Reviewerly/exHarmony huggingface dataset:
Rancang Bangun Sistem Informasi Modul Procurement pada Aplikasi PT Jala Informatica dengan Bahasa Pemrograman Adobe Coldfusion

Recording an item is often fraudulent, for example, misuse of company assets with false statements to present financial statements from the accounting division so that this can be declared a criminal act of corruption. To avoid the act of cheating, a web-based application was created to be used by admins and users so that it would later become an information system for recording a procurement of goods. The procurement system for the success of the ERP system that focuses on the procurement module is based on the Coldfusion Family. This study aims to determine the success of the CORE-ERP system owned by PT Jala Informatica by creating a system designed for the procurement module with the prototyping method. Some testing systems are by the UAT standard with the blackbox method black box is based on the appearance and function of the existing features on the system. the test results on purchase orders, upload items, approvals, and general receive notes are declared successful.
PERANCANGAN SISTEM INFORMASI E-INVENTARIS BARANG PADA PUSAT REHABILITASI NARKOBA AR RAHMAN

Currently the use of technology in the dissemination of information is very important for organizations or agencies. An information system is currently very supportive of activities for organizations or agencies which will then be reprocessed to be more useful for users of the information system itself. The Ar-Rahman Drug Rehabilitation Center itself is a rehabilitation center for drug addicts. To support their work, the staff at the Ar-Rahman Drug Rehabilitation Center are currently using the facilities available there. One of them is recording inventory of goods. Currently, the recording is still done manually, namely by recording what items are purchased and borrowed. From these causes, it is urgently needed to build an E-Inventory Information System Design at the Ar Rahman Drug Rehabilitation Center which functions to record any assets that are already owned that were previously recorded manually in the future to be digital. In the design it will use dfd and erd while the database uses waterfall. The expected results are an inventory system design that will be implemented in . Ar-Rahman Drug Rehabilitation Center and can be used as a basis for developers to create an inventory system. Ar-Rahman Drug Rehabilitation Center.
Sistem Informasi Smart Security untuk Perumahan dengan QR Code Berbasis Web

This information system aims to make it easier for security officers to record residents who enter or leave the housing. This information system helps the housing admin get data on residents who enter and leave housing. There is no data collection system available for residents who will enter or leave the Graha Bakti Persada housing area. The unavailability of a support system that can be used as an effort to prevent crime. Building a Smart Security Information System with a web-based QR Code. Create a system that makes it easier for security officers. see the QR Code results based on the appropriate citizen ID in the database. The research methodology is to analyze the problems that occur, and design procedures. Suggestions that can be used as a reference for further system developers are the need to improve functions and menus in the application.
Sistem Pencarian Lokasi Guru Private Di Kota Pekanbaru Berbasis WEB

Since the pandemic spreads because of Corona Virus in Indonesia, a lot of ways that the government to prevent the spreads. so that the government makes the announcement for school by online and doing teaching and learning at each house. many parents are worried because they feel the teaching and learning activities from home is not enough. therefore is needed to have a system thats able to display information about the location of the private teacher in Pekanbaru.the Geographic system information is a system computer based that combines between the elements of the map and information designed to obtain, process, manipulate, analyze, demonstrate, and display the spacial data to resolve , process and research the problems.this research uses a google maps to showing the information about searching a location and information and data about private teacher
What are the Realities

The question of what is real is familiar in physics. This paper addresses this question through the notions of reality in the models of of the world (schemata) that are created by the information gathering and utilizing systems (IGUSes) in the Universe. That way the question of what is real becomes an emperical quastion that can be answered by the standard scientific methods of observation and test.
Philippine Eagle Optimization Algorithm

We propose the Philippine Eagle Optimization Algorithm (PEOA), which is a meta-heuristic and population-based search algorithm inspired by the territorial hunting behavior of the Philippine Eagle. From an initial random population of eagles in a given search space, the best eagle is selected and undergoes a local food search using the interior point method as its means of exploitation. The population is then divided into three subpopulations, and each subpopulation is assigned an operator which aids in the exploration. Once the respective operators are applied, the new eagles with improved function values replace the older ones. The best eagle of the population is then updated and conducts a local food search again. These steps are done iteratively, and the food searched by the final best eagle is the optimal solution of the search space. PEOA is tested on 20 optimization test functions with different modality, separability, and dimension properties. The performance of PEOA is compared to 11 other optimization algorithms. To further validate the effectiveness of PEOA, it is also applied to image reconstruction in electrical impedance tomography and parameter identification in a neutral delay differential equation model. Numerical results show that PEOA can obtain accurate solutions to various functions and problems. PEOA proves to be the most computationally inexpensive algorithm relative to the others examined, while also helping promote the critically endangered Philippine Eagle.
Learning for Robust Combinatorial Optimization: Algorithm and Application

