Reviewerly/exHarmony huggingface dataset:
Automatic text summarization

In the recent years we have seen an increasing amount of data generation in every field. It becomes our utmost priority to manage this data. The data produced can be structured or unstructured. When it comes to gain knowledge through data, it becomes easier if we only get a summary out of it. In this digital era, most of us do not have enough time to go through many pages of data. Text Summarization aims to retrieve only the important information out of a large text document. This can be achieved through NLP techniques.
Pengenalan Angka Tulisan Tangan Menggunakan Jaringan Syaraf Buatan

Background: It is a chalange to build a program thatbehave intelligent like human. Specially how to build aprogram that able to learn in order to solve a specificproblem. In this reserarch will be developed a computerprogram implementing an artificial neural network thatlearns to recognize handwritten digits. The focus onhandwritting recognition because it is an excellentprototype problem for learning about neural network ingeneral.Aims: Building an intelligent program that able torecognize hand written number (digits).Methode: Artificial Neural Network withBackpropagation architecture and Stochastic gradientdescent learning algorithm wich is implemented in Pythonprogramming language.Result: The program can recognize handwritten digitswith an accuracy over 96 percent, without humanintervention.Conclusion and Advice: A good learning algorithm thatbe learned with bad learning data will perform worse thana simple learning algorithm that be learned with goodlearning data. It is suggested that this research to beimproved with capability to recognize handwritten letter.
Analysis of Probabilistic multi-scale fractional order fusion-based de-hazing algorithm

In this report, a de-hazing algorithm based on probability and multi-scale fractional order-based fusion is proposed. The proposed scheme improves on a previously implemented multiscale fraction order-based fusion by augmenting its local contrast and edge sharpening features. It also brightens de-hazed images, while avoiding sky region over-enhancement. The results of the proposed algorithm are analyzed and compared with existing methods from the literature and indicate better performance in most cases.
Rethinking Politeness Principle in Pragmatics Study

The study focuses on Politeness Principle found in the movie Kung Fu Panda 1 using Leech’s theory.Leech defines politeness as forms of behaviour that establish and maintain comity. He proposed six types of politeness maxim such as tact maxim, generosity maxim, approbation maxim, modesty maxim, agreement maxim, and sympathy maxim. The objectives of this study are to classify the type of politeness maxim used in the movie, to know the frequency of the most and the least maxim used in the movie, and to explain how the figures in the movie used politeness principle in the communication.The writers used descriptive analysis in analyzing the politeness principle used in the movie and used a simple quantitative analysis to know the frequency of the politeness principle. The result of the study shows that all politeness maxim is used in the movie with the frequency tact maxim 10 utterances (9,8%), generosity maxim 5 utterances (4,9%), approbation maxim 24 utterances (23,5%), modesty maxim 11 utterances (10,8%), agreement maxim 45 utterances (44,1%), and sympathy maxim 7 utterances (6,9%).Keywords: Pragmatics, Politeness principle, Movie.
Perbandingan Metode Collaborative Filtering dan Hybrid Semantic Similarity

Recommender system is a component which has been developed for online commerce purposes. In this issue, one of the popular methods that has been widely used is collaborative filtering. However, this method has some drawbacks and needs to be improved. Therefore, in this research a combination of Collaborative Filtering (CF) and semantic similarity method has been compare with original CF, and the result expected reducing some deficiencies on the original collaborative filtering method. Based on the performance tests, the results conclude that the combination can reduce some weaknesses on the original collaborative filtering, especially on the cold-start item and sparsity issue.
LibGuides: ORCID ID's and your Online Researcher Identity: Home

ORCID (Open Researcher and Contributor ID) provides a persistent digital identifier that distinguishes you from every other researcher and, through integration in key research workflows such as manuscript and grant submission, supports automated linkages
Implementasi Kegiatan Kepramukaan Dalam MengembangkanKarakter Disiplin dan Tanggung Jawab Anggota Racana Ki/Nyi Ahmad Dahlan Universitas Muhammadiyah Surakarta

