Reviewerly/exHarmony huggingface dataset:
Practical Meta-Reinforcement Learning of Evolutionary Strategy with Quantum Neural Networks for Stock Trading

We show the practicality of two existing meta-learning algorithms Model-Agnostic Meta-Learning and Fast Context Adaptation Via Meta-learning using an evolutionary strategy for parameter optimization, as well as propose two novel quantum adaptations of those algorithms using continuous quantum neural networks, for learning to trade portfolios of stocks on the stock market.The goal of meta-learning is to train a model on a variety of tasks, such that it can solve new learning tasks using only a small number of training samples.In our classical approach, we trained our meta-learning models on a variety of portfolios that contained 5 randomly sampled Consumer Cyclical stocks from a pool of 60.In our quantum approach, we trained our quantum meta-learning models on a simulated quantum computer with portfolios containing 2 randomly sampled Consumer Cyclical stocks.Our findings suggest that both classical models could learn a new portfolio with 0.01% of the number of training samples to learn the original portfolios and can achieve a comparable performance within 0.1% Return on Investment of the Buy and Hold strategy.We also show that our much smaller quantum meta-learned models with only 60 model parameters and 25 training epochs have a similar learning pattern to our much larger classical meta-learned models that have over 250,000 model parameters and 2500 training epochs.Given these findings, we also discuss the benefits of scaling up our experiments from a simulated quantum computer to a real quantum computer.To the best of our knowledge, we are the first to apply the ideas of both classical meta-learning as well as quantum meta-learning to enhance stock trading.
Evaluation of Information Access with Smartphones

Kato, Makoto P.NTCIR 1CLICK and MobileClick are the earliest attempts toward test-collection-based evaluation for information access with smartphones. Those campaigns aimed to develop an IR system that outputs a short text summary for a given query, which is expected to fit a small screen and to satisfy users’ information needs without requiring much interaction. The textual output was evaluated on the basis of iUnits, pieces of relevant text for a given query, with consideration of users’ reading behaviors. This chapter begins with an introduction to NTCIR 1CLICK and MobileClick, explains the evaluation methodology and metrics such as S-measure and M-measure, and finally discusses the potential impacts of those evaluation campaigns.
Strain analysis at flat surfaces of loaded members using digital image correlation technique

This research examines the applicability of the planned Digital Image Correlation (DIC) system to measure the strains in tensile experiments. DIC is a low-cost optical technique, and is an appropriate measurement used to measure surface displacement, strain and stress map distribution without any contact with the tested surfaces. In the present research, the tensile test is conducted on two different flat samples, which are painted in a speckle pattern on the tested surface to use DIC features in stain measurements. To guarantee the efficiency of the planned DIC system, the DIC code has been built using MATLAB programming language. The obtained results from DIC technique is compared with the results from open-source software (Ncorr), the finite element analysis (ANSYS) as well as the exact and analytical solutions. The comparison results showed that there was A quite acceptable and agreement achieved between them. According to the exact solution, The percentage of accuracy of the obtained results for the Aluminum without hole plate was around (89-93) % whereas the accuracy with the NCORR was about 96 %. For the second copper plate with a central hole, the accuracy has been obtained to be (80.7-99) % with the analytical solution wherein its value has reached (81-97) % with Ncorr software.
RANCANG BANGUN SISTEM PENGAMBILAN KEPUTUSAN PEMILIHAN BEASISWA PADA SMP 4 PSKD JAKARTA SELATAN

Decision support system (DSS) the election of receiver scholarship only use Simple Additive Weighting (SAW) method for application of the calculation, no discuss other methods. for determine election of receiver scholarship at Junior High School PSKD 4 jakarta appropriate with criteria who gaves. the criteria involve rating, income parents of month, total of certificate, burden of parents. For support election of receiver scholarship then the method of research to use is Simple Additive Weighting (SAW), where every criterion gives rating factor. after researcher did research that Simple Additive Weighting (SAW) method that process can gives output rating who has one system who can gives rating at every student from listing result them get.  Result of research was there thing device who make with progaming language Java Netbeans and the storage at database MYSQL can give smoothness in processing decision support system the election of receiver scholarship at junior high scholl PSKD 4 based on java and this research also can do rating alternative from result calculation weight of value student with use Simple Additive Weighting (SAW) method.
Pengembangan Media Pembelajaran E-Fotonovela Fisika Menggunakan Android Berbasis Karakter untuk Siswa Tuna Rungu ( SLB – B )

