Reviewerly/exHarmony huggingface dataset:
Rapid and accurate object detection on drone based embedded devices with dilated, deformable and pyramid convolution

There are more and more demands on deep learning based object detection on embedded devices, such as drone surveillance. However, there are some obstacles for object detection on embedded devices, such as: compu- tational complexity, variance on objects' rotation and scale, and small-size objects. We design an embedded compatible object detection algorithm, which have solve the above problem. We use Dilated and Depth-wise separable convolution to optimize base network for reducing model's parameter and speeding up process. We use Deformable Convolution to sort out variance on rotation and scale. We adopt Feature pyramid structure for locating small-size objects. The embedded platform is NVidia TX2. We have collected data by drone and made a dataset by self. The experiments on our dataset to verify our algorithm. In terms of accuracy, our method achieves high precision on detecting ground objects, while in terms of speed, it processes RGB images of 512 x 512 size in 9 images per second.
PERBANDINGAN ALGORITMA CART DAN NAÃVE BAYESIAN PADA KASUS DIAGNOSIS PENYAKIT DIABETES

Diabetes mellitus is a disease that threatens serious health, can cause death and the World Health Organization (WHO) estimates that every 10 seconds there is one diabetes patient who dies of this disease. This makes researchers and practitioners focus their attention on detecting / diagnosing diabetes mellitus and preventing it because this disease can cause complications. The method used in this research is problem identification, data collection, pre-processing stage, classification method, validation and evaluation and conclusion drawing. The algorithm used in this study is CART and NaA¯ve Bayes by using a dataset taken from the UCI Indian Pima database repository which consists of clinical data of patients who detected positive and negative diabetes mellitus. The validation and evaluation methods used are 10-cross validation and confusion. Matrix for precision, recall and F-Measure. The results of calculations that have been done, the results of the accuracy of the CART algorithm are 76.9337% with precision 0.764%, recall 0.769%, and F-Measure 0.765%. While the diabetes dataset tested by the NaA¯ve Bayes algorithm gets an accuracy value of 73.7569% with precision 0.732%, recall 0.738%, and F-Measure 0.734%. From these results it can be concluded that to diagnose diabetes mellitus it is recommended to use the CART algorithm.
Using Cooperative Integrated Reading and Composition (CIRC) Model With Aldiko Book Reader to Improve the Reading Comprehension Achievement of the Elevent Year Students of SMA 2 Parepare

This thesis studies about Using Cooperative Integrated Reading and Composition (CIRC) Model with Aldiko Book Reader to Improve the Reading Comprehension Achivement of the Elevent Year Students of SMA Negeri 2 Parepare. There are two problem statements in this research, these are 1) Is the use of coperative integrated reading and composition (CIRC) model with Aldiko book reader efective to improve the reading comprehension achivement of the eleventh year students of SMA Negeri 2 Parepare? and 2) Are the student interested in learning reading using cooperative integrated reading and composition (CIRC) model with Aldiko book reader? This research used quasi-experimental method, that applied one experimental group and one control group in this research. The researcher used cluster random sampling technique which takes IPA 2 class as an experimental group and IPA 3 class as a control group. The total sample are 74 students. The data colled through pretest and posttest. The data analysis by using t-test. The result of this research finally showed that the students comprehension in reading text was 68.38 in their pretest, but increase in the posttest with mean score was 82.16. It means that the alternative hypothesis is accepted, which the t-test value was greater than t-table value. In the posttest, the t-test value is 6.589 while t-table value is 2.021. Based on the result of data analysis, the writer concludes that using cooperative integrated reading and composition (CIRC) model with Aldiko book reader effective to improve the reading comprehension achievement of the student in reading text.
Text Mining Preprocessing Techniques and its Significance based on the Dataset

Social Network can be termed as a network of social interactions and personal relationships. The most popular social networks include Facebook, Google+ and Twitter. The content shared in such networks is usually unstructured text. Nowadays, various algorithms are being generated and analyzed to understand and extract meaningful inferences from such unstructured data. In this survey, we have the tendency to review the text mining techniques and analyze combination of those techniques to get varied textual patterns from the social networking sites. Here are some of the techniques used in preprocessing .
A Multi-Channel Embedded DSP Closed-Loop Control System for Musical Robots

