Reviewerly/exHarmony huggingface dataset:
Duct-tape and dreams

The making and tinkering movement has become increasingly mainstream over the past decade, pioneered in part through the popularity of magazines like `Make', events such as Maker Faire and DIY websites including `Instructables'. Science centres and museums have been developing their own ideas, notably the Tinkering Studio at the Exploratorium. In this commentary piece, we reflect on why this movement has a strong appeal for the Life Science Centre in Newcastle upon Tyne and why we are in the process of developing a new making and tinkering space to help us enact our centre's vision to `Enrich lives through science'.
High-level Semantic Feature Detection: A New Perspective for Pedestrian Detection

Object detection generally requires sliding-window classifiers in traditionor anchor-based predictions in modern deep learning approaches. However, eitherof these approaches requires tedious configurations in windows or anchors. Inthis paper, taking pedestrian detection as an example, we provide a newperspective where detecting objects is motivated as a high-level semanticfeature detection task. Like edges, corners, blobs and other feature detectors,the proposed detector scans for feature points all over the image, for whichthe convolution is naturally suited. However, unlike these traditionallow-level features, the proposed detector goes for a higher-level abstraction,that is, we are looking for central points where there are pedestrians, andmodern deep models are already capable of such a high-level semanticabstraction. Besides, like blob detection, we also predict the scales of thepedestrian points, which is also a straightforward convolution. Therefore, inthis paper, pedestrian detection is simplified as a straightforward center andscale prediction task through convolutions. This way, the proposed methodenjoys an anchor-free setting. Though structurally simple, it presentscompetitive accuracy and good speed on challenging pedestrian detectionbenchmarks, and hence leading to a new attractive pedestrian detector. Code andmodels will be available at \url{https://github.com/liuwei16/CSP}.
Internet of Things in Healthcare

This article discusses the impact of the Internet of Things (IoT) on the development and modernization of healthcare.The demand for connected devices covers many industries, including healthcare.The Internet of Things revolutionizes patient data collection and records, performs individual health assessments.The author examines various possibilities, recent advances in the field of the Internet of things, including various mobile health monitoring applications, inhalers, smart contact lenses.Special attention is focused on intelligent continuous glucose monitoring (CGM).The progress of the Internet of Things has reached even the launch of smart hospitals.Managers have access to predictive analytics, thanks to which they can solve a problem before it happens.The problem of the help of the Internet of Things when solving problems of chronic diseases is considered.As for the future, the growing interaction of artificial intelligence and the Internet of things in the health sector is likely, according to the author, to create more intelligent IoT devices that can perform actions autonomously.Besides, in the future, such next-generation devices will be able to provide intelligent services, allowing real-time data processing.
Perancangan Sistem Informasi Akademik Pada Sekolah Menengah Kejuruan Negeri (SMKN) 1 Lintau Buo Menggunakan PHP MYSQL

The school website is a vehicle for schools to show themselves to the global community, as well as a medium of information for anyone who wants to know more about the school. The school website gets attention, good responses from various parties from education staff, students and the community. State Vocational High School 1 Lintau Buo (SMK N 1 Litau Buo) is one of the National Vocational High School Vocational Schools (SMK SSN) in Tanah Datar District which needs to interact and socialize with the wider community by providing complete and clear information about the school. Previously this school has never had an Academic Information System as a media campaign, and provision of information to students, parents, guardians and the wider community. Therefore, the school still uses manual way in conveying information. Manual way in delivering such information is felt to still have many shortcomings, such as the coverage of pemebaranya still less extensive and limited information content. The results of this study are: An Academic Information System built with PHP and MySQL can work with the ability: can perform input and storage process faster, smaller data files, due to using mysql database, and can be operated easily.
Efficient Regular Language Search for Secure Cloud Storage

Cloud computing provides flexible data management and ever-present data access.However, the repository services provided by cloud server is not trusted by customers.The data's provided by cloud server can be easily stolen by intruders.Searchable encryption could provide the functions of confidentiality protection and privacy-preserving data retrieval, which is an important tool for secure storage.In this paper, we propose an efficient large universe regular language search scheme for the cloud storage, which privacy is preserving and secure against the off-line keyword guessing attack (KGA).A notable highlight of the proposal over other existing schemes is that it supports the regular language encryption and deterministic finite automata (DFA) based data retrieval.The large universe construction ensures the extendibility of the system, in which the symbol set does not need to be predefined.Multiple users are supported in the system, and the user could generate a DFA token using his own private key without interacting with the key generation centre.Furthermore, the concrete scheme is efficient and formally proved secure in standard model.Extensive comparison and simulation show that this scheme has function and performance superior than other schemes.
Summarization of Multiple News Videos Considering the Consistency of Audio-Visual Contents

