Reviewerly/exHarmony huggingface dataset:
Digital Audio Watermarking: An Overview

Abstract A real watermarking procedure is required for copyright security and confirmation of protected innovation. This work recommends an advanced watermarking procedure which makes utilization of concurrent recurrence veiling to conceal the watermark data. The calculation is grounded on Psychoacoustic auditory model and Spread spectrum hypothesis. It creates a watermark sign utilizing spread range hypothesis and implants it into the sign by measuring the covering edge utilizing modified Psychoacoustic auditory model. The contrast between the first and the watermarked duplicate is intangible as the watermark is formed to lie beneath the veiling edge. Recuperation of the watermark is performed without the learning of the first flag. Keywords: Watermarking, Psychoacoustic auditory model, copyright security
Simultaneous description of logical design and implementation of automated driving systems.

As represented by automated driving systems, the complexity of in-vehicle systems is rapidly increasing. The process related to the design, implementation, and validation of the system has become complicated. To reduce this complexity, a function description method suitable for the development of an automated driving system and an interpreter for directly executing this function description in software are proposed. To describe the function logically and strictly, the description sentence is based on an ontology model for traffic context. The description is also based on one-time predicate logic to enable verification by a theorem prover. By using this method, the behaviors of the automated driving system are directory linked with the description of the function definition.
College English Writing Instruction in the Big Data Era - From the Process Approach Perspective

In this study an online writing platform has been built based on the new information technology of the big data era. The aim of the current study is to explore how and when the platform may affect students’ writing performance. A total of 82 students participated in this study and they were divided into the experimental group (n=40) and the control group (n=42). The pre-test scores indicated that the two groups were in the same level with respect to the EFL writing. Although both group students were taught in a process approach method, only the experimental group was allowed to use the online platform. According to the post-test, both group students had increasingly improved their writing competence by immersing in the writing-process approach, but the experimental group of students performed significantly better than their peers. Combining the data from three sources (timed essay tests, attitude questionnaire and student interview), it can be concluded that the online platform positively influences students’ pre-writing and post-writing performance but is less influential on them during the writing stage.
Double Channel 3D Convolutional Neural Network for Exam Scene Classification of Invigilation Videos

This paper presents a double channel 3D convolution neural network to classify the exam scenes of invigilation videos. The first channel is based on the C3D convolution neural network, which is the status-of-arts method of the video scene classification. The structure of this channel is redesigned for classifying the exam-room scenes of invigilation videos. Another channel is based on the two-stream convolution neural network using the optical flow graph sequence as its input. This channel uses the data from the optical flow of video to improve the performance of the video scene classification. The formed double channel 3D convolution neural network has appropriate size of convolution kernel and pooling kernel design. Experiments show that the proposed neural network can classify the exam-room scenes of invigilation videos faster and more accurately than the existing methods.
PENGEMBANGAN MEDIA PEMBELAJARAN SPARKOL VIDEOSCRIBE BERBASIS BLOG MATERI MENULIS PUISI PADA SISWA KELAS X IPS-A DI MA AL-ANWAR DIWEK JOMBANG

This research is motivated by the increasingly rapid technological advances in the world of education and the widespread use of social media among adolescents. In addition, there is no media in the form of blog-based videoscribe that is used to support Indonesian language learning especially poetry writing material. This study aims to explain the process of developing, quality and implementation of blog-based videoscribe media. Research the type of research and development uses Sadiman's model which has seven steps in the development procedure, namely identification of student needs, formulation of instructional goals, formulation of material points, formulation of measuring instruments for success, writing media scripts, validating and revising, conducting trials and revision. Based on the validation process, blog-based video subscription media obtained an overall average yield of 82.6% with very valid qualifications. The results of validation by media experts obtained a value of 72.15% with valid qualifications, while from material experts obtained a value of 88% with very valid qualifications. Indonesian linguists1 scored 80% with valid qualifications, while Indonesian linguists2 scored 84% with highly valid qualifications. The results of validation by IT experts (graphic design) obtained 92% results with very valid qualifications and blogger experts obtained 80% results with valid qualifications. Based on the results of field trials there are significant differences. This was evidenced by the pre-test and post-test values that showed X2 results more than X1 (80.2 ≥ 73.3). So, blog-based video subscription learning media has been proven to significantly improve Indonesian language learning especially for poetry writing material.
Research on Cultural Inheritance Teaching of Environmental Protection Lamp Design in Han Dynasty Based on Virtual Reality Technology

