Reviewerly/exHarmony huggingface dataset:
Dynamic Multi-Keyword Ranked Search Based on Simhash in Cloud Computing

More and more organizations and users are attracted by the low-cost and high-quality cloud service to outsource their data into the cloud storage. The sensitive data has to be encrypted to protect its privacy. The traditional ciphertext full-text retrieval scheme directly calculates the inner product of high-dimensional encryption vectors, which has a huge amount of computation. In this paper, a Simhash-based multi-keyword ranked search scheme is proposed to achieve efficient full-text retrieval of massive ciphertext data. This scheme constructs SMRI index based on the idea of Simhash's dimensionality reduction. It processes the document's feature words into hash fingerprints and segments them. In order to prevent the leakage of ciphertext information in retrieval process, documents and query keywords are transformed into vectors, and then the vectors are extended and encrypted by improved SkNN algorithm. The B+ tree is constructed with segmented fingerprints and encrypted vectors, and the results are carried out by "filter-refine" strategy. Firstly, the candidate results are obtained by matching the segmented fingerprints, which reduces computation largely. Then calculate the Hamming distance and vector product between the candidate results and trapdoor to get the top-k results. The experimental results show that SMRI has the advantages of high retrieval efficiency, low computational complexity, saving time and space costs, and is suitable for fast and secure retrieval of massive ciphertext data.
Innovative Educational Practices: Classification, Design, Modeling

Innovative educational practices are local education phenomena created to solve actual problems in the field of education. Creators of practices implement an authors idea, which allows you to go beyond the boundaries of the normative field of educational activities. The multiplicity and variability of innovative educational practices, the lack of a description from the position of didactics make it difficult to use them as a resource for the development of education. The authors of this entry developed didactic models of various educational practices, carried out classification, determined and characterized the design stages. They analyzed and described the theory of solving inventive problems (TSIP), dramahermeneutics, the technology of education in the global information community (TEGIC), a tutor support of educational activity, action learning, panoramic learning, and others from the didactic positions. The classification of educational practices is based on the allocation of educational problems solved by a particular practice. The entry defines several stages of designing innovative educational practices: - Initiation of educational practice. - Planning and development of a practice. Definition of criteria for its intended effectiveness. - Implementation of a practice. It’s institutionalization. - The stage of completion of a project. In developing models of educational practices, we proceeded from the fact that the didactic model is a descriptive model, including a description of target, value, content, procedural, effective components. The absence of a mathematical apparatus does not reduce its scientific significance.
IDENTIFICATION ANALYSIS OF ULTRAMAFIC-MAFIC INTRUSIONS IN THE MAMONSKY COMPLEX OF THE VORONEZH CRYSTALLINE MASSIF

The paper describes the methods and results of identification analysis of the petrophysical parameters in ultramafic-mafic rocks from the Mamon intrusive complex in the Khopersky megablock of the Voronezh crystalline massif. In order to create identification models, the authors chose one of the boregoles within the Nizhnemamon deposit as the reference one. For different types of rocks, characteristic correlation equations of the relationship of density with other petrophysical parameters were obtained. The obtained identification equations of the reference borehole were applied to similar rocks from other (ordinary) boreholes located within the Khopersky megablock. The modeling showed that it is possible to apply the group method of data handling in order to solve the most important task, which is to say that is the differentiation of even-aged intrusions as ore and barren.
3D Segmentation For Kidney Data

The segmentation pipeline consists two parts, first, we process 3d data into a series of 2d images, then send them into a popular segmentation neural network-deeplab v3+ to get segmentation result.
Online Signature Verification through Scaled Histogram of Oriented Gradients

Since signatures are an integral part of our everyday lives, that represent a legally binding seal of approval; it is essential for them to be verified accurately. Online signature verification is used to confirm an individual's identity based on realtime characteristics that are compiled during the act of signing. It is often used to reduce fraud in institutions such as banks and other credit service providers, since it offers a robust alternative to the traditional offline signature verification. This study aims to complement existing efforts in this field by employing Histogram of Oriented Gradients (HOGs) as a feature extraction mechanism that feeds into a template matching exercise based on Normalized Cross Correlation (NCC). The scale at which HOGs are applied is controlled in order to investigate the trade-off between granularity and verification effectiveness. Accuracies of 78% and 70% are obtained on the SVC2004 dataset for complete and half signature coverage respectively. This highlights the importance of global context when using realtime features, since it appears that useful information is lost when using separate HOGs for the first and second half of an online signature.
Zig-zag diagonal and ANN for English character recognition

