Miracle-dz/UniFAR-FTUs huggingface dataset:
Finite theories before and after the discovery of a Higgs boson at the LHC

Finite Unified Theories (FUTs) are N = 1 supersymmetric Grand Unified Theories (GUTs) which can be made finite to all‐loop orders, based on the principle of reduction of couplings, and therefore are provided with a large predictive power. Confronting the predictions of SU(5) FUTs with the top and bottom quark masses and other low‐energy experimental constraints a light Higgs‐boson mass in the range Mh ∼ 121–126 GeV was predicted, in striking agreement with the recent discovery of a Higgs‐like state around ∼ 125.5 GeV at ATLAS and CMS. Furthermore the favoured model, a finiteness constrained version of the MSSM, naturally predicts a relatively heavy spectrum with coloured supersymmetric particles above ∼ 1.5 TeV, consistent with the non‐observation of those particles at the LHC. Restricting further the best FUT's parameter space according to the discovery of a Higgs‐like state and B‐physics observables we find predictions for the rest of the Higgs masses and the supersymmetric particle spectrum.
Scene classification using multi-scale deeply described visual words

ABSTRACT This article presents a deep learning-based Multi-scale Bag-of-Visual Words (MBVW) representation for scene classification of high-resolution aerial imagery. Specifically, the convolutional neural network (CNN) is introduced to learn and characterize the complex local spatial patterns at different scales. Then, the learnt deep features are exploited in a novel way to generate visual words. Moreover, the MBVW representation is constructed using the statistics of the visual word co-occurrences at different scales, which are derived from a training data set. We apply our technique to the challenging aerial scene data set: the University of California (UC) Merced data set consisting of 21 different aerial scene categories with sub-metre resolution. The experimental results show that the statistics of deeply described visual words can characterize the scene well and improve classification accuracy. It demonstrates that the proposed method is highly effective in the scene classification of high-resolution remote-sensing imagery.
Multiscale Singularity Analysis of Cutting Forces for Micromilling Tool-Wear Monitoring

This paper introduces a novel approach for tool condition monitoring (TCM) in micromilling, which is based on the analysis of singularity of cutting force waveforms and the statistical distribution of the singularity measure. It is a multiscale approach with both localized and global cutting force analyses. The local singularity characteristics of the cutting force are measured by the Holder exponent at the point and determined by wavelet transform modulus maxima. The global characteristics are measured by the singularity spectrum, which represents the overall behavior of the singularity among different tool-wear states. Experimental studies from both micromilling of copper and steel show that the axial component of the cutting force is robust and most discriminant for TCM using its singularity measurements.
The use of ground-penetrating radar to develop a track substructure characterisation model

The characterisation of track substructure is an integral component of track maintenance and rehabilitation. Traditionally this is done by determining the geotechnical properties of the discrete track formation layers by excavating test pits and sampling the substructure layers. The development of geophysical investigation techniques such as ground-penetrating radar (GPR) allows continuous assessment of the condition of the track substructure. The research described in this paper uses GPR to develop a track substructure characterisation model and provides classifications for both the ballast and formation layers. The ballast and formation were classified into four classes, namely very good, good, moderate and poor. When applying the model to two sections of track (with generally good and poor quality) 82% and 100% of classes had only one class difference compared to the traditional characterisation tests for the formation and ballast layers respectively. The GPR track substructure characterisation model that was developed therefore compares well with traditional characterisation techniques and will result in significant cost and time reduction. The characterisation of the track using GPR provides a continuous classification and enhances the accuracy of the data on which a maintenance engineer can base decisions.
Learning with collaborative inquiry: a science learning environment for secondary students

When inquiry-based learning is designed for a collaborative context, the interactions that arise in the learning environment can become fairly complex. While the learning effectiveness of such learning environments has been reported in the literature, there have been fewer studies on the students’ learning processes. To address this, the article presents a study of science learning in a computer-supported learning environment called Collaborative Science Inquiry (CSI), which integrates guided inquiry principles for activity design, employs modelling and visualisation tools for promoting conceptual understanding and incorporates key computer-supported collaborative learning (CSCL) elements for enabling students’ collaboration. With the aim of understanding the process of students’ conceptual changes supported by the CSI learning environment as used in a secondary school, data on students’ test achievements, responses to learning tasks and peer discussions in collaboration were collected, analysed and discussed. The results of the qualitative and quantitative data analysis indicated that guided inquiry coupled with CSCL elements facilitated by the CSI system can engage students in inquiry activities and promote their conceptual understanding in a progressive way.
Surface-Tension Driven Heterogeneous Integration of Thin Film Photonic Devices Using Micro-Contact Printing for Multi-Material