Based on the influence of virtual reality technology on teaching research and the new challenge of teaching research to virtual reality technology, this paper uses Maya, Rhino, PROE, 3D MAX, Unity3D and other high-precision software to realize the virtual restoration of historical relics through the case study of environmental protection copper lamps unearthed in Han Dynasty in China. The related parameters of Han Dynasty environmental protection lamp in the process of virtual reduction are analyzed and the simulation experiment is carried out. By consulting the relevant data of environmental protection lamps and lanterns in Han Dynasty in China, this paper makes a detailed study on the pattern, material, color and modeling of cultural relics, and then through the practical course operation of VR end and Web end, completely reduces the shape of the utensils and carries on the virtual modeling and the actual exercise display. Through the virtual simulation experiment teaching project of environmental protection lamp design in Han Dynasty in China, on the one hand, immersive VR virtual simulation experiment teaching can truly experience the excellent traditional cultural design works of China, which is conducive to carrying forward cultural confidence and transforming this kind of national pride into the motive force of learning. On the other hand, through immersive VR virtual simulation, we can experience the process of immersive cultural relics restoration, and deeply understand the design of its environmental protection structure. This experiential learning style can trigger learners to establish a more intuitive artistic feeling and integrate design concepts into their own design works, which is one of the effective ways to assist learning by means of science and technology.
Finding Command Injection Vulnerabilities

A server that is running an application can be compromised using arbitrary operating system (OS) commands if there are certain types of web security vulnerabilities. These commands compromise the application and all its data. Not only that, an attacker can take advantage of OS command injection vulnerabilities to compromise other parts of the hosting infrastructure and finally, attack other applications related to the compromised one.
PENDETEKSIAN CITRA DAUN TANAMAN MENGGUNAKAN METODE BOX COUNTING

Different types of plants make identification difficult. Therefore, we need a system that can identify the similarity of the leaves based on a reference leaf. Extraction can be done by taking one part of the plant and the most easily obtained part is the leaf part. Natural objects such as leaves have irregular shapes and are difficult to measure, but this can be overcome by using fractal dimensions. In this research, image detection of plant leaves will be carried out using the box counting method. The box counting method is a method of calculating fractal dimensions by dividing images into small boxes in various sizes. Image detection using fractal dimension values, we know which leaves the match with the reference. In this study,10 species of leave were tested, with each species 10 samples of plant leaves. Image testing of plant leaves uses a variety of r box size, namely 1/2 ,1/4 , 1/8 , 1/16 ,1/32 , 1/64 , 128which obtain an average match accuracy of 44%. Keywords: Box Counting, Fractal dimension
ANALISIS DAN PERANCANGAN SISTEM INFORMASI PENJUALAN ONLINE PADA PO SUCCESFULL GARDEN

PO Succesfull Garden is an individual company engaged in selling bicycle’s stuff such as bicycles, bicycle spareparts and bicycle accessories. PO Succesfull Garden is located on Makrampai Street number 04 inTebas District, Sambas Regency, West Borneo. With the rapid development of information technology and fierce business competition, make PO Succesfull Gardenutilizing information technology specifically internet in interacting with consumers without being separated  by time and space. PO Succesfull Garden in order to serve consumers within a wider range and increase the number of sales transactions, e-commerce becomes the preferred service chosen by PO Succesfull Garden along with the development of information technology. In designing the research, the author uses descriptive research design. While the data collection method used were interviews, observation and literature study. Systems analysis techniques used by the author is UML (Unified Modeling Language). Application design techniques used by the authors are text editor sublime text 3 and database design using MySQL 5.6. In conclusion, this proposed system can reach a wider market, so it is expected to increase the sale of PO Succesfull Garden. Keywords: Analysis, Design, Information System, E-commerce
Pano: Optimizing 360{\deg} Video Streaming with a Better Understanding of Quality Perception

Streaming 360° videos requires more bandwidth than non-360° videos. This is because current solutions assume that users perceive the quality of 360° videos in the same way they perceive the quality of non-360° videos. This means the bandwidth demand must be proportional to the size of the user's field of view. However, we found several qualitydetermining factors unique to 360°videos, which can help reduce the bandwidth demand. They include the moving speed of a user's viewpoint (center of the user's field of view), the recent change of video luminance, and the difference in depth-of-fields of visual objects around the viewpoint. This paper presents Pano, a 360° video streaming system that leverages the 360° video-specific factors. We make three contributions. (1) We build a new quality model for 360° videos that captures the impact of the 360° video-specific factors. (2) Pano proposes a variable-sized tiling scheme in order to strike a balance between the perceived quality and video encoding efficiency. (3) Pano proposes a new qualityadaptation logic that maximizes 360° video user-perceived quality and is readily deployable. Our evaluation (based on user study and trace analysis) shows that compared with state-of-the-art techniques, Pano can save 41-46% bandwidth without any drop in the perceived quality, or it can raise the perceived quality (user rating) by 25%-142% without using more bandwidth.
Generation of Natural Traffic Sign Images Using Domain Translation with Cycle-Consistent Generative Adversarial Networks.

