Reviewerly/exHarmony huggingface dataset:
Design of web vulnerability scanner based on go language

The vulnerability scanner designed in this paper completed the collection of information and scanning of vulnerability, including six parts: input assets, asset collection, vulnerability profile, plug-in upload, single case detection and report display. The framework of vue realized the front end that included six pages, and the framework of gin realized the back end. The interface completed the separation of the front and back end. The database using MySQL designed seven tables. This scanner can avoid tedious and repetitive work, it can realize automatic scanning and testing of network vulnerabilities.
A study on light-weight cryptographic methods providing high data security in cloud

A study on light-weight cryptographic methods providing high data security in cloud - With the emergence of cloud computing,
A Fuzzy AHP Decision Support System for the Election (E-Voting)

Advanced technology provides an easy way to carry out various activities. An example is the E-voting application, a voting method, and counting votes in general elections using electronic devices. E-voting is a relatively new technology to support the implementation of democratic parties. In the implementation of conventional voting, mistakes often occur caused by human error. This project aims to design E-Voting for the election of the Chair of the Engineering Student Association using the AHP method. The benefit of this E-Voting is that we do not need to print ballot papers, so it supports the green technology program. Voting is also easy to do because only by touching the image mark on the touch panel represents the ballot. Thus, it is considered possible to facilitate persons with disabilities by using additional electronic features on the same device.
Analisis Graph Clustering Terhadap User Behavior Di Official Account Facebook Universitas Bina Darma Palembang

At a time when the times are increasing, it cannot be denied that almost some people use social media as a means of communication. Not only is it a means of communication, even social media is a place to show their habits. Without realizing it, the more information that is spread on social media regarding self-information, it will make information that can benefit others. User Behavior Analytics as defined by Gartner is a cybersecurity process of detection of insider threats, targeted attacks and financial fraud. The UBA solution looks at patterns of human behaviour and then applies algorithms and statistical analysis to detect meaningful anomalies of those patterns. Gephi is an open-source network visualization platform that can be used to analyze various cases using graph visualization. One of these analyzes can be done by using data that has been scraped from social media, Facebook, social media, Bina Darma University to get data visualization of the cases being tested. From these results, the graph clustering process is carried out in Gephi to obtain data clusters. The results will then be analyzed and identified so that they can become material for information about social media user behaviour.
DEVELOPMENT AND EVALUATION OF MOBILE LEARNING-APP ON SELECTED BASIC TECHNOLOGY CONCEPTS IN ILORIN METROLIS

The Integration of mobile technologies into instruction has a great potential to stimulate learning, engage students and improve classroom and outdoor teaching. In spite of the enormous benefits of mobile devices for instruction, mobile devices have not yet been deployed for learning in Nigeria secondary school, thus the objective of this study was to develop and evaluate mobile learning-App on selected Basic Technology Concepts in Ilorin Metropolis. This study is a research design and development of the Model type. Five (5) Educational Technology experts, five (5) Basic Technology experts and three (3) computer science expert were randomly selected for the study. Basic technology Learning-App, Educational Technology expert rating guide, basic technology expert rating guide computer science expert rating guide were employed. Mean rating and standard deviation were used to answer the research questions. The results of the findings indicated that ;(i) Educational technology experts rate the developed basic technology mobile learning-App as suitable for instruction with mean value 3.42> 2.5 (ii) Basic technology experts rate the developed basic technology mobile learning-App suitable for instruction with mean value 3.43 > 2.5 among others. The study concluded that the developed basic technology learning App is suitable for teaching and learning basic technology. The implication of these findings is that the learning App will create an effective teaching and learning experience of basic technology in upper basic secondary school. It was therefore recommended that; secondary school teachers should be trained on how to develop learning Apps irrespective of their area of specialization.
Identifying the Rules for the Evaluation of English Language Speaking Skill: A Library Based Review

The main purpose of this study is to propose some principles for the testing of speaking skill. It focuses on exploring the types of speaking tests, characteristics of a good speaking test, administration of a speaking test, types and appropriateness of speaking tasks, analysis of IELTS speaking test and scoring of oral assessment. The data is collected from various sources such as web search engines, articles from different research journals and from different books as it is a library based research. This essay concludes that to develop speaking skill, appropriate measure to test the speaking skill is very important. For an assessor, it is very important to have knowledge of the criteria for the preparation of oral test. Moreover, selection of tasks to test speaking skill and scoring criteria of these tests can lead a test to a standard oral test.
Semantic Location Privacy Protection Algorithm Based on Edge Cluster Graph

