Reviewerly/exHarmony huggingface dataset:
Wavelet method of hiding text information in audio signals

Abstract In the last few years, in connection with the widespread use of media networks for transmitting multimedia information, it is important to build stegosystems on their basis. The least significant bits for embedding a message can turn out to be ineffective using traditional methods of modification and steganography methods, allowing to embed messages in areas that cannot be significantly distorted during processing by modern encoders, are especially important. One of the tools that allows this embedding is a discrete wavelet transform. Wavelet transform is a relatively new and powerful analysis and processing tool. The method of secret transmission of a text message by hiding in sound files and subsequent recovery without loss is considered in this article. The basic of method is a discrete wavelet transform on biorthogonal wavelets. A web application implementing this method has developed. The implementation language is Python.
Rainfall Trend Analysis by Mann-Kendall Test: A Case Study of Andong Dam Basin

강우량은 홍수 예방 및 가뭄 관리를 비롯한 수자원의 효과적인 관리를 위해 무엇보다 중요하다. 더욱이 기후변화의 영향으로 장래 수자원의 변동은 인간 생활에 매우 심각한 영향을 미칠 것으로예측되고 있다. 본 연구에서는 안동댐 유역에 대한 42년간(1977~2018년)의 연강우량, 월강우량 및월 최대강우량에 대한 경향분석을 실시하였다. 통계방법에는 모수적 검정과 비모수적 검정이 있다. 강우량과 같이 특정 확률분포를 따른다고 전제할 수 없는 경우 비모수적 검정을 사용한다. 따라서본 연구에서는 비모수적 방법 중 강우량 추세분석을 위해 널리 사용되는 Mann-Kendall 검정 방법을사용하였다. Mann-Kendall 검정 결과 유의수준 5%(0.05) 이내로 10월강우량과 7월 최대강우량은 증가경향이 확인되었다. 또한 유의수준 10% 이내에서 8월 최대강우량은 감소하는 것으로 분석되었다. 본 연구의 결과는 특정 유역에서 발생하는 물부족과 홍수관리를 비롯한 수자원관리의 장기적 계획을 수립하고자 할 때 매우 유용할 것으로 생각된다.Rainfall has become a primary concern for flood control and effective water resources management. It is predicted that the reduction of available water resources due to climate change will exert a severe influence on human life. This study conducted a trend analysis on the annual rainfall, monthly rainfall, and monthly maximum rainfall at Andong Dam basin for 42 years from 1977 to 2018. Statistical hypothesis tests were performed by a nonparametric test because the rainfall data do not follow a particular probability distribution. This study utilized the Mann-Kendall test, one of the commonly used nonparametric testing methods, in order to analyze the rainfall trend variations. It is confirmed that the October rainfall and July maximum rainfall show an increasing trend according to the 5% confidence level. In addition, the August maximum rainfall reveals a decreasing trend according to the 10% confidence level.
Augmented Reality Image Generation with Optical Consistency using Generative Adversarial Networks

Various methods are used for estimating light source informations from real objects to achieve optical consistency in augmented reality (AR), but in practice, there are difficulties in using real objects. We propose a method of achieving optical consistency without estimating the light source information, using generative adversarial networks (GANs) that input AR images without optical consistency and mask image. The generated AR images from our proposed method show the appropriate expression of drop shadows and reflections of surrounding objects.
[Development and Testing of Multi-mode Elbow Joint Muscle Strength Training Device].

