Miracle-dz/UniFAR-FTUs huggingface dataset:
Hamiltonian-Preserving Discontinuous Galerkin Methods for the Liouville Equation With Discontinuous Potential

Numerically solving the Liouville equation in classical mechanics with a discontinuous potential often leads to the 4 challenges of how to preserve the Hamiltonian across the potential barrier and a severe time step constraint according to the CFL 5 condition. Motivated by the Hamiltonian-preserving ﬁnite volume schemes by Jin and Wen [19], we introduce a Hamiltonian- 6 preserving discontinuous Galerkin (DG) scheme for the Liouville equation with discontinuous potential in this paper. The DG 7 method can be designed with arbitrary order of accuracy, and oﬀers many advantages including easy adaptivity, compact stencils 8 and the ability of handling complicated boundary condition and interfaces. We propose to carefully design the numerical ﬂuxes 9 of the DG methods to build the behavior of a classical particle at the potential barrier into the numerical scheme, which ensures 10 the continuity of the Hamiltonian across the potential barrier and the correct transmission and reﬂection condition. Our scheme 11 is proved to be positive and stable in L 1 norm if the positivity-preserving limiter is applied. Numerical examples are provided to 12 illustrate the accuracy and eﬀectiveness of the proposed numerical scheme. 13 results show 2D2V test discontinuity of HPDG
T HE NEW GLOBAL DIVISION OF LABOUR – HOW IS THE WORLD ECONOMY AFFECTED BY OUTSOURCING AND OFFSHORING ?

Outsourcing is a term which has been the focus of both a theoretical literature spawning models of a firm’s decision to outsource and the impact on industry equilibrium outcomes, and an empirical literature which seeks to measure it. Broadly defined, the term outsourcing refers to the purchase of goods and services that were previously produced inside a company. The company providing the goods and services can be located in the same country (domestic outsourcing) or outside the country of the purchasing company (international outsourcing). The international component of outsourcing relates to switches of sourcing from within to between countries. Feenstra and Hansen (2005), for instance, explicitly formalize and estimate a model of ownership and control in outsourcing to China.
Classifying Implant-Bearing Patients via their Medical Histories: a Pre-Study on Swedish EMRs with Semi-Supervised GanBERT

In this paper, we compare the performance of two BERT-based text classifiers whose task is to classify patients (more precisely, their medical histories) as having or not having implant(s) in their body. One classifier is a fully-supervised BERT classifier. The other one is a semi-supervised GAN-BERT classifier. Both models are compared against a fully-supervised SVM classifier. Since fully-supervised classification is expensive in terms of data annotation, with the experiments presented in this paper, we investigate whether we can achieve a competitive performance with a semi-supervised classifier based only on a small amount of annotated data. Results are promising and show that the semi-supervised classifier has a competitive performance with the fully-supervised classifier.
Massive Machine Type Communication using Non-Orthogonal Multiple Access with Convolutional Neural Network Approach

: The 5G cellular network supports massive Machine Type Communication (mMTC) for Wireless Sensor Network (WSN) application. In this paper, High Altitude Platforms (HAPs) is used as a replacement for Base Station (BS). So that the cluster head (CH) from every cluster will send information owned to the HAPs by using the Power Domain Non-Orthogonal Multiple Access (PD NOMA) as a multiple access technique. PD NOMA uses the Successive Interference Cancellation (SIC) technique on the receiver side. SIC process is proven effective for detecting PD NOMA signal by sorting the received signal strength and then decoding it. However, error from the prioritized signal that has high decoding has a tremendous impact on the prioritized signal that has a way lower decoding, and this error can then further spread with the SIC process. In this paper, we propose a Convolutional Neural Network (CNN) approach to decode information from multiple CH without performing traditional communication signal processing. The simulation is already done by the Rician channel with 11 CH that is connected to the HAP. From the series of simulations that have been done, we can see that the CNN used to replace the conventional SIC on the uplink PD NOMA can detect NOMA signals without the use of conventional signal processing. The CH node nearest to the HAP requires a lower SNR than the CH node farthest from the HAP to achieve BER = 10-4 in both conventional uplink PD NOMA and uplink PD NOMA with CNN. Uplink PD NOMA with CNN has a lower complexity than conventional uplink PD NOMA.
Comparison of Leaf Recognition using Multi-layer Perceptron and Support Vector Machine

: Identification of leaves from digital images using various automatic pattern recognition algorithms results in performance degradations. Here, various leaf features are been extracted and exposed to Multi-layer Perceptron and Support Vector Machine. The leaf images are taken from the Columbia Dataset and that are preprocessed to get the region of interest (ROI). The shape, color and vein features are then extracted from the selected ROI. The prominent features are then found out by using Principal Component Analysis (PCA). The reduced feature sets are supplied to these algorithms for identification. Total 150 samples were taken from this dataset spreads over 10 different leaf species. Multilayer Perceptron and Support vector machine are trained with 104 leaf images and are been tested and validated using 23 leaf images each. A comparison is made between the performances of these two learning methods and found that the leaf recognition accuracy of the support vector machine is better than that of Multilayer Perceptron algorithm.
Consumer perception and behavior towards plant based meat and animal meat

