government bond market’s size. In contrast, the balance of state budget and the interest spread have significant negative influence on the development of government bond market. This paper could not find significant relationship between exchange rate variability, banking size and size of this market. The research’s results are suggestion to develop government bond market in ASEAN+3 countries and for further researches in the future.
A novel mechanism for left-right asymmetry establishment involving tissue remodeling and MyoID

How novel left-right asymmetries evolve in animals is unknown. Drosophila pachea males display a unique left-right asymmetry in the genital organs and mate in a right-sided position onto the female. In flies, male genitalia undergo a clockwise 360° rotation during development. To test if this tissue remodeling process is linked to asymmetry development in the male genitalia of Drosophila pachea, we developed CRIPSR and transgenesis in this singular species. As in D. melanogaster, mutants of the MyoID gene homolog undergo reverse rotation of the developing genitalia. In addition, they have mirror-image asymmetric genitalia. Although their genital asymmetry is reversed mutants still adopt a right-sided copulation posture. Our results reveal a novel mechanism for establishing left-right asymmetry in animals, involving complex tissue remodeling and MyoID.D. pachea genital left-right size asymmetry is established through MyoID-mediated tissue remodelling and does not determine the direction of mating posture.
The cost of municipal sewage treatment – structure, origin, minimization – methods of fair cost comparison and allocation

Cost comparison in the field of wastewater treatment is a difficult task, particularly concerning sewages charges in different countries. German wastewater management is, for one thing, known to be very efficient, yet, for another, comparatively costly on an international scale. In this context, the marginal conditions typically prevailing in the field of sewage treatment in Germany should be mentioned: dense population and industrialization with high export-oriented production rates, high-profile purification requirements enforced by law. To establish a valid cost comparison, it is necessary to include both the investment and the operating expenses within the scope of the overall annual costs. The major factors impacting the different cost types are represented. Only if these factors are taken into account and quantified, will cost comparison be fair and lead to useful results. Ten hints for cost minimization are given to serve as a guideline for successful and responsable cost reduction. Cost transparency is the prerequisite for the possibility to develop saving potentials while simultaneously securing the social and political acceptance of the charges levied, and to compare the different plants with one another. Experience from Ruhrverband, a water management association for an entire catchment area, being responsible for planning, building and operation of 94 wastewater treatment plants and other plants for water quantity and water quality management, is reported.
Integrated high quality rectifier-regulators

A family of AC-to-DC converters which integrate the functions of low harmonic rectification, low frequency energy storage, and wide bandwidth output voltage control into a single converter containing one, two, or four active switches is presented. These converters utilize a discontinuous conduction mode input inductor, an internal energy storage capacitor, and transformer secondary circuits which resemble the bridge, forward, flyback, or Cuk DC-DC converters. A large-signal equivalent circuit model for this family which uses the loss-free resistor concept is presented. Design strategies and experimental results are given. High performance regulation with satisfactory line current harmonics is demonstrated with conventional duty ratio control. Further improvements in line current are possible by simultaneous duty ratio and switching frequency control. <<ETX>>
Endodontic Biofilms - A Review

: Biofilm like structures are the main form in which bacteria infecting the root canal system are organized. Bacterial biofilms can be found in virtually all areas of the root canal system, including the main canal, apical and lateral ramifications, isthmuses, and recesses. Biofilms are very frequent in the apical part of root canals of teeth with primary or posttreatment apical periodontitis. It consists of microbial cells of different species and is organized in multiple cell layers, embedded within a matrix. The composition and structure of this endodontic biofilm are highly variable. Biofilm infection may be very difficult to reach and eradicate and may require special strategies for successful management. This review article briefly describes different types of endodontic biofilms, its characteristics and eradication.
Analytical Relationship between the Electrical Parameters of the PV Array and External Factors based on the Lambert W-Function