The purpose of this study is to describe: 1) Implementation of scouting activities in developing the character of discipline; 2) Implementation of scouting activities in developing the character of responsibility; 3) Constraints and solutions for implementing scouting activities in developing the character of discipline and responsibility. This type of research uses qualitative descriptive. The subjects of this study were Dewan Racana, Pemangku Adat, and members of Racana. The object of this research is the implementation of scouting activities in developing the character of the discipline and responsibilities of Racana members. Data collection used in this study is by semi-structured interview techniques, observation, and documentation. The validity of the data is done by means of data source triangulation and technical triangulation. Data analysis is done by applying an interactive analysis model. The results of the study: 1) Implementation of scouting activities in developing the character of discipline that requires members to confirm if they are late or unable to attend activities, members are divided into Reka Kerja arrangements, members must obey the rules, time scoring and work programs of Racana are based on awareness, realizing his duties and responsibilities as a young member, devotee, and scout pandega, guided by MKO, Customs, and GBPK. 2) Implementation of scouting activities in developing the character of responsibility, namely by carrying out the mandate given, participating as OC, SC, and Co in each session, and arguing according to ethics. 3) Constraints in the implementation of scouting activities in developing the character of discipline and responsibility, namely busy members outside Racana make members less active in activities, lack of coordination, and lack of understanding of the rules so that it sometimes creates technical obstacles. The solution is to maximize existing members, make approaches as well as motivate, and delegate constrained tasks and socialize existing rules.
The Formation of Hidden Negative Capital in Banking: A Product Mismatch Hypothesis

This paper investigates the phenomenon of hidden negative capital (HNC) associated with bank failures and introduces a product mismatch hypothesis to explain the formation of HNC. Given that troubled banks tend to hide negative capital in financial statements from regulators to keep their licenses, we attempt to capture this gambling behavior by evaluating product mismatches reflecting disproportions between the allocation of bank assets and the sources of funding. We manually collect unique data on HNC and test our hypothesis using U.S. and Russian banking statistics for the 2004{2017 period (external validity argument). To manage the sample selection concerns, we apply the Heckman selection approach. Our results clearly indicate that product mismatch matters and works similarly in both U.S. and Russian banking systems. Specifically, an increase in mismatch has two effects: it leads to a higher probability that a bank's capital is negative and raises the conditional size of the bank's HNC. Further, we demonstrate that the mismatch effect is heterogeneous with respect to bank size being at least partially consistent with the informational asymmetry view. Our results may facilitate improvements in the prudential regulation of banking activities in other countries that share similar features with either the U.S. or Russian banking systems.
Trajectory Optimization on Manifolds: A Theoretically-Guaranteed Embedded Sequential Convex Programming Approach.

Sequential Convex Programming (SCP) has recently gained popularity as a tool for trajectory optimization due to its sound theoretical properties and practical performance. Yet, most SCP-based methods for trajectory optimization are restricted to Euclidean settings, which precludes their application to problem instances where one must reason about manifold-type constraints (that is, constraints, such as loop closure, which restrict the motion of a system to a subset of the ambient space). The aim of this paper is to fill this gap by extending SCP-based trajectory optimization methods to a manifold setting. The key insight is to leverage geometric embeddings to lift a manifold-constrained trajectory optimization problem into an equivalent problem defined over a space enjoying a Euclidean structure. This insight allows one to extend existing SCP methods to a manifold setting in a fairly natural way. In particular, we present a SCP algorithm for manifold problems with refined theoretical guarantees that resemble those derived for the Euclidean setting, and demonstrate its practical performance via numerical experiments.
User perception of technologies in libraries

Information Technology is the collective term for various technologies involved in the processing and transmission of information. The various technologies like computertechnology, barcode technology, RFID technology, CCTV technology, remote access technology etc. can be adopted in libraries to provide better services to the users.Manipal Academy of Higher Education, a premier higher education institute is striving hard to provide excellent library services to its stake holders. The adoption of various technologies to provide better library services is explained in the paper. An attempt is made to capture theuser perception on IT applications in libraries
High Capacity Lossless Data Hiding for JPEG images by NLCM Relationship Constrcution

In this paper, we propose a high capacity lossless data hiding (LDH) scheme that achieves high embedding capacity and keeps the image quality unchanged. In JPEG bitstream, Huffman coding is adopted to encode image data. In fact, some Huffman codes are unused in the bitstream. The secret data can be embedded by replacing the used Huffman code with the unused Huffman code. Different from the previous schemes, the proposed scheme adopts the Non-equal length code mapping (NLCM) method to construct mapping relationship, which is not limited to the Huffman code lengths in a mapping set are equal. To further improve the embedding capacity and reduce the increased file size caused by data embedding, the proposed scheme reduces the existing coding redundancy. Experimental results show that our proposed scheme can obtain higher embedding capacity than previous high capacity schemes for JPEG images and the image quality of marked JPEG image is unchanged. In addition, the increased file size is reduced more than previous works.
Exploring on the Basic Properties of Polynomial

The polynomial is the important conception of algebra and even whole, but are not strictly defined it in elementary mathematics, the concept and nature of use it directly. In essence it is imprecise. According to the strict definition of algebra, it should be used to form to real number of all sequences to define it. In this paper, we begin by defining and developing notation for polynomials in one indeterminate over a ring. And using real number all sequences as the definition of a polynomial, then define polynomial addition, and polynomial multiplication, finally define ring of multivariate polynomial, and proves that the nature of it
Survey Paper on Quality Cluster Generation Using Random Projections

