Reviewerly/exHarmony huggingface dataset:
AUDIO STEGANOGRAPHY USING LIVE AUDIO STREAM AS COVER WITH DYNAMIC KEY GENERATION

This paper presents a novel approach to audio steganography, by considering stream covers (live audio) as cover.A stream cover is a cover where the sender has no access to the entire sequence of numbers in the embedding process as defined by Stefan et al (2000).The cover utilized to hide secret data(stego) and the original cover should be similar and thereby not raising any suspicion to the intruder.Because of this requirement audio files are well suited cover for embedding the secret information as they are popular among humans.In live audio steganography there is an added advantage as the cover is unique each and every time, as it may be the communication between two individuals just like a casual telephonic talk.The intruder will not have the reference audio to compare perceptual and non-perceptual quality of the audio unlike famous audio files which are publicly available.LSB insertion is a common, simple approach to embedding information in a cover.Unfortunately, this approach is vulnerable to steganalysis.Instead of using every byte, it is possible to select some bytes in a random manner according to a secret key.Sharing of this key is a time-consuming process with the risk of man in the middle attack, hence its proposed in this paper where in the key will be based on the current time.The sender and the receiver will generate the key by considering current time as seed followed by mathematical manipulations by bringing the advantage of randomness without the risk of key sharing.
A Framework for Automated Extraction of Information for Clinical Decision Support from Images of Flow Charts and Decision Trees

Decision trees (DTs) are ubiquitous, indispensable tools for clinicians in a point of care setting, yet little progress has been made in techniques to automatically analyze them. Here we report results from DT-DECON, a general method to extract information and information flow from decision tree images, classify them according to automatically generated, maximally discriminative categories, and index them according to localized information content. Our pipeline uses a combination of feature engineering and machine learning methods to take image files and produce a corresponding directed graph, where nodes correspond to boxes and edges correspond to arrows. This serves as a standardized representation which is readily machine interpretable and can be applied.We develop a methodology to classify constituent nodes in these graphs according to their processual role, and use aggregate semantic categorization for nodes of each type to generate and determine class membership for any given population of decision trees. Relevant subgraphs are then enumerated by considering all possible truncated traversals of a decision tree. These paths are stored in tabular form according to bifurcation results, which facilitates use of traditional indexing procedures to enable return of specifically relevant subtrees. This algorithm is applied to several classic medical texts within the Elsevier corpus and a hand curated corpus of COVID-19 specific decision trees. Several querying methods are demonstrated, including a fuzzy tokenized search, a universal sentence embedding based question relevancy retrieval system, and a chatbot that can navigate decision trees based off user input.
Training Program "Psychology of the Commercial Organization Staff's Attitude Towards Money"

Introduction. Commercial organizations' efficiency can be improved, among other ways, through the formation of staff's harmonious attitude towards money and staff's active participation in the development and implementation of the organization's monetary policies. Aim: to develop the content and design of the training program for the formation of commercial organization staff's harmonious attitude towards money. Methods. The technological approach by L. Karamushka and a number of interactive techniques (unfinished sentences, "brainstorming", small-group work, group discussions, role-playing games, work with Internet resources, psychological workshops, creative homework, etc.) aimed at organizing trainees' joint activities and communication. Results. The author has proposed a 56-hour-long training program "Psychology of the Commercial Organization Staff's Attitude Towards Money", which includes the following five training sessions: "The Concept of Money and Their Role in Commercial Organization Staff's Life", "The Impact of the Commercial Organization Staff's Organizational and Psychological Characteristics on Staffs' Attitudes towards Money", "The Commercial Organizations' Organizational and Psychological Characteristics that Affect Commercial Organization Staff's Attitudes towards Money", "Commercial Organizations' Monetary Policy: it Content and Organizational and Psychological Problems", "The Main Directions of Commercial Organizations' Monetary Policies." Conclusions. The proposed training program can be used for commercial organization staff's psychological training as well as in shaping and pursuing monetary policies of commercial organizations.
Do My Emotions Influence What I Share? Analysing the Effects of Emotions on Privacy Leakage in Twitter