News videos are valuable multimedia information on real-world events. However, due to the incremental nature of the contents, a sequence of news videos on a related news topic could be redundant and lengthy. Thus, a number of methods have been proposed for their summarization. However, there is a problem that most of these methods do not consider the consistency between the auditory and visual contents. This becomes a problem in the case of news videos, since both contents do not always come from the same source. Considering this, in this paper, we propose a method for summarizing a sequence of news videos considering the consistency of auditory and visual contents. The proposed method first selects key-sentences from the auditory contents (Closed Caption) of each news story in the sequence, and next selects a shot in the news story whose “Visual Concepts” detected from the visual contents are the most consistent with the selected key-sentence. In the end, the audio segment corresponding to each key-sentence is synthesized with the selected shot, and then these clips are concatenated into a summarized video. Results from subjective experiments on summarized videos on several news topics show the effectiveness of the proposed method.
Remote Sensing Image Registration Based on the HEIV Model

In Earth observation missions, a large number of remote sensing images (RSIs) are obtained through satellites and aerial photography. RSIs are often huge and they generally have large edge distortions. Therefore, registration is required when the RSIs are used for mapping and change-detection. Since the RSIs usually have complex variation and the large distortions, the current existing global image registration algorithms cannot achieve high-precision matching of the target area. We propose a method based on the Heteroscedastic error-in-variables (HEIV) model to solve the registration problem of RSIs. Though HEIV model, the registration parameter estimation problem can be expressed as a quasi-linear form of the design matrix, which consists of observation vectors and parameter vectors with heteroscedasticity. Based on the image pre-processing and feature intensity, the HEIV model is utilized to estimate the registration parameters. Experiments are carried by using the RSIs taken with helicopter in comparison with the method based on Harris corner registration and the method based on SIFT registration, respectively. Compared with the Harris, the best group’s accuracy is increased by 54.76%. In comparison with the SIFT algorithm, the T-Rank group’s increment on RMSE is 1.88%. The results show that our method has more advantages in the parameter estimation of RSI registration and it can be better applied to Earth observation missions.
Finding Shortest Distance Path and Object Detection and Avoidance Using Image Processing and Artificial Intelligence

In this work we will be implementing Shortest distance path finding algorithm and object detection voidance using Image Processing and artificial intelligence.The work will be focuses on generating shortest path using A star algorithm and object avoidance using Image Processing.Work will also represent insert static map with the help of images.Insertion of object will be testing with different shapes and sizes to represent on the graph.
PLAGIARISM IN CREATING ACADEMIC BASED ARGUMENTATIVE ESSAY: THE STRATEGIES TO AVOID IT

Through this paper, the strategies of avoiding plagiarism implemented by the participants were presented. There were 136 fifth semester students of English Language Education Study Program (hereafter, ELESP) in Mahasaraswati Denpasar University who willingly contributed to the research investigation. All of them enrolled the Writing IV course which mainly focuses on academic writing and plagiarism. To attain the data, an open-ended questionnaire was distributed which followed by interview and Focus Group Discussion (henceforward, FGD). The obtained data were analyzed by means of Interactive Model which involves data collection, data filter, data presentation, and verification. It was found that the students encompassed 4 strategies in the attempt to avoid plagiarism such as producing a thorough outline prior to drafting, using own words, citing: quoting, paraphrasing, and utilizing plagiarism checker. These strategies are categorized into 3 different divisions based on the period of applying them.
Simplified Video Surveillance Framework for Dynamic Object Detection under Challenging Environment

An effective video surveillance system is highly essential in order to ensure constructing better form of video analytics. Existing review of literatures pertaining to video analytics are found to directly implement algorithms on the top of the video file without much emphasis on following problems i.e. i) dynamic orientation of subject, ii)poor illumination condition, iii) identification and classification of subjects, and iv) faster response time. Therefore, the proposed system implements an analytical concept that uses depth-image of the video feed along with the original colored video feed to apply an algorithm for extracting significant information about the motion blob of the dynamic subjects. Implemented in MATLAB, the study outcome shows that it is capable of addressing all the above mentioned problems associated with existing research trends on video analytics by using a very simple and non-iterative process of implementation. The applicability of the proposed system in practical world is thereby proven.
SISTEM PENDUKUNG KEPUTUSAN KLINIS MANAJEMEN NEONATAL BERBASIS ALGORITMA MTBS