This study aims to develop E-fotonovela media for deaf students in SMLB-B. The research method used is the Research and Development (R &amp; D) method with the ADDIE model (Analysis, Design, Development, Implementation, and Evaluation). The subjects of the study were deaf students of high school level (SMLB-B), which were conducted in two schools namely SLB N 6 Jakarta and SLB N 7 Jakarta. Research and development produces E-fotonovela media in the form of books with Android-assisted, magnetic materials that are suitable for use based on an average expert judgment of 98% with very good criteria. The assessment of the effectiveness of the media obtained a percentage of 94% with very good criteria, and based on the effectiveness of learning outcomes obtained a value of 74.5% good criteria, which means that the photonovela media on magnetic material is suitable for use as a learning medium in SMAL-B (deaf). While the characters obtained after using E-fotonovela with the thunkecable android application are shown by the overall average score for the 6 principle characters of users at a high level of honest average = 8,189; average discipline = 7.834; average curiosity = 6,545; creative average = 8.037; average cooperation = 8,500 and average responsibility = 8,310.
Research Guides: LSC 375: Social Media Analytics (Fall 2020): Evaluating Information

This guide provides links to selected resources from among library collections and services to support students in LSC 375.
Flexible Learning Design and Implementation Based on Big Data

The traditional face-to-face schooling model can now not meet the needs of in addition education outstanding talents.Only through the huge information studying evaluation version, we can discover deeply and take a look at the learner's studying method, find out the getting to know rules, and then provide them in keeping with the characteristics and wishes of each pupil; personalised adaptive gaining knowledge of and learning methods to give complete play to the ability of students.This research starts from the connotation and alertness of huge facts, and the comprehensiveness of the statistics and the capability "huge value".Based on massive facts analysis, a personalized adaptive online mastering analysis model is built from 4 dimensions: Data and Environment (Who), How and Target (Why).Taking C-language programming as an example, this paper analyzes the shape of learning technique based on large facts and adaptive getting to know, the visualization of getting to know technique and the empirical impact of getting to know.The research results display the information analysis of college students' mastering conduct and knowledge mastery.It can suggest a affordable getting to know course and appropriate gaining knowledge of resources, and can provide well timed and correct comments on the learning effect of students, and offer customized carrier intervention, which is conducive to the merchandising of teaching and learning.
Adaptive Developmental Resonance Network

Adaptive resonance theory (ART) networks, including developmental resonance network (DRN), basically use a vigilance parameter as a hyperparameter to determine whether a current input can belong to any existing categories or not. The problem here is that the clustering quality of those networks is sensitive to the vigilance parameter so that the users are required to fine-tune the parameter delicately beforehand. Another problem is that those networks only deal with a hyperrectangular decision boundary, which means they cannot learn categories of arbitrary shape. In addition, the order of data processing is a critical factor to categorize clusters correctly because each category can expand its boundary into the areas of other categories erroneously. To deal with these problems, we propose an advanced version of DRN, Adaptive DRN (A-DRN), which learns the vigilance parameters assigned for individual category nodes as well as category weights. The proposed A-DRN combines close categories to construct a cluster that contains the categories identifying a cluster boundary of arbitrary shape. Our A-DRN also employs a sliding window. The sliding window buffers sequential data points to presume the data distribution roughly, which helps our network to have a robust and consistent performance to a random order of input data. Through the experiments, we empirically demonstrate the effectiveness of A-DRN in both synthetic and real-world benchmark data sets.
Fruit Fly Algorithm: A Brief Review

An optimization algorithm gives an optimum solution by executing iteratively and comparing it with different solutions. Therefore, many optimization algorithms have been discussed and used in all kinds of fields in the past few years. In this study, a brief description of an optimization algorithm called Fruit Fly algorithm (FFOA) is presented. This algorithm is based on the concept of the fruit flies and their extraordinary methods in finding a way to their food. Due to this, it has been applied in many of the research fields like science, engineering, medical, agriculture, etc., in many forms.
trickle-dribble-drizzle

Author(s): Garcia, Tomas | Abstract: This music score was submitted for the Kaleidoscope 2020 Call for Scores, an open access collaboration with the UCLA Music Library.
네트워크 분석 방법을 활용한 국어 진로 선택 과목 탐색 연구

The purpose of this study is to explore Korean language career electives, conduct detailed network requirements, and present the results after conducting a network analysis. As a result, it was found that the requirements for “advertising linguistics” and “language and visual arts” were high and required for many languages related jobs at the same time. It was found that this is a requirement that plays a major role in connecting Korean language-related jobs. Therefore, it was proposed to develop a career elective related to this requirement. The findings of this study are limited in that they do not take into account all of the hierarchies, totality, realism, and completeness that an elective should have. But It is hoped that this will be used as a basis for developing a Korean language course.
Secure Access Control Model for Cloud Computing Environment with Fuzzy Max Interval Trust Values