Pattern recognition is the most popular are in the modern world.Significant progress has made in English character and digits recognition technology.However, the performance of the existing system of English character and digits recognition can be increased.This study is suggested a novel method, zig-zag diagonal feature extraction method along with ANN to increase the recognition rate of the English character and digit recognition system.The proposed method of this method is tested on an official dataset of English characters (EMNIST) and English digits (MNIST), achieving a 99.8% accuracy and 94% accuracy, respectively.
Cyber Capability Planning and the Need for an Expanded Cybersecurity Workforce

Cybersecurity is a national concern for the United States, yet the cybersecurity workforce is currently understaffed. Military capability planning can be used as a framework to evaluate and establish cybersecurity workforce development models, such as the National Initiative for Cybersecurity Education (NICE) Framework. These models can be used in a way that provides the nation a methodology to enhance human resource capabilities and fill the cybersecurity workforce deficit. Furthermore, this report discusses the importance of establishing and enhancing strategic recruitment initiatives that can be utilized for building a cybersecurity pipeline.
A Reading Tutor for Low-Literacy Adults

According to the Organization for Economic Cooperation and Development (OECD), the mean proficiency in literacy among adults in the US and Canada is at Level 2. Adults at this level cannot process dense texts, eliminate irrelevant information, perform multi-step operations, or evaluate the reliability of a source. The Reading Tutor is a website that was created to help low-literacy adults improve their English. It will be free to use the website that is personalized to the literacy level of every user. Creating a website allows people to increase their literacy levels without facing the stigma that comes with attending a class in person. Adults are inclined to improve their English because it often affects their career potential, socio-economic status, and health. The Reading Tutor has two major components: the passages and the scenarios. Passages are stories that the user can read and answer questions about. Scenarios are plots with questions that the user must answer to move on. In recent work, the information for each scenario was organized into spreadsheets to simplify the process of entering data into the code.&#x0D; The system architecture consists of HTML, CSS, Javascript, MySQL, Python, and Django. The newest development in this project was the improvement of the user intake experience. Before starting the passages and scenarios, the website collects information from each adult. The user "interests" pages are the latest additions to the site and these pages ask about the user’s hobbies. That data will then be used to incorporate their interests into later questions. It was important to add this feature to the website because relevance is a motivator for the user demographic. The next steps for the website are to log the user’s interests into the database. Future enhancements also include the creation of more scenarios to accommodate to the different user interests.&#x0D;
Word Image Representation Based on Sequence to Sequence Model with Attention Mechanism for Out-of-Vocabulary Keyword Spotting

To realize keyword spotting by means of query-by-example, learning efficient representation for word images is an essential issue. However, the amount of vocabulary at the training stage is often far less than the complete vocabulary of a certain language in various learning based representation approaches. Thus, unseen vocabularies might be taken as query keywords which may not exist in training set. Therefore, out-of-vocabulary (OOV) is frequently occurred in keyword spotting. In this paper, a sequence to sequence model with attention mechanism has been proposed to generate representation vectors of word images for solving the problem of OOV. After that, similarities can be calculated between each word image and a given query keyword image on their representation vectors. And then, a ranking list can be formed in descending order of the similarities for a collection of word images. Experimental results demonstrate that the proposed representation approach can be competent for the task of OOV keyword spotting and outperforms various baseline and state-of-the-art methods.
A system for reasoning-based link prediction in large knowledge graphs

This poster paper presents an efficient method R-Linker for link prediction in large knowledge graphs, based on rule learning. The scalability and efficiency is achieved by a combination of several optimisation techniques. Experimental results show that R-Linker is able to handle KGs with over 10 million of entities and more efficient than existing state-of-the-art methods including RLvLR and AMIE+ in rule learning stage for link prediction.
Extractive Text-Based Summarization of Arabic Videos: Issues, Approaches and Evaluations