Plant-based alternatives to traditional animal products have gotten a lot of interest in recent years. We are investigating the driving forces and hurdles that affect Indian customers when it comes to purchasing these specific items by combining current data with our own quantitative analysis. We utilise the Theory of Reasoned Action paradigm to do this. When it comes to picking meals, Indian consumers prioritise their health and the environment, but they also consider flavour, eating traditions, and how their environment impacts them. The significance of our research is underscored by the fact that, first and foremost, the topic is relatively new; the majority of comparable studies have been published in the last 10 years, and nothing has been written about consumer behaviour toward these items in Sweden. Furthermore, the research integrates the current TRA model with some novel techniques to explore the issue of plant-based alternative adoption. This addresses some of the criticisms made against the traditional TRA approach. As a result of our conclusion, we are able to offer future advice to firms in the plant-based replacement food market.
Performance of Different SLAM Algorithms for Indoor and Outdoor Mapping Applications

Indoor and outdoor mapping studies can be completed relatively quickly, depending on the developments in Mobile Mapping Systems. Especially in indoor environments where high accuracy GNSS positions cannot be used, mapping studies can be carried out with SLAM algorithms. Although there are many different SLAM algorithms in the literature, each can produce results with different accuracy according to the mapped environment. In this study, 3D maps were produced with LOAM, A-LOAM, and HDL Graph SLAM algorithms in different environments such as long corridors, staircases, and outdoor environments, and the accuracies of the maps produced with different algorithms were compared. For this purpose, a mobile mapping platform using Velodyne VLP-16 LIDAR sensor was developed, and the odometer drift, which causes loss of accuracy in the data collected, was minimized by loop closure and plane detection methods. As a result of the tests, it was determined that the results of the LOAM algorithm were not as accurate as those of the A-LOAM and HDL Graph SLAM algorithms. Both indoor and outdoor environments and the A-LOAM results’ accuracy were two times better than HDL Graph SLAM results.
Introducing RezoJDM16k: a French KnowledgeGraph DataSet for Link Prediction

Knowledge graphs applications, in industry and academia, motivate substantial research directions towards large-scale information extraction from various types of resources. Nowadays, most of the available knowledge graphs are either in English or multilingual. In this paper, we introduce RezoJDM16k, a French knowledge graph dataset based on RezoJDM. With 16k nodes, 832k triplets, and 53 relation types, RezoJDM16k can be employed in many NLP downstream tasks for the French language such as machine translation, question-answering, and recommendation systems. Moreover, we provide strong knowledge graph embedding baselines that are used in link prediction tasks for future benchmarking. Compared to the state-of-the-art English knowledge graph datasets used in link prediction, RezoJDM16k shows a similar promising predictive behavior.
The IARPA BETTER Program Abstract Task Four New Semantically Annotated Corpora from IARPA’s BETTER Program

IARPA’s Better Extraction from Text Towards Enhanced Retrieval (BETTER) Program created multiple multilingual datasets to spawn and evaluate cross-language information extraction and information retrieval research and development in zero-shot conditions. The first set of these resources for information extraction, the “Abstract” data will be released to the public at LREC 2022 in four languages to champion further information extraction work in this area. This paper presents the event and argument annotation in the Abstract Evaluation phase of BETTER, as well as the data collection, preparation, partitioning and mark-up of the datasets.
SHOPPING CONVENIENCE UMKM JAKARTA DAN YOGYAKARTA MELALUI VIRAL MARKETING MEDIA FANPAGE

Penelitian ini bertujuan untuk mengetahui shopping convenience konsumen UMKM yang mengarah pada keuntungan yang di terima oleh konsumen dan kualitas yang diterima oleh konsumen karena pembelian secara on line melalui viral marketing media fanpage. Metode penelitian dilakukan secara deskriptif yang bersifat follow up study dengan objek penelitian UMKM yang terdapat di Yogyakarta dan Jakarta, teknik sampling dilakukan secara purposive. Indikator Shopping convenience yang dibahas dalam penelitian ini adalah ease of use dan usefulness. Hasil dari penelitian ini membuktikan bahwa viral marketing dengan media fanpage meningkatkan shopping convenience konsumen dalam melakukan kegiatan transaksi jual beli online. Tingkat shopping convenience konsumen atas ease of use dimana konsumen percaya bahwa teknologi fanpage dapat digunakan dengan mudah dan bebas dari masalah sebesar 86% masuk dalam klasifikasi sangat setuju dari total responden, sedangkan shopping convenience konsumen atas usefulness sebesar 79% masuk dalam klasifikasi setuju dimana konsumen percaya bahwa penggunaan fanpage akan meningkatkan performa mereka dalam membeli dan memilih barang secara online
The Impact of Job Stress, Job Satisfaction and Job Burnout on Turnover Intention among Project Management Team Members in Industrial Cities in The Kingdom of Saudi Arabia