Clustering is the grouping of a particular set of objects based on their characteristics, aggregating them according to their similarities.Regarding data mining, this methodology partitions the data implementing a specific join algorithm, most suitable for the desired information analysis.Clusters will obtained by using densitybased clustering and DBSCAN clustering.DBSCAN cluster is a fast clustering technique, large complexity and requires more parameters.To overcome these problems uses the OPTICS Density-based algorithm.The algorithm requires single factor, namely the least amount of points in a cluster which can necessary as input in density-based technique.Using random projection improving the cluster quality and runtime.
Where Transformation and Cyber Security Meet

Joseph Rose is a senior solutions architect specialising in infrastructure and security with a varied career across banking, financial services, insurance, defence, aviation, utilities and more. Here, he tells Johanna Hamilton AMBCS about the changing face of cyber security.
Structure learning of Bayesian networks involving cyclic structures

Many biological networks include cyclic structures. In such cases, Bayesian networks (BNs), which must be acyclic, are not sound models for structure learning. Dynamic BNs can be used but require relatively large time series data. We discuss an alternative model that embeds cyclic structures within acyclic BNs, allowing us to still use the factorization property and informative priors on network structure. We present an implementation in the linear Gaussian case, where cyclic structures are treated as multivariate nodes. We use a Markov Chain Monte Carlo algorithm for inference, allowing us to work with posterior distribution on the space of graphs.
Why h-Index

At present, one of the main ways to gauge the quality of a researcher is to use his or her h-index, which is defined as the largest integer n such that the researcher has at least n publications each of which has at least n citations. The fact that this quantity is widely used indicates that h-index indeed reasonably adequately describes the researcher’s quality. So, this notion must capture some intuitive idea. However, the above definition is not intuitive at all, it sound like a somewhat convoluted mathematical exercise. So why is h-index so efficient? In this paper, we use known mathematical facts about h-index—in particular, the results of its fuzzy-related analysis—to come up with an intuitive explanation for the h-index’s efficiency.
Deep Reinforcement Learning for Detecting Malicious Websites

Phishing is the simplest form of cybercrime with the objective of baiting people into giving away delicate information such as individually recognizable data, banking and credit card details, or even credentials and passwords. This type of simple yet most effective cyber-attack is usually launched through emails, phone calls, or instant messages. The credential or private data stolen are then used to get access to critical records of the victims and can result in extensive fraud and monetary loss. Hence, sending malicious messages to victims is a stepping stone of the phishing procedure. A \textit{phisher} usually setups a deceptive website, where the victims are conned into entering credentials and sensitive information. It is therefore important to detect these types of malicious websites before causing any harmful damages to victims. Inspired by the evolving nature of the phishing websites, this paper introduces a novel approach based on deep reinforcement learning to model and detect malicious URLs. The proposed model is capable of adapting to the dynamic behavior of the phishing websites and thus learn the features associated with phishing website detection.
State-Reification Networks: Improving Generalization by Modeling the Distribution of Hidden Representations

Machine learning promises methods that generalize well from finite labeled data. However, the brittleness of existing neural net approaches is revealed by notable failures, such as the existence of adversarial examples that are misclassified despite being nearly identical to a training example, or the inability of recurrent sequence-processing nets to stay on track without teacher forcing. We introduce a method, which we refer to as \emph{state reification}, that involves modeling the distribution of hidden states over the training data and then projecting hidden states observed during testing toward this distribution. Our intuition is that if the network can remain in a familiar manifold of hidden space, subsequent layers of the net should be well trained to respond appropriately. We show that this state-reification method helps neural nets to generalize better, especially when labeled data are sparse, and also helps overcome the challenge of achieving robust generalization with adversarial training.
The Accuracy of Indonesian Language Rules in Exam Questions Made by Teachers in Junior High School (SMPN) 27 Medan Academic Year 2016-2017 and 2017-2018

Evaluation is the result of the teaching and learning process carried out by teachers and students. Assessment serves to measure students' understanding of the material given by the teacher. Evaluation or procurement activities also play an important role in improving the quality of learning. As for the accuracy of the use of the Indonesian language rules in the class and UAS test exam questions made by Indonesian Language teachers in SMP 27 for the last two years, namely in the total of 195 questions consisting of multiple-choice descriptions, it was found that 86 questions (44%) were not effective and 99 questions (51%) are effective. The most common mistake is the alignment and unity of ideas and economics. The accuracy of the use of the operational word in this study is quite good, because only 5 questions (3%) are incorrect and 190 other questions (97%) are stated correctly.
The Lifetime Frontier: Search for New Physics with Long-Lived Particles