The neonatal period is an important period in life. Infant Mortality Rate (IMR) is the number of infant deaths in the first 28 days of life (neonatal) per 1000 live births (PERMENKES No 53, 2014). IMR in Indonesia is still high compared to other ASEAN countries, data in 2016 shows that IMR reaches 25.5, it’s meaning that there are around 25.5 deaths per 1,000 babies born (BPS, 2016). Poor neonatal management clinically will cause abnormalities, and can even lead to lifelong disability, and death, while administratively can cause legal problems. Neonatal management requires complete clinical data support, relevance, accurate and timeliness aspects. This research is a mixed method research with action research approach and prototype method in the development of Clinical Decision Support System (CDSS). This study produced CDSS based on Integrated Childhood Illness Management (IMCI) algorithm for neonatal service management in primary health care center. The results of testing system using black-box technique is accordance with the requirements and obtained a valid overall result. DSS IMCI can be integrated with Electronic Health Record (EHR) so can occur for appropriate clinical decision making.&#x0D;
Application of Thermo-sensor in Brain-computer Interface

The high precise thermo-sensors are introduced to the brain-computer interface for data acquirement. The structures, parameters and properties of most recent thermo-sensors are presented in detail. The suitable signal acquisition system is also discussed in this paper.
Theoretical and Methodological Principles of Formation of the Spiritual Values of Students in the Conditions of Higher Education Institution

The paper is devoted to the existing problems within the process of spiritual values formation which is essential for the students of a higher education institution.The author gives a definition of the term "spiritual values of student youth" and specifies the structural components of this personal complex.The article presents a series of pedagogical conditions, forms and methods of education that will promote the spiritual and value self-affirmation of the student's personality.The paper reveals the content and peculiarities of pedagogical support in the process of spiritual values formation of student youth in the center of modern higher education.
PERANGKAT WIRO 1.0 SEBAGAI ALAT BANTU PROSES PENGUMPULAN INFORMASI WIFI

Information gathering activities are currently implemented with laptop equipment and external antennas. Such a device may cause suspicion that leads to personnel vulnerabilities in the field. This research will discuss about the design of equipment that is more flexible and small to support information gathering activities of wifi signal analysis by utilizing Rasberry Pi device as a replacement for laptop devices. The research method begins by describing how data retrieval works through wifi, how the Rasberry Pi works and then designing the device and the software system used.This design produces a special wifi signal gathering device pack 4-way handshake that has smaller dimensions, practical, avoid suspicion and able to operate automatically.
Victim Blaming bei Cyberbullying. Der Einfluss der Privatsphäreeinstellung auf die Opferschuldzuschreibung

SCM Studies in Communication and Media , Seite 115 - 134
Pengaruh Media Audio terhadap Kemampuan Menyimak Bahasa Jerman Mahasiswa Program Studi Pendidikan Bahasa Jerman Universitas Negeri Makassar

This study aimed to obtain data about the influence on the ability listen to audio media students of German Language Study Program, Foreign Language Education Department Faculty of Languages and Literature, Makassar State University. The type of this research is a quantitative research using quasi-experimental. The research design used in this study is a pretest-posttest control group design. The population in this study is a student of German language Study Program, Foreign Language Education Department Faculty of Languages and Literature, Makassar State University 2016/2017, with the number of 46 people. The sample in this study is the total sample. Analysis of the data is an inferential statistical analysis using t-test. The calculation result is t test (8.61) &gt; t table (2.015) with alpha level (0.05). That means, there is an effect using audio media on listening skills of students.
Pendekatan Games Dalam Meningkatkan Motivasi Belajar Siswa Bagi Relawan Gemma Insani Indonesia

The aim of this workshop is to become Gemma Insani volunteers have got the ability of classroom management and basic knowlegde about education psychology is related how the way to give the students motivate by using games in learning process. The event is followed by 25 volunteers Gemma Insani Depok. The methods are used in the workshop such presentation, discussion and question and answer, and simulation from the volunteers. The result of the workshop are (1) to train the volunteers’ teaching ability who have got different education background. In application kinds of games that used for all subjects in education level. This event can help hopefully to motivate the students in learning. (2) to use kind of methods in learning process so the student will not feel bored, and (3) be able to have creative thinking in creating or making games based on student- education level.
OCCLUSION HANDLED BLOCK-BASED STEREO MATCHING WITH IMAGE SEGMENTATION

This paper chiefly deals with techniques of stereo vision, particularly focuses on the procedure of stereo matching.In addition, the proposed approach deals with detection of the regions of occlusion.Prior to carrying out stereo matching, image segmentation is conducted in order to achieve precise matching results.In practice, in stereo vision, matching algorithm sometimes suffers from insufficient accuracy if occlusion is inherent with the scene of interest.Searching the matching regions is conducted based on cross correlation and based on finding a region of the minimum mean square error of the difference between the areas of interest defined in matching window.Middlebury dataset is used for experiments, comparison with the existed results, and the proposed algorithm shows better performance than the existed matching algorithms.To evaluate the proposed algorithm, we compare the result of disparity to the existed ones.
Testing Carbohydrate Substance as Flash Based Flipbook Learning Media