This research is aiming to figure out the impact of job stress, job satisfaction and job burnout on turnover intention among project management team members in industrial cities in the kingdom of Saudi Arabia. The research sample consisted of 212 respondents and the data were collected using electronic questionnaires. Statistical procedures were applied using SPSS (means, standard deviations, correlation analysis, reliability analysis) and AMOS (Path analysis). The research findings showed that there are positive relationships be tween job burnout and turnover intention and between job stress and job burnout. The findings showed a negative relationship between job burnout and job satisfaction and between job satisfaction and turnover intention. The findings showed a positive relationship between job burnout and turnover intention. The results of this research can be used as a reference for industrial fields in the Kingdom of Saudi Arabia to improve the public awareness and enhance the organizational efficiency.
F INANCE , C ONTROL , AND P ROFITABILITY : T HE I NFLUENCE OF G ERMAN B ANKS

Bank intermediated finance has been cited frequently as the preferred means for channeling funds from savers to firms. Germany is the prototypical economy where universal banks allegedly exert substantial influence over firms. Despite frequent assertions about the considerable power of German banks and the advantages of a bank relation, empirical support is mixed. With a unique dataset and a focus on the fragility/sturdiness of inferences, this paper evaluates German bank influence in terms of three hypotheses: 1) do bank influenced firms enjoy lower finance costs? [No]; 2) is bank influence a solution to control problems? [Yes]; 3) do bank influenced firms have higher profitability? [No]. Coupled with results about the control consequences of concentrated ownership, these results suggest that bank influence serves as a substitute control mechanism, one of several available for addressing corporate control problems.
Building information modelling and green buildings: challenges and opportunities

ABSTRACT The advent of building information modelling (BIM) is revolutionising the conventional practices of the construction industry and has reinforced the impact of the design process on the building project’s overall life cycle. The industry is also moving towards sustainability through owners being committed to having green rated buildings and infrastructure. However, green buildings and their rating systems face several obstacles and shortcomings that hinder their sustainability. Several studies have considered BIM for sustainability aspects, but these were not connected directly with such obstacles. This paper is a literature review that links the obstacles and shortcomings faced in green buildings and their associated rating systems with the potential capabilities of BIM. The limitations of BIM in the green building industry was also addressed. The main obstacles and shortcomings faced are high upfront costs and delays, design complexities and documentation requirements, superior performance enhancement requirements, and skewness towards environmental sustainability. The paper was written from a realisation that a more consolidated future research direction is needed in academic studies that address the quest for sustainability though BIM. Findings indicate future areas of BIM technology research include fully automating BIM-rating system integration, collaboration and intellectual property issues, and the unaccommodating contractual approaches for multiple party involvement needed in a BIM platform.
Vessel : a lightweight container for network analysis

TCP adaptation and retransmission strategies provide robust advantages by abstracting the development of applications on the Internet from the development of lower layers. However, the abstraction hides useful low-level information from researchers and administrators who could otherwise use the insights from the performance of TCP and lower layers to diagnose problems and improve TCP performance. Though common tools exist for manual analysis of TCP performance, some of these tools are outdated or arduous to easily use. The primary contribution of this thesis is Vessel, a tool to supplement existing tools with per-connection instrumentation, improving the ability to perform network analysis tests while providing sufficiently detailed information to identify differences with different tests. Vessel leverages the Extended Berkeley Packet Filter and Linux network namespaces. We demonstrate the utility of the tool by analyzing TCP flows associated with competing web-based speed measurement tests. Thesis Supervisor: David D. Clark Title: Senior Research Scientist
Statistical Significance of Mission Parameters on the Deflection Efficiency of Kinetic Impacts: Applications for the Next-generation Kinetic Impactor