Social media has become an integral part of modern day society. With increasingly digital societies, individuals have become more familiar and comfortable in using Online Social Networks (OSNs) for just about every aspect of their lives. This higher level of comfort leads to users spilling their emotions on OSNs and eventually their private information. In this work, we aim to investigate the relationship between users’ emotions and private information in their tweets. Our research questionis whether users’ emotions, expressed in their tweets, affect their likelihood to reveal their own private information (privacy leakage) in subsequent tweets. In contrast to existing survey based approaches, we use an inductive, data-driven approach to answer our research question. We use state-of-the-art techniques to classify users’ emotions, and privacy scoring and employ a newtechnique involving BERT for binary detection of sensitive data. We use two parallel classification frameworks: one that takes the user’s emotional state into account and the other for the detectionof sensitive data in tweets. Consecutively, we identify individual cases of correlation between the two. We bring the two classifiers together to interpret the changes in both factors over time duringa conversation between individuals. Variations were found with respect to the kinds of private information revealed in different states. Our results show that being in negative emotional states,such as sadness, anger or fear, leads to higher privacy leakage than otherwise.
Sosialisasi Penyajian Dan Pembuatan Laporan Sesuai PSAK 45 Di SDN 11 Lenteng Agung

In order to community service, IBI Kosgoro 1957 seeks to help the problems faced by community groups. This form of community service is socialization of presentation and creation of reports in accordance with PSAK 45 in 2019. The presentation of The Responsibility report or more familiarly known as SPJ / LPJ is generally part of the relevant school financial statements, the presentation of an activity information data that has been carried out, with the reporting of implementation indicators recording every income and financial related expenses sourced from the school's operational assistance fund. As an operator, school or administrative management team on the accountability report, of course it is obligatory to be able to make a report in an accountable and transparent manner. Related to that, the importance of socialization towards the presentation of accountability report refers to psak 45 non-profit institutions that we socialize to assist the treasurer or administrator in carrying out his duties in the school, whether at the elementary, junior high, high school or vocational school level.&#x0D; Keywords: Socialization, Presentation and creation of Report, PSAK 45
Internet Resources Collection and Arrangement

Traditionally, a library is regarded as a place to collect, arrange and distribute information. However, librarians have no choice but to start to emphases the use of internet resources vis-à-vis the rapid growing of Internet and its spreading users. This phenomenon is especially evident in those schools which focus on research teaching, where teachers and students highly require the academic information. These schools always demand the good quality of resources in their libraries. Libraries equipped with internet resources have been set up comprehensively in recent years, users can search for valuable and useful web links from the mainpages of their libraries. Librarians are unlikely to know every subject in every domain, it is therefore a heavy task for them to collect good internet resources, not even mention the relative maintenance and update work. The motivation of the idea that“students collect and make by themselves the top internet resources” is hence come up to my mind.
Verification of Frequently Used Korean Handwritten Characters Through Artificial Intelligence

Handwriting verification is a behavioral biometric that matches handwritten characters to determine whether it is written by the same person. Because each person has a different handwriting, it is used by investigative agencies for the purpose of presenting court evidence. However, it cannot be defined as a rule because the standards for visual reading of experts are ambiguous. In other words, different experts can make different decisions for the same pair. Therefore, we propose a handwriting verification method based on artificial intelligence that excludes human subjectivity. For 4 frequently used Korean characters, genuine or imposter pairs of the same character were trained with a Siamese-based ResNet network. The verification accuracy for the trained model was about 80%. Through this experiment, the objectivity of handwriting biometric through deep learning was confirmed, and a basis for comparison with verification performance through human eyes was prepared.
A Study of Affective Factors that Contribute to Middle School Students’ Use of Spoken English

The purpose of this study is to investigate affective factors that distinguish the high spoken English use group from the low spoken English use group among Korean EFL middle school students. This study focuses on the variables of communication strategy, willingness to communicate, self-concept, motivation, and anxiety. A questionnaire on communication strategy, willingness to communicate, self-concept, motivation, anxiety, and the use of spoken English was designed and administered to 112 students of eighth grade in a province. The findings of the study are as follows: (1) the middle school students’ levels of extrinsic motivation and speaking anxiety were high, while the levels of self-concept, intrinsic motivation, and the use of spoken English were low, (2) the highest positive relationship was found between willingness to communicate (WTC) and the use of spoken English, while the highest negative relationship was observed between speaking anxiety and the use of spoken English, (3) willingness to communicate (WTC), academic self-concept, and communication anxiety were statistically significant factors that distinguished the high spoken English use group from the low spoken English use group. Based on the findings, some suggestions were made in regard to helping students improve their use of spoken English.
A Comparative Analysis of Deadlock Avoidance and Prevention Algorithms for Resource Provisioning in Distributed MEC