: The main goal of this research is to find and to analyze qualitatively, the current/voltage characteristics of the photovoltaic (PV) array. The proposed mathematical model is based on the single diode equivalent circuit; the analytical relationship between the electrical characteristics of the PV module and external environmental factors such as the intensity of solar radiation and temperature are taken into account. Mathematical and computer modeling are of the particular importance under the conditions of a significant spread in the values of external factors which occur in the mountain and remote desert areas in Central Asia. A mathematical analysis of the resulting transcendental equation is carried out using a Lambert W-function which has been the subject of a large number of publications.
Consensus Mechanisms in Blockchain Technology: A Review

: A Blockchain is an Accessible to all, distributed ledger that can record transactions between two parties fast and scalable and in everyone check the validity of the information and permanent way. Blockchain, the foundation of Bitcoin, has received massive attentions recently. Cryptocurrencies such as Bitcoin enable users to submit payment transactions without going through centralized trusted Associations. Blockchain based applications are springing up, covering many fields including financial services, reputation system and Internet of Things (IoT), and so on. However, there are still many challenges of Blockchain technology such as scalability and security problems waiting to be overcome. This paper presents a comprehensive overview on Blockchain technology. We provide an overview of Block chain architecture firstly and consensus algorithms used in different Blockchains. And also In this paper we modify tendermint consensus algorithm.
Antimicrobial Activity of Tagetus Erectus against MDR Pathogens

: The antimicrobial activity of Tagetus erectus leaves against pathogenic bacteria was studied. Plant extract was prepared using Methanol and was suspended in DMSO solution. Comparative study of leaf extract was evaluated by Agar well diffusion method against Staphylococcus aureus, Bacillus cereus, Salmonella typhi and Escherichia coli. The study showed maximum Zone of Inhibition (ZOI) against Gram -positive bacteria rather than Gram - negative bacteria which is due to the difference in the cell wall composition of the bacteria. Thus, the Antimicrobial Activity found in the Methanol extract of the leaves showed better inhibitory effect on the Gram positive bacteria i. e. S. aureus and B. cereus.
A Fully Automated Car Parking Lot

Most car parking lots in the country have not been fully automated and many of them serve temporal, manual parking needs. A fully automated car parking lot assures of flexibility, improved efficiency and minimisation of manual tasks. In this paper, use was made of Siemens Step 7 PLC and WinCC Flexible Advanced software to design a fully automated car parking lot. The number of parking spaces available, the parking space number and position, arrival and departure times of cars and the time spent at the parking space are provided by the design. Simulations of designed system using Simatic PLC SIM confirmed the fulfillment of the design criteria and reliability of the developed flowcharts. Remote operator monitoring and control of the car parking lot has been actualised. Simulation results on the parking of six cars for a time duration of 0.5 hr, 1 hr, 1.5 hrs, 2 hrs, 2.5 hrs and 3 hrs, respectively yielded a total amount of GH 17.00. It stands to reason that hitherto existing manual car parking lots should be converted into the fully automated type using a PLC and an HMI workstation in order to bring orderliness and deserving responsibility to car parking in Ghana.
A Review on Interpretable and Explainable Artificial Intelligence in Hydroclimatic Applications

This review focuses on the use of Interpretable Artificial Intelligence (IAI) and eXplainable Artificial Intelligence (XAI) models for data imputations and numerical or categorical hydroclimatic predictions from nonlinearly combined multidimensional predictors. The AI models considered in this paper involve Extreme Gradient Boosting, Light Gradient Boosting, Categorical Boosting, Extremely Randomized Trees, and Random Forest. These AI models can transform into XAI models when they are coupled with the explanatory methods such as the Shapley additive explanations and local interpretable model-agnostic explanations. The review highlights that the IAI models are capable of unveiling the rationale behind the predictions while XAI models are capable of discovering new knowledge and justifying AI-based results, which are critical for enhanced accountability of AI-driven predictions. The review also elaborates the importance of domain knowledge and interventional IAI modeling, potential advantages and disadvantages of hybrid IAI and non-IAI predictive modeling, unequivocal importance of balanced data in categorical decisions, and the choice and performance of IAI versus physics-based modeling. The review concludes with a proposed XAI framework to enhance the interpretability and explainability of AI models for hydroclimatic applications.