Learning to optimize (L2O) has recently emerged as a promising approach to solving optimization problems by exploiting the strong prediction power of neural networks and offering lower runtime complexity than conventional solvers. While L2O has been applied to various problems, a crucial yet challenging class of problems -- robust combinatorial optimization in the form of minimax optimization -- have largely remained under-explored. In addition to the exponentially large decision space, a key challenge for robust combinatorial optimization lies in the inner optimization problem, which is typically non-convex and entangled with outer optimization. In this paper, we study robust combinatorial optimization and propose a novel learning-based optimizer, called LRCO (Learning for Robust Combinatorial Optimization), which quickly outputs a robust solution in the presence of uncertain context. LRCO leverages a pair of learning-based optimizers -- one for the minimizer and the other for the maximizer -- that use their respective objective functions as losses and can be trained without the need of labels for training problem instances. To evaluate the performance of LRCO, we perform simulations for the task offloading problem in vehicular edge computing. Our results highlight that LRCO can greatly reduce the worst-case cost and improve robustness, while having a very low runtime complexity.
Beyond Model Splitting: Preventing Label Inference Attacks in Vertical Federated Learning with Dispersed Training

Abstract Federated learning is an emerging paradigm that enables multiple organizations to jointly train a model without revealing their private data. As an important variant, vertical federated learning (VFL) deals with cases in which collaborating organizations own data of the same set of users but with disjoint features. It is generally regarded that VFL is more secure than horizontal federated learning. However, recent research (USENIX Security’22) reveals that it is still possible to conduct label inference attacks in VFL, in which attacker can acquire privately owned labels of other participants; even VFL constructed with model splitting (the kind of VFL architecture with higher security guarantee) cannot escape it. To solve this issue, in this paper, we propose the dispersed training framework. It utilizes secret sharing to break the correlations between the bottom model and the training data. Accordingly, even if the attacker receives the gradients in the training phase, he is incapable to deduce the feature representation of labels from the bottom model. Besides, we design a customized model aggregation method such that the shared model can be privately combined, and the linearity of secret sharing schemes ensures the training accuracy to be preserved. Theoretical and experimental analyses indicate the satisfactory performance and effectiveness of our framework.
Reading Ability of Grade 7 Students in Rebokon Agricultural and Vocational High School and Its Effect to Their Academic Performance

Reading skill is the ability to decode meaning from a text.The skills include phonics, word recognition, vocabulary, decoding and fluency.For one to be a proficient reader, one must possess these vital skills.Results indicated that a correlation did exist between reading and mathematics performance at the early elementary level when including grades seven.School administration should take possible actions in this dilemma.If schools fail to do so, the academic performance of the Grade 7 students will remain until they reach higher grade levels.Reading is the ability to understand words contained in a document and make use of the knowledge for personal growth and development.In addition to this, comprehension can really help the student to understand the meaning of the text words for words.In this study, data of student's respondent from their school academic performance reports will be used to find out of there is a relationship between the relationship of reading ability and the academic performance of students.At the point of finality, we as researchers hope that this study and investigation will become successful and prosperous.
Lifelong Generative Modelling Using Dynamic Expansion Graph Model

Variational Autoencoders (VAEs) suffer from degenerated performance, when learning several successive tasks. This is caused by catastrophic forgetting. In order to address the knowledge loss, VAEs are using either Generative Replay (GR) mechanisms or Expanding Network Architectures (ENA). In this paper we study the forgetting behaviour of VAEs using a joint GR and ENA methodology, by deriving an upper bound on the negative marginal log-likelihood. This theoretical analysis provides new insights into how VAEs forget the previously learnt knowledge during lifelong learning. The analysis indicates the best performance achieved when considering model mixtures, under the ENA framework, where there are no restrictions on the number of components. However, an ENA-based approach may require an excessive number of parameters. This motivates us to propose a novel Dynamic Expansion Graph Model (DEGM). DEGM expands its architecture, according to the novelty associated with each new databases, when compared to the information already learnt by the network from previous tasks. DEGM training optimizes knowledge structuring, characterizing the joint probabilistic representations corresponding to the past and more recently learned tasks. We demonstrate that DEGM guarantees optimal performance for each task while also minimizing the required number of parameters. Supplementary materials (SM) and source code are available in https://github.com/dtuzi123/Expansion-Graph-Model.
LTB curves with Lipschitz turn are par-regular