We introduce a surface-tension driven heterogeneous integration of thin film photonic devices using a surface wetting modification. In this process, the combination of a micro-contact printing method and plasma surface modification is used to se- lectively form a binding liquid on an integration host substrate. With predefined integration areas using the binding liquid, thin film GaAs photodetectors (PDs) are successfully integrated. We have demonstrated the implementation of this integration method by presenting a multi-material photonic integrated structure with integratedGaAsbasedthinfilmPDsandapolymerwaveguideona silicon substrate. The measured average misalignment of the inte- grated PDs was 2.8 mf rom the predefined integration locations. Stable electrical contact between the PDs and the host substrate has been confirmed with dark and photocurrent measurements. The proposed process has the potential towards a low-cost, par- allel heterogeneous integration of III-V photonic devices on a sil- icon platform.
A Sequential Hypothesis Testing Algorithm For Rapid Accurate Discrimination Of Tachyarrhythmias

We describe an algorithm for discrimination of supraventricular tachycardia (SVT) and ventricular tachycardia (VT) in implantable arrhythmia termination devices. The goal of an arrhythmia detection algorithm is to classify the rhythm as quickly and as accurately as possible. The sequential hypothesis testing method that we apply allows an elegant tradeoff between accuracy and detection time. The false positive (FP) and false negative (FN) rates are predefined within the algorithm for each decision that the program makes. Thus the detection time can be decreased if absolute accuracy is not essential, and the accuracy of the algorithm can be increased at the expense of a quick decision. 30 data segments were analyzed: 9 normal sinus rhythms(NSR), 9 SVT. and 12 VT. 23 of the segments were correctly classified within 3 seconds and all 30 were correctly diagnosed in 8 seconds.
Peran Pemerintah Daerah Dan Partisipasi Pelaku Usaha Dalam Pengembangan UMKM Manik-Manik Kaca di Kabupaten Jombang

This research was backed by the reality that micro, small and medium enterprises underwent significant development than large enterprises, development can be seen from the large amount of business units and labor absorbed, also in the Regency of Jombang, micro, small and medium enterprise has significant development, one of the micro, small and medium enterprises which evolved significantly is glass beads. Significant development of glass beads due to role of local government through the department of cooperatives and small, medium enterprises as well as the active participation of the businessman glass beads. Therefore, this study aims to describe the role of local government in the development glass beads and describe participation of businessman in the development of glass beads too. This research used a descriptive qualitative method. The samples of the research were taken by using a purposive sampling technique. The data of the research were gathered through observation, in-depth interview, and documentation (content analysis). The data were validated through data triangulation. The data were then analyzed by using an interactive technique of analysis comprising data reduction, data display, and conclusion drawing. The results showed that local government acted as a facilitator that is manifested through training activities, capital and technology assistance, the local government also acted as a catalyst that is manifested through promotional products activities, and determination of glass beads as a superior product Jombang Regency. While the participation of businessman is participation in decision making by providing ideas in meeting group between government and businessman, then participation in implementation by coordination of training activities, also participation in taking of benefit in the form of increase business turnover.
Component Object Model (COM)

The Component Object Model COM ActiveX Technology Background The Component Object Model The Problem That COM Solves The Essence of COM What Is a COM Interface? The IUnknown Interface and the QueryInterface() Member Function Reference Counting: The AddRef() and Release() Functions Class Factories The CCmdTarget Class The MYMFC28A Example: A Simulated COM The MYMFC28A From Scratch Real COM with the MFC Library The COM CoGetClassObject() Function COM and the Windows Registry Runtime Object Registration How a COM Client Calls an In-Process Component How a COM Client Calls an Out-of-Process Component The MFC Interface Macros The MFC COleObjectFactory Class AppWizard/ClassWizard Support for COM In-Process Components The MYMFC28B Example: An MFC COM In-Process Component MFC COM Client Programs Containment and Aggregation vs. Inheritance Note: The IUnknown Interface
The exploitation of provenance and versioning in the reproduction of e-experiments

