Miracle-dz/UniFAR-FTUs huggingface dataset:
Seismic Anisotropy and 
Stress of the Canterbury 
Plains

The Mѡ=7.1 Darfield (Canterbury) earthquake struck on 4 September 2010, approximately 45 km west of Christchurch, New Zealand. It revealed a previously unknown fault (the Greendale fault) and caused billions of dollars of damage due to high peak ground velocities and extensive liquefaction. It also triggered the Mw=6.3 Christchurch earthquake on 22 February 2011, which caused further damage and the loss of 185 lives. The objective of this research was to determine the relationship between stress and seismic properties in a seismically active region using manually-picked P and S wave arrival times from the aftershock sequence between 8 September 2010-13 January 2011 to estimate shear-wave splitting (SWS) parameters, VP =VS-ratios, anisotropy (delay-time tomography), focal mechanisms, and tectonic stress on the Canterbury plains. The maximum horizontal stress direction was highly consistent in the plains, with an average value of SHmax=116 18 . However, the estimates showed variation in SHmax near the fault, with one estimate rotating by as much as 30° counter-clockwise. This suggests heterogeneity of stress at the fault, though the cause remains unclear. Orientations of the principal stresses predominantly indicate a strike-slip regime, but there are possible thrust regimes to the west and north/east of the fault. The SWS fast directions (ø) on the plains show alignment with SHmax at the majority of stations, indicating stress controlled anisotropy. However, structural effects appear more dominant in the neighbouring regions of the Southern Alps and Banks Peninsula.
A case study on the use of a conceptual modeling framework for construction simulation

Construction simulation has been an active area of research in the last six decades. Nevertheless, there has been a gap between academia and industry in realizing the capabilities of simulation to support decision-making in construction. One of the well-recognized reasons is the difficulty of undertaking comprehensive simulation studies by construction practitioners, who usually lack sufficient knowledge and skills to adequately build simulation models. Efforts to bridge this gap have been focused on simplifying the computer coding and model implementation stages of construction simulation studies with limited research on the early stage of defining the model and abstracting the system, i.e., conceptual modeling. The conceptual modeling stage is known to be one of the most difficult tasks in a simulation study. Thus, several frameworks to support building conceptual models have been proposed in simulation literature. This study contributes to the research efforts to promote simulation in the construction industry through the adoption of a conceptual modeling framework. It demonstrates the application of the proposed conceptual modeling framework in a case study of piling operations. The findings of this paper reinforced the significance of conceptual modeling by confirming the role of the conceptual model as a communication link between stakeholders. Moreover, the conceptual model was used as a specification document for developing a flexible model that can be replicated in other settings. The use of a documented conceptual model assisted in managing the overall simulation study efficiently, which, in turn, lead to reductions in time and effort for different modeling activities.
AUTOMOTIVE: A case study on AUTOmatic multiMOdal drowsiness detecTIon for smart VEhicles

As technology and artificial intelligence conquer a place under the spotlight in the automotive world, driver drowsiness monitoring systems have sparked much interest as a way to increase safety and avoid sleepiness-related accidents. Such technologies, however, stumble upon the observation that each driver presents a distinct set of behavioral and physiological manifestations of drowsiness, thus rendering its objective assessment a non-trivial process. The AUTOMOTIVE project studied the application of signal processing and machine learning techniques for driver-specific drowsiness detection in smart vehicles, enabled by immersive driving simulators. More broadly, comprehensive research on biometrics using the electrocardiogram (ECG) and face enables the continuous learning of subject-specific models of drowsiness for more efficient monitoring. This paper aims to offer a holistic but comprehensive view of the research and development work conducted for the AUTOMOTIVE project across the various addressed topics and how it ultimately brings us closer to the target of improved driver drowsiness monitoring.
Fast MIMO Beamforming via Deep Reinforcement Learning for High Mobility mmWave Connectivity

Future 5G/6G wireless networks will be increasingly using millimeter waves (mmWaves), where fast and efficient beamforming is vital for providing continuous service to highly mobile devices in the presence of interference and signal attenuation, manifested by blockage. In this paper, we propose a novel and efficient method for mmWave beamforming in massive multiple-input multiple-output (MIMO) systems to achieve the aforementioned goals with low complexity in such scenarios. In doing so, we utilize deep reinforcement learning (DRL) to maximize the network’s energy efficiency subject to the quality of service (QoS) constraint for each user equipment (UE) and obtain its hybrid beamforming matrices. In doing so, we assume each UE is simultaneously associated with multiple access points (APs), i.e., simultaneous beamforming to/from multiple APs (coordinated multipoints) is needed for each UE. We also propose a low-complexity training algorithm, based on approximate message passing, which is well suited for the network edge. Besides, we develop a distributed scheme to reduce communications overhead via federated DRL. Extensive simulations show significant performance improvement over existing methods.
Numerical verification of an Industrial code to simulate accurately large scale Hydrodynamics events