Understanding how to deflect an incoming asteroid is of great importance and a focus of research undertaken internationally by the planetary defense community. Deflection of an asteroid by a kinetic impactor is one such mitigation method that has a high degree of technological maturity. In 2022, NASA’s planetary defense mission, the Double Asteroid Redirection Test (DART), will provide the first full-scale technology demonstration of a kinetic impactor. However, the DART mission is just a single test of one kinetic impactor design, prompting the question: Is it possible to optimize the design of a kinetic impactor to make it the most efficient deflector that it can be? In this paper, we use high-fidelity hydrodynamic simulations to examine the effect of five mission parameters (impactor mass, impact velocity, impactor composition, impactor geometry, and target strength) on three observables related to deflection efficiency (crater morphology, ejecta distribution, and momentum transfer) resulting from kinetic impacts. We find that the most significant mission parameters for determining postimpact factors are the impact velocity, impactor mass, and target strength. The impactor geometry and impactor composition emerge as statistically nonsignificant. Overall, we find that the ogive impactor geometry results in the highest variance in predicting the momentum enhancement factor (β), and that generally, impactors with smaller volumes and flat leading edges (plates and rings) produce smaller craters and less ejecta mass compared to impactors with larger volumes and sharper leading edges (spheres, ogives, and cones).
Dynamic Modelling for the Development of a Self-Stabilizing Helipad Platform for Navy Applications

This paper provides the study, modelling and the development of Stewart platform for navy applications. A Helipad on the ship enhances the functioning capabilities of Airforce and Navy. During storm and other extreme conditions in sea, ship experiences heavy forces which tilts the ship and produces the motions along Yaw, Pitch and Roll axis. This proposed system designed by us will compensate for the motions and maintain the stability of platform for landing or take-off of the Helicopter and it is comprised of top platform (On which Helicopter lands), Bottom platform (which lies on ship), intermediate actuating layer with six actuators, sensor to detect the change in the position of the ship. As ship experiences storm, tilt in the bottom platform occurs, sensor attached to bottom platform detects the change, controller then generates the corresponding actuating signal to the actuators and the top platform corrects the tilt, maintaining position stability on top platform that enables the landing of the helicopter.
A Simple Yet Effective Corpus Construction Method for Chinese Sentence Compression

Deletion-based sentence compression in the English language has made significant progress over the past few decades. However, there is a lack of large-scale and high-quality parallel corpus (i.e., (sentence, compression) pairs) for the Chinese language to train an efficient compression system. To remedy this shortcoming, we present a dependency-tree-based method to construct a Chinese corpus with 151k pairs of sentences and compression based on Chinese language-specific characteristics. Subsequently, we trained both extractive and generative neural compression models using the constructed corpus. The experimental results show that our compression model can generate high-quality compressed sentences on both automatic and human evaluation metrics compared with the baselines. The results of the faithfulness evaluation also indicated that the Chinese compression model trained on our constructed corpus can produce more faithful compressed sentences. Furthermore, a dataset with 1,000 pairs of sentences and ground truth compression was manually created for automatic evaluation, which, we believe, will benefit future research on Chinese sentence compression.
The tendency of using borrowings among English language students: A case study

Perhaps the most frequently encountered outcomes of language change are due to borrowing. Hence, this study focused on exploring whether the usage of English borrowings is increasing, the reasons behind this occurrence and the effect of borrowings on translated texts. The issue was deemed worth exploring since it represents a contemporary problem that linguists deal with. To conduct this research a mixed method was applied where questionnaires were distributed to fifty students of the University of Prishtina, English Language and Literature Department, who had attended or were attending translation courses. The outcomes of the research suggest and support the idea that the practice of using Anglicisms is increasing, students are among those who use borrowings in their translations, regardless of being aware that it can affect the quality of translation. Amongst other significant outcomes, it was concluded that the exposure to media has the greatest impact on increasing the productivity of borrowing English words in Albanian.
Moonshine beyond the Monster: The Bridge Connecting Algebra, Modular Forms and Physics

Acknowledgements Introduction: glimpses of the theory beneath Monstrous moonshine 1. Classical algebra 2. Modular stuff 3. Gold and brass: affine algebras and generalisations 4. Conformal field theory: The physics of Moonshine 5. Vertex operator algebras 6. Modular group representations throughout the realm 7. Monstrous Moonshine Epilogue Notation References Index.
AN EFFICIENT TOPOLOGY FOR ELECTRIC VEHICLE BATTERY CHARGING WITH ENHANCED CHARGE CONTROLLER

— A choice of logical converter topology plays a notable role in the battery charging of electric vehicles (EVs). In this paper, snubber less stage of rectifier cascaded with snubber less stage of the dc-dc converter is proposed in which stage I eliminates the need of front-end rectifier, and no further circuitry is required for switching operation of rectifier stage. Due to pulse width modulation (PWM) switches share the same gating signal for positive as well as negative cycle operation. Second stage converter uses asymmetrical pulse width modulation (APWM) technique in which zero voltage switching (ZVS) is achieved for all active switches, and near zero current switching (ZCS) for low side, active switches are attained during the charging range of the battery. The size of auxiliary inductance required is decreased for ZVS with APWM compared to previously proposed APWM with snubber circuitry. We are adding P+R controller for better efficiency.Due to a reduction in the size of auxiliary inductor and absence of snubber circuit results in an efficient battery charger topology. The MATLAB simulation is done of the proposed converter to validate the results.