Miracle-dz/UniFAR-FTUs huggingface dataset:
Analysis of the Coupled Dynamics of an Offshore Floating Multi-Purpose Platform: Part B — Hydro-Elastic Analysis With Flexible Support Platform

A multi-purpose platform (MPP) is an offshore system designed to serve the purposes of more than one offshore industry. Indeed, over the past decades, a number of industries have expanded, or are expanding, from onshore to offshore locations (renewables, aquaculture, tourism, mineral extractions, etc), and the research on these type of platform is increasing. In the present work, a MPP able to accommodate wind turbines, wave energy converters, and aquaculture systems is considered. For an overview of the MPP platform considered and its research context, please refer to the EU H2020 project overview (OMAE 2019-96104). This work presents the second part (Part B) of the analyses of the dynamics of the floating support structure for this MPP, focusing on the hydro-elastic analysis, while its complementary rigid-body hydrodynamic analysis is presented in Part A (OMAE2019-96212). The aim here is to assess if the support platform structural elasticity has a substantial impact on the dynamic response of the platform. A beam model and a 3D solid model of the support structure have been developed, and the inertial forces, hydrodynamic added mass forces, hydrostatic and mooring restoring forces have been considered in the hydro-elastic analyses performed. The results show that the dynamic response to the wave loads is not substantially influenced by the elasticity of the support structure, and that, at first approximation, a rigid-body approach is acceptable.
Multi-modal sensing drifters as a tool for repeatable glacial hydrology flow path measurements

Abstract. Lagrangian drifters are a practical way to measure natural flow features in surface channels. In this study, small cylindrical drifters (length 12 cm, diameter 4 cm) were deployed in a supraglacial channel. Each drifter recorded the total water pressure, linear acceleration, magnetic field strength and rate of rotation at 100 Hz. Based on an ensemble analysis of repeated field deployments (n = 55), it was found that the pressure sensors consistently delivered the most accurate data, where values remained within ±0.11 % of the total pressure time-averaged mean (95 % confidence interval). Magnetometer readings also exhibited low variability across deployments, maintaining readings within ±2.45 % of the time-averaged mean of the magnetometer magnitude. Linear acceleration measurements were found to have substantially larger 95 % confidence intervals, spanning ±34.4 % from the time-averaged mean magnitudes. Furthermore, the drifter speed along the supraglacial channel was estimated by integrating the linear acceleration, providing a 95 % confidence interval of ±24.5 % of the time averaged mean magnitude. The major contribution of this work is to provide a statistical assessment of multimodal drifters, repeatedly deployed in a 450 m long supraglacial channel reach, with a focus on developing a repeatable field measurement methodology including uncertainty. The results of this work show that multimodal drifters are capable of highly repeatable field measurements in supraglacial channels.
Examining Commitment in Electronic Knowledge Repository Usage

Electronic knowledge repositories (EKRs) are used by organizations to codify, store, and disseminate knowledge. This study presents and tests a research model that examines the role of commitment in the use of EKRs in professional service firms. In particular, this study examines how three types of commitment (affective, calculative, and normative commitment) affect employees' EKR usage behavior. Survey results of 230 EKR users from four large public accounting firms indicate that both affective and calculative commitments exhibit significant positive influence on EKR usage. The effect of an organization's collaborative norms and a user's organizational identification on the three types of commitment is also explored. This study raises implications for researchers and practitioners interested in knowledge management and particularly for professional service firms on how to leverage EKRs to gain a competitive advantage.
Kiwifruit root manipulation - potential for fruit dry matter improvements / by Kevin Patterson (and others)

Updates the results of trials to quantify the effects of root pruning of Hort16A and Hayward kiwifruit plants over the 2007-2008 and 2008-2009 seasons. Explains the technique of and rationale for root pruning and the risks and unknown factors associated with the technique. Touches on research in progress.
Geochemistry and Nd isotopes of Lower Permian siliciclastic rocks from central Tibet, western China: Evidence for Early Permian initiation of the rifting between the Lhasa and Qiangtang blocks?