With the development of positioning technology and the popularity of mobile devices, location-based services have been widely deployed. To use the services, users must provide the server accurate location information, during which the attacker tends to infer sensitive information from intercepting queries. In this paper, we model the road network as an edge cluster graph with its location semantics considered. Then, we propose the Circle First Structure Optimization (CFSO) algorithm which generates an anonymous set by adding optimal adjacent locations. Furthermore, we introduce controllable randomness and propose the Attack-Resilient (AR) algorithm to enhance the anti-attack ability. Meanwhile, to reduce the system overhead, our algorithms build the anonymous set quickly and take the structure of the anonymous set into account. Finally, we conduct experiments on a real map and the results demonstrate a higher anonymity success rate and a stronger anti-attack capability with less system overhead.
Retrieval Augmentation to Improve Robustness and Interpretability of Deep Neural Networks.

Deep neural network models have achieved state-of-the-art results in various tasks related to vision and/or language. Despite the use of large training data, most models are trained by iterating over single input-output pairs, discarding the remaining examples for the current prediction. In this work, we actively exploit the training data to improve the robustness and interpretability of deep neural networks, using the information from nearest training examples to aid the prediction both during training and testing. Specifically, the proposed approach uses the target of the nearest input example to initialize the memory state of an LSTM model or to guide attention mechanisms. We apply this approach to image captioning and sentiment analysis, conducting experiments with both image and text retrieval. Results show the effectiveness of the proposed models for the two tasks, on the widely used Flickr8 and IMDB datasets, respectively. Our code is publicly available this http URL
The Suitability of Video Learning Media on Youtube with Poetry Writing Learning Materials Curriculum

This research is motivated by the large number of video learning media teaching materials to write poetry texts taken from Youtube without any adjustment and filtering of the content contained. The purpose of this study was to analyze the results of the suitability of video learning media on Youtube with the curriculum of writing poetry in class X SMA. The method used in this research is descriptive qualitative with research data sources obtained from Youtube. The results of this study refer to the indicators of the suitability of writing poetry in the curriculum by paying attention to the building blocks, namely theme, diction, language style, image, structure, and appearance. The results of the analysis show that in the discussion of the poetry theme there are four videos that are in accordance with the 2013 revised curriculum. One of the videos did not describe the theme material in detail. The diction material is discussed in all videos analyzed by the researcher. Furthermore, the language style is presented in all videos with a variety of different explanations according to the development of each presenter. In the presentation of image material, only one video describes it in detail, namely the video entitled Poetry Writing Learning Videos. In the material physical and mental structure, the physical and mental structure of the poetry is described as a whole. These structures are conveyed in all the indicator points of this research analysis which are part of the physical and mental part of the poetry. In the form or typography presented in four videos explaining the lyrics, good, and characteristics.
THE TEACHING OF ENGLISH FOR HOTEL AT NEPTUNE KEDIRI

This research was carried out to answer three objectives of study. Those are the teaching of English for Hotel at Neptune Kediri, response of the students towards the teaching of English for Hotel at Neptune Kediri and the tutor’s solution of the problems faced by students. The design was descriptive qualitative. The research instruments were observation sheet, interview note/sheet, document, and field note. The data collecting method were observation, interview, documentation, and field note. The result of this study showed that the teaching process of English for hotel at NEPTUNE had been supported by syllabus and lesson plan, the material was taken from book and internet, the media is using whiteboard and lcd tv. The method which was used was communicative learning and drill method, the technique which was applied in the class was direct question, problem based learning, discussion and role play technique. The evaluation of this program was taken by daily, mid semester and final semester. Tutor takes the student activeness and ability every meeting, mid and final evaluation take by interview test and witten test. From the result about the students’ perception was known that students had problems in constructing idea for speaking, less vocabulary and less confidence. From the students’ problem, the tutor gave solution by giving them tips and more discussion to increase their comprehension in speaking English.
Admissions - STUDENT INNOVATION SUPPORTED BY SZÉCHENYI DUO COMPETITION

Szechenyi Istvan University is committed to supporting student innovation: the institution strives to embrace all entrep
Memory Pool Publisher Algorithm for Preventing Malicious Fork in the Bitcoin Environment

