Reviewerly/exHarmony huggingface dataset:
Continuous Measurements for Advanced Quantum Metrology

We review some recent results regarding the use of time-continuous measurements for quantum-enhanced metrology. First, we present the underlying quantum estimation framework and elucidate the correct figures of merit to employ. We then report results from two previous works where the system of interest is an ensemble of two-level atoms (qubits) and the quantity to estimate is a magnetic field along a known direction (a frequency). In the first case, we show that, by continuously monitoring the collective spin observable transversal to the encoding Hamiltonian, we get Heisenberg scaling for the achievable precision (i.e., 1 / N for N atoms); this is obtained for an uncorrelated initial state. In the second case, we consider independent noises acting separately on each qubit and we show that the continuous monitoring of all the environmental modes responsible for the noise allows us to restore the Heisenberg scaling of the precision, given an initially entangled GHZ state.
Manzoni e la lingua

This paper provides an overview of two types of writings by and about Manzoni published in the years 2007-2017: new editions of Manzoni’s works about language, and critical studies about them; studies on Manzoni’s language, performed with linguistic tools. Editions, books and essays that belong to these groups are presented, discussed and finally listed.
Investigating the Robustness and Stability to Noisy Data of a Dynamic Feature Selection Method

The curse of dimensionality is one of the major problems faced by machine learning researchers. If we consider the fast growing of complex data in real world scenarios, feature selection (FS) becomes a imperative step for many application domains to reduce both data complexity and computing time. Based on that, several studies have been developed in order to create efficient FS methods that performs this task. However, a bad selection of one single criterion to evaluate the attribute importance and the arbitrary choice of the number of features usually leads to a poor analysis. On the other hand, recent studies have successfully created models to select features considering the particularities of the data, known as dynamic feature selection. In this paper, we evaluate one of this successful methods, called pareto front based dynamic feature selection (PF-DFS), to test its stability and robustness in noisy data. We used 15 artificial and real world data with additional noise data. Results shown that the PF-DFS is more stable to noisy scenarios than existing feature selection methods.
Intensity Distribution From a Single-Bulb Solar Simulator Identification Through Inverse Ray Tracing

Abstract Through the flux characterization of a high flux solar simulator, all directional information of the flux distribution is lost. Therefore, an experimental approach is necessary to restore the directional information. In this study, 13 heat flux maps were experimentally obtained from a 10 kWe Xenon arc solar simulator through an indirect flux mapping technique, implementing the use of one Lambertian target. The formulation of the inverse problem of experimentally determining the intensity distribution at the focal plane is presented. In addition, a Monte Carlo ray tracing in-house code modeling the Xenon arc is developed and used to generate the experimentally obtained flux maps and intensity at the focal plane to be used as a reference. Two intensity interpolation schemes were examined; a zeroth and first-order schemes. It is shown that a first order interpolation unnecessary complicates the inverse problem. The percentage error reduced from 90.9% to 82.6% when changing the interpolation scheme from a first to zeroth-order, in addition to a five times reduction in computational time. Furthermore, a new approach of constraining the formulated system of equations with an equality constraint that works by eliminating some of the intensity values that cannot be traced back to the ellipsoidal reflector is proposed. Therefore, it can be used as a technique to change the ill-conditioned problem to a well-conditioned one, without depending heavily on Tikhonov regularization methods. This new approach provided intensity values at the focal plane with a reduced percentage error from 52.2% to 30.4% for the zeroth-order interpolation scheme.
Stochastic Relational Network

Reasoning about relations among a set of objects is one of the key aspects of human intelligence, and Relational Networks (RNs) are one of the classes of architectures that specializes in such relational reasoning. However, RNs are limited in their general applicability due to significant (quadratic) complexity of all-pair comparative operations. In this paper, we propose Stochastic RN (SRN) that learns to prune distractors and pick task-related objects that are crucial for relational reasoning, thereby reducing forward and backward computation costs with minimal sacrifice. We empirically show that our approach is effective in a real-world visual question-answering task, where vanilla RNs might be computationally expensive to run due to the sheer number of candidate objects for each image.
CloudFormation-Based Tools

In Chapter 2 , we looked at a variety of tools that form an ecosystem around CloudFormation. In this chapter, we'll take a look at two of these tools: Troposphere, a DSL wrapper, and Sceptre, an orchestration tool. We will discover how these tools interact with CloudFormation and how they can enhance our use of CloudFormation. Specifically, we will cover the following:
LibGuides: ALI Open Educational Resources: Home

A guide to Open Educational Resources provided by the Affordable Learning Committee of the Academic Libraries of Indiana (ALI)
Klassifikasiya metodlarının zərərli proqramların aşkarlanmasına tətbiqi

