Reviewerly/exHarmony huggingface dataset:
Factors of length ratio and mass at chaos of double pendulum system

The double pendulum consists of two pendulums attached with the pivot of the second pendulum located at the end of the first pendulum by a rigid bar, massless and considers the effect of gravity. The double pendulum system has strange and unpredictable behaviour. Chaos in a double pendulum system is usually used as an example of chaos in mechanical systems. The chaotic system is characterized by a sensitive system to the initial condition. It means that giving the initial condition with a small difference will give a different solution. Lyapunov Exponent is used to calculating the range of two trajectories with a small difference of initial condition, where the positive exponent value shows two different solutions close at the beginning then more diverge away. In this paper, we determine parameters that will cause the double pendulum system to reach chaos easily. To facilitate this, the equations of the double pendulum motion are simplified by =gl1,β=gl2,δ=m2m2. In particular, we focus on determining the mass ratio and length ratio from the double pendulum system. In some simulations with simulation program that have been made in Maple, the program has resulted in the greater value of δ at the specific problem shows that the system needs the value of θ1,θ2,θ˙1,θ˙2, as first initial condition smaller to reaches chaos easily.
IMPROVING THE STUDENTS’ ACHIEVEMENT IN WRITING NARRATIVE TEXT BY APPLYING SPORE (Setting, Problem, Order Of Action, Resolution, End) STRATEGY XI GRADE OF MAS AL WASHLIYAH 22 TEMBUNG

This study aims to discover the improvement of the students’ achievement in writing narrative text by Applying Spore Strategy. The objective of this study is to find out whether the Spore Strategy can improve students’ achievement in writing narrative text or not. This study was conducted by using classroom action research. The subject of the research was class XI MIA of Mas Al Washliyah 22 Tembung which consists of 34 students. This study applied quantitative and qualitative data. The data of this study were obtained quantitatively through writing test which show that the students score kept improving in every test and qualitatively based on diary notes, observation sheet,and Interview sheet which show that teaching learning process ran well, the students were active, enthusiastic, and interested in writing. In the first test, the mean score was 56.8. in the second test, the mean score was 67.2, and in the third test the mean score was 81.2, The research findings indicated that Spore Strategy significantly improved students’ achievement in writing narrative text.
LDA Topic Generalization on Museum Collections

In this paper, we proposed text segmentation algorithm which is effective in detecting similarities between museums in various nations. Text segmentation is to improve the readability of large corpus of text data which is very necessary for museum information’s, and the proposed method does not need heavy training on texts and just necessary to train on running material with departing the topics and representing vectors which are words of the document. Our suggested topic extends text boundary among small measures in three stages: First applying latent Dirichlet allocation (LDA) and word2vec, then computing document features and detected broadcast similarities, and finally, applying machine learning clustering algorithms to find the sub-topic differences. We used this algorithm on three storybooks which are text dataset, and the results that represent our method have better performance than TF-IDF and N-gram algorithm.
Examination of Defense Method for Tor User Specific Purpose Attacks by Dummy User Attached Communication

In recent years, the anonymous communication system Tor that prevents the user’s access destination website from being specified has become widespread. However, attack methods for anonymity are gradually evolving. As one of the attack methods, there is a “web fingerprint attack” that identifies the Web site accessed by the user from the characteristics of the flowing packets. Therefore, in this paper, we examine a defense method against fingerprint attack against Tor. We devised a method to rewrite the “user fingerprint information” in the access history of legitimate users by analyzing the Tor Hidden Service packet and accessing the target site and dummy site simultaneously using approximate routing with multiple Tor browsers did. This “dummy user generated noise” shows that the effect of fingerprint attack can be reduced.
Learning Discriminative Classifier Parameter for Visual Object Tracking by Detection

In this paper, we propose an algorithm to learn the discriminative parameter vector in successive frames of a video. The learned parameter vector is used for visual object tracking. The learning method selects some positive and negative examples from example sets. Using iterative steps, one set of positive and negative example is selected in a single iteration. The weight update strategy is then used to estimate the proportionate weight of selected example set. The examples are selected based on the criterion that when the parameter vector is updated using these examples, the classification score between parameter vector and some examples will be higher. The proportionate weights are estimated to each selected example pair based on exploring different weights; using assumption that when the parameter vector is updated, it results in higher classification score between some positive examples and the updated parameter vector. The update strategy further estimates the scalar multiplier value of selected example pairs, except the first pair, considering the target appearance change and the target drift. The tracking results of the proposed discriminative parameter learning method is comparable to the state-of-the-art video trackers.
Prevention of Cross-Site Scripting Attacks in Web Applications