The decentralised and collaborative nature of MultiAccess Edge Computing (MEC) contributes in achieving a lowerend to end latency. However, MEC nodes are prone to adeadlock due to the limited amount of available computationalresources. It is extremely important to eradicate deadlock from the MEC to meet the network latency requirements and maintain a reliable MEC system. This can be achieved by employing an adequate deadlock strategy. In this context, deadlock prevention and deadlock avoidance are the two principal strategies to handle deadlock. Deadlock prevention detects and recovers the system. However, deadlock avoidance eradicates the problem from the system. In this paper, a deadlock-aware collaborative edge decision algorithm has been proposed to eradicate deadlock and maintain network reliability in MEC systems. Additionally, deadlock avoidance and prevention schemes have been evaluated using Bankers resource request avoidance algorithm, wound wait algorithm and wait-die algorithms for resource provisioning incollaborative MEC. Furthermore, the effectiveness of deadlockavoidance and prevention algorithms in real-time scenarios has been analysed in MEC systems. The metrics used in this paper for comparison includes Round-trip time, Queue waiting time and CPU utilization.
GP with Image-Related Operators for Feature Learning

Many image-related operators, including image descriptors, filtering operators and pooling operators, can be employed as functions in GP to achieve effective feature learning. However, this has not been extensively investigated in GP due to the limitations of the current GP representations. This chapter proposes a new GP-based approach with a flexible program structure and a number of image-related operators for feature learning in image classification. In this new approach, a new program structure, a new function set with many image-related operators, a new terminal set are developed. The performance of the proposed approach is examined on 12 benchmark datasets, including seven datasets with a large number of instances, and compared with a large number of effective algorithms. An in-depth analysis is conducted to deeply analyse the proposed approach to understand why it can achieve good performance.
Problems and Improvement Measures of Online Teaching in Post-Epidemic Period

In the spring of 2020, teaching is all transferred online. Schools at all levels have done a lot of training and platform experiments. At that time, we didnâ€™t consider too much but hope to smoothly progress online teaching. Now that online teaching has been completed for a semester, it is time to reflect on existing problems and study improvement measures. Based on the teaching experience, we put forward the shortcomings from three aspects: content, form and effect, and give improvement measures according to the first-line teaching experience.
A Study on Privacy Issues and Solutions of Public Data in Education

With the development of information and communication technology, various data have appeared and are being distributed. The use of various data has contributed to the enrichment and convenience of our lives. Data in the public areas is also growing in volume and being actively used. Public data in the field of education are also used in various ways. As the distribution and use of public data has increased, advantages and disadvantages have started to emerge. Among the various disadvantages, the privacy problem is a representative one. In this study, we deal with the privacy issues of public data in education. First, we introduce the privacy issues of public data in the education field and suggest various solutions. The various solutions include the expansion of privacy education opportunities, the need for a new privacy protection model, the provision of a training opportunity for privacy protection for teachers and administrators, and the development of a real-time privacy infringement diagnosis tool.
Comparison of the Effectiveness Between Pop-Up Book and Poster as a Media Towards Oral Health Knowledge of 5<sup>th</sup> Grader Students of Elementary School 20 Banda Aceh

Oral health is an integral part of overall health which influences one's quality of life.Oral health problem in children occurs due to lack of oral health maintenance.Dental health education needs props, the use of props in changing children's behaviour is very important.The purpose of this study is to identify the effectiveness of pop-up book and poster towards oral health knowledge.This study is a quasi-experimental design, using pre-test and post-test.The population of this study is 5 th grader students of elementary school 20 Banda Aceh which is 70 students in total devided into 2 groups, each group consists of 35 students.Sampling technique used was total sampling which was divided into two groups, pop-up book group and poster group.Students' knowledge score before and after dental health education was measured by questionnaire.The data obtained was analysed using t-test.The result of the study showed that there were significant increased scores in both media (p<0,05), followed by t-test to compare pop-up book and poster media.The result showed that there were significant increased score in pop-up book media.The conclusion of this study is dental health education using pop-up book as a media is more effective compared to posters in increasing oral health knowledge of 5 th grader students of elementary school 20 Banda Aceh.
VR and AR Technology on Cultural Communication

The theme of this platform is built around “the road of Hess”, which was initiated in the modern maritime Silk Road capital-Quanzhou, as the core of design and programming. The history of Silk Road will be presented with panorama technology, which is one of the network multimedia technology. In the form of Web APP, the real records and spread of the humanities and scenic sites of Quanzhou will be showed in 720° perspective. An immersive experience of 3D live virtual can be expected. The aim of this study is to simulate and realize the all-around real scene. In the paper, the tasks of the VR panorama fused construction include image acquisition, image registration, image smoothing, image modification by the algorithm and mathematical theory behind splicing fusion, the panoramic camera category and projection model, panoramic transformation and collection principle, the image registration of feature point and transform frequency domain. The product positioning of “maritime silk route culture” will be presented by 18 selected spots in Quanzhou. The study, with an overall design and an organization of connecting different scenes, is for the virtual scene roaming system, which is based on image.
Temporal Hints in 3D Hand Pose Estimation