Abstract─In recent years, the increasing variety and complexity of malware, facing personal data with threat requires research towards detection and analyzing.This study investigated the methods of analyzing and detecting malware, applied classification methods on dataset based features extracted from 138047 malware and benign files using the python framework, and the effectiveness of the methods have been analyzed using the evaluation metrics.
A Spatial and Temporal Analysis of Atmospherics Parameters Retrieved by a Neuro-varationnal Method off the West African Coast

In this work, we study spatial and temporal atmospherics parameters evolution retrieved by neuro-variationnal method from SeaWiFS observations measured off the west African coast.&#x0D; The SeaWiFS sensor measures the radiance above the top of atmosphere (TOA) solar irradiance.&#x0D; SeaWiFS use standard algorithm to invert the signal in order to retrieve weakly absorbing aerosol optical thickness (AOT) less than 0.3 whereas the Senegalese coasts are frequently crossed by desert dust plumes from large optical thickness.&#x0D; A neural algorithm, so-called SOM-NV, was developed to deal with absorbing aerosols and to retrieve their optical parameters, off the Senegalese coast, from SeaWiFS observations.&#x0D; The impact of meteorological variables on these restitutions was studied over the entire period of the observations that we analyzed and over the whole studied area, on the one hand, but also in a more thorough way on three "sub-area" located in north, south and center. The results obtained showed that the composition of aerosols in the atmosphere is a function of the seasons. High altitude zonal U winds are correlated with non-desert aerosols of -62.16% in winter and autumn. The correlation is -60.32% between dust aerosols and the zonal wind.
Structure From Motion on XSlit Cameras

We present a structure-from-motion (SfM) framework based on a special type of multi-perspective camera called the cross-slit or XSlit camera. Traditional perspective camera based SfM suffers from the scale ambiguity which is inherent to the pinhole camera geometry. In contrast, an XSlit camera captures rays passing through two oblique lines in 3D space and we show such ray geometry directly resolves the scale ambiguity when employed for SfM. To accommodate the XSlit cameras, we develop tailored feature matching, camera pose estimation, triangulation, and bundle adjustment techniques. Specifically, we devise a SIFT feature variant using non-uniform Gaussian kernels to handle the distortions in XSlit images for reliable feature matching. Moreover, we demonstrate that the XSlit camera exhibits ambiguities in pose estimation process which can not be handled by existing work. Consequently, we propose a 14 point algorithm to properly handle the XSlit degeneracy and estimate the relative pose between XSlit cameras from feature correspondences. We further exploit the unique depth-dependent aspect ratio (DDAR) property to improve the bundle adjustment for the XSlit camera. Synthetic and real experiments demonstrate that the proposed XSlit SfM can conduct reliable and high fidelity 3D reconstruction at an absolute scale.
pnlbwh/TBSS: Integrate html report generation with main process

Integrate writeHtml.py with tbss_all calculate meanFAmask in FSL way merge 4D data according to sequence provided in caselist
Comparison of Pixel Correlation Induced by Space-Filling Curves on 2D Image Data

Space-filling curves are well known for preserving pixel locality when they are used as paths to traverse 2D image data. Some prediction-based compression algorithms make use of these curves to ensure high pixel values correlation during 2D image data traversal. This work explores the distribution of pixel correlation induced by all possible space-filling curves on 2D image data and demonstrates that commonly used curves, such as the Hilbert or the Peano curves, do not provide the best possible pixel correlation for natural photographic images. Using experimental data collected on a large set of such images, we demonstrate that row-prime ordering is the best choice for preserving maximum pixel values correlation while reducing the dimensionality of 2D natural photographic image data.
Effective Communication of Patient Information Leaflets (PILs) in Selected Malaria Drugs in Nigeria

Communication is a soul-train that connects the humans of the same speech community. Effective communication is even a larger soul-train that promotes a peaceful co-existence among the humans. It is established that fracas of all sorts ensue when a society debars effective communication; to misunderstand or not know medical inscriptions attracts the worst health catastrophe that a society can ever imagine. It is against this background that this study investigates if the educated Nigerian malaria users understand the instructions contained in selected Nigerian Malaria Drug Patient Information Leaflets (PILs). The study designed a questionnaire, which consisted of nine question items, and administered it on 900 educated Nigerians through the Google Form Online Outlet (GFOO). To analyse the data, the study applied the non-inferential tools of frequency count and percentage in order to draw conclusions from the natures and features of the data obtained for the study. The study presents, among other findings, that the majority of the educated Nigerians do not understand the PILs of the malaria drugs due to the strange or technical nature of the words, and the complex nature of the sentences used to write the leaflets.
Key Competencies for Digital Personnel in the Cyber Economy and How to Master Them