Fifteen Lower Permian siliciclastic rocks from central Tibet were analysed for the major and trace elements, and ten samples among them were chosen for determination of Nd isotopic compositions. They are characterized by low concentrations of SiO2 and low ratios of SiO2/Al2O3, moderate abundances of Fe2O3 + MgO (mudstones, 7.28–9.72 wt.%; sandstones, 4.62–10.02 wt.%) and TiO2 (mudstones, 0.55–0.95 wt.%; sandstones, 0.53–0.99 wt.%), significant enrichments of light rare‐earth elements (LREEs) relative to the heavy REEs (HREEs; average (La/Yb)N = 9.8 [mudstones] and 9.48 [sandstones]), flat HREE distribution, obvious negative Eu anomalies (average Eu/Eu* = 0.68), higher Th/Sc and La/Sc ratios, and negative initial εNd values (on average −7.2 and −8.5 for sandstones and mudstones, respectively). The mixing modal analysis based on some elemental pairs and Nd isotopic composition, respectively, Nd depleted mantle model age (TDM) and initial εNd values, uniformly indicates that about 30–40% mafic materials could have been added into these sedimentary rocks. These siliciclastic rocks could have formed in a setting of rifting between the Lhasa and Qiangtang blocks, when a 280 Ma mantle plume upwelling event was occurring in northern Gondwana.
Adaptive k-class estimation in high-dimensional linear models

Abstract In this paper, we explore the k-class estimator in high-dimensional linear models with potential endogeneity issues which are very common in empirical economics studies. K-class estimator has the advantage of incorporating many popular estimators such as the OLS estimator, two stage least squares (2SLS) estimator, limited information maximum likelihood (LIML) estimator, etc., as k takes on different values. Our main innovations are: 1) In the newly proposed high-dimensional k-class estimator, we allow the value of k (hence the level of endogeneity) to be determined by the data. Therefore, our method is very useful in empirical studies where the researcher do not know the severity of endogeneity or the importance of variables in a very large pool of candidate covariates. 2) In this paper, the adaptive LASSO method is incorporated into the generalized k-class estimation for variable selection and coefficient estimation in both the structural and reduced form equations. We show that the adaptive LASSO type k-class estimator has oracle properties. In simulation studies, we show that our new estimator can choose the optimal k value as well as achieving the minimum MSE among a set of popular estimators in finite samples where the number of potential endogenous variable is large.
Analyzing Diabetic Data using Classification Algorithms in Data Mining

Backgrounds/Objectives: Huge medical datasets available in various data repositories which are used for real world applications. To visualize the useful information stored in data warehouses, the Data Mining (DM) methods are enormously utilized. One of such domain is medical domain, in which the function of DM approach raises speedy recovery of sickness over indications. On the way to categorize and predict symptoms in medicinal data, a variety of DM methods are utilized by different researchers. From many techniques of DM, classification is one of the main techniques. The classification techniques classify the unseen information in all areas including medical diagnostic field. The very dangerous disease in medicinal field is diabetes disease which is affected for many peoples in popular countries like India. Methods/Statistical Analysis: The impact of categorization is very important in authentic earth applications in all fields. To categorize the rudiments allowing to the applications of the elements during the predefined set of modules are used by classification methods. Very popular classification algorithms J48, Support Vector Machines (SVM), Classification and Regression Tree CART and k-Nearest Neighbor (kNN) for diabetic data are used for this research work. Findings: To discover the presentation of these classification methods, diabetic data as an input. For the most part, this research work is supported out to associate the techniques in the calculation of the presentation accurateness in diabetic data. The above mentioned techniques are used for diabetic data to categorize its accuracy in terms of its performance. Methods: The conclusion of this research work is choosing the top algorithm for the input data for the best classifier. Applications/Improvements: Some of other algorithms are analyzed using the same data set for the similar type of results is discussed in future. Also, some of the clustering algorithms are applied using the same data set to find highly affected diabetic patients.
Experimental electron-detachment cross sections for collisions of 
O2−
 with 
N2
 molecules in the energy range 50–7000 eV

