Reviewerly/exHarmony huggingface dataset:
A Quantum Version of Pollard’s Rho of Which Shor’s Algorithm is a Particular Case

Pollard’s Rho is a well-known classical strategy for factoring integers that are not prime powers. We present (1) a new theorem that characterizes the availability of nontrivial factors in the universe of search of Pollard’s Rho. The running time of Pollard’s Rho is reduced to polynomial-time on a quantum model of computation so long as we use a certain set of functions for generating the sequence of numbers that compose the method’s universe of search. We also present (2) an expression of a quantum procedure that implements Pollard’s Rho. The characterization given by (1) has led us to the conclusion that Pollard’s Rho is a generalization of Shor’s algorithm, but one obstacle stands in the way of this fact: the set of functions for generating the sequence of numbers must have a closed-form formula so we can take advantage of quantum parallelism; the closed-form formulas we have so far found are dependent on the order of an element in the multiplicative group of integers modulo a composite, whose fast computation can currently only be done by Shor’s algorithm. However, the quantum version of Pollard’s Rho is still useful even with this limitation: when Shor’s algorithm fails to factor the composite but correctly computes the order of the chosen element in the group of integers modulo the composite, a quantum version of Pollard’s Rho can use that order to try to factor the composite with an effective constant-factor faster runtime compared to running Shor’s algorithm a second time.
Image deraining using multi-scale aggregated generator network

Rain streaks attached to a camera may seriously affect the visibility of the background and considerably degrade image quality. We handle this problem by removing rain streaks to convert a rainy image into a clean one. This creates a problem in that the information with respect to the background of the occluded parts is close to being lost for the most part. To remove rain streaks from a single image, we employ a multi-scale aggregated generator network. Differing from previous generative adversarial networks, an enhanced generator block (EGB) is applied in the generator; this broadens the receptive field of the input features and enhances the attention to rain streaks details. In addition, both the generator and the discriminator networks contain the visual mask that learns the rain streak regions and their surroundings during training. By putting the mask forward, the generator network focuses on rain streaks and the surrounding regions and the discriminator network is capable of evaluating the local consistency of the restored regions.
The Effect of Using TGT on Students' Writing Skill in Short Functional Text

The purpose of this study was to determine the effect of Team Games Tournament techniques on short functional Text. In this research used quantitative method which the data is served by numerical and tasted statistic formula of the-test. The research design is quasi experimental which involves 30 students in VIII7 as the Control and 30 students VIII1 as the experimental Class. The researcher gave pretest before teaching learning activity has been finished. The researcher gave posttest to know the student achievement of short functional text especially in writing skill in short message. The scores of both pretest and posttest were analyzed by statistic descriptive test. The data were test by normality test, homogeneity test and hypothesis test. In this research it can be seen that the mean score of experimental class in post-test was 90.63.and the pre-test was 52.06.while the mean score of control class in post-test was 80.26 and the pre-test was 42.33. The students’ mean scores of the experimental class was higher than the control class. Based on the result of the t-test and the differences between the mean of score in experimental class and control class, it can be summarized that the Team Games Tournament Technique has a significant effect on Short Functional Text at 8th grade students of SMPN 7 Tanjungpinang.
AI Assisted Internet Finance Intelligent Risk Control System Based on Reptile Data Mining and Fuzzy Clustering

AI-assisted Internet finance intelligent risk control system based on the reptile data mining and fuzzy clustering is designed and implemented in the paper. The novelties are proposed as follows. (1) General-purpose web crawlers often use certain crawling strategies to shorten the crawling time, more commonly used are the depth priority, the AI is adopted to optimize the tool. (2) The prevention of network script viruses must first start with the standard use of script files, and resolutely resist script files with unknown sources, the fuzzy data mining model is integrated to achieve efficient algorithm. (3) Internet finance intelligent risk control system is implemented through the software. The experiment has shown the performance.
Нейрофізіологічне підґрунтя символдрами як психодинамічного напрямку психотерапії