The current formation of the cyber economy requires the development of new competencies in the labor force. In this chapter, the author considers the key competencies that need to be developed. The increase of the role of information technologies in the modern economy presents new challenges for those who work in retail, the public sector, finance, and production. In order to achieve the expected increases in competitiveness, organizations must ensure that their management systems ensure the high levels of personnel training.
Fast digital image correlation using parallel temporal sequence correlation method

Digital image correlation (DIC) is a noncontact technique that is widely used for deformation measurement, but improving the calculation efficiency to achieve real-time DIC calculation has always been a big concern. A parallel temporal sequence DIC method is proposed, which chooses seed points to determine the integer-pixel displacement and applies the moving least-squares fitting technique to acquire the subpixel displacement. This method avoids traditional complex iterations and takes full advantage of the GPU parallel computing. Results of a simulation experiment and an actual experiment demonstrate the accuracy and efficiency of the proposed algorithm. The calculation speed in the simulation experiment of the proposed method achieved 463,320 POI/s, whereas the speed in the actual experiment was 432,866 POI/s, when the speed of the ICGN method was 2700 POI/s and 2074 POI/s under the same accuracy, respectively. Also, the subpixel displacement calculation made up less than 1% of the entire calculation. The computational efficiency could be further enhanced if a faster integer-pixel displacement calculation method is discovered or a parallel algorithm is used.
REVIEW OF ROAD DRAINAGE SYSTEM (CASE STUDY: JALAN CIGOMBONG KM 16 - KM 23)

A good road drainage system is needed to ensure that road user activities are not disrupted due to rain puddles. The cause of inundation that occurs is land use change, there is no drainage channel, the channel is not well connected, the channel is closed due to widening of the road without considering drainage channels. Given this, research needs to be carried out on the condition of the existing drainage system as a material consideration for evaluating its feasibility and planning a drainage system that is able to overcome the inundation that occurs. Writing this final project refers to primary data and secondary data that already exist. The rainfall data came from the Climatology and Geophysics Meteorological Agency, Balai Besar Region II, Bogor Regency, which is the Darmaga huajn rainfall measurement station and the PUPR Binamarga Office of Bogor Regency. Meanwhile, to find out the dimensions of the existing drainage channels obtained by conducting surveys and direct observation to the field. Data analysis which was carried out was hydrological and hydraulics analysis. Hydrological analysis includes the analysis of rainfall frequency, determining the repeat period, calculating the concentration time, analyzing the rainfall intensity, and calculating the flow flow plan. Based on the results of hydrological analyzes, the hydraulics analysis is then performed, such as calculating the plan channel profile and calculating the height of the planned channel guard. From all of these analyzes, the results of the drainage study on the Cigombong KM 16 - KM 23 highway were carried out, that is, the entire capacity of the existing canals was not able to accommodate the planned flow discharge for a return period of 2 years 5 years 50 years. In addition, the results of the analyzes that have been carried out show that the rain that occurs during a certain period of time and a certain return period greatly affects the planned drainage channel profile and is due to the large amount of garbage in the channel which affects the reservoirs in the drainage that often occur frequently
Migraine, Dizziness and Motion Sickness: Are we going in straight lines?

Editorial
Modification of Forms and Methods in the Educational Achievements Assessment of the Students – Requirements of Our Times

In article is considered the relevance of reconsideration of the established evaluation practices of process and educational outcomes of the students in institutions of higher education. Also, it is noted, the necessity in modification of whole relationships, which arising in the educational process. The contemporary assessment forms of knowledge, skills, abilities and competencies aimed at creating a new educational conditions, changing the content, technologies, training tools, strengthening the self - monitoring skills of the students, increasing their responsibility for educational process and for results were considered.
Forward Private Searchable Encryption with Conjunctive Keywords Query

Dynamic searchable symmetric encryption (DSSE) allows addition and deletion operation on an encrypted database. Recently, several attack works (such as IKK) show that existing SSE definition which leaks access pattern and search pattern cannot capture the adversary in the real world. These works underline the necessity for forward privacy. To achieve forward privacy, updating search token is considered as a simple yet efficient method. In this paper, we concentrate on scenario of updating a batch of files containing the same keyword and propose an efficient forward private searchable encryption (EFSE) scheme with a novel batch update. In this scenario, by batch update method, the search token corresponding to the keyword only needs to be updated once. Then for each file in the batch, we use updated search token combining number of this file in the batch to transform the pair (file, keyword) into encrypted index. In the scenario mentioned above, the number of updating search token operation in our EFSE is 1, while the one in existing forward private searchable encryption scheme based on updating search token is the size of batch. In addition, by integrating Cash’s OXT scheme, we extend our EFSE scheme to support conjunctive keywords query. Finally, we give the rigorous security analysis for our proposed two schemes and give performance evaluation for the basic one.
Implementing the motion-based video clipping algorithm for monitoring surveillance video streams