An experimental setup has been implemented to obtain absolute total electron detachment cross sections and relative ionization cross sections in the energy range 50–7000 eV in gas-phase collisions between anionic beams and neutral molecular targets. The primary anionic beam (O 2 − ) is produced through a pulsed hollow cathode discharge-induced plasma, deﬂected and focused towards the collision region where the molecular target is maintained at a well-known pressure. Electron detachment cross sections are measured from the attenuation of the O 2 − beam after interaction with N 2 molecules conﬁned in a gas cell. Negative and positive fragment ions produced during the collisions are extracted and mass analyzed by time-of-ﬂight mass spectrometry. Relative ionization cross sections are derived from the ratio of the measured positive ion fragment intensities (N 2 + , N + ) to the primary O 2 − beam intensity.
Stochastic synchronization of delayed multiagent networks with intermittent communications: An impulsive framework

This paper investigates the stochastic synchronization problem of delayed multiagent networks with intermittent communications. Two kinds of impulsive effects are taken into account, ie, impulsive controller (positive impulsive effect) and impulsive disturbance (negative impulsive effect). Impulsive controller allows the synchronization to be realized and requires only state information exchange at discrete time instants such that the communication cost of bandwidth is reduced. Meanwhile, impulsive disturbance is inevitable in most of practical systems and therefore is taken into consideration at discrete time instants. Sufficient conditions for synchronization are given in terms of the graph topology, the control coupling gains, and the individual agent dynamics parameters, which indicates that synchronization can be realized if the impulsive effects coefficients and communication rate are suitably selected. Simulation results verify the effectiveness of the proposed synchronization protocol.
Forest Soil Quality and Potentials for Food Systems Health in the Takamanda National Park in South Western Cameroon

Soil is a basic natural resource for food production, the vast majority of food we consume is either directly or indirectly derived from soil. Soil quality determines the quantity and quality of foods grown. Protecting the soil’s physical, chemical and biological integrity is therefore of vital importance in safeguarding global food security. This paper evaluates the physical and chemical properties of soils in the rainforest of the Takamanda in Southwestern Cameroon and their implications on agricultural productivity and food security. Soils were randomly sampled using a bucket soil auger at the left, middle and right flank of the 50 ha Takamanda forest dynamic plot. Soils were sampled from three flanks at depths of 0 - 10 cm, 10 - 20 cm and 20 - 30 cm. Bulk density increased with soil depth in all the flanks. Soil nitrogen, organic carbon, potassium, magnesium, sodium, phosphorus and cation exchange capacity were greater in topsoil (0 - 10 cm) than subsoils. Soil Ca and pH were slightly greater at 20 - 30 cm soil depths with value of 0.45 cmol (+)/kg and 4.24 respectively. Soil C/N ratio was highest (13.12) in 10 - 20 cm soil depth though it was not significantly different from the other soil depths. To promote food production, an integrated cost-effective approach to soil management should comprise the use of acid-tolerant species of crop plants, efficient use of fertilizers, suitable crop rotations, crop diversification and agroforestry.
PM2.5 Prediction Based on Random Forest, XGBoost, and Deep Learning Using Multisource Remote Sensing Data

In recent years, air pollution has become an important public health concern. The high concentration of fine particulate matter with diameter less than 2.5 µm (PM2.5) is known to be associated with lung cancer, cardiovascular disease, respiratory disease, and metabolic disease. Predicting PM2.5 concentrations can help governments warn people at high risk, thus mitigating the complications. Although attempts have been made to predict PM2.5 concentrations, the factors influencing PM2.5 prediction have not been investigated. In this work, we study feature importance for PM2.5 prediction in Tehran’s urban area, implementing random forest, extreme gradient boosting, and deep learning machine learning (ML) approaches. We use 23 features, including satellite and meteorological data, ground-measured PM2.5, and geographical data, in the modeling. The best model performance obtained was R2 = 0.81 (R = 0.9), MAE = 9.93 µg/m3, and RMSE = 13.58 µg/m3 using the XGBoost approach, incorporating elimination of unimportant features. However, all three ML methods performed similarly and R2 varied from 0.63 to 0.67, when Aerosol Optical Depth (AOD) at 3 km resolution was included, and 0.77 to 0.81, when AOD at 3 km resolution was excluded. Contrary to the PM2.5 lag data, satellite-derived AODs did not improve model performance.
ENHANCE RFID SECURITY AGAINST BRUTE FORCE ATTACK BASED ON PASSWORD STRENGTH AND MARKOV MODEL