The continuous automatic calibration of musical robots is an important step toward enabling them to create accurate, reliable, and expressive performances. Several attempts have been made to achieve this using external laptops, single-board computers and off-the-shelf hardware, but these solutions have various drawbacks that preclude their use in many musical robotics contexts. This paper presents a new, custom-built embedded DSP system that is capable of up to 32 channels of high quality audio input and output, created to carry out musical information retrieval tasks on the sonic output of musical robots in real time while they are performing. The results of these analyses are continuously fed to musical robot control hardware in order to inform their performance. The design and construction of the circuit board is described, the Musical Information Retrieval (MIR)-based algorithms carried out by the board are outlined, the system's performance in representative applications are evaluated, and its various implications to the field of musical robotics and beyond are discussed. By integrating this system into new musical robots, the result is instruments that are able to `listen' to the audible results of their own actuations in real time, and continuously calibrate their actions to best represent the intentions of the programmed musical composition or live input.
View synthesis by shared conditional adversarial autoencoder

An important problem for both image processing and computer version is to synthesize the novel view of a 3D object. We propose a shared conditional adversarial auto-encoder (SCAAE) network that is trained end-to-end on the task of rendering previously unseen object given a single image of this object. The model uses the advanced GAN framework to build the generator by introducing U-net, which can generate a novel view image based on the input image and a controllable condition signal. The FCN model is used to construct the D-network to distinguish real and fake images. We also propose a new objective function which considers both the distribution consistency and transformation persistence. We designed a SCAEE network to generate multi-view images of objects, instead of the three dimensional effect of physical models, which solves the shortcoming of artificial modeling. Experiments demonstrate that the new network structure is better than other already existing.
A Novel Recommendation Algorithm Based on Diffusion of Innovation Theory

Determining whether an item is "novel" for target users is a crucial problem and understanding their preference and awareness degree of the item has been widely investigated in novelty recommendations.A recommendation algorithm based on "diffusion of innovation" theory was proposed in this study to verify the novelty of recommendation results on the precondition of ensuring their accuracy.Items were clustered using the K-means clustering algorithm.Users' positivity of innovation adoption for each item was calculated on the basis of the items adopted by the users, and then the novelty of the items for target users was calculated by combining their popularity change, user preference, and user difference.Results of traditional recommendation algorithms were integrated for recommendation on the basis of fusion strategy results.The effectiveness of the proposed algorithm was verified through an offline experiment.Results indicate that the novelty of the recommendation list of the proposed algorithm is remarkably higher than that of traditional algorithms.The novelty is high when the quantity of alternative sets reaches 400 or more, where the average popularity of the recommendation list declines by 40%, and the coverage is elevated by 100%, thereby improving the ability of the proposed system to extract all kinds of items.This study serves as reference for the improvement of user satisfaction with recommendation systems.
A Similarity Based Representation for Identifying Healthcare Anomalous Activities

A Vision Based Patient Monitoring system focuses on detecting abnormal activities of a patient. In real-world, factors like occlusion and view point variations make the activity recognition task challenging. This work proposes a similarity-based representation for healthcare activities including abnormal patient activities such as coughing, sneezing, vomiting, falling, etc. Global and depth-based representations such as histogram of optical flow, displacement between skeletal sequences and relative position of skeletal joints are used to represent the spatio-temporal dynamics of activities. A benchmark data namely "NTU RGB + D Action Recognition dataset" is used for testing the performance of the proposed approach. A comparison of the proposed methodology against other state-of-the-art approaches has proved the discrimination of the proposed approach.
KEEFEKTIFAN PENGGUNAAN TEKNIK DERET KATA DALAM PEMBELAJARAN MENULIS KREATIF PUISI

The attitude of students' disinterest and the inaccuracy of the teacher in choosing techniques or learning methods for learning to write poetry, it is necessary to research effective learning techniques for learning to write poetry. This study also aims to determine the effectiveness of the use of word series techniques in improving the ability to write creative poetry. The results showed a significant difference in the posttest scores of creative writing poetry of the control group and experimental group students. In the control group there were 6 students who got low scores, 29 students got medium scores, and 2 students got high scores. In the experimental group there were 2 students who got low scores, 18 students got medium scores, and 15 students got high scores. This shows that there are significant differences in the ability to write creative poetry between the control group and the experimental group. The t-test results of the pretest and posttest scores of the experimental group produced a tcount of 2007 with a df of 35 and a table of 0.13 at a significance level of 5%. This shows that the effective word series technique is used in learning to write poetry because the value of t-count <-table (-2.007 <- 0.13).
Effect of Blended Learning, Parenting Parents, Peer Interaction, and Efficacy of Self Motivation to Learn