In this paper, we present and evaluate a method for extractive text-based summarization of Arabic videos. The algorithm is proposed in the scope of the AMIS project that aims at helping a user to understand videos given in a foreign language (Arabic). For that, the project proposes several strategies to translate and summarize the videos. One of them consists in transcribing the Arabic videos, summarizing the transcriptions, and translating the summary. In this paper we describe the video corpus that was collected from YouTube and present and evaluate the transcription-summarization part of this strategy. Moreover, we present the Automatic Speech Recognition (ASR) system used to transcribe the videos, and show how we adapted this system to the Algerian dialect. Then, we describe how we automatically segment into sentences the sequence of words provided by the ASR system, and how we summarize the obtained sequence of sentences. We evaluate objectively and subjectively our approach. Results show that the ASR system performs well in terms of Word Error Rate on MSA, but needs to be adapted for dealing with Algerian dialect data. The subjective evaluation shows the same behaviour than ASR: transcriptions for videos containing dialectal data were better scored than videos containing only MSA data. However, summaries based on transcriptions are not as well rated, even when transcriptions are better rated. Last, the study shows that features, such as the lengths of transcriptions and summaries, and the subjective score of transcriptions, explain only 31% of the subjective score of summaries.
Reusable and interactive classes: a new way of object composition

Separating object features from base classes is one of the popular ways of software development.Some popular programming approaches like object-oriented programming, feature-oriented programming, and aspect-oriented programming follow this approach.There are four advantages of using features: 1) Instantiability: the ability to create instances of a feature, 2) Reusability: the quality of a feature being reusable in many compositions, 3) Loosely coupled composability: the ability to compose/decompose features easily at object instantiation time (not offering new data types for compositions), and 4) Interactability: the ability of a feature to crosscut (interact with) other features inside the object.Existing approaches do not find strong evidence to support these advantages altogether.In this paper, we propose a new approach that provides all the advantages mentioned above.In our approach, each feature is developed as a class that can be instantiated or reused.A new composition method is also proposed to compose features of an object where it is instantiated.In such a way, a feature can be either a complete object or part of a big object.In fact, composing different reusable features yields object variations, since features can be easily added/removed in a loosely coupled manner.To make features interactive, we augment them with events.Events provide the interactions among the different features of an object.We show that events are soft dependencies that do not affect the reusability of features while method callings in inheritance-based models do.
Gratifications of digital media: A demographic view from four countries in south-east Asia

The Gratification Obtained is an essential part of media studies.It analyzes the gratifications obtained by the media users.This paper reveals findings from observations towards the digital media users in four countries in Southeast Asia using 5 key indicators; namely self-expression, learning needs, leisure & entertainment, escape from real life and killing time, with an analysis from the demographic perspective of the respondents including gender, education, country and age.The results of the survey show that gratifications obtained in the digital media in these countries were not correlated with gender and education, but it was different or correlated with country and age of the respondents.
Designing for Serendipity in a University Course Recommendation System.

Collaborative filtering based algorithms, including Recurrent Neural Networks (RNN), tend towards predicting a perpetuation of past observed behavior. In a recommendation context, this can lead to an overly narrow set of suggestions lacking in serendipity and inadvertently placing the user in what is known as a bubble. In this paper, we grapple with the issue of the filter bubble in the context of a course recommendation system in production at a public university. Our approach is to present course results that are novel or unexpected to the student but still relevant to their interests. We build one set of models based on course catalog descriptions (BOW) and another set informed by enrollment histories (course2vec). We compare the performance of these models on off-line validation sets and against the system's existing RNN-based recommendation engine in an online user study of undergraduates (N = 70) who rated their course recommendations along six characteristics related to serendipity. Results of the user study show a dramatic lack of novelty in RNN recommendations and depict the characteristic trade-offs that make serendipity difficult to achieve. While the machine learned course2vec models performed best on off-line validation tasks, it was the simple bag-of-words based recommendations that students rated as more serendipitous. We discuss the role of the kind of information presented by the system in a student's decision to accept a recommendation from either algorithm.
Information System Security of Indonesia Terrestrial Border Control