The use of finite-precision arithmetic generates round-off errors at each arithmetical expression so some mathematical properties are lost during the computing of a numerical code. Consequently, the same numerical code using the same input data could produce different results on different computers. The round-off error propagation is exacerbated in High Performance Computing since trillions of floating arithmetic operations can be performed each second. Moreover, due to the domain decomposition, the floating point arithmetic operations are not performed in the same order. There is therefore a need to detect the effect of round-off error propagation in order to make confidence about the results of the simulation. This paper deals with an overview of the numerical verification activities performed at EDF R&D on the parallel TELEMAC-2D code modelling the 2D free surface hydrodynamics. Firstly, a framework developed at EDF R&D to study the effect of the round-off error propagation on the quality of a simulation is exposed. Then, the xD+P approach which has been proposed to measure the numerical quality of the computed values is presented. Finally, a recent work dealing with the improvement of the floating point summation is discussed.
M-CMA for digital signal processing adaptive antennas with microwave beamforming

This paper proposes a novel algorithm, called M-CMA (Modified Constant Modulus algorithm), which is unparalleled to give adaptability to microwave beamforming phased array antennas. Since microwave analog beamformers basically require much less RF devices than digital beamformer, the microwave analog beamformers based on M-CMA, that is adaptive microwave beamformers, can be cheaply fabricated. Therefore, they are much suitable for mobile communication systems where both miniaturization and low-cost are required for the equipment. Actually, M-CMA obtains the gradient vector by perturbing the microwave beamforming control voltage. Though M-CMA is implemented with a digital signal processor, M-CMA controls the microwave analog beamformer by utilizing the gradient vector. The microwave analog beamformer based on M-CMA is analyzed to have the following characteristics. (1) The beamformer can point its main beam to the desired direction in AWGN channels. (2) Although the beamformer has possibility to fail in ill solutions in CCI (Co-Channel Interference) channels, M-CMA can converge to the optimum solution when the desired direction is roughly a priori known.
Potential Target Region Extraction and Isolated Forest With Statistical Correlation Representation for Hyperspectral Anomaly Detection

Anomaly detection is a hot topic in the field of hyperspectral image (HSI) processing, which aims to find anomalous targets through spatial and spectral differences from a complex background. However, there still remains two unsolved problems in anomaly detection methods: 1) since the global image covers more complex scenes, it inevitably suffers a lot of false alarms in the anomaly detection and 2) the sensitivity of the target to the global mode or the local mode detector is different. A detector that only considers one mode usually misses some targets, which makes the detection rate low. This article proposes an anomaly detection method for HSIs with potential target region extraction. The potential target region is extracted through the combination of the tensor robust principal component analysis (RPCA) and the curvature circle model. The obtained subregions are used in the region traversing method to filter out the areas not containing the target. In addition, in order to adapt to the different targets contained in the region, the proposed method combines the isolated forest of the global model and the statistical correlation of the local model, thereby enhancing the separability of the target and the background. Experimental results show that the proposed method can effectively extract potential target regions and greatly reduce the false alarm rate. Furthermore, the proposed method can highlight the target for a higher detection rate and accuracy.
Transfer function design of stable high-order sigma-delta modulators with root locus inside unit circle

In this paper, a systematic method to design stable high-order sigma-delta modulator (SDM) transfer functions, with no need of stability mechanisms, is proposed. It is shown that a high-order SDM can be absolutely stable if the departure angles of the root locus of its noise-shaping function are properly designed. Tradeoffs between stability and performance of the SDMs are presented.
Production of magnetic planetary gear and measurement of basic properties

A non-contact gear mechanism is important for the non-contact transmission of a torque and a motion. In this paper, a magnetic gear system without contact which requires no lubricant oil is proposed. The driving gear consists of some iron discs with gear teeth whose shape is an involute curve. The discs of the follower gear are inserted in the gaps between the discs of the driving gear, and the attractive forces between the discs generate the torque transmission. Using the magnetic gear system, a magnetically connected planetary gear device is developed. Moreover we measure and study the slip torque as static property, and the step-out torque as dynamic property due to implication of rotational speed.
The issue of control in multivariate systems. A contribution of structural modelling