RFID systems are one of the important techniques that have been used in modern technologies; these systems rely heavily on default and random passwords. Due to the increasing use of RFID in various industries, security and privacy issues should be addressed carefully as there is no efficient way to achieve security in this technology. Some active tags are low cost and basic tags cannot use standard cryptographic operations where the uses of such techniques increase the cost of these cards. This paper sheds light on the weaknesses of RFID system and identifies the threats and countermeasures of possible attacks. For the sake of this paper, an algorithm was designed to ensure and measure the strength of passwords used in the authentication process between tag and reader to enhance security in their communication and defend against brute-force attacks. Our algorithm is design by modern techniques based on entropy, password length, cardinality, Markov-model and Fuzzy Logic.
PENGARUH AKUNTABILITAS, TRANSPARANSI, DAN KUALITAS PELAYANAN TERHADAP MINAT MUZAKI MEMBAYAR ZAKAT

This study aims to determine the effect of accountability, transparency, and service quality on the interest of muzaki (study at zakat institutionsSurabaya). This study uses a quantitative approach with multiple linear regression analysis. The population in this study is all muzaki registered at zakat institutions in Surabaya. The sampling technique using convenience sampling. This study uses 6 (six) zakat institutions that have been selected by taking a sample of 120 muzaki. Primary data collection in this study used a questionnaire. Based on the results of the study show that accountability, transparency, and service qualitypartially have a positive and significant effect on the interest of muzaki to paying zakat. Accountability, transparency, and service qualitysimultaneously have a positive and significant effect on the interest of muzaki to paying zakat.Keywords: Accountability, Transparency, Service Quality, Interest, Zakat, Zakat Institution
Self-consolidating concrete for precast, prestressed concrete bridge elements

The following thesis presents the results of four full scale beams tests as part of a research program conducted at McGill University. The purpose is to study the applicability of existing design provisions, in the American Association of State Highway and Transportation Officials (AASHTO) specifications, for the use of self-consolidating concrete (SCC) in precast pretensioned bridge girders. The test specimens had an overall length of 31 ft (9.4m) with a center-to-center span of 29 ft (8.8m). They were cast in four batches with different concrete attributes: two non air-entrained SCC mixtures and two high-performance concretes. For each type, compressive strengths of 8,000 and 10,000 psi (55.2 and 69 MPa) with release strengths of 5,000 and 6,250 psi (34.5 and 43 MPa) at 18 hours, respectively, were tested. Each girder was prestressed with eight Grade 270 seven-wire low-relaxation prestressing strands of 0.6 in (15.2 mm) diameter. Six of the strands were straight and two were harped twice, 4’-11” (1.5 m) from mid-span. The specimens were supported on neoprene bearing pads at their ends, and were tested with two equal point loads located 4’-11” (1.5 m) from mid-span. This research project demonstrated that the shear failure of the girders exceeded the predicted nominal shear resistance given by the 2004 AASHTO Specifications. The experimental flexural resistance also exceeded the predicted nominal resistance. %%%%Le present memoire expose les resultats de quatre poutres pleine grandeur faisant partie integrante d’une etude effectuee a l’Universite McGill. Le but de cette etude est de valider l’applicabilite des provisions de conception existantes, de l’Association Americaine des Autoroutes d’Etat et des Officiers de Transport (norme AASHTO), pour l’usage de beton autoplacant (BAP) dans les poutres precontraintes et prefabriquees de ponts.Les specimens testes ont une longueur maximale de 31 pieds (9.4 m) avec une distance du centre au centre de 29 pieds (8.8 m). Les poutres ont ete coulees une a la fois avec differentes sortes de beton: deux d’entres-elles a partir de beton autoplacant sans air entrappe, et deux avec du beton haute-performance. Pour chaque sorte, une resistance compressive de 8,000 et 10,000 psi (55.2 et 69 MPa) avec une resistance, avant de precontraindre le beton, de 5,000 et 6,250 psi (34.5 et 43 MPa) a 18 heures, respectivement, ont ete testees. Chaque poutre etait precontrainte avec huit tendons, grade 270, de 0.6 in (15.2 mm) de diametre. Six de ces tendons etaient horizontaux alors que deux etaient inclines 59 pouces (1.5 m) de chaque bord de l’axe central. Les specimens etaient supportes aux deux extremites sur des pads de neoprene et etaient testes avec deux charges concentriques situees 59 pouces (1.5 m) de l’axe central.Cette recherche a demontrer que la capacite en cisaillement des poutres testees excedait les valeurs nominales prevues par les normes AASHTO 2004. Les valeurs experimentales de la resistance a la flexion des poutres aussi excedent les valeurs nominales predises.
High Speed Circuit Design Based on a Hybrid of Conventional and Wave Pipelining