Cross-site scripting is a vulnerability in Web applications that can be exploited by injecting malicious script codes such as JavaScript into a Web application. A cross-site scripting technique allows an authorised user to inject malicious codes into a Web application and perform malicious activities. This paper analyses the traditional methods used in preventing cross-site scripting. A security framework is then proposed to improve the security of Web applications against Web-scripting attacks. This framework defines a security checklist, which comprises a set of rules. These rules contribute towards strengthening the security of Web applications and making them more robust to cross-site scripting attacks.
Summarization of Asynchronous Data

Programmed content outline is a central NLP application that intends to gather a source content into a shorter form. The quick increment in interactive media information transmission over the Internet requires multi-modular outline (MMS) from nonconcurrent assortments of content, picture, sound, and video.  Here, we propose an MMS strategy that joins methods of NLP, discourse preparing a PC vision to investigate rich data contained multi-modular information and improve the nature of MMS. The key thought is to connect the semantic holes between multi-modular Substance. For sound data, we plan a way to deal with specifically utilize its translation and to surmise the remarkable quality of the interpretation with sound sign. For visual data, we gain proficiency with the joint portrayals of content and pictures utilizing a neural system. At that point, we catch the inclusion of the created rundown for significant visual data through content picture coordinating or multi-modular theme demonstrating. At last, all the multi-modular angles are considered to produce a printed rundown by amplifying the striking nature, non-excess, intelligibility and inclusion through the planned enhancement of submodular capacities. We further present an openly accessible MMS corpus in both languages English and Chinese. The trial results show that our techniques beat other aggressive standard strategies.
The adaptive key frames extraction method based on representativeness and independence features

For the existing traditional method to extract key frames from the video sequence with gradual change of content, there are problems of having too much redundancy or too much loss in the extraction results and other issues, a new key frames extracting method for adaptively extracting the video key frames has proposed in the paper. The experimental results have shown that the proposed method can effectively extract video key frames, especially for the video with gradual change of content, which can express more succinctly and comprehensively. The experiments on a large number of videos containing various scenes have shown that the key frames extracted by the proposed algorithm can more fully express the main content of video. When dealing with content gradient video, the effect is better. The content adaptively determines the number of key frames based on video.
LibGuides: Remote Research and Dance: Self-Care

This guide brings together the varied resources available to our patrons while conducting their research remotely.
Recurrent Neural Networks Analysis Application Effect of Economy Sentiment on Car Manufacturing

The objective in this research is to apply the recurrence neural network for car manufacturing with economy sentiment. The process applies two parallel mathematical methods from matrix approach and graph representation. First the randomly changes in production lines are studied regardless of economy sentiment. Secondly the change of production lines is considered in the case of changing economy sentiment. Thirdly the combination of the two processes in matrix form and graph form is constructed. It is seen that the graph, nodes and recursive process approach will lead to the recurrent neural network as timely sequence process. The development of the matrix conversion to graph representation is done and explained in figures in detail.
LibGuides: Federal Register Library: Search Tips

The Federal Register is the official journal of the federal government of the United States. The database is updated daily and its coverage is comprehensive, beginning from inception in 1936. Search Tips
Novel approach in multilingual and mixed English-Arabic test collection

Mixing languages together in text and in talking is a major feature in non-English languages in developing countries. This mixed grammar is also emerging in SMS, Facebook communication, searching the web and any future attempts also may increase the footprint of such a mixed language knowledge base. Traditional information retrieval (IR) and cross-language information retrieval (CLIR) systems do not exploit this natural human tendency as the underlying assumption is that user query is always monolingual. Accordingly, the majority of the text collections are either monolingual or multilingual. This paper explores the trends of mixed-language querying and writing. It also shows how the corpus is validated statistically and how an Arabic lexicon can be extracted using co-occurrence statistics. Results showed that the distribution of frequencies of words in the corpus is very skewed the vocabulary growth is a good fit. The results of how to handle mixed queries are also summarised.
On the Tandem Duplication Distance.

A tandem duplication denotes the process of inserting a copy of a segment of DNA adjacent to its original position. More formally, a tandem duplication can be thought of as an operation that converts a string $S = AXB$ into a string $T = AXXB,$ and is denoted by $S \Rightarrow T.$ As they appear to be involved in genetic disorders, tandem duplications are widely studied in computational biology. Also, tandem duplication mechanisms have been recently studied in different contexts, from formal languages, to information theory, to error-correcting codes for DNA storage systems. The of determining the complexity of computing the tandem duplication between two given strings was proposed by [Leupold et al., 2004] and, very recently, it was shown to be NP-hard for the case of unbounded alphabets [Lafond et al., 2019]. In this paper, we significantly improve this result and show that the tandem duplication distance problem is NP-hard already for the case of strings over an alphabet of size $\leq 5.$ We also consider the problem: given strings $S$ and $T$ over the same alphabet, decide whether there exists a sequence of duplications converting $S$ into $T$. A polynomial time algorithm that solves this (existence) was only known for the case of the binary alphabet. We focus on a special class of strings---here referred to as alternating---that generalize the special structure of binary strings to larger alphabets. We show that for the case of purely alternating strings from an alphabet of size $\leq 5$, the existence can be solved in linear time.
The Implementation of Know-Want-Learned Strategy toImprove Student’s Reading Comprehension of the Grade Eight Student’s of MTSS Zending Medan in Academic Year2018/2019