This paper builds upon Judea Pearl’s directed acyclic graphs approach to causality and the tradition of structural modelling in economics and social science. The paper re-examines the issue of control in complex systems with multiple causes and outcomes, in a specific perspective of structural modelling. It begins with three-variable saturated and unsaturated models, and then examines more complex systems including models with collider and latent confounder discussed by Pearl. In particular, focusing on the causes of an outcome, the paper proposes two simple rules for selecting the variables to be controlled for when studying the direct effect of a cause on an outcome of interest or the total effect when dealing with multiple causal paths. This paper presents a model building strategy that allows a statistical model to be considered as structural. The challenge for the model builder amounts to developing an explanation through a recursive decomposition of the joint distribution of the variables congruent with background knowledge and stable with respect to specified changes of the environment.
Derivation of interconnect length distribution in X architecture LSIs

The prediction model for the interconnect length distribution (ILD) in LSIs with orthogonal interconnects based on Rent's empirical rule is extended to the prediction of ILD for the X Architecture containing diagonal interconnects and all-directional interconnects. The effectiveness of the X Architecture is evaluated based on the new prediction model.
Green manufacturing (GM): past, present and future (a state of art review)

Green manufacturing (GM) is fast emerging as the sustainable manufacturing solution that has the potential to solve most problems that the world faces today. GM covers the entire product life cycle from conceptual design to disposal in a benign, harmless manner causing no or minimal adverse impact on environment by optimum use of resources and reduction of waste and pollution. 4Rs (reduce, reuse, recycle, remanufacture) is slowly being accepted and adopted as the model of growth and sustainability the world over. There is a very large volume of literature available on GM dealing with several aspects. This paper is an attempt to comprehensively and systematically review the same and put it in a format which can be easily comprehended and applied. This is an effort of analysing around 123 papers from around 73 leading journals spread over last 15 years. This entire database is critically reviewed and properly classified by the authors. The analysis further revel several emerging issues and challenges which need to be addressed. The key challenge identified is the absence of unified comprehensive GM framework. The authors have finally suggested one such universal GM framework.
Mechanisms for interdomain traffic engineering with LISP

Internet is composed of the inter-connection of tens of thousands of independent networks called Autonomous Systems (ASes). ASes that only provide connectivity to the other ASes are called Internet Service Providers (ISPs). The vast majority of ASes in the Internet are multi-homed with several ISPs to reduce their costs and improve their capacity and robustness. Multi-homing increases the path diversity and thus might enable ASes to choose better quality paths. Unfortunately, the current Internet design does not allow to optimize routing for performance. Indeed, the routes are propagated gradually from AS to AS. If an AS has several routes for a given destination, it can only advertise and use its best one. In addition, the current Internet routing suffers from scalability issues. As a consequence, ASes lack of control on the traffic entering their network. In this thesis, we propose new techniques to enable performance based interdomain incoming traffic engineering. These techniques allow any AS to control its incoming traffic to follow paths that optimize the efficiency (e.g., minimize the delay or maximize the bandwidth). For that purpose, we first introduce a system that allows an AS to control its incoming traffic in a scalable way. This system relies on the Locator/ID Separation Protocol (LISP). We improve the scalability and the robustness of the LISP control-plane with LISP-Tree. Afterward, we present a system that is able to rank the paths in order to determine the best path according to any arbitrary performance criterion. We call this system IDIPS (for ISP-Driven Informed Path Selection). Finally, we show how to combine LISP, LISP-Tree, and IDIPS to achieve performance based interdomain incoming traffic engineering.
Intrusive and Non-Intrusive Load Monitoring (A Survey)