This study aims to produce a flash-based flipbook and find out the quality of flash-based flipbook products that are suitable for use as supporting learning media. The study consisted of preliminary research in the form of carbohydrate test practicum consisting of barfoed test, benedict test and iod / lugol test. The results of the study were developed into flash-based flipbook using macromedia flash and microsoft word 2010 through the data entry stage to the developer software, preparation of layouts and provision of activities on flash-based flipbook. The final product in the form of flipbook is flash-based. Flash-based flipbook was assessed by 1 material expert, 1 media expert, 1 science teacher, 3 peer reviewers, and tested on 10 junior high school students. The results of the evaluation of flashbased flipbook according to material experts were 90.87% (Very good), media experts 88.10% (Very good), peer reviewers 93.39% (Very good), biology teachers 75.00% (Good) , and 85.6% (Very good) student response. Based on this assessment, the flash-based flipbook that was developed is worthy of being used as a source of learning biology.
Learning Diversified Features for Object Detection via Multi-region Occlusion Example Generating

Object detection refers to the classification and localization of objects within an image by learning their diversified features. However, the existing detection models are usually sensitive to the important features in some local regions of the object. The existing algorithms cannot learn the diversified features regarding to each region effectively, which limit the performance of the model to a certain range. In this paper, we propose a novel and principle method called Multi-region Occlusion Example Generating (MOEG) to guide the detection model in fully learning the features of the various regions of the object. MOEG can generate completely new occlusion examples and it enables our detection model to learn the features of the remaining regions in the object by blocking the important regions in the proposal. It is a general method to generate occlusion examples and it can be implemented to most mainstream region-based detectors very easily such as Fast-RCNN and Faster-RCNN. Our experimental results indicate a $$2.4\%$$ mAP boost on VOC2007 dataset and a 4.1% mAP boost on VOC2012 dataset compared to the Fast-RCNN pipeline. And as datasets become larger and more challenge, our method MOEG become more effective as demonstrated by the results on the MS COCO dataset.
Dependency of GPA-ES Algorithm Efficiency on ES Parameters Optimization Strength

In herein presented work, the relation between a number of ES iterations and convergence of the whole GPA-ES hybrid algorithm will be studied due to increasing needs to analyze and model large data sets. Evolutionary algorithms are applicable in the areas which are not covered by other artificial intelligence or soft computing techniques like neural networks and deep learning like a search of an algebraic model of data. The difference between time and algorithmic complexity will be also mentioned as well as the problems of multitasking implementation of GPA, where external influences complicate increasing of GPA efficiency via Pseudo Random Number Generator (PRNG) choice optimization. Hybrid evolutionary algorithms like GPA-ES uses GPA for solution structure development and Evolutionary Strategy (ES) for parameters identification are controlled by many parameters. The most significant are sizes of GPA population and sizes of ES populations related to each particular individual in GPA population. There is also a limit of ES algorithm evolutionary cycles. This limit plays two contradictory roles. On one side the bigger number of ES iterations means less chance to omit good solution for wrongly identified parameters, on the opposite side large number of ES iterations significantly increases computational time and thus limits application domain of GPA-ES algorithm. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium provided the original work is properly cited.
Comparison between behavioral and structural explanation in learning by model-building

In science education, building models of dynamical systems is a promising method for understanding various natural phenomena and artifacts with scientific concepts. It is, however, difficult to learn skills and concepts necessary for modeling. Though several model-building learning environments (MBEs) have been developed with potentially useful methods for assisting students, the verification of them has been limited so far. Most studies evaluated their effectiveness by measuring the degree of model completion by students, or total learning effect that consists of several types of assistance. In this study, we investigated how students learn modeling skills and concepts of system dynamics through modeling dynamical systems, focusing on how students’ behavior and understanding are influenced by the type of assistance and students’ prior knowledge. We implemented the function that detects the difference of a model by students from the correct model and gives one of the two types of feedback: structural explanation indicates structurally erroneous parts of a model by students to promote students’ model completion, while behavioral explanation suggests erroneous behavior of a model by students to promote students’ understanding about the cause of error. Our experiment revealed the following: (1) Students assigned to structural explanation showed high model completion, but their understanding depended on whether they used the feedback appropriately or not. (2) Students assigned to behavioral explanation showed less model completion, but once they completed models, they acquired a deeper understanding.