Reproducibility has long been a cornerstone of science, and is now becoming a key research area for e-Science. This is because it provides a way to validate, and build on, previous results. Underpinning reproducibility in e-Science is provenance, which has the potential to provide scientists with a complete understanding of data generated in eexperiments, including the services that produced and consumed it. This thesis explores the issues in exploiting provenance for reproducibility. Based on this, a reproducibility framework is designed and implemented to allow past experiments to be reproduced. Seven aspects of reproducibility are considered: 1) experiments, 2) reproducibility, 3) provenance, 4) provenance models, 5) provenance and versioning, 6) automatic transformation of provenance to support reproduction, and 7) a reproducibility taxonomy. A key to reproducibility is the provenance model: a data model that structures information about an e-experiment. A review of existing provenance systems shows that the problem caused by services being updated has been neglected. This can have a severe impact on the ability to reproduce experiments and it is therefore argued that the issue of service versioning must be addressed. Even after information on the provenance of an execution, and versioning of services, is captured there is the need for a method to transform this knowledge into a form that allows past experiments to be reproduced: that is another output of this thesis. The thesis focuses on the use of work ow as a means to represent the composition, and to execute experiments. This work explores how work ows can be automatically generated to re-execute past experiments. In order to do this, a transformation algorithm is described that maps a past experiment's execution log data into a work ow format that can be read and processed by the workow system. The thesis also introduces a Reproducibility Taxonomy that captures and structures the information required for reproducibility in the presence of versions and provenance.
Dynamical Mechanical Systems Under Random Impulses

dynamical mechanical systems under random impulses is available in our book collection an online access to it is set as public so you can get it instantly. Our book servers spans in multiple countries, allowing you to get the most less latency time to download any of our books like this one. Merely said, the dynamical mechanical systems under random impulses is universally compatible with any devices to read.
High throughput implementation of an adaptive serial concatenation turbo decoder

The complete design of a new high throughput adaptive turbo decoder is described. The developed system is programmable in terms of block length, code rate and modulation scheme, which can be dinamically changed from frame to frame, according to varied channel conditions or user requirements. A parallel architecture with 16 concurrent SISOs has been adopted to achieve a decoding throughput as high as 35 Mbit/s with 10 iterations, while error correcting performance are within 1dB from the capacity limit. The whole system, including the iterative decoder itself, de-mapping and de-puncturing units, as well as the input double buffer, has been mapped to a single FPGA device, running at 80 MHz, with a percentage occupation of 54%.
Advanced Differential Quadrature Methods

Thank you for downloading advanced differential quadrature methods. Maybe you have knowledge that, people have search hundreds times for their chosen readings like this advanced differential quadrature methods, but end up in malicious downloads. Rather than enjoying a good book with a cup of coffee in the afternoon, instead they juggled with some malicious virus inside their laptop. advanced differential quadrature methods is available in our digital library an online access to it is set as public so you can get it instantly. Our book servers hosts in multiple countries, allowing you to get the most less latency time to download any of our books like this one. Kindly say, the advanced differential quadrature methods is universally compatible with any devices to read.
Lessons From America An Exploration

From the combination of knowledge and actions, someone can improve their skill and ability. It will lead them to live and work much better. This is why, the students, workers, or even employers should have reading habit for books. Any book will give certain knowledge to take all benefits. This is what this lessons from america an exploration tells you. It will add more knowledge of you to life and work better. Try it and prove it.
An RF-MEMS based SP4T switched LNA MMIC used in a 24 GHz beam-steering antenna module

This paper presents an RF-MEMS SP4T switched LNA MMIC used in a 24 GHz beam-steering antenna module. The SP4T LNA has a measured gain of 10-16 dB at 16-30 GHz (NF=2.6-3.0 dB at 16-26 GHz) with up to 37 dB of isolation at 24 GHz when one of the four MEMS switches are closed while the other switches are open. To the authors' knowledge, this work represents a first-time realisation of a MEMS SP4T LNA MMIC used as an on-chip active beam-switching network in an adaptive antenna. The experimental results successfully demonstrate that the MEMS SP4T LNA can be used to control the antenna beam in 4 different directions between -55° and 45° in the same plane.
Development of Well Placement Optimization Model using Artificial Neural Network and Simulated Annealing

This study presents the development of a well placement optimization model, combining an artificial neural network, which enables high-speed calculation, with a simulated annealing algorithm. The conventional FDM simulator takes excessive time when used to perform a field scale reservoir simulation. In order to solve this problem, an artificial neural network was applied to the model to allow the simulation to be executed within a short time. Also by using the given result, the optimization method, SA algorithm, was implemented to automatically select the optimal location without taking any subjective experiences into consideration. By comparing the result of the developed model with the eclipse simulator, it was found that the prediction performance of the developed model has become favorable, and the speed of calculation performance has also been improved. Especially, the optimum value was estimated by performing a sensitivity analysis for the cooling rate and the initial temperature, which is the control parameter of SA algorithm. From this result, it was verified that the calculation performance has been improved, as well. Lastly, an optimization for the well placement was performed using the model, and it concluded the optimized place for the well by selecting regions with great productivity.
Hopping And Related Phenomena