Muscle strength training plays an important role in improving limb movement function, preventing muscle atrophy and promoting muscle function recovery in patients with various bone and joint diseases. The sports function of elbow joint is closely related to people's daily life activity ability. At present, Chinese muscle strength training devices are depended on import. Therefore, it is of great significance to develop muscle strength training devices. Based on the concepts and characteristics of isometric training, isotonic training, passive training and isokinetic training, in the upper computer, the servo driver and servo motor are controlled through the LabView interface, and the real-time torque is detected by the torque sensor, realizing four training modes. The main parameters of the multi-mode elbow joint muscle strength training device meet the requirements, and the trainers have a good experience.
Design and Implementation of River Data Acquisition and Storage System Based on Cloud Platform

Abstract In view of the huge geospatial information data in the Yangtze River Basin, messy data storage and difficulty in searching, a cloud platform for river scientific research was established based on Browser/Server Architecture. The system design comprehensively considers and balances the advancement and maturity, enabling the system to mass-store and manage data from various units or departments, multiple types and multiple channels, and to provide advanced data management methods to ensure data security and data unified management, thus providing researchers with fast and reliable data information. The system realizes a set of standards, a map, a library and a platform for the whole basin, which is of great significance to the standardized management and application of data in the Yangtze River Basin.
A PROFICIENT IDENTITY BASED SIGNATURE SCHEME WITH DESIGNATED VERIFIER FOR E-VOTING

A democratic system cannot be complete without adding the key feature of Voting in it. There are two ways to execute the voting process. One is physical voting system and the other one is electronic voting or e-voting system. Our study has been done in the context of e-voting system. In our paper, we have studied the identity (ID) based signature scheme with designated verifier to construct an e-voting system much trustworthy by the side of the voter. In this scheme, not only the voter can authenticate that whether her/his vote is casted or not but he/she can also validate it by using facility of receipt generation. This scheme also protects the privacy of casted vote. We have achieved this by proposing a proficient Identity Based signature scheme with designated verifier for receipt generation in e-voting.
A MapReduce Framework for Detection of Tandem Repeats in DNA Sequences

DNA data produced by highly parallel next generation sequencing technologies entering into the field of bioinformatics as a flood, but traditional single processor based tandem repeat computing methods are not able to keep that pace.Microsatellite, also named as simple sequence repeats(SSR) with size 1-6 bp, are tandem repeats in DNA data is a sequence of two or more contiguous copies of same nucleotide sequence.These are playing very important roles in the fields of genetic diversity, forensic applications, genetic markers, mapping studies of human genome, and in disease diagnosis.There are many tools exist to detect these repeats, most of them were implemented around many assumed constraints, implemented on available hardware to minimise execution time; Existing tools possess different kind of advantages and disadvantages with each other.Hence a tool with exhaustive search for all tandem repeats is required.We proposed an efficient and constraint free Hadoop MapReduce based approach for detecting tandem repeats.It works in parallel and takes functional advantages of key -value based implantations.It displays one kind of repeat and all its occurrence in entire file a once, consolidates all kinds of repeats.Our experimental results are more readable, easily interpretable.It shows that the proposed approach more efficient with respect to increased data size when other tools have limitations.
Effect of Single Particle-Particle Interface on Photoelectrodes Performance

Light-to-energy conversion is an encouraging approach to overcome the energy crisis and generate clean fuels (e.g., hydrogen) and electricity. Photoelectrochemical cells (PECs) and photovoltaics (PVs) are two main technologies that have been used extensively for such conversion. PECs and PVs are consisting of a semiconducting electrode as light absorber materials. Traditionally, PECs and PVs are fabricated by accumulating a film of nanostructured semiconductors in which, the photogenerated charge carrier (e.g., electrons) has to pass through several nanostructures’ interfaces. We designed a sophisticated photoelectrochemical cell setup and used a focused laser beam ( i.e. , ~400 nm) to locally generate charge carriers at different location, i.e., before and after particle-particle interface. Our sub-particle, single-interface photocurrent measurements revealed that indeed there is a noticeable photocurrent drop per interface. Thus, such quantitative metric should be considered for surface and interface engineering of photoelectrode in PECs and PVs.
Penerapan Algoritma RC6 dan Algoritma Elias Delta Code Pada Aplikasi Pengamanan dan Kompresi Short Message Service (SMS) Berbasis Android