Cloud computing needs service provider with reliable communication for increasing the user trust.As existence of cloud depends on quality of services, evaluation of this trust value needs to be carried out by the cloud.Many of the web services provided by E-commerce, social sites, digital platform maintain this for the faith of user by estimating the reliability of service provider.This paper focuses on a model that can identify real nodes by its behavior in cloud.Here fuzzy max interval values have been evaluated from the transactional behavior of the node in fixed interval.By increase in transaction count, trust value of real node trust increases and trust value of malicious nodes decreases.The work is based on Role based Access Control (RBAC), which has three type of roles (Admin, Data owner, Node).Data owner content security was achieved by AES algorithm and only trusted node can access those resources.Experiment was performed by carrying out simulations on ideal and environment under attack.Analysis of evaluation parameters values shows that proposed model of fuzzy max interval trust is better as compared to other existing Domain Partition Trust Model (DPTM), for identification of malicious nodes.
Morphosyntactic Transfer from a Spoken Heritage Dialect to the Standard Variety

This study examines cases of morphosyntactic transfer from Syrian Arabic to Modern Standard Arabic (MSA) in the production of heritage speakers who are not only bilingual (L1 Syrian Arabic, L2 English), but also diglossic; Syrian Arabic is their heritage language (HL), and MSA is the form they learned in school. Two control groups, native speakers of Syrian Arabic and learners of MSA, were also included. The proposal presented here is that adolescent heritage speakers of Syrian Arabic have a more developed Syrian Arabic grammar, which results in- transfer to MSA, and that degree and duration of input-output and exposure to both varieties impact the type and number of non-target forms in the production of the studied heritage group. The goal is to find the extent of such transfer, how it is manifested, and whether it is also related to sentence and subject type or other factors. The focus of this study is verbs in SV and VS sentences in MSA, where the subject is a nominal DP and the verb is in the third person. The agreement patterns in VS and SV sentences are asymmetrical in MSA but they are not in Syrian Arabic. The SV order in MSA reflects different agreement patterns with both genders and all three numbers, whereas in Syrian Arabic there is one default non-singular verb form. In this paper I provide a formal account of the differences among the agreement patterns in MSA and Syrian Arabic within the Minimalist framework. Using this approach, a morphosyntactic transfer of agreement features from Syrian Arabic to MSA is argued to be a transfer of T0 features. The results demonstrate that errors in the MSA verb produced by the heritage speakers differ from those of MSA learners and that more than half of the heritage speakers’ errors are compatible with morphosyntactic agreement forms in Syrian Arabic. These findings provide evidence for transfer from Syrian Arabic to MSA. It is possible that when three linguistic systems are competing (L1, L2, and L3) and where L1 is the most dominant, L2 is less developed than L1 but more developed than L3, and L2 and L3 are typologically close, transfer takes place from L2 to L3. More research to address this question is needed. The study contributes to the understanding of agreement in heritage speakers’ production and the phenomenon of transfer in bilingual and diglossic situations.
A Study on Threats and Possible Approaches for Microgrid Safety and Control

Microgrids with a potential structure developed as a system that combines renewable energy sources, energy storage systems and loads.Microgrids are capable of improving the quality, Reliability and efficiency of the power delivered to the consumers both in grid connected and Islanded mode.However, when implementing microgrids, a variety of problems concerning the security issues have to be handled.The existing modes of operation and the existing DERs are capable of causing the traditional security schemes to be unproductive.Therefore, novel security approaches have been developed.Thus, in this paper a complete review on the modern security approaches is discussed considering the security issues explained above.Prominence to surveys related to adaptive protection is exhibited in this paper, which are believed as favourable solution for microgrid safety and control.The paper briefly presents a microgrid structure and addresses the safety and control challenges observed in the existing Microgrid.Later the paper focuses on overview of Adaptive protection and the possible novel protection schemes for microgrid safety and control found in the technical research articles.However, it can be noticed that efforts are still required to attain a complete solution for the safety and control challenges observed in the existing Microgrid.
Research Guides: Digital Collections: Project Criteria

This page states and clarifies the criteria for prospective Gleeson Library Digital Collection projects.
Revelio: A MimbleWimble Proof of Reserves Protocol.

We reveal Revelio, a new privacy-preserving proof of reserves protocol for Grin exchanges. By design, Revelio allows the detection of collusion between exchanges while hiding the identities of the outputs owned by the exchange in a larger anonymity set of outputs.
Concept And Types Of Computer Information As Evidence In The Criminal Process Of The Republic Of Uzbekistan

In this article the concept of information, the right to access information, computer information are studied and discussed.In addition, the provisions on the information society are disclosed.Also, in the article the types of computer information and some features of their use in criminal proceedings are defined and disclosed.
Adversarial Eigen Attack on Black-Box Models