Thank you for downloading hopping and related phenomena. As you may know, people have search hundreds times for their favorite readings like this hopping and related phenomena, but end up in infectious downloads. Rather than enjoying a good book with a cup of tea in the afternoon, instead they cope with some harmful virus inside their computer. hopping and related phenomena is available in our digital library an online access to it is set as public so you can download it instantly. Our book servers saves in multiple countries, allowing you to get the most less latency time to download any of our books like this one. Merely said, the hopping and related phenomena is universally compatible with any devices to read.
FACIAL EXPRESSION IDENTIFICATION BY USING FEATURES OF SALIENT FACIAL LANDMARKS

Facial expression recognition/identification (FER) systems plays vital role in the field of biometrics. Localizing the facial components accurately is a challenging task in image analysis and computer vision. Accurate detection of face and facial components gives effective performance with classification of expressions. This paper proposes feature based facial recognition system using JAFFE and CK databases. 18 facial landmarks were located using Haar cascade classifier. The distances between 12 points were extracted as features. These features were classified using SVM and K-NN classifier and comparison based on accuracy and execution time is done. The proposed algorithm gives better performance
Generating object proposals for improved object detection in aerial images

Screening of aerial images covering large areas is important for many applications such as surveillance, tracing or rescue tasks. To reduce the workload of image analysts, an automatic detection of candidate objects is required. In general, object detection is performed by applying classifiers or a cascade of classifiers within a sliding window algorithm. However, the huge number of windows to classify, especially in case of multiple object scales, makes these approaches computationally expensive. To overcome this challenge, we reduce the number of candidate windows by generating so called object proposals. Object proposals are a set of candidate regions in an image that are likely to contain an object. We apply the Selective Search approach that has been broadly used as proposals method for detectors like R-CNN or Fast R-CNN. Therefore, a set of small regions is generated by initial segmentation followed by hierarchical grouping of the initial regions to generate proposals at different scales. To reduce the computational costs of the original approach, which consists of 80 combinations of segmentation settings and grouping strategies, we only apply the most appropriate combination. Therefore, we analyze the impact of varying segmentation settings, different merging strategies, and various colour spaces by calculating the recall with regard to the number of object proposals and the intersection over union between generated proposals and ground truth annotations. As aerial images differ considerably from datasets that are typically used for exploring object proposals methods, in particular in object size and the image fraction occupied by an object, we further adapt the Selective Search algorithm to aerial images by replacing the random order of generated proposals by a weighted order based on the object proposal size and integrate a termination criterion for the merging strategies. Finally, the adapted approach is compared to the original Selective Search algorithm and to baseline approaches like sliding window on the publicly available DLR 3K Munich Vehicle Aerial Image Dataset to show how the number of candidate windows to classify can be clearly reduced.
Increased Noise in Cortico-Cortical Integration After Mild TBI Measured With the Equivalent Noise Technique

The bulk of deficits accompanying mild traumatic brain injury (mTBI) is understood in terms of cortical integration—mnemonic, attentional, and cognitive disturbances are believed to involve integrative action across brain regions. Independent of integrative disturbances, mTBI may increase cortical noise, and this has not been previously considered. High-level integrative deficits are exceedingly difficult to measure and model, motivating us to utilize a tightly-controlled task within an established quantitative model to separately estimate internal noise and integration efficiency. First, we utilized a contour integration task modeled as a cortical-integration process involving multiple adjacent cortical columns in early visual areas. Second, we estimated internal noise and integration efficiency using the linear amplifier model (LAM). Fifty-seven mTBI patients and 24 normal controls performed a 4AFC task where they had to identify a valid contour amongst three invalid contours. Thresholds for contour amplitude were measured adaptively across three levels of added external orientation noise. Using the LAM, we found that mTBI increased internal noise without affecting integration efficiency. mTBI also caused hemifield bias differences, and efficiency was related to a change of visual habits. Using a controlled task reflecting cortical integration within the equivalent noise framework empowered us to detect increased computational noise that may be at the heart of mTBI deficits. Our approach is highly sensitive and translatable to rehabilitative efforts for the mTBI population, while also implicating a novel hypothesis of mTBI effects on basic visual processing—namely that cortical integration is maintained at the cost of increased internal noise.