This research was aimed to find out the improving students‟ reading byusing KWL Strategy. The subject of this research was eight grade of MTssIslamic Zending Medan 2018-2019 academic year. It was consisted of oneclass and 31 students as respondents. The object of this research was toimprove students‟ reading comprehension by using KWL Strategy . Theresearch of this study was conducted by using calssroom action research. Thedata used in this research were quantitative and qualitative data and theinstruments of collecting data were used such as: Pre-test and Post-test,interview sheet, observation sheet, and photography evidence. The quantitativedata were taken from the test. The test was given to the students in form of pretest, post test in the first cycle, and the post-test in the second cycle.The result of the analyzing the data showed that there was an improvingon the students‟ vocabulary mastery from each cycles. It was showed from themean of pre-test was 6645. Where, there were 4 student got successfull scorecriteria or it was only 12,90% and 27 students‟ got unsuccessful or it was87,09%. After doing cycle I by using KWL Strategy , there was an improvingof the result of the students‟ mean was 69,51. Where, 7 students got successfulcriteria score or it was only 22.58% and 24 students‟ got unseccessful criteriascore or it was 77,41%. Then doing repairing for second cycle after reflectionon the first cycle, there was improving of students‟ mean was 79,83. Where, 20students‟ got successful criteria score or it was 64,51% and 11 students‟ gotunsuccessful criteria score or it was 35,48%. In other words, it could beconcluded that the use of KWL Strategy improved the students‟ readingcomprehension and their interest in reading comprehension.
Perancangan Sistem Informasi Catatan Kesehatan Ibu Hamil dan Ibu Bersalin Berbasis SMS Notifikasi

The maternal health record is a record that contains the development of the fetus and the pregnant health record as well, this note is very important as a reference when a pregnant woman will give birth so that in addition to this note is given to the patient (pregnant women) midwife and gynecologist place control should also have this health record. Patients also often forget to bring even forget to put or keep this health notebook so forget the date of return control that has been written on the note note. Patients should not forget the date of re-control and not be empty of health record book then made the design of health information system for pregnant mother and mother-based sms notification with the aim can be a reminder of date of control visit for pregnant mother and reminded of date of estimated delivery. Methods of data collection is done by direct observation, interview and literature study. System design using UML modeling language. The result of this research is the design of information system of maternity health record and maternity based on sms notification with purpose as reminder of date of control visit for pregnant mother and reminder of estimated date of labor and assist in better management of maternal and maternal health record.
Prediction Intervals based on Doubly Type-II Censored Data from Gompertz Distribution in the Presence of Outliers

The study aims at getting the Bayesian predication intervals for some order statistics of future observations from the distribution of Gompertz (Gomp (α, β)).Doubly Type-II censored data has assisted obtaining in the presence of single outlier that arose from the different same family members of distribution.Single outlier of type β β0 and β+β0 are considered and bivariate independent prior density for α and β are used.The problem of solving the Double integral to obtain the closed form for α and β, leads us to use MCMC for calculating the Bayesian Predication Intervals.The use of numerical examples and statistical data has enable to properly present and describe the procedure.We conclude that the Bayesian predication intervals are shorter for y1 than y5 when we are increasing the β0 value.
Design of Remote Hydraulic Teaching System

Abstract In this paper, a set of remote hydraulic teaching experiment system is designed and developed based on the demand of teaching experiment of hydraulic related courses in colleges and universities, which can enable teachers or students to conduct experiment operation on the field hydraulic testing platform at the remote client, so as to facilitate teachers and students to carry out hydraulic teaching experiment and research. The main contents of this paper are as follows: according to the requirements of hydraulic servo control system related to the teaching experiment, the experimental project of remote hydraulic teaching experiment system is determined. Through the analysis and comparison of C/S and B/S software system architectures, the remote monitoring scheme based on B/S mode is determined. Completed the design of the hydraulic circuit of the hydraulic test bench, developed the field measurement and control system based on LabVIEW, and built the remote monitoring system based on B/S mode. The development of the remote hydraulic teaching experiment system was completed. The input signal response experiment and load characteristic experiment of the valve-controlled motor electro-hydraulic speed servo control system were carried out on the remote client to the field hydraulic experiment platform, and the experimental results were analyzed. The experimental process and results have reached the expected target and meet the demand of remote hydraulic experiment.
[Estimation on the individual treatment effect among heterogeneous population, using the Causal Forests method].