In this study software was developed that could be useful to improve the security of messages that occur in communication via SMS. SMS is a service provided by cellular phones to its users to communicate through sending short messages at a low cost. SMS is very popular, aside from being cheap, messages sent can be received by the recipient well and quickly. With this compression and security, the SMS was successfully sent and secured with smaller bits than the previous SMS. The results of compression and security using the Elias Delta Code Algorithm and RC6 Algorithm the appearance of characters or symbols that will arrive at numbers that can only be used with Android
Assessing the stability of selected software components for reusability

The need to develop software of great quality with timely delivery and tested components gave birth to reuse. Component reusability entails the use (re-use) of existing artifacts to improve the quality and functionalities of software. Many researches have considered and justified common reusability factors such as customizability, portability, interface complexities, understandability/Documentability etc. but with limited works on stability as a factor. The need to experiment stability (in the context of volatility) as a factor for determining component reusability, is an attempt to lend our voice to the domain of component reusability. This study introduces and justifies stability, in the context of volatility of software component, as a factor that determines the reusability of software components. As part of the study’s methodology, sixty-nine (69) software components were collected from third party, and data extracted from their features were used to compute the metric values of stability. The experimented conducted proved the stability status of the various component types considered.
The Relationships between the P.E. Class Satisfaction and the Learning Environment among High School Students in Henan Province in China

The purpose of the study is to find out relationship between P.E. course learning environment and Class satisfaction of high school students in Henan province, China.BR In order to achieve the goal, conducted random sampling to select the high school, and used convenience sampling to distribute the questionnaires. total of 1,400 questionnaires used for analysis. Based on the collected data, Win SAS Ver.9.2 was applied for analysis with frequency analysis, confirmatory analysis, construct validity, correlation analysis and multiple linear regression analysis. The results of this study can be summarized as follows:BR First, sub-variables of learning environment, perceived challenge, perceived risk, perceived competition and perceived control, have positive influence on mastery experience. sub-variables of class satisfaction; cognitive development had positive relationship with perceived challenge, perceived risk, perceived competition, and normative success had positive relation to perceived challenge, perceived risks, perceived competition. Interaction with others positively influenced on perceived risk and perceived competition. Health and enjoyment factor had significant influence on perceived risks, perceived competition and perceived control. And enjoyment and relaxation significantly influenced on perceived risks, perceived competition and perceived control.
Towards Preserving the Ephemeral: Texture-Based Background Modelling for Capturing Back-of-the-Napkin Notes

A back-of-the-napkin idea is typically created on the spur of the moment and captured via a few hand-sketched notes on whatever material is available, which often happens to be an actual paper napkin. This paper explores the preservation of such back-of-the-napkin ideas. Hand-sketched notes, reflecting those flashes of inspiration, are not limited to text; they can also include drawings and graphics. Napkin backgrounds typically exhibit diverse textural and colour motifs/patterns that may have high visual saliency from a low-level vision standpoint. We thus frame the extraction of hand-sketched notes as a background modelling and removal task. We propose a novel document background model based on texture mixtures constructed from the document itself via texture synthesis, which allows us to identify background pixels and extract hand-sketched data as foreground elements. Experiments on a novel napkin image dataset yield excellent results and showcase the robustness of our method with respect to the napkin contents. A texture-based background modelling approach, such as ours, is generic enough to cope with any type of hand-sketched notes.
Statistical modelling of experts’ perceptions of the ease of signature simulation