Video-based traffic sign recognition poses a highly challenging problem due to the significant number of possible classes and large variances of recording conditions in natural environments. Gathering an appropriate amount of data to solve this task with machine learning techniques remains an overall issue. In this study, we assess the suitability of automatically generated traffic sign images for training corresponding image classifiers. To this end, we adapt the recently proposed cycle-consistent generative adversarial networks in order to transfer automatically rendered prototypical traffic sign images for which we control type, pose, and-to a degree-background into their true-to-life counterparts. We test the proposed system by extensive experiments on the German Traffic Sign Recognition Benchmark dataset [1] and learn that both a HOG-feature-based SVM classifier and a state-of-the-art CNN exhibit reasonable performance when solely trained on artificial data. Consequently, it is well suited as data augmentation method and allows for covering uncommon cases and classes.
Instance Stixels: Segmenting and Grouping Stixels into Objects.

State-of-the-art stixel methods fuse dense stereo and semantic class information, e.g. from a Convolutional Neural Network (CNN), into a compact representation of driveable space, obstacles, and background. However, they do not explicitly differentiate instances within the same class. We investigate several ways to augment single-frame stixels with instance information, which can similarly be extracted by a CNN from the color input. As a result, our novel Instance Stixels method efficiently computes stixels that do account for boundaries of individual objects, and represents individual instances as grouped stixels that express connectivity. Experiments on Cityscapes demonstrate that including instance information into the stixel computation itself, rather than as a post-processing step, increases Instance AP performance with approximately the same number of stixels. Qualitative results confirm that segmentation improves, especially for overlapping objects of the same class. Additional tests with ground truth instead of CNN output show that the approach has potential for even larger gains. Our Instance Stixels software is made freely available for non-commercial research purposes.
Evaluation of Visual Based Augmented Reality (AR) Learning Application (V-ARA-Dculia) for Dyscalculia Learners

The rapid growth in technology have affected processes in various domains such as business, healthcare, agriculture and education. Computer related applications used in these domains are available so easily, that it is impossible to imagine a situation without them. Technologies that were available but hardly commonly used a few decades ago such as Virtual Reality (VR) and Augmented Reality (AR) have now become technologies that are fast gaining interests in most fields including service related1 fields such as healthcare and education. The basic idea of AR is to superimpose sense enhancements over a real-world environment. It is a perfect solution for learners with learning difficulties as it combines the advantages of multi senses of the learners, helps them to understand learning better when the integration of both virtuality and reality is embedded in their learning applications. AR is mostly effectively used when computer generated visual enhancements are integrated into real life applications. Thus, this paper highlights the evaluation of the visual-based AR learning application to investigate its plausible assistive functions that can help dyscalculia learners learn Mathematics in a more meaningful way. Findings of the study showed that the students who had difficulties on memory, abstraction, sequencing processing, motor and visual perception, found the visual-based Augmented Reality (AR) Â technology embedded in an application, a positive assistive learning application that can help dyscalculia learners learn mathematics more effectively. Â Â
Detecting Anomalous Driving Behavior using Neural Networks.

The ability to robustly detect abnormal driving behavior has the potential to limit traffic accidents and save many lives. Abnormal driving behavior that threatens road safety includes aggressive, anxious, nervous, and unstable driving. Any of these can lead to dangerous situations in traffic. Therefore, we aim to provide a robust mechanism to detect such abnormal driving behavior. In this paper, we present our work in this regard which focuses on neural networks-based anomaly detection approaches. We consider autoencoder replicator neural networks and long short-term memory networks; comparing them to a previously employed Isolation Forest. We show that introducing a post-processing approach, that takes into account the recent history of a vehicle, reliable anomaly detection for driving behavior can be achieved based on the recurrent neural network. Its performance is well suited for application in a large scale detection system for driver assistance or autonomous vehicles.
Augmented Reality in Library Services: A Panacea to Achieving Education and Learning 4.0

Augmented Reality (AR) concept is presently discussed as one of the foremost technologies of the next industrial revolution. AR has turned out to be a prevalent topic in educational research over the years as existing literature reflects the multiple benefits of its incorporation into educational setting however, the potential of achieving the Education 4.0 through the provision of AR based university library services is scarce in the literature. This paper conducts a content analysis of the literature to bridges the gap by discussing how AR usage for library services can serve as a remedy to achieve Education 4.0. We stand on the strength of service innovation model to point out numerous ways by which AR can be used to provide library services. This finding will assist university community as complimentary effort to achieving quality teaching, learning and research to foster the education and learning 4.0.
Live on Stage: STEM: Shumate Dives into Theatrical Sound