Objective: This project aimed to explore the effectiveness of estimating individual treatment effect on real data, among the heterogeneous population, with Causal Forests (CF) method, to find out the characteristics of heterogeneous population. Methods: We designed and conducted four computer simulation schemes to verify the effect of estimating on individual treatment, using the CF under four different environments of the treatment effects. Real data was then analyzed for the catheterization on right heart. Results: Results from the simulation process showed that the values on individual treatment effect that were estimated by causal forests were consistent with the population effect as well as in line with the expected distribution under the setting of four different effect values. Results of real data analysis showed that values of individual treatment effect among most patients appeared positive, so the use of RHC could cause an increase of the '180-day mortality rate' in the sampled population. Patients with lower predicted probability of 2-mo survival and albumin were more likely to have a lower risk of death after using the RHC. Conclusion: CF method could be effectively used to estimate the individual treatment effect and helping the individuals to make decision on the receipt of treatment.目的： 探讨因果森林在异质性人群中估计个体处理效应的有效性及如何应用于实例数据以挖掘异质性人群特征。 方法： 设计4种模拟方案，通过模拟试验验证因果森林在不同处理效应环境设置下对个体处理效应进行估计的效果，并应用于右心导管插入术实例数据集进行分析。 结果： 模拟试验结果表明，在4种不同效应值设置下，用因果森林方法所估计的个体处理效应值都能与总体效应相吻合，符合预期分布；实例数据分析结果显示绝大多数患者个体处理效应为正值，使用RHC会导致该样本人群180 d死亡率增高，2月生存模型估计概率和白蛋白含量偏低的患者在使用RHC后更倾向于有较低的死亡风险。 结论： 因果森林能够有效地估计个体处理效应，为个体是否接受某种处理提供建议。.
Data Analysis of Earth Observation Data from Copernicus Satellites

Open Data Cubes are platforms that contain open source satellite data and provide analysis tools for governments or organizations. The Swedish version is known as Swedish Space Data Lab (SSDL) and ...
EGA: An Enhanced Genetic Algorithm for Numerical Functions Optimization

Optimization is the process of making something as good or effective as possible. Optimization problems are used over many fields such as economics, science, industry and engineering. The growing use of optimization makes it essential for researchers in every branch of science and technology. To solve optimization problems many algorithms have been introduced, while achieving a higher quality of results in terms of accuracy and robustness is still an issue. Metaheuristics are widely recognized as efficient approaches for many hard optimization problems. In this study, to achieve a higher quality of results in numerical functions optimization, two new operators named N-digit lock search (NLS) and Two-Math crossover are introduced to enhance the genetic algorithm (GA) as a widely used metaheuristic. The NLS operator is inspired by the N-digit combination lock pattern and enhances the exploitative behavior of the GA by calibrating the current best solution and the relatively new Two-Math crossover operator combines both two-point and arithmetic crossover techniques to guide the overall search process better. The proposed enhanced genetic algorithm (EGA) is tested over 33 benchmark mathematical functions and the results are compared to some population-based, particle swarm optimization (PSO2011) and artiﬁcial bee colony (ABC) algorithms, and single-solution based, simulated annealing (SA), pattern search (PS), and vortex search (VS). A problem-based test is performed to compare the performance of the algorithms, which results shows the proposed EGA outperforms all other algorithms, SA, PS, VS, PSO2011 and ABC. In addition, it surprisingly finds the global best points for almost all 33 test functions with a constant value for 2 out of 3 EGA operators.
Musikaliska Uttryckssätt Som Jag Använder : En Analys

AbstractThe essay is an analysis by William Benckert where he defines and discusses the musical tools of expression he used when performing and composing music for his exam concert. Most of the com ...
LibGuides: Mutual Aid Networks Resources: Home

Resources to help individuals connect with city, community, neighborhood and other grassroots aid networks.
Implementation and Evaluation on Automated E-Learning Contents Creation Based on Natural Language Processing Techniques

E-Learning automation is a set of computer instructions used to solve the difficulties of effective E-Learning systems management. And based on the merits of natural language processing techniques, E-Learning automation has already achieved great progress, such as automatic E-Learning online quizzes creation and students’ questions answering. This research mainly focuses on finding a powerful method for E-Learning contents creation to solve the problem of difficulties in E-Learning system management. This research can be mainly divided into four steps: Firstly, automatically summarize relevant texts to get straightaway texts from the source version. Secondly, detect keywords from generated summaries. Then, delete the detected keywords from summaries. Finally, rearrange outputs from previous steps to generate online questions and learning materials.