The article is devoted to theoretical analysis of the neurophysiological basis of theimagination technique of psychodynamic psychotherapy. Brain structures that areinvolved in creating and maintaining an image of an object that is not currently presentor was not present in the subject's sensory field has been described. The Default modenetwork is considered as a probable substrate of Guided Affective Imagery in particularand psychotherapeutic changes in general. The process of Guided Affective Imagery ischaracterized, which allows to implement recontextualization and re-consolidation ofpast experience.Guided affective imagery (GAI) is a hierarchically organized and structuredsystem of techniques and principles of psychotherapeutic use of imagination. Guidedaffective imagery is a psychodynamic psychotherapy, which makes unconsciousmotivations, conflicts and defense mechanisms visible with the aid of images fromwithin and deals with these unconscious matters.The process of imagination is based on the ability of brain neurons to create andmaintain an idea of ​​an object, that is currently not present in the sensory environment ofthe subject, and also to combine the previously obtained perceptual images to create theoriginal products.The process of imagination involves the structure of the left temporal particle, theprefrontal and parietal region up to the temporal particle of the brain. The idea of ​​thepoint of view of others and the creation of imagery (imagination) are specific cases of amore general process of self-projection, that involves the medial, parietal and frontallobe, or the Default mode network (DMN) .The Default mode network is probably the ground for psychotherapeutic changesin general, and the psychotherapeutic process can modulate these brain structures.Guided affective imagery is able to enhance the psychotherapeutic process byactivating the primary process and positive emotions. Guided affective imagery providesconditions for the establishment of such therapeutic relationship, which makes possiblethe recontextualisation and reconsolidation of past experience. The result is a new set ofimplicit memories, so person operates on the basis of another psychic landscape, whichleads to a new behavior and a new experience in the present and future.
Intercept-Resend Attack on SARG04 Protocol: An Extended Work

In this paper, intercept/resend eavesdropper attack over SARG04 quantum key distribution protocol is investigated by bounding the information of an eavesdropper; then, the attack has been analyzed. In 2019, simulation and enhancement of the performance of SARG04 protocol have been done by the same research group in terms of error correction stage using multiparity rather than single parity (Omar, 2019). The probability of detecting the case in the random secret key by eavesdropper is estimated. The results of intercept/resend eavesdropper attack proved that the attack has a significant impact on the operation of the SARG04 protocol in terms of the final key length.
Adoption of Mobile Technology Application at a Technical University in Ghana

This study seeks to examine determinants that can influence students intention to use a mobile technology application.To examine these determinants, this study adopted mobile service acceptance model that have constructs such as context, personal characteristics and initiatives, trust, perceived usefulness, perceived ease of use and intention to use.A sample of 170 students from Ho Technical University (HTU) experimented with HTU GPA mobile technology application after which a questionnaire was administered.Partial least square structural equation modeling (PLS-SEM) was used in analyzing data that was collected.The results from the study showed that trust, perceived usefulness and perceived ease of use have significant effect on students intention to adopt HTU GPA mobile technology application.Trust had the most significant effect on students intention to adopt the mobile technology application.Context had significant effect on perceived usefulness and perceived ease of use which indirectly influenced students intention to adopt the application.The results from this study provide both researchers and practitioners insights into determinants that impact students adoption of mobile technology application in a university.For researchers, this study contributes to existing literature on intention of students to adopt a mobile technology application while for practitioners it helps them gain a better insight into what key features to consider during the design and development of mobile technology applications.
The Use of YouTube Social Media to Educate Society through Virtual Literacy during COVID-19 Pandemic

The existence of new media with the rapid development of information and communication technology makes a massive change in various aspects of life.Information and communication technology makes the world borderless so that education and literation toward society possible to do anytime and anywhere.Virtual literacy by using social media Youtube is a solution during the COVID-19 pandemic.The concept of virtual literacy is used by the Ministry of Agriculture's Library in educating society, especially farmers.A qualitative descriptive approach is employed in this study especially observation.This study used media theory to observe the use of YouTube social media as a communication medium in conducting virtual literacy in society.The results showed that virtual literacy conducted by the Ministry of Agriculture's Library was not optimal yet, because there are still many internet users not accessing the YouTube channels, seen from the lack number of subscribers.Internet networks that are not spread evenly in Indonesia become one of the factors the low access of the public to the Youtube channel of the Ministry of Agriculture's Library.
Development E-Book of Flipbook Type on Environmental Change Material to Train Science Literacy Grade X High School