Today, Information Technology (IT) becomes an integral part of human life. IT boosts every sector, such as infrastructure, economics, agriculture, social, organization, and politics. The institutional systems are developed according to the specific business requirements, processes, flows, and security. Pos Lintas Batas Negara ‘integrated cross-border post’ (PLBN) is a designated authority consisting of the Custom, Immigration, and Quarantine (CIQ). Each section has a different Standard Operation Procedure (SOP). This research aims to develop a secure information system based on Confidentiality, Integrity, and Availability (CIA) concepts. The CIA is embedded in the ISO 27001 and McCumber Cube approach. The research focuses on the Secure Immigration Information System (SIIS). This research is conducted in the Wini immigration office. The researchers observe the immigration activities on the location, interview the immigration officers, and collect information. The researchers produce an effective, efficient, and security application prototype system.
Real-time high-speed 5-D hyperchaotic Lorenz system on FPGA

Chaotic systems have several engineering applications such as cryptology, random number generators, image processing and secure communication. A basic structure used in these studies is a chaotic oscillator design that produces a chaotic signal. In this paper, 5-D hyperchaotic Lorenz system (Hu, 2009) has been implemented on FPGA using Heun algorithm to improve the chaos-based embedded engineering applications. The 32-bit IEEE-754-1985 floating point format has been used in the Heun-based design. The design has been coded in VHDL. The maximum operating frequency of FPGA-based 5-D hyperchaotic Lorenz system reaches 430.146 MHz. In addition, a real circuit realisation of 5-D hyperchaotic Lorenz system has been performed using analogue circuit elements. The results of FPGA-based new 5-D hyperchaotic Lorenz system have been compared with the results of computer-based numerical simulation and then the error analyses (MSE and RMSE) have been carried out.
A Fuzzy Multi-Layer Color QR Code Decoder Algorithm

In this paper, we proposed a multi-layer QR code decoder algorithm to recognize the colour of an extended QR code.The extended QR code enhanced the locator pattern, a component in the QR code to provide more colours.The algorithm starts with the detection of the QR code, followed by selecting colour reference from the extended QR code.Then, dynamic fuzzy sets from colour values are produced for each colour using colour reference from the QR code.QR code colour enhancement is then implemented based on fuzzy set decision.Next is colour de-multiplexing for the enhanced colour QR code, to get monochrome QR code by decoding the extended QR code.We obtain the original file and compare our decoder with existing decoder in terms of the success rate.The experiment shows a success rate of 80% recognition and detection from computer screen, 34% better compared to previous work.Furthermore, 70% recognition and detection is produced from printed paper, 44.27% better compared to previous work.
Perancangan Arsitektur Teknologi Informasi Menggunakan Framework TOGAF Pada Koperasi Budi Karya

This study discusses the design of information technology enterprise architecture in the cooperation of Budi Karya. The main problem encountered is that the management still uses a bookkeeping system. The information obtained in each section has not been integrated with other, the IT management organization structure is not sufficient because there is no staff who have specialized IT experts, and require development in information technology. This was stated in one of the Budi Karya cooperation missions which read "Adopting the development of information technology and modern management systems". This study aims to produce process architecture, data, applications and technology that can be a reference for implementing all activities in cooperation of Budi Karya. This research uses the TOGAF (the Open Group Architecture Framework) which is a framework that has detailed methods and tools for developing and implementing enterprise architecture, with 8 architectural phases of vision, business architecture, information system architecture, technology architecture, opportunities and solutions, migration plan, implementation Governance, and architecture change management. Data collection is done by direct observation interviews and literature studies. The results of all these phases will produce a detailed framework of process architecture, data architecture, application architecture, and architecture in cooperation of Budi Karya&#x0D; Keywords: Enterprise, Architecture, Cooperation, framework, TOGAF
Antyscam – Practical Web Spam Classifier

To avoid of manipulating search engines results by web spam, anti spam system use machine learning techniques to detect spam. However, if the learning set for the system is out of date the quality of classification falls rapidly. We present the web spam recognition system that periodically refreshes the learning set to create an adequate classifier. A new classifier is trained exclusively on data collected during the last period. We have proved that such strategy is better than an incrementation of the learning set. The system solves the starting–up issues of lacks in learning set by minimisation of learning examples and utilization of external data sets. The system was tested on real data from the spam traps and common known web services: Quora, Reddit, and Stack Overflow. The test performed among ten months shows stability of the system and improvement of the results up to 60 percent at the end of the examined period.