The perceived complexity of handwriting traces by forensic experts is a critical element in the process by which opinions regarding the authorship of handwriting are formed. Variations in experts’ perceptions of how complex an image is can significantly impact on the appropriate administration of social justice . There currently exists no test which is available in forensic science which provides a guide for the expert. This study used discriminate function analysis to construct a model which can be used for such a test. The model is based on 13 government forensic experts’ perceptions of how easy or difficult it would be to successfully simulate each of 300 signatures. The variables used by the model to classify these signatures into three complexity groupings were ‘number of turning points’ and ‘number of intersections and retraces’. The test was validated by comparing the model’s calculation of complexity grouping versus fourteen forensic experts’ groupings of an additional 197 signatures. Although substantial variation was found between the experts’ perceptions overall, up to 72.9 % of their perceptions of complexity could be predicted by the model. Misclassification rates were found to be highest when discriminating between signatures where a qualified opinion in the direction of identification would be expressed versus those where a full opinion would be expressed. There was no misclassification associated with signatures where a full opinion would be expressed versus those for which no opinion would be expressed. This test can now be trialed in routine forensic casework and should provide forensic experts with a guide to signature complexity. Research should now be focused on validating the expert perceptions outlined in this paper. Purchase Article - $10
The impact of online games on language aggression behavior of adolescents in warnet

This study aimed to determine the impact of online games on language aggression behaviors in adolescents at an internet cafe, using observation of four internet cafes in South Tangerang. The results indicated the main languages and dirty words that are used and appear as mockeries among internet cafe users, including “monkey,” “dog,” “pig,” “turmeric,” and others. This demonstration is known to highly influence the development of adolescent language at school and at home, as it promotes the habit of directing dirty and unethical words both to fellow friends and older people if these characteristics are left unchecked. Thus the family, especially the parents, has a major role to play, through control attempts, while the school as an educational institution should assist the community to instill character and morals in society.
A COMPARATIVE STUDY OF THE STUDENTS’ INTERESTS OF INTERMEDIATE CHINESE COMPREHENSIVE TEXTBOOKS (Study Case of “Meili Hanyu Comprehensive Volume III” and “Developing Chinese Intermediate Comprehensive Course Volume I”)

This article compares “Meili Comprehensive Volume III” with the “Developing Chinese Intermediate Comprehensive Course Volume I”. The subjects of this research were the students of 2-1 classes and 2-2 classes of the short course of Guangxi Normal University. The purpose of this research is to understand students' interest in textbook topics and to know which topics are more interesting to students. The result of this research show that the topic of  Hanyu is rich and attractive, but this set of textbooks is more suitable for students studying in Guilin, because its content is relatively strong for Guilin. It may not be suitable for students outside Guilin. The topic of Meili Hanyu is much more difficult than Developing Chinese. In addition, the intermediate students of Guangxi Normal University are interested in the topic of “Meili Hanyu”, especially about love and family.
Detecting breast cancer using Neural Networks

The goal of this paper is to detect the breast cancer using neural networks. Image processing techniques play an important role in the diagnostics and detection of diseases and monitoring the patients having these diseases. Breast Cancer detection of medical images is one of the most important elements of this field. Because of low contrast and ambiguous the structure of the tumor cells in breast images, it is still a challenging task to automatically segment the breast tumors. Our method presents an innovative approach to the diagnosis of breast tumor incorporates with some noise removal functions, followed by improvement features and gain better characteristics of medical images for a right diagnosis using balance contrast enhancement techniques (BCET). The results of second stage is subjected to image segmentation using Fuzzy c-Means (FCM) clustering method and Thresholding method to segment the out boundaries of the breast and to locate the Breast Tumor boundaries (shape, area, spatial sizes, etc.) in the images. The third stage feature extraction using Discrete Wavelet Transform (DWT). Finally the artificial neural network will be used to classify the stage of Breast Tumor that is benign, malignant or normal. The early detection of Breast tumor will improves the chances of survival for the patient. Probabilistic Neural Network (PNN) with radial basis function will be employed to implement an automated breast tumor classification.
Research on Design of BLM System

The BLM (Building Lifecycle Management) system owns characteristics of building information integration and whole process management, which is able to effectively improve the deficiencies of traditional building information management methods, thus avoiding the problems of information gaps and information islands in the communication among different project participants. Following the guidance of the BLM concept, this paper proposes architecture of the BLM system, and completes the development of the prototype system by integrating related technologies including ASP.NET, AJAX and WebGL. The main function modules are all described in details in the paper. The proposal and development of the system is aiming at solving the problems of information management and information sharing in the construction project, and providing ideas and methods for reference in following research and practice of BLM.
Ha Dou Ken Music: Mapping a joysticks as a musical controller