E-book type flipbook is an excellent learning media to be used as teaching material because the design displayed can attract the attention of students. This e-book type of flipbook also helps students to learn biology, especially the subject of changes in class x high school environment. This study aims to develop a flipbook type E-book on environmental change material as a biological learning material that has been tested theoretically and empirically. Theoretical feasibility uses validation attachments which are assessed from the validator of the material expert and the scientific literacy expert. This e-book type of flipbook refers to the scientific literacy indicator from the 2009 version of the Pisa which has 3 points namely a) explaining the phenomenon scientifically b) identifying scientific issues c) interpreting data and evidence scientifically. While empirical eligibility is assessed from the readability test and response questionnaire. This research method uses the concept of Hannafin and Peck. Hannafin and Peck's concept uses the stages of analysis, design, development, and implementation. The analysis and design phase is carried out July-December 2019 at SMA Muhammadiyah 4 Surabaya and the Biology Department, FMIPA UNESA. The implementation phase was carried out on April 24, 2020, with the trial of 20 grade X students of SMA Muhammadiyah 4 Surabaya. The research instrument used a Likert scale for the validation sheet, Fry chart for the readability test sheet, Guttman Scale for the student response questionnaire test sheet. The data obtained were analyzed with quantitative descriptions. The results of this study indicate that the flipbook type e-book on environmental change material is theoretically feasible based on the validity sheet assessed from the material expert validator and the scientific literacy expert. The validity results showed an average of 88.27% of the very feasible categories. Besides that, the empirical feasibility test uses a readability test and student questionnaire responses. In the readability test results using the fry graphic shows, all the subchapters entered in level 10 categories. Then in the results of the questionnaire test the students' responses in the Guttman scale test showed an average of 93% of the excellent category&#x0D; Keywords : e-book, environment change, science literacy
imec-ETRO-VUB at W-NUT 2020 Shared Task-3: A multilabel BERT-based system for predicting COVID-19 events

In this paper, we present our system designed to address the W-NUT 2020 shared task for COVID-19 Event Extraction from Twitter.To mitigate the noisy nature of the Twitter stream, our system makes use of the COVID-Twitter-BERT (CT-BERT), which is a language model pre-trained on a large corpus of COVID-19 related Twitter messages.Our system is trained on the COVID-19 Twitter Event Corpus and is able to identify relevant text spans that answer pre-defined questions (i.e., slot types) for five COVID-19 related events (i.e., TESTED POSITIVE, TESTED NEGATIVE, CAN-NOT-TEST, DEATH and CURE & PREVENTION).We have experimented with different architectures; our best performing model relies on a multilabel classifier on top of the CT-BERT model that jointly trains all the slot types for a single event.Our experimental results indicate that our Multilabel-CT-BERT system outperforms the baseline methods by 7 percentage points in terms of micro average F 1 score.Our model ranked as 4 th in the shared task leaderboard.
Aprender a vivir juntos un reto para la educación hoy

This article analyzes the possible issues of living together at school as well as its multiple manifestations within the school environment. In terms of methodology, the hermeneutic circle was developed. Seeing, making a judgment and acting were the focus of attention, a procedure that belongs to the same structure of the article. Firstly, the researcher started by seeing where the context concept was clarified in order to present the different current scenarios of the students while identif ying situations that affected coexistence. Secondly, a judgment (reflection) was made to the light of different authors so as to understand the obstacles that impeded living together in spite of contrasts. Last but not least, based on acting, the researcher came back to the context to present possible solutions (classroom project) to face the challenge that education has nowadays in terms of making school environments that favor selfhood, alterity and otherness possible, while also considering the institutional charisma.
Detection Method of Track Locating Point Based on Yolo V3

This paper presents a method to determine the position of the train in the track by detecting the track locating points, and establishes the image data sets of the track locating points. Because the locating points on each track are unique, the number of locating point image samples is very small, which poses a great challenge to the accuracy of locating point detection. We apply the target detection algorithm of Yolo V3 to the field of track location point detection, and propose three improvements. Firstly, the training data sets are expanded by data enhancement of images. Then K-means clustering algorithm is used to analyze the size of the anchor boxes of the data sets, and new clustering centers are obtained. Finally, the multi-scale training method is used to make the model adapt to images of different resolutions. The results indicate that compared with the original network, the improved Yolo V3 model not only has better adaptability to image detection with different quality and resolution, but also has higher mean average precision and better detection effect.
Efficient Replanning Technique for QoS-aware Web Service Composition

A Web service is a service provided by software systems to support machine to machine inter-operations over Web. Given a set of Web services and a goal, the QoS-aware Web service composition problem constructs a composite Web service with the optimal accumulated QoS value, which satisfies the given goal specification. However, in the real world environment, frequent changes happen inherently - for instance, temporary machine down, heavy system workload, and network failure. If the solution we have constructed is not valid anymore due to the changes, we have to solve a new problem again. Ordinary approaches to find a new solution from scratch may waste computation time, since they explore the whole searching space again. Hence, in this paper, we propose a novel replanning algorithm, which does not solve the new composition problem from scratch but explores only the changed space to identify the new optimal solution. In the experiment, our replanning algorithm can deal with the composition problem much faster than the original algorithm to solve from scratch.
LibGuides: Design: Useful Websites

Focused information, content and Library resources for students and researchers in the Lancaster Institute for the Contemporary Arts
All guides: Solo Librarian Interest Group: Overview

A forum for solo librarians to network together. General information about the special interest group.
Gaussian Process And Compbined Kernel Supported Analyzing Hyper Supernatural Reflectivity