Communication is exchanging or transfer of the data so that the internet of things is but something like transferring of data or things or we can say exchanging several things. The use of authorized systems from the help of the internet is calculated as by 2020 that there will be the availability of billions of systems all around. The objective for the project shall be defining safekeeping alert system of devices by taking care of the power-related aspects by the internet of things.
ANALISA METODE DATA MINING PADA PRODUKSI PERIKANAN LAUT YANG DIJUAL DI TEMPAT PERIKANAN IKAN (TPI)

The purpose of this research is that the results of the utilization of fish resources in producing marine fisheries by fishermen can be good using the K-Means clustring method. Data was obtained from the Central Statistics Agency (BPS) and assisted using RapidMiner software. Data used from 2013-2017 consisted of 21 Provinces. With these data can be obtained data with high-level clusters (C1), namely Central Java with production 587002.8 and low-level clusters (C2) provinces of Aceh, North Sumatra, West Sumatra, Bengkulu, Lampung, Bangka Belitung Islands, DKI Jakarta, West Java , DI Yogyakarta, East Java, Banten, Bali, West Nusa Tenggara, West Kalimantan, Central Kalimantan, North Sulawesi, Central Sulawesi, South Sulawesi, Southeast Sulawesi and Gorontalo with a production of 20302.28. This can be input to the government for provinces that have low water catchment areas to be of more concern based on the cluster that has been done.Keywords: K-Means, Sea Fish Production, Clustering, Territory
Geology and metallogeny of the Mt. Carlton district, Bowen Basin (NE Australia)

NE Queensland, Australia is characterized for hosting abundant magmatic-hydrothermal mineral deposits related to Carboniferous and Permian magmatism (Henderson, 1980; Champion and Bultitude, 2013). Some of these deposits are located in the northern tip of the Bowen Basin, 150 km south of Townsville. Evolution Mining holds the ground of the Mt. Carlton district that includes the only deposit currently in production, the Mt. Carlton Au-Cu-Ag deposit (Sahlstrom et al., 2018), and several other prospects of porphyry copper, high-sulfidation and low-sulfidation epithermal type mineralization. In this study, we present a detailed chronostratigrapy based on newly obtained LA-ICP-MS U-Pb zircon dating in order to distinguish the different volcanoplutonic events through time. Additionally, we also provide a new and complete geochronological work on the different mineral prospects based on step-heating Ar-Ar (alunite, illite and adularia), to correlate volcanoplutonic stages with mineralization events.
Here is the #questiontheweb grant @shsabrams @hickstro ...

Here is the #questiontheweb grant @shsabrams @hickstro and I submitted https://jgregorymcverry.com/questiontheweb #lra19
IMPROVING THE STUDENTS’ VOCABULARY MASTERY THROUGH HANGMAN GAME AT SMA NEGERI 1 TEBING TINGGI KAB. SERDANG BEDAGAI.

The capability in mastering the language is closely related to vocabulary so that we can master the language itself. One of the factors is teaching by using media, for example Mobile phone. The mobile phone offer many kinds of applications for different purposes. One of the applications is Hangman Game. This research has also shown that Hangman Game is effective to improve students’ vocabulary. However the use of mobile phone as media in Indonesia still relatively few and the impact of it is the students have not motivation and passive in the class because they feel bored. They also have not a lot of vocabulary. The subjects of this study were 20 students at 10th grade in SMA Negeri 1 Tebing Tinggi Kab. Serdang Bedagai in academic year 2018/2019. The participant of this research was 20 students. This research was aimed to find out the improving the students’ vocabulary mastery Through Hangman Game. This research was conducted by using classroom action research that consists of 2 cycles. The researcher used the technique by Miles and Huberman for the analysis of qualitative data that were taken from interview, observation, researcher’s note and documentation. While the quantitative data were taken from the test that has given to the students in form of pre-cycle, cycle I and the cycle 2. The result of this research showed that the mean of the students score in pre-cycle was 55,00 in which there were 3 from 20 students who passed the standard minimum score or KKM. In the post test I, there were 9 students who passed the test or 45% who improved and the mean score in the cycle I was 67,45. Meanwhile, in the cycle II, the mean score was 81,45. There were 16 students or 80% passed the standard minimum score. It indicated that Hangman Game could improve the students’ vocabulary mastery. The finding revealed that Hangman Game gave new atmosphere in learning process, so the students were more active, enthusiastic and had good motivation in learning process. Besides that Hangman is effective to improve students’ vocabulary.