The study was aimed to determine whether the effect of blended learning, parenting parents, social peers, and self-efficacy on motivation to learn. This study was conducted over three months, starting from October 2019 until December 2019. The method used in this study is a survey method with the approach of causality. The population in this study is a randomized population totaling 200 respondents. Data collection techniques used are literature and questionnaire techniques. For data analysis techniques we use SmartPLS software version 3. PLS (Partial Least Square) with structural equation analysis (SEM). The results of this study indicate that each variable has the same influence.
Optical circuits cross dimensions

Accessing the physics of higher-than-three-dimensional systems is naturally challenging. Researchers have now demonstrated that light dynamics in a one-dimensional array of carefully arranged photonic waveguides mimics the time evolution of particles in high-dimensional lattices.
Peningkatan Kemampuan Membaca Pemahaman Menggunakan Teknik Skimming

Reading is one of the main activities among the four language skills that need to be developed continuously since the basic level. The objective of this research is to find out whether skimming techniques can improve the ability to read English text comprehension in Campus V UNM students parepare or not. This type of research is a Pre-Experimental study and the population in this study is UPP PGSD Parepare 2014 class of 30 students. The instrument used in this study uses a multiple choice written test. The conclusion that can be drawn from this study is that by using skimming techniques can improve the ability to read English text understanding in students of the UNV V Parepare campus
RANCANG BANGUN APLIKASI E-BOOK PANDUAN MAINTENANCE KOMPUTER MENGGUNAKAN METODE TEXT TO SPEECH BERBASIS ANDROID

Problems with how to maintenance on a computer that is published by several publishers are generally in the form of prints. The purpose of this study was to design an android-based computer e-book maintenance application guide, and implement the TTS method on an android-based computer maintenance e-book guide application. This application is built on the Android operating system using the Java programming language, and prototyping methods. Data collection is done by collecting data from literature review. From the results of the implementation testing carried out from the five main menus it produces data in the form of sound, images, text, and videos from each trouble menu, so that this application can be used and well received as a solution to existing problems.
Sonic Argumentation 1 + 2

With this special issue we are delighted to introduce you to ten new audio papers developed for Seismograf. The 10 audio papers are published in two volumes: The first, #22 Sonic Argumentation I, gathers scholars from artistic research in music, and the second, #23 Sonic Argumentation II, presents papers by scholars from ethnography, literature and sound studies.
Image Quick Search Based on F-shift Transformation

Searching a given image belongs to which part of an image is a practical significance topic in computer vision, image and video processing. Commonly the images are compressed for efficient storage and transfer, while if we want to search a given image form images, we need to decompress them first and then process our task. In this paper, we give a quick image searching method based on F-shift compressed images, which means no decompression processes are needed. The basic principle lies on the attribute of F-shift transformation (similar to Haar wavelet transformation), where each of the data are quality-guaranteed. This property ensure we can just search the high frequency component of a compressed image to reach our goal. Getting benefit from the fact that no decompression process are needed, the efficiency of our method can be promoted significantly.
Specialized Terminology in the Video Game Industry: Neologisms and their Translation

The video game industry is growing at a very fast pace. At present, it is the biggest entertainment industry in the world, selling even more than film and music industries. Newly-developed technologies provide video game creators with the necessary tools to develop more complex game worlds, and user interaction is more important than ever. Each one has its own terminology and complexities, which must be perfectly understood in order to deliver high-quality work. Therefore, translators must be deeply aware of how all these technologies and game worlds work. More importantly, they need to be familiar with the specialized terminology they are going to come across while working in the video game industry. This paper is part of a series of studies where a corpus of 300 games is used to analyze the terminology needs of video game translation and interpreting. Specifically, this paper focuses on the relevance of neologisms—as they are one of the basic traits that define a specialized language—and defines the type of neologisms that can be found when localizing a video game with the overall goal of proving that they are common in the video game industry.
Unintentional Insider Threats Countermeasures Model (UITCM)

Most organisations see technological controls as the solution to their information security problems. However, with all these technologies, it was evidently investigated that human errors are unavoidable.Unintentional insider is the biggest insider threat of all.Thus the objective of this paper is to propose a conceptual model as a countermeasure towards unintentional insider threats The proposed model in this research was adapted from (Generic Mitigation Strategies for Information Leaks) developed by Wan (2018) and (2019), It was expanded by combining it with UIT Mitigation Strategies and Countermeasures recommendations mentioned by previous studies.
Pompe disease: PAS-positive lymphocyte vacuoles as diagnostic screening test