Abstract— Blockchain technology is used by most Bitcoin systems to store all historical transaction information. Blockchain is a chain of blocks similar to the linked list structure and can be changed to a fork structure, in which there are two types of forks: useful fork or an intentional fork structure. A useful fork may appear when the rules of the Bitcoin system are updated. On the other hand, the intentional fork may appear when a miner has supercomputer properties, generates a set of blocks as a private branch, and does not publish this branch to the blockchain until its length exceeds the length of the main branch. A set of blockchain transactions will be rollbacked when the intentional fork occurs in the Bitcoin system, user waiting times will increase, and miner rewards will illegally increase. A Memory pool publisher algorithm is suggested in this paper to avoid the fork issues in the Bitcoin system, for instance: intentional fork, rollback problem, users waiting time. The proposed algorithm is to make the system a single publisher and divide the block's construction into two phases. A miner constructs a block and sends it to the memory pool as the first phase. The memory pool will send the construction block to the blockchain as the second phase. The findings indicate that the proposed algorithm has a strong potential to avoid the blockchain's intentional fork problem and thus minimize user waiting times for the rollback problem.
On the Power of Nondeterministic Circuits and Co-Nondeterministic Circuits

Revealing the power of nondeterministic computation and co-nondeterministic computation is one of the central problems in computational complexity. In this paper, we consider the two computation and deterministic computation in Boolean circuits. We give the first separations on the power of deterministic circuits, nondeterministic circuits, and co-nondeterministic circuits in general circuits. More precisely, we prove the following facts. There is an explicit Boolean function f such that the nondeterministic \(U_2\)-circuit complexity of f is at most \(2n + o(n)\) and the deterministic and co-nondeterministic \(U_2\)-circuit complexity of f is \(3n - o(n)\). There is an explicit Boolean function f such that the co-nondeterministic \(U_2\)-circuit complexity of f is at most \(2n + o(n)\) and the deterministic and nondeterministic \(U_2\)-circuit complexity of f is \(3n - o(n)\).
Action Quantum Speed Limits

We introduce action quantum speed limits (QSLs) as a family of bounds on the minimal time to connect two states that, unlike the usual geometric approach, crucially depend on how the path is traversed, i.e., on the instantaneous speed. The two approaches provide consistent bounds when the instantaneous speed is optimized along a fixed path and we demonstrate this explicitly for the case of a thermalizing qubit employing techniques from optimal control theory. In addition, we critically analyze the interpretation of QSLs based on different choices of metric establishing that, in general, these open-system QSL times provide an indication of optimality with respect to the geodesic path, rather than necessarily being indicative of an achievable minimal time.
Cognitive Foundations of Search

The purpose of information systems is to help people find information to meet their task goals. Understanding the user’s capacities to interact with a search system can inform all aspects of information system design. The future of search is intelligent and cooperative. Systems will need to engage the user as more than a mere query-generation engine. Next generation search system design will benefit from understanding the cognitive processes that drive interactive information retrieval.This workshop is an introduction to human cognitive processes from the perspective of information search. Starting with the human memory system and knowledge, the participant will learn about the human attention allocation system, and the stages of information processing from low-level recognition to acquiring meaning. Then, higher level interaction processes will be examined, including cognitive constraints on problem solving and decision processes. Finally, meta-cognitive processes including ’feeling of knowing’ and sense of completeness will be discussed.The workshop will connect material from neurobiology, cognitive science, AI, information science, and philosophy of mind. Everything is organized around human information retrieval and processing, so participants will be able to apply this cognitive perspective to their interests and challenges. The goal of the workshop is to introduce and connect current understanding of human cognitive processes in the context of interactive information retrieval. A collection of resources for deeper investigation will be provided.There will be little math and scientific nomenclature will be minimized in favor of a focus on the cognitive processes involved in search. Examples and illustrations will be drawn from legal search, but the practical comments will apply to any interactive information service.OutlineThree 50 min sessions (10 min breaks)Foundations • Human Memory System• Concepts and Knowledge - The shiny beasts of thought.• Attention allocation - The two systems of human attention: reactive and goal-directed.Search interaction • Recognition and information processing - Especially text information acquired by the vision system• Decision making under uncertainty - Satisficing, problem (re)representation• Sessions, tasks, and goals - Intention, attention, and action to an end. Context, centering and coherence.Higher order processes • Meta-cognitive processes - Tip of the tongue (TOT), Feeling of knowing (FOK), time duration, self-monitoring in search processes• Cognitive penetrability - How deeply can humans introspect on their interaction processes?• Trust formationWho may be interested? Those with interest in product development, customer discovery, customer service, search engineering, UI/UX, and related research and development.Duration: A packed 3 hours.
Does Contact Tracing Work? Quasi-Experimental Evidence from an Excel Error in England