There is not discussion about the need of energyconservation, it is well known that energy resources are limitedmoreover the global energy demands will double by the end of2030, which certainly will bring implications on theenvironment and hence to all of us.Non-Intrusive load monitoring (NILM) is the process ofrecognize electrical devices and its energy consumption basedon whole home electric signals, where this aggregated load datais acquired from a single point of measurement outside thehousehold. The aim of this approach is to get optimal energyconsumption and avoid energy wastage. Intrusive loadmonitoring (ILM) is the process of identify and locate singledevices through the use of sensing systems to support control,monitor and intervention of such devices. The aim of thisapproach is to offer a base for the development of importantapplications for remote and automatic intervention of energyconsumption inside buildings and homes as well. For generalpurposes this paper states a general framework of NILM andILM approaches.Appliance discerns can be tackled using approaches fromdata mining and machine learning, finding out the techniquesthat fit the best this requirements, is a key factor for achievingfeasible and suitable appliance load monitoring solutions. Thispaper presents common and interesting methods used.Privacy concerns have been one of the bigger obstacles forimplementing a widespread adoption of these solutions; despitethis fact, developed countries like those inside the EU and theUK have established a deadline for the implementation ofsmart meters in the whole country, whereas USA governmentstill struggles with the acceptance of this solution by itscitizens.The implementation of security over these approachesalong with fine-grained energy monitoring would lead to abetter public agreement of these solutions and hence a fasteradoption of such approaches. This paper reveals a lack ofsecurity over these approaches with a real scenario.
A Bibliometric Analysis of Neuromarketing: Current Status, Development, and Future Directions

The growth interesting in discovering the consumers' behaviours, emotional and cognitive processes in marketing research have led to an increasing number of publications. This paper aims to evaluate the global research trends in neuromarketing based on the most productive journals, countries, institutions, authors, the number of documents and citations. This paper was structured based on the Preferred Reporting Items for Systematic Reviews and MetaAnalyses (PRISMA) framework to select all relevant documents for this study. A total of 143 papers have been extracted from the Scopus database. The findings revealed that Spain is the leading country with 27 publications, and the most productive institution was Universidad Complutense de Madrid with nine documents. In addition, Babiloni F. is the most prolific author with four publications and 143 citations. Interestingly, although Frontiers in Psychology is the most productive journal with 17 publications, the Journal of Economic Psychology has the highest average citation per item.
Extended State Observer Based Interval Type-2 Fuzzy Neural Network Sliding Mode Control With Its Application in Active Power Filter

Aiming at the difficulties in modeling the active power filter (APF) system and the susceptibility to parameter perturbation and external disturbance, this article proposes a new adaptive sliding mode controller with using a nonlinear extended state observer (NESO) based on an interval type-2 fuzzy neural network (IT2FNN) structure. The IT2FNN is designed to estimate the unknown control coefficient, so that the NESO can estimate the state of the system and the total disturbance including the unmodeled dynamics and external disturbances, and then perform feedforward compensation to achieve active disturbance rejection. Simulation and experimental results show that the proposed control strategy is effective in the harmonic suppression of the APF system and has better steady-state and dynamic performance compared with the existing methods.
Solid State Transformer Concept Development.

Abstract : This report describes an effort made to determine the feasibility of developing a circuit using power semiconductor devices to duplicate the function of the power transformer. A circuit concept has been developed which duplicates the primary function of voltage stepup/stepdown but does not demonstrate the DC isolation characteristic of normal transformers. Several characteristics of the circuit appear very attractive, such as increased voltage regulation and relatively high efficiency. (Author)
Slot permeance effects on rotor slot harmonics in induction machines

Induction machines form the backbone of a substantial portion of the adjustable speed drives' applications. Among the current estimation techniques available for speed-sensorless induction motor drives, speed measurement based on rotor slot harmonic (RSH) detection in machine line current happens to be a prominent one. The paper attempts to investigate the effect of slot permeance on the production of RSH. Simulation studies on a small motor but with a popular stator, rotor slot and pole combination suggest that their effect is less significant compared to rotor space harmonics effect. The cause of the less significant slot harmonic is shown to be the reverse rotating field caused by voltage unbalances and constructional imperfections and is thus absent in an ideal machine running from a balanced supply.
A seat sensitivity study on vertical vibrations and seat pressure distributions using numerical models

The introduction of a new comfortable car seat or interior is a time consuming and costly process for car and seat manufacturers. The application of numerical models of human and seat could facilitate this process. Vertical vibrations and seat pressure distributions are two objective parameters that have been related to the subjective feeling of (dis)comfort that can be predicted by numerical tools. In this paper, human models suitable for prediction of human behaviour in vertical vibrations and seat pressure distributions are applied in a seat sensitivity study. The objective of this paper is to evaluate the applicability of the human models as design tools for car and seat developers in an early stage of the design process. The sensitivity of the output of the models for variations in seat characteristics for seat developers in the design process of a new comfortable car seat has been studied. The human models proved to be valuable tools for seat developers in an early stage of the design process. The design study shows that human model behaviour in vertical vibrations is sensitive to variations in cushion and suspension stiffness. Seat pressure distributions are sensitive to variations in cushion thickness and cushion stiffness.