The proliferation marker Ki67 has prognostic and predictive values in breast cancer, and the cutoff of the Ki67 label index (LI) is a key index for chemotherapy. However, poor interobserver consistency in Ki67 assessment has limited the clinical use of Ki67, especially in luminal cancers. Here, we reported a modified Ki67 assessment method, size-set semiautomatic counting (SSSAC) and investigated its interobserver reproducibility.One hundred invasive breast cancer tissues were set immunostained for Ki67 in one laboratory, scanned as digital slides, and sent to 41 pathologists at the laboratories of 16 hospitals for Ki67 LI assessment using size-set semiautomatic counting (SSSAC), size-set visual assessment (SSVA) and size-set digital image analysis (SSDIA) with a specific image viewing software (Aperio Image Scope, Leica, Germany). The intraclass correlation coefficient (ICC) and Bland-Altman plot were used to evaluate interobserver reproducibility. The Wilcoxon signed-rank test was used to analyze the difference in the Ki67 values assessed by SSSAC and SSDIA.SSSAC demonstrated better interobserver reproducibility (ICC = 0.942) than SSVA (ICC = 0.802). The interobserver reproducibility was better in Ki67 homogeneously stained slides and centralized hot-spot slides than in scattered hot-spot slides. The Ki67 value assessed with SSSAC was obviously higher than that assessed with SSDIA (negative ranks (SSDIA < SSSAC): N = 80, sum of ranks = 4274.50; positive ranks (SSDIA > SSSAC): N = 17, sum of ranks = 478.50; Z = −6.837; P < 0.001).SSSAC shows satisfactory interobserver reproducibility in the Ki67 assessment of breast cancer and may be a candidate standard method for Ki67 LI assessment in breast cancer and other malignancies.
Wonder bodies, computational prosthesis, and automated creativity: what is expressing who?

Situating our bodies in a neoliberalist landscape with trans-humanist desires to go beyond our own bodies biological limits, consumed as part of the everyday media news/entertainment (e.g. genome experimentation), and sold as part of our everyday networked technology (e.g. mobile, wearable, AI), we find that everyday gestures, acts and spaces are transformed into capitalised labour and datafied.In the deep reliance on machine agency, as these become every-day body-prosthesis, and as we trust automated practices (e.g. google maps for directions) over evolving our own sensing-bodies, how creative are we able to be now and what is gained and lost in becoming wonder humans? These questions will be discussed in the context of computational art installations, as materialised techno-social imaginaries and ludic environments, from which the audience-participants can ‘express’ themselves, and challenge their own techno-cultural programming.
Klasifikasi Penjualan Obat Pertanian Laris Dan Kurang Laris Pada UD Cahaya Tani Menggunakan Metode Decission Tree

Pesticides are chemicals or chemicals used to kill pests in plants that can inhibit plant growth so that they have an impact on poor yields. UD. Cahaya Tani is one of the drug stores in Moyot Village, Sakra Sub-district, which provides various kinds of medicinal drugs needed by farmers in Moyot Village, Sakra, Sakra, East Lombok. The purpose of this study is to classify the types of drugs which are included in the best-selling category and are not in demand. In this case using the classification method of data mining by applying the decission tree method. Where this method works by forming a decision tree. Based on the results of tests that have been carried out by applying 10 cross validation, the highest accuracy is obtained in the K-Fold Validation 8 with a value of 97.43% and the Under Curve Area which is 0.985. DOI : 10.29408/jit.v2i2.1489
Hand Detection Based on Multi-scale Fully Convolutional Networks

Accurate hand detection is a challenging task because of large variations of hand images in real-world scenarios. We present a simple yet powerful multi-scale fully convolutional network structure that yields fast and accurate hand detection on challenging VIVA dataset. The proposed model directly detects and locates hands in driver’s cab of various size, shape, appearance, and illumination in full images without time-consuming region proposal step. The simple model with the well-designed loss functions promotes the proposed approach to achieve very good hand detection results.
Implementing FAIR Data Infrastructures (Dagstuhl Perspectives Workshop 18472)

The open science movement is gaining strength and momentum worldwide, signalling a fundamental shift in how scientific research is made accessible and reusable. In order to fulfill the promises of open science, reliable and sustainable research data infrastructures must be developed. While the FAIR data principles provide a promising conceptual basis for developing such data infrastructures, they do not provide technological guidance on how to do so. Computer science is uniquely situated to fill this gap by researching and developing tools and technical specifications which can help to realize the creation of FAIR data infrastructures. To this end, this Dagstuhl Perspectives Workshop brought together computer scientists and digital infrastructure experts from across disciplinary domains to discuss key challenges and technical solutions to implementing and promoting the establishment of FAIR-compliant infrastructures for research data. This manifesto reports the findings from the workshop and provides recommendations along two lines: (1) how computer science can contribute to implementing FAIR data infrastructures and (2) how to make computer science research itself more FAIR.