In this system, we gauge join a section choice technique, taking into account molecule swarm update (PSO), with a piece procedure, uphold vector machines (SVM), to lessen the dimensionality of hyper ridiculous information for demand.We review several undeniable kernals, including some improved for hyper absurd assessment.Specifically, an advancing segment called perception point subordinate (OAD) piece, from the outset pronounced for Gaussian Process descend into sin, was released up for SVM gathering.The SVM with the adjusted kernal was then applied to prompt the segment confirmation of a twofold kind of PSO.We embrace the strategy utilizing hyper powerful edifying records got of most recent tests from Western Australia.The test outcomes show that our framework can reasonably reduce the measure of highlights while keeping, or in any case, changing, the presentation of the SVM classifier.With current and moving toward symbolism spectrometers, mechanized band examination procedures are depended upon to draw in gainful unmistakable check of most significant social occasions to help improved treatment of terrible information into evaluations of biophysical factors.
STM16:9fft_VR : Virtual surrealism and site specific VR

Through this abstract, STM16:9fft_VR, a pilot for a VR film is discussed and presented. The project is developed through a collaboration between Nicole Neidert, choreographer, Joakim Envik Karlsson ...
PRETRAINING AND AUGMENTATION IN NAMED ENTITY RECOGNITION TASK FOR CYBERSECURITY DOMAIN IN RUSSIAN

The paper presents the results of applying the BERT representation model in the named entity recognition task for the cybersecurity domain in Russian. Several variants of the model were investigated. The best results were obtained using the BERT model, trained on the target collection of information security texts. This model achieved results, which were 15 percentage points of F1-macro measure greater than results of CRF, the best method in previous experiments for the same task and data. We also explored a new form of data augmentation for the task of named entity recognition.
Jejaring Sosial Wisata Kuliner dengan NoSql

Tourist attractions have been developed in various places with each uniqueness, one of the most sought after tourism places is a culinary tourism place. Because of the many culinary scattered in various regions, it takes technology that can facilitate the user in search of culinary tourism and can connect with other users, in this case we can use social networks. In a social network it takes a database that can hold large data, NoSQL (Not Only SQL) is a database that has no schema, and can develop horizontally. The use of NoSQL allows the system to search for faster data processes on large-scale data, one of which is like on a social network. This research uses ASP. The Net to build dynamic Web applications, and JMeter is used to test the performance of the created applications that can measure the volume or quantity. From the test results obtained that the website can accommodate well against many users who access the Web with 49.5 ms for sample time, response time interval of 16 ms, and time to connect 7.2 ms.Keywords : Social Networking, Not Only SQL, Culinary Tour, ASP. Net, JMeter.
USING NARRATIVE TEXT TO IMPROVE STUDENTS’ READING COMPREHENSION SKILL OF THE GRADE ELEVEN STUDENTS

The aim of this research to discover the students’ difficulties in understanding narrative text, to know whether the use of narrative text can improve the students’ reading comprehension, and to know the understanding level of students in reading comprehension. The study was qualitative in the action research approach. The subjects of the study were 30 students. The data for this study was qualitative. The results of this study showed that the students encountered difficulties in reading comprehension of vocabulary mastery, finding specific and general information from the text. The students did not interested to read a long text that the teacher dominated the class, never gave feedback, and modeled the teaching strategy. The researcher used the narrative text to improve students’ reading comprehension. It displayed the improvement of student’s average scores. On the pre-test the average score was 5.06, on the first cycle the average score was 5.8, then on the second cycle, the average score was 6, 36. Furthermore, in the post-test, the average score was 8, 03. The level of students’ reading comprehension is categorized at a good level. Finally, the researcher concludes that using narrative text effective in improving students’ reading comprehension.
BLEU Neighbors: A Reference-less Approach to Automatic Evaluation

Evaluation is a bottleneck in the development of natural language generation (NLG) models.Automatic metrics such as BLEU rely on references, but for tasks such as open-ended generation, there are no references to draw upon.Although language diversity can be estimated using statistical measures such as perplexity, measuring language quality requires human evaluation.However, because human evaluation at scale is slow and expensive, it is used sparingly; it cannot be used to rapidly iterate on NLG models, in the way BLEU is used for machine translation.To this end, we propose BLEU Neighbors, a nearest neighbors model for estimating language quality by using the BLEU score as a kernel function.On existing datasets for chitchat dialogue and open-ended sentence generation, we find that -on average -the quality estimation from a BLEU Neighbors model has a lower mean squared error and higher Spearman correlation with the ground truth than individual human annotators.Despite its simplicity, BLEU Neighbors even outperforms state-of-the-art models on automatically grading essays, including models that have access to a gold-standard reference essay.