Due to severe self-occlusions and complex articulated pose in hand motion, 3D hand pose estimation remains a challenging task. Most of the state-of-the-art approaches focus on how to extract spatial information effectively around the hand while ignoring the temporal consistency of hand motion, which may give hints on the locations of the occluded joints in the current frame. Inspired by solutions in action recognition, we propose to use temporal information to alleviate hand pose estimation. Specifically, we use a temporal branch to efficiently extract the temporal information of continuous image frames with negligible computational costs through convolution. By combining spatial information, our network can output more accurate hand pose estimation results. We conduct experiments on datasets with consecutive frames. Compared with methods that only use spatial information, our network achieves lower prediction errors. The experimental results also confirm our idea that the temporal information of hand motion is helpful for hand pose estimation.
A Gradient-based Kernel Approach for Efficient Network Architecture Search

It is widely accepted that vanishing and exploding gradient values are the main reason behind the difficulty of deep network training. In this work, we take a further step to understand the optimization of deep networks and find that both gradient correlations and gradient values have strong impacts on model training. Inspired by our new finding, we explore a simple yet effective network architecture search (NAS) approach that leverages gradient correlation and gradient values to find well-performing architectures. To be specific, we first formulate these two terms into a unified gradient-based kernel and then select architectures with the largest kernels at initialization as the final networks. The new approach replaces the expensive ``train-then-test'' evaluation paradigm with a new lightweight function according to the gradient-based kernel at initialization. Experiments show that our approach achieves competitive results with orders of magnitude faster than ``train-then-test'' paradigms on image classification tasks. Furthermore, the extremely low search cost enables its wide applications. It also obtains performance improvements on two text classification tasks.
Implementation of the pedagogical experiment on the issues of formation of the readiness of teachers of natural specialties to the development of entrepreneurial enterprise

Institutions of postgraduate pedagogical education provide the formation of readiness of teachers, including natural sciences, to develop entrepreneurial competence of high school students, which became the basis of experimental pedagogical research.The author defines the task: to identify the conceptual principles of the organization of experimental and pedagogical research to determine the readiness of teachers of natural specialties to develop entrepreneurial competence of high school students; to characterize the stages of implementation and analyze the methodological tools of pedagogical experiment.Experimental pedagogical research "Formation of readiness of teachers of natural specialties in the system of postgraduate pedagogical education for the development of entrepreneurial competence of high school students" involves establishing patterns of professional growth of teachers and identifying their readiness to implement entrepreneurial competence in practice.This pedagogical experiment was implemented from August 2015 to June 2019 and included the following stages: ascertaining, formative and generalizing.Based on the theoretical research, we have developed the stages, content and methods of experimental work performed within the dissertation research.The results of the pedagogical experiment testify to the positive dynamics of the formation of the readiness of teachers of natural specialties of experimental groups for the development of entrepreneurial competence of high school students in the system of postgraduate pedagogical education.
Audio Codec Using Legendre Functions for Simplified Digital Telephony

Speech signal is based on the more complex anatomy of the mouth, throat, and nasal bone.Such speech signals are controlled by digital signal processing for encoding and by compressing the same speech.Many speech signal processing methods and standards have been developed by many researchers for audio codec's such as CELP.Advanced mathematical transformations such as Fourier, Lagrange, Hamilton, Legendre were developed for such applications.Signal processing using its equations through certain algorithms and methods to develop signals for various novel applications.Based on laryngeal pulses and oral cavity filter patterns, these techniques can be used to encode speech patterns more efficiently without losing signal clarity.In this paper a novel method of encoding speech with much simpler computations has been evolved.The famous spherical harmonic Legendre polynomials have been the key to the technique.Good compression, decent sound quality and above all, simplicity are the claimed advantages of the method.A new approach, using the spherical harmonic oscillator functions of Legendre is introduced here for this application.Thus, this paper describes this alternate scheme for speech compression and coding.Its usefulness lies in the simplicity relative to the more involved CELP techniques currently in use.
Embodied narratives : Embodied experiences as a call for action

Things, spaces and people collaborate in order to create an immersive experience. This project investigates this collaboration in order to combine them for an embodied way of tell and perceive stor ...