Black-box adversarial attack has attracted a lot of research interests for its practical use in AI safety. Compared with the white-box attack, a black-box setting is more difficult for less available information related to the attacked model and the additional constraint on the query budget. A general way to improve the attack efficiency is to draw support from a pre-trained transferable white-box model. In this paper, we propose a novel setting of transferable black-box attack: attackers may use external information from a pre-trained model with available network parameters, however, different from previous studies, no additional training data is permitted to further change or tune the pre-trained model. To this end, we further propose a new algorithm, EigenBA to tackle this problem. Our method aims to explore more gradient information of the black-box model, and promote the attack efficiency, while keeping the perturbation to the original attacked image small, by leveraging the Jacobian matrix of the pre-trained white-box model. We show the optimal perturbations are closely related to the right singular vectors of the Jacobian matrix. Further experiments on ImageNet and CIFAR-10 show that even the unlearnable pre-trained white-box model could also significantly boost the efficiency of the black-box attack and our proposed method could further improve the attack efficiency.
[AI-Machine Learning] Optimized Sensorless Human Pose Estimation for a Kpop Dance Application

There has been a great effort to use technology to make exercise more interactive, measurable and gamified. However, in order to optimize the detection accuracy, these efforts have always translated themselves into motion detection with multiple sensors including purpose specific hardware, which results in extra expenses on both the content production and consumption and induces limitations on the final mobility of the user. In this paper we aim to improve the accuracy, learning speed and detail range of Posenet’s AI sensorless human pose detection by using an artificial neural network to optimize its extraction and comparison algorithms, changing the current model that uses a ResNet convolutional neural network (CNN) to a model using DenseNet and developing a new algorithm for detailed corrections using relevant artificial neural networks. The findings here will be applied on a posture correction system for a dance and fitness application.
Study the Relationship between the Surface Air Temperature and the Evapotranspiration in Kirkuk City of Iraq.

This research aims to study the relationship between the surface air temperature and the evapotranspiration In the stations of Kirkuk city (Latitude: 35.47 °N, Longitude: 44.39° E) (Haweija, Alton Copery, Daquq and Qara enger) by using data of (Surface Air Temperature and Evapotranspiration) In (2013), which was obtained from the Iraqi Agro meteorology Network / Ministry of Agriculture. In this study the relationship between air temperature and values of evapotranspiration has been investigated by calculation the correlation coefficient by using program of Microsoft excel 2010, the results indicated the existence of strong linear correlation between the monthly and seasonally average of air temperature and the monthly and seasonally sum of evapotranspiration In the four studying stations. Monthly correlation coefficient values between (0.963 – 0.978), while Seasonally correlation coefficient values between (0.80 – 0.99) in studying stations. This indicates that the increasing in surface air temperature leads to increase the values of evapotranspiration, and the decreasing in surface air temperature leads to decrease the values of evapotranspiration .
Dynamic Epistemic Logic with Assignments, Concurrency and Communication Actions

This work proposes an extension of Dynamic Epistemic Logic with Communication Actions by adding the notion of postconditions from Dynamic Epistemic Logic with Assigments to deal with boolean assignments to action models. Other concurrent logics, like Concurrent Epistemic Action Logic introduced by Ditmarsch, Hoek and Kooi, do not deal with boolean assignments. We present an axiomatization and show that the proof of soundness, completeness and decidability can be done using a reduction method.
CLOUD LOG REASSURING SOUNDNESS AND SECRECY THEME FOR CLOUD FORENSICS

User activity logs can be a valuable source of information in cloud forensic investigations; hence, ensuring the reliability and integrity of such logs is crucial. Most existing solutions for secure logging are designed for conventional systems rather than the complexity of a cloud environment. In this paper, we propose the Cloud Log Assuring Soundness and Secrecy (CLASS) process as an alternative scheme for the securing of logs in a cloud environment. In CLASS, logs are encrypted using the individual user’s public key so that only the user is able to decrypt the content. In order to prevent unauthorized modification of the log, we generate proof of past log (PPL) using Rabin’s fingerprint and Bloom filter. Such an approach reduces verification time significantly. Findings from our experiments deploying CLASS in OpenStack demonstrate the utility of CLASS in a real-world context.
Modeling and Rendering of Ocean Plane Visual Communication Scene Based on SLIP Model

Liu, A.Q., 2020. Modeling and rendering of ocean plane visual communication scene based on SLIP model. In: Bai, X. and Zhou, H. (eds.), Advances in Water Resources, Environmental Protection, and Sustainable Development. Journal of Coastal Research, Special Issue No. 115, pp. 313-316. Coconut Creek (Florida), ISSN 0749-0208.With the continuous progress of earth observation, data processing and other technologies, 3d modeling and rendering of the sea surface have a vital impact on the visual reality of the application system. In some applications, the sea surface itself is the focus of visualization and the basic environment for other applications. The purpose of this paper is to realize the rapid and realistic rendering of the sea surface based on the wave model and grid generation. Based on the SLIP model, a new algorithm for image enhancement is proposed. The sea surface image was analyzed and studied, and the video image method based on SLIP model was proposed to achieve the purpose of video image sharpening, and the ocean surface effect communication modeling was established.