Preserving the topology during a digitization process is a requirement of first importance. To this end, it is classical in Digital Geometry to assume the shape borders to be par-regular. Par-regularity was proved to be equivalent to having positive reach or to belong to the class C 1,1 of curves with Lipschitz derivative. Recently, we proposed to use a larger class that encompasses polygons with obtuse angles, the locally turn-bounded curves. The aim of this technical report is to define the class of par-regular curves inside the class of locally turn-bounded curves using only the notion of turn, that is of integral curvature. To be more precise, in a previous article, we have already proved that par-regular curves are locally turn-bounded. Incidentally this proof lead us to show that the turn of par-regular curves is a Lipschitz function of their length. We call the class of curves verifying this latter property the curves with Lipschitz turn. In this technical report, we prove the converse assertion : locally turn-bounded curves with Lipschitz turn are par-regular. The equivalence is stated in Theorem 3.1 and the converse assertion is proved in Lemma 3.2. In section 1, we recall the definition of par-regularity and equivalently of sets with positive reach. In section 2, we present the notions of curves locally turn-bounded and of curves with Lipschitz turn. Throughout this latter section, some of intermediate steps (Lemmas 2.3 and 2.11) are proved just after the introduction of their related notions. The last section (section 3) is dedicated to the proof of the equivalence of the notions.
The Credibility Cryptocurrency Valuation: Statistical Learning Analysis for Influencer Tweets

Cryptocurrency has attracted significant attention. Considering the number of individuals investing in bitcoin, their motivations are comparatively less clear than traditional investment decisions. As of December 2020, the market has continuously increased in cryptocurrency. Especially, the spike of joke Dogecoin shows the weirdness of the modern meme economy with the support of Elon Musk, whom himself appointed as "Dogefather". In this paper, we analysis the impact of tweets by Elon musk and present some statistical analyze with event study.
A model sufficiency test using permutation entropy

Using the ordinal pattern concept in permutation entropy, we propose a model sufficiency test to study a given model's point prediction accuracy. Compared to some classical model sufficiency tests, such as the Broock et al.'s (1996) test, our proposal does not require a sufficient model to eliminate all structures exhibited in the estimated residuals. When the innovations in the investigated data's underlying dynamics show a certain structure, such as higher-moment serial dependence, the Broock et al.'s (1996) test can lead to erroneous conclusions about the sufficiency of point predictors. Due to the structured innovations, inconsistency between the model sufficiency tests and prediction accuracy criteria can occur. Our proposal fills in this incoherence between model and prediction evaluation approaches and remains valid when the underlying process has non-white additive innovation.
Image Hashing Through Spatio-triad Relationship

Authenticating the content of the digital image has profound influence in legal matters and in court rooms. Image forensics plays an important role towards it. Proposed approach helps to authenticate the original image by generating a content based image signature that is a unique fingerprint for the image. Our novel approach establishes spatio triad relationship among features and finds the centre of gravity or centroid of the same after indexing. Topology of the triad relationship for the content based low level feature descriptors is preserved through aggregation until single key feature is deduced which is a 128 bit signature hash value and represented in decimal form. Density of feature keypoints influences the centre of gravity which acts as a unique signature for the given image. Manipulated image cannot contribute to restore / regenerate the same signature. We have verified our authentication approach for standard benchmark image dataset like MICC-F220, Columbia Image Splicing Evaluation dataset and Image manipulation dataset from Friedrich Alexander University and have found satisfactory results for the same. Content based image signature obtained is used to verify authenticity of image and for retrieval of video from database. Content based image fingerprint generated can also be considered for embedding as a watermark.
TEACHING ADVANCED LISTENING DURING COVID-19 PANDEMIC: LECTURERS’ STRATEGIES EXPLAINED