The increasing capabilities of multimedia appliances demand arithmetic circuits with higher speed and reasonable power dissipation. A common technique to attain those goals is synchronous pipelining, which increases the throughput of a circuit at the expense of longer latency, and it is therefore suitable where throughput takes priority over latency. Two synchronous pipelining approaches, conventional pipelining and wave pipelining, are commonly employed. Conventional pipelining uses registers to divide the circuit into shorter paths and synchronize among sub-blocks, while wave pipelining uses the delay of combinational elements to perform those tasks. As wave pipelining does not introduce additional registers, in principle, it can attain a higher throughput and lower power consumption. However, its throughput is limited by delay variations, while delay balancing often leads to increased power dissipation. This dissertation proposes a hybrid pipelining method called HyPipe, which divides the circuit into sub-blocks using conventional pipelining, and applies wave pipelining to each subblock. Each sub-block is derived from a single base circuit, leading to a better delay balance and greater throughput than with heterogeneous circuits. Another requirement for wave pipelining to achieve high speed is short signal rise and fall times. Since CMOS wide-NAND and wide-NOR gates exhibit long rise and fall times and large delay variations, they should be decomposed. We show that the straightforward decomposition using alternating levels of NAND and NOR gates results in large delay variations. Therefore, we propose a new decomposition method using only one gate type. Our method reduces delay variations by up to 39%, and it is appropriate for wave pipelining based on standard-cells or sea-of-gates. We laid out a 4×4 HyPipe multiplier as a proof of concept and performed a post-layout SPICE simulation. The multiplier achieves a throughput of 4.17 billion multiplications per
Application Limits of the Airgap Maxwell Tensor

Airgap Maxwell tensor is widely used in numerical simulations to accurately compute global magnetic forces and torque but also to estimate magnetic surface force waves, for instance when evaluating magnetic stress harmonics responsible for electromagnetic vibrations and acoustic noise in electrical machines. This article shows that airgap surface forces based on Maxwell tensor with a circular contour depend on the radius of application. The dependence of surface forces on radius is analytically explained using an academic case of a slotless electric machine. The corrective coefficients that should be applied to transfer the airgap surface forces to stator (or rotor) bore radius are presented. The coefficients depend on the airgap geometry and surface forces wavenumber. The use of transfer coefficients is recommended to quantify the deviation due to the radius of application in the airgap. In addition, the transfer coefficients could be applied to correct the radial surface force component on the tip of the teeth assuming infinite permeability.
A MODEL STUDY OF ALONGSHORE SEDIMENT TRANSPORT RAT

Alongshore sediment transport rate was studied in a 3-dimensional mobile bed coastal model and was found to depend on the beach profile and rate of wave energy dissipation in addition to the normal wave and sediment parameters. Alongshore sediment transport rate was found to be strongly related to the surf similarity parameter, a single parameter simplistically describing beach profile and breaker type.