Contact tracing has been a central pillar of the public health response to the COVID-19 pandemic. Yet, contact tracing measures face substantive challenges in practice and well-identified evidence about their effectiveness remains scarce. This paper exploits quasi-random variation in COVID-19 contact tracing. Between September 25 and October 2, 2020, a total of 15,841 COVID-19 cases in England (around 15 to 20% of all cases) were not immediately referred to the contact tracing system due to a data processing error. Case information was truncated from an Excel spreadsheet after the row limit had been reached, which was discovered on October 3. There is substantial variation in the degree to which different parts of England areas were exposed -- by chance -- to delayed referrals of COVID-19 cases to to the contact tracing system. We show that more affected areas subsequently experienced a drastic rise in new COVID-19 infections and deaths alongside an increase in the positivity rate and the number of test performed, as well as a decline in the performance of the contact tracing system. Conservative estimates suggest that the failure of timely contact tracing due to the data glitch is associated with more than 125,000 additional infections and over 1,500 additional COVID-19-related deaths. Our findings provide strong quasi-experimental evidence for the effectiveness of contact tracing.
Enabling Efficient On-Device Self-supervised Contrastive Learning by Data Selection

This work aims to enable efficient on-device contrastive learning from input streaming data after a model is deployed on edge devices such as robots or unmanned aerial vehicles (UAVs) so that they can adapt to a dynamic new environment for higher accuracy. On the other hand, such data usually does not have any labels, calling for unsupervised learning. Most recently, contrastive learning has demonstrated its great potential in learning visual representation from unlabeled data. However, directly applying it to streaming data requires storing a large dataset on-the-fly, which will quickly drain edge devices’ storage resources. In this paper, we propose a framework to automatically select the most representative data from unlabeled input stream on-the-fly, which only requires the use of a small data buffer for dynamic learning. What is more, considering the fact that the data are not independent and identically distributed (iid) as in the traditional training process, we score new data as they come in by measuring the quality of their representations without requiring any label information, based on which the data in the buffer will be updated. Extensive experiments show that the learning speed and accuracy are greatly improved compared with approaches without data selection.
Application to predict the new student’s score using time series algorithm

With the rapid development of information technology in this era, data accuracy is essential in our daily lives to solve existing problems. The existence of information is beneficial in helping the decision-making process. Therefore, any existing information can be further processed and analyzed to be used as new knowledge so that it is useful to determine the right decision. The purpose of this research is to determine whether an application using the time series algorithm such as Auto Regression, ARMA (Auto Regression Moving Average), and Triple Exponential Smoothing model. They can forecast prediction scores that may help to solve the student's admission problem. In this case of the project, the researcher found that the Universitas Muhammadiyah Surakarta's admission system is not evaluated correctly in accepting students and controlling incoming students' quality due to the lack of insights. This time series application is one solution to help manage incoming students' quality and quantity, especially in the Universitas Muhammadiyah Surakarta. This application is developed using a web framework called Django, a full-stack Python web framework that encourages rapid growth and clean, pragmatic design. The Auto Regression model is chosen as a prediction model in One Day Service (ODS) Universitas Muhammadiyah Surakarta. It has a better performance than ARMA and Triple Exponential Smoothing and a higher chance to avoid overfitting than the other two models that are more complex for the ODS data.
SECI-SYS: secretariat database managementsystem / Nor Syamimi Iliani Che Hassan ...[et al.]

SECI-SYS is a system software developed as a platform to store, retrieve, and update data regarding information management. Secretariat, in this regard acts as the people responsible for maintaining effective records and file administration. In conjunction with 2nd Kelantan International Learning and Innovation Exhibition 2019 (KILIEx 2019), SECISYS is established to ensure the management of data is consistently organized and remained to be easily accessible by the end users. SECI-SYS is governed by the information processing cycle which consists of four major stages; input, processing, storage and output. In brief, the procedures include data entry (input stage) followed by data coding and updating (processing stage), data keeping (storage stage) and finally producing desired data for respective users (output stage). Due to the varying needs from multiple angles, SECI-SYS plays a pivotal role as the core data feeder to enable the committees to access the information. In the absence of SECI-SYS, missing of files, overlapping of information, and iscommunication as a whole, shall be expected to occur. Consequently, database management system for KILIEx 2019 will be dysfunctional thus, disrupt the flow of the event. With this SECI-SYS, the anagement of database will be made convenient due to its multiple access, user-friendly, cloud storage function and zero charge for its development. SECI-SYS allows room for additional features to be included in order to maximize the functions for advanced users such as the merging data for managing pharma ommercialization due to its marketabilit
Basic methods of statistical analysis in psychological measurements

The integration of computer and mathematical disciplines takes place on a substantive and procedural aspect and forms a new independent scientific and educational field.The integrated content of academic disciplines becomes information-intensive and is aimed (in terms of the intellectual development of the individual) to develop the ability to think in information-intensive categories.