Listening is one of the four sub-skills in English that need to be mastered. Learning will be more effective when using the appropriate learning strategies. In this pandemic period, appropriate learning strategies are necessary to optimize learning. The purpose of this research is to find out what strategies lecturers need and use in teaching advanced listening during COVID-19 at UIN Ar-Raniry and how lecturers apply and implement the strategy in teaching advanced listening during COVID-19 at UIN Ar-Raniry. The researcher used email and WhatsApp as the media. The data collection method used in this study is qualitative, using a narrative approach. In collecting data, the researcher also used data collection techniques using the semi-structured interview type. The researcher used data reduction and written summarization to analyze the data. The participants are three permanent lecturers and one substitute lecturer in the Department of English Language Education of Ar-Raniry State Islamic University. They are selected purposively using specific criteria. This study’s results indicate that using the right strategy in the learning process will produce effective learning. All participants can investigate their right thoughts, opinions, and arguments, including any aspect of listening teaching strategies.
A Deep Study on the Performance of the Spatial Density Distribution Method to Recognize Handwritten Signatures

A signature is a special identifier that confirms a person's identity and distinguishes him or her from others. The main goal of this paper is to present a deep study of the spatial density distribution method and the effect of a mass-based segmentation algorithm on its performance while it is being used to recognize handwritten signatures in an offline mode. The methodology of the algorithm is based on dividing the image of the signature into tiles that reflect the shape and geometry of the signature, and then extracting five spatial features from each of these tiles. Features include the mass of each tile, the relative mean, and the relative standard deviation for the vertical and horizontal projections of that tile. In the classification stage, four measurements of the Euclidean distance were used. While the accuracy rates for 4854 samples drawn from five different evaluated standard datasets ranged from 92.24% to 100%.
Motivation of Student Management Subjects in Universities Based on Network Intelligence

With the intelligent development of the society and the development of the big data era, the network intelligence applications in various fields have deeply penetrated them, and colleges and universities, as the place where information technology is most widely used, have been profoundly affected by the network intelligence. In this context, besides the traditional use of digitalization, informatization, and networking to assist in managing students’ studies and life, the work of the main body of student management in colleges and universities is also gradually developing towards intelligence. In the research of this study, through the application and development of network intelligence, the intelligent research of college student management is carried out by using the technical advantages of massive data access, so as to improve the motivation of college student management subjects through intelligence, make students feel the orderly and reliable humanized management while improving the efficiency of student management, and provide sufficient technological guarantee for college management.
Distributed Multi-Ant Colony System Algorithm using Raspberry Pi Cluster for Travelling Salesman Problem

The traveling salesman problem is addressed in this paper by introducing a distributed multi-ant colony algorithm that is implemented on a Raspberry Pi cluster. The implementation of a master and eight workers, each running on Raspberry Pi nodes, is the central component of this novel technique. Each worker is responsible for managing their own colony of ants, while the master coordinates communications among workers’ nodes and assesses the most optimal approach. To put the newly built cluster through its paces, several datasets of traveling salesman problem are used to test the created cluster. The findings of the experiment indicate that a single board computer cluster, which makes use of multi-ant colony algorithm, is a viable alternative for distributed computing. This approach's extensibility options are extensively discussed as well.
Application of Heart Rate Combined with Acceleration Motion Sensor in Sports Dance Teaching

Because of the large amount of exercise, sports dance has the characteristics of good viewing and strong movement, and has gradually entered the campus in recent years. However, sports dance is not only difficult, but also has a wide variety of categories except modern dance and Latin dance. In addition to these two categories, there are 10 kinds of dances in total. Therefore, in teaching, schools have no choice, and students cannot understand which dance styles are most effective for students’ physical exercise. In order to solve the problem that there are many kinds of sports dance and the effect of students’ exercise is unclear, this paper studied sports dance teaching based on heart rate combined with acceleration motion sensor, and obtained the energy consumption in sports dance teaching by using this measurement method. After comparing the effects, four kinds of dance activities, namely quickstep, waltz, rumba, and samba, which are more conducive to physical exercise, were screened out for students in the complex sports dance. In addition, in order to confirm the experimental results of the article, after the teacher improved the physical dance teaching according to the content of the article, it was found that before the experiment, the average scores of the two groups of subjects were 17.5 points and 16.75 points. After the experiment, the scores of the two groups increased by 3.5 points and 2.8 points, respectively. Through the experimental results and data, it can be shown that the research in this paper has played a good role in the improvement of sports dance teaching.