The structure of a digital musical instrument (DMI) can be splitted up in three parts: interface, mapping and synthesizer. For DMI’s, in which sound synthesis is done via software, the interaction interface serves to capture the performer’s gestures, which can be mapped under various techniques to different sounds. In this work, we bring videogame controls as an interface for musical interaction. Due to its great presence in popular culture and its ease of access, even people who are not in the habit of playing electronic games possibly interacted with this kind of interface once in a lifetime. Thus, gestures like pressing a sequence of buttons, pressing them simultaneously or sliding your fingers through the control can be mapped for musical creation. This work aims the elaboration of a strategy in which several gestures captured by the interface can influence one or several parameters of the sound synthesis, making a mapping denominated many to many. Buttons combinations used to perform game actions that are common in fighting games, like Street Fighter, were mapped to the synthesizer to create a music. Experiments show that this mapping is capable of influencing the musical expression of a DMI making it closer to an acoustic instrument.
Automated Elbow Point Extraction and Upper Arm Length Estimation from 3D Human Body using Neural Network

Elbow point is a very important landmark for body measurement and certain garments. However, little attention has been invested. It is rather difficult to extract the elbow point based on the commonly used geometric methods since 1) the arm and elbow have high degrees of freedom, and 2) there is no prominent feature when the arm is unbent. In this paper, we use human stature, one of the most accessible measurement, to estimate the elbow point for arbitrary arm poses. Specifically, we first train two end-to-end neural networks for males and females to estimate the Euclidean length of the upper arm, and then propose a framework to approximate the elbow point and to calculate the tape measurement of the upper arm. Experimental results have verified that our method is efficient for clothing applications. The mean squared errors for male network and female network on the test dataset are 3.23 and 2.69, respectively. Both the absolute errors for the tape measurement of the upper arm for males and females are less than 1 cm.
(Invited) Binary Stochastic Neurons and Compound Synapses from Nano-Magnets

In this presentation I will introduce the nCORE center CAPSL’s activities towards a probabilistic spin logic for Boolean and Non-Boolean computing. While magnetic materials in storage devices are part of our electronic world since many decades and are explored more recently by the semiconductor industry for memory applications such as Spin-transfer torque magnetic random-access memory (STT-RAM), spin based devices for logic applications are still in their infancies. Mimicking a CMOS type logic with magnets requires a “ Write ” and a “ Read ” unit as well as proper input/output isolation. Based on this, a device concept in which charge-to-spin conversion occurs through the Giant Spin Hall Effect (GSHE) [1], dipolar coupling mediates the information transfer from a magnet in the Write unit to another one in the Read unit, and a magnetic tunnel junction (MTJ) is used as the Read unit was proposed in 2012 under the name charge spin logic (CSL) [2]. Next, I will explain in how far the use of low-barrier magnets cannot only help to reduce power consumption of CSL devices but introduces a conceptually new way of computing through the introduction of “tunable randomness”. This idea, that is also known as probabilistic spin logic (PSL), was introduced in 2017 [3] and uses a counterintuitive aspect of magnets, namely their capability of creating a truly random magnetic signal if low-barrier circular nano-magnets are used. In particular, I will connect PSL with activities in the realm of quantum computing as well as neural networks. [1] L. Liu, C.-F. Pai, Y. Li, H. W. Tseng, D. C. Ralph, and R. a. Buhrman, Science 336 , 555 (2012). [2] S. Datta, S. Salahuddin, and B. Behin-Aein, Applied Physics Letters 101 , 252411 (2012). [3] K. Y. Camsari, R. Faria, B. Sutton and S. Datta. Physical Review X 7 , 031014 (2017).