The search for new physics with long-lived particles is an ongoing and thriving effort in the High Energy Physics community which necessitates new search strategies such as novel algorithms, novel detectors, etc...For these reasons, one could perhaps add another frontier, the Lifetime Frontier, to the standard three (Energy, Intensity and Cosmic). In this talk, I will describe a BSM physics model whose characteristic signatures are decays of new (mirror) fermions at displaced vertices, a domain belonging to the Lifetime Frontier. It is a model of {\em non-sterile} right-handed neutrinos whose masses are proportional to the electroweak scale $\Lambda_{EW} \sim 246 \, GeV$. The model proposed a solution to the strong CP problem with a surprising connection between the sizes of the neutrino masses and the $\theta$-angle which contributes to the neutron electric dipole moment.
ENGLISH TEACHING METHODS IN WRITING DESCRIPTIVE TEXT OF SMK NEGERI 1 PULAU RAKYAT

This study was aimed to describe the English Teaching Methods in writing descriptive text and the problems faced by the teacher. This study was conducted by using descriptive qualitative research design. The subject of this research was an English teacher of SMK NEGERI 1 Pulau Rakyat. The techniques of collecting data were by observing the process of teaching writing comprehension of descriptive text at X Grade students and interviewing the English teacher. The techniques of collecting data were observation and interview. This study found that the teacher at SMK NEGERI 1 Pulau Rakyat used the method in teaching writing descriptive text. The English teacher used the lecture method and discussion method to teach in the descriptive text and the students get difficulties in comprehending the material. The application lecture method and discussion method is not appropriate with scientific approach of 2013 Curriculum. The result and response from the students to the teacher’s method are still not effective. The teacher should not apply the methods in written but also in spoken. And the problems faced by the teacher were the first is about the lack of students’ vocabularies, and the second is about the students’ participations when work in group. This study also found that the teacher’s methods not integrated with the scientific approach of 2013 Curriculum. The implementation of methods in teaching writing should can make teaching learning process more interesting and help the students’ understanding and skill of writing comprehension better.Key words: Teaching Method, Writing, Descriptive Text.
Learning Open Information Extraction of Implicit Relations from Reading Comprehension Datasets

The relationship between two entities in a sentence is often implied by word order and common sense, rather than an explicit predicate. For example, it is evident that "Fed chair Powell indicates rate hike" implies (Powell, is a, Fed chair) and (Powell, works for, Fed). These tuples are just as significant as the explicit-predicate tuple (Powell, indicates, rate hike), but have much lower recall under traditional Open Information Extraction (OpenIE) systems. Implicit tuples are our term for this type of extraction where the relation is not present in the input sentence. There is very little OpenIE training data available relative to other NLP tasks and none focused on implicit relations. We develop an open source, parse-based tool for converting large reading comprehension datasets to OpenIE datasets and release a dataset 35x larger than previously available by sentence count. A baseline neural model trained on this data outperforms previous methods on the implicit extraction task.
Adapting Image Super-Resolution State-of-the-arts and Learning Multi-model Ensemble for Video Super-Resolution

Recently, image super-resolution has been widely studied and achieved significant progress by leveraging the power of deep convolutional neural networks. However, there has been limited advancement in video super-resolution (VSR) due to the complex temporal patterns in videos. In this paper, we investigate how to adapt state-of-the-art methods of image super-resolution for video super-resolution. The proposed adapting method is straightforward. The information among successive frames is well exploited, while the overhead on the original image super-resolution method is negligible. Furthermore, we propose a learning-based method to ensemble the outputs from multiple super-resolution models. Our methods show superior performance and rank second in the NTIRE2019 Video Super-Resolution Challenge Track 1.
Network-Hexagons: H3-LISP Based Mobility Network

This document specifies combined use of H3 and LISP for mobility-networks: - Enabling real-time tile by tile indexed annotation ofpublic roads - For sharing: hazards, blockages, conditions,maintenance, furniture.. - Between MobilityClients producing-consumingroad geo-state information - Using addressable grid of channels ofphysical world state representation
Dancing for computers

Manus Island viewers are warned that this story contains images of deceased persons. Information and communication technologies (ICTs) drastically shifted the nature of work in all professions across the globe over the last 40 years. Yet, disparity exists between the global north and communities in the global south, as regards differences of access and resources to support the use of ICTs in many rural and remote communities. Dancing for Computers tells the story of community celebration by Ponam Islanders, in Manus Island in Papua New Guinea, on receipt of a couple of donated re-conditioned computers from the Queensland University of Technology in Brisbane, Australia. One aspect of the story is that of the generosity of university staff as they donate to the Learning Potential Fund to support students from disadvantaged backgrounds. The other aspect of the story is that of grateful recipients from a community that lacks electricity or running water, yet understands the possibilities of learning through computers and the broader application of this learning in improving various aspects of life. In memory of Damien Pahapat, Kaiyeh Chief, Broadcaster and Public Servant