In 2014, when Margaret Shumate's Dallas-Fort Worth middle school produced the rock musical Next to Normal, Shumate was introduced to the student sound designer, Declan Kunkel, in preparation for running sound for the school's upcoming production of Cinderella Meets the Wolfman. She was blown away by the rock musical about a suburban family struggling with a mother's worsening bipolar disorder, and today, it is still one of her favorites. Shumate, called to fill in for the regular sound engineer, was blown away by what she describes as "all the pretty lights and switches on the sound board." Shumate knew then that she wanted to work in theater, and since that time, she continued to develop a unique skill set that combines theater with science, technology, engineering, and mathematics (STEM).
MENINGKATKAN KEMAMPUAN BERTANYA SISWA MELALUI LAYANAN BIMBINGAN KELOMPOK DI KELAS VII-3 SMP NEGERI 29 MEDAN PADA TAHUN PELAJARAN 2016-2017

Lertina Pakpahan. The improving of stuents’ competence in asking through group guidence service at VII-3 grade SMP Negeri 29 Medan in 2016/2017 academic year. The aim of this study is to improve stuents’ competence in asking through grouping guidence service at VII-3 grade SMP Negeri 29 Medan in 2016/2017 academic year. The method used in this study is classroom action research with three cycles. The sunjects of this study are 36 students. The technique in collecting data is test, qustioner and observation.The technique of analizing data in this study is descriptive comparation. It is because to compare the score both first and second cycles and to compare the students’ competence in grouping guidence service . In analyzing data gottten in this study, The researcher also conducts descriptive persentation analyzing data. The result of the study shows there is the improving of students’ involving in grouping guidence service, It is seen from new aspect understanding. The improving are in positif feeling, action plan, anthusiasm. These aspsecs can be observeb during the study. The improving can be seen in asking competence, the questiion is in spontanious, atending the situation in asking, atending the way of asking siuitable with the value and norm. There are nine indecators in asking competence which is observeb. The improving can be seen from the cycle I, II and III. In Cycle I, The average percentage is 45,52%, In The second cycle is 60% and the third cycle is 87,77%. The average level of improving in asking in first cycle is 45,51%, in the second cycle is to be 66,99% and the third cycle is improving to be 93, 32%. Key words: Asking competence, grouping guidence service
Download contact details as a CSV file for Councillor Matt Dent

Download a CSV file containing contact information for Councillor Matt Dent. CSV files can be inported to databases and spreadsheets
LibGuides: Digital Citizenship K-12: 9th - 12th

This libguide is intended to guide teachers and students through resources on digital citizenship. The focus of digital citizenship instruction is to teach people how to use the internet and technology responsibly and with best practices.
Investigations of the Influences of a CNN's Receptive Field on Segmentation of Subnuclei of Bilateral Amygdalae

Segmentation of objects with various sizes is relatively less explored in medical imaging, and has been very challenging in computer vision tasks in general. We hypothesize that the receptive field of a deep model corresponds closely to the size of object to be segmented, which could critically influence the segmentation accuracy of objects with varied sizes. In this study, we employed AmygNet, a dual-branch fully convolutional neural network (FCNN) with two different sizes of receptive fields, to investigate the effects of receptive field on segmenting four major subnuclei of bilateral amygdalae. The experiment was conducted on 14 subjects, which are all 3-dimensional MRI human brain images. Since the scale of different subnuclear groups are different, by investigating the accuracy of each subnuclear group while using receptive fields of various sizes, we may find which kind of receptive field is suitable for object of which scale respectively. In the given condition, AmygNet with multiple receptive fields presents great potential in segmenting objects of different sizes.
Multi-Stage Residual Fusion Network for LIDAR-Camera Road Detection.

Only a few existing works exploit multiple modalities of data for road detection task in the context of autonomous driving. In this work, a deep learning based approach is developed to fuse LIDAR point cloud and camera image features over a bird's eye view representation. A two-stream fully-convolutional network is designed as encoder to extract general features of two types of data. Instead of limiting the fusion processing at a single stage or to a predefined extent, we propose a multi-stage residual fusion strategy to merge the feature maps in a residual learning fashion, and integrate the information at different network depth. Experiments conduct on KITTI road benchmark show that our proposed method has a significant improvement over single modality methods and other fusion approaches. And it is also among the top-performing algorithms.