Reviewerly/exHarmony huggingface dataset:
Directed Homotopy in Non-Positively Curved Spaces.

A semantics of concurrent programs can be given using precubical sets, in order to study (higher) commutations between the actions, thus encoding the geometry of the space of possible executions of the program. Here, we study the particular case of programs using only mutexes, which are the most widely used synchronization primitive. We show that in this case, the resulting programs have non-positive curvature, a notion that we introduce and study here for precubical sets, and can be thought of as an algebraic analogue of the well-known one for metric spaces. Using this it, as well as categorical rewriting techniques, we are then able to show that directed and non-directed homotopy coincide for directed paths in these precubical sets. Finally, we study the geometric realization of precubical sets in metric spaces, to show that our conditions on precubical sets actually coincide with those for metric spaces. Since the category of metric spaces is not cocomplete, we are lead to work with generalized metric spaces and study some of their properties.
A Short Flows Fast Transmission Algorithm Based on MPTCP Congestion Control

With the development of cloud computing and big data technology, traffic in the network presents new features. Real-time online interactive applications are increasing, mainly including web services, instant messaging, online commerce, advertising systems. They have very stringent latency requirements. However, the data traffic generated by data backup, movie download, data mining require high bandwidth. When large and small flows are transmitted concurrently, a series of problems will arise. MPTCP treats long and short flows equally. In this way, packets of long flows will preempt bandwidth at the bottleneck link, fill the router's whole queue buffer. This will cause the short flows transmission timeout. To solve these problems, we propose a novel algorithm named MPTCP-SPTA (MPTCP short flows fast transmission algorithm). The algorithm give high priority to short flows based on the congestion control algorithm, then introduce the Explicit Congestion Notification mechanism(ECN) in MPTCP. Through extensive network simulator (NS-3) simulations, we demonstrate that MPTCP-SPTA outperforms TCP and MPTCP in three typical network topology, which can significantly reduce the completion time of the small flow and effectively improving the total throughput of the network.
Exploring Ambient Air Quality Notifications for Smart Rooms

Many regular meeting participants know the atmosphere of a meeting in a closed room when the air becomes stifling and uncomfortable. With increased concentration of carbon dioxide (CO2), the cognitive performance of participants can also suffer as a result. Therefore, it makes sense to retrofit such meeting rooms with smarthome technology to improve the air quality. However, existing meeting rooms often do not have built-in ventilation systems. Hence, smart technology can be used to measure air quality and communicate that by ambient notifications such as ambient lighting. Actively ventilating a room is then left to the participants of a meeting. This paper reports on a user study demonstrating that the kind of unobtrusive notification from an ambient air quality display has a significant influence on response times of perceiving the information while being concentrated on the course of the meeting.
Prediksi Tingkat Kedatangan Wisatawan Asing Menggunakan Metode Backpropagation (Studi Kasus: Kepulauan Mentawai)

The tourism industry is always growing and plays an important role in the national economy, both as the second largest contributor to foreign exchange and as a large labor absorber. This study aims to optimize production using the Artificial Neural Network (ANN) method. The technique used is Backpropagation. The data processed is data on the number of foreign tourists from 2017 to 2019 in the Mentawai Islands. The results of the momentum obtained are 2-5-1 on the division of data into 2, namely training data for 2017 and 2018 and test data for 2019. The optimal prediction result is 0.99847, so this research is very helpful in predicting the arrival rate of foreign tourists in Mentawai Islands.
Penggunaan Bahasa Daerah pada Buku Bacaan Siswa Terbitan Kemdikbud

&lt;p class="abstract"&gt;This study aims to identify the use of regional languages in student reading books published by the Ministry of Education and Culture. This type of research is a qualitative descriptive study. The object of research is the local language in the student reading book published by the Ministry of Education and Culture entitled "Kenara Anak Suku Gayo" and "Kain Kulit Kayu Dei". The data from this study are student reading books published by the Ministry of Education and Culture which contain local languages. The data source in this research is an archive or document in the form of a student reading book published by the Ministry of Education and Culture which contains local languages. Data collection techniques use the technique of listening and note taking, the researcher first reads the reading book "Kenara Anak Suku Gayo" and "Kain Kulit Kayu Dei" published by the Ministry of Education and Culture to carefully determine the use of local languages, then record in full and then identify the use of local languages in the book reading. Data analysis techniques using flow analysis. The results showed that the Ministry of Education and Culture has efforts to preserve local languages, use Indonesian, and master foreign languages. The language used in the students' reading book "Kenara Anak Suku Gayo" and "Kain Kulit Kayu Dei" is not purely using Indonesian, but there is interference with local languages. The percentage of the use of local languages in the reading books of "Kenara Anak Suku Gayo" is 40%, while in the reading books of students "Kain Kulit Kayu Dei" 20%.&lt;strong&gt;&lt;/strong&gt;&lt;/p&gt;
Design of Underground Displacement Measurement System Based on Mutual Inductance and Hall Effect

Abstract Deep displacement monitoring of rock and soil is important for landslide warning. By using mutual inductance effect and Hall Effect, the author designed the underground displacement sensing unit through the solenoid and permanent magnet and the Hall sensor. The author designed the Hall voltage measurement circuit and installation device, and used the mutual inductance voltage measurement circuit that the laboratory has realized, which can accurately collect the mutual inductance voltage and the Hall voltage in real time. Through the 485 communication, the collected data is transmitted to the upper computer, the mathematical model established by the curve fitting method can be used to measure the real-time displacement of the deep part of the rock and soil. The experimental result shows that the horizontal displacement measurement range is 0-40mm, and the measurement accuracy can reach 1.5mm. It can measure the underground displacement within a reasonable error range.
Action Recognition Using High Temporal Resolution 3D Neural Network Based on Dilated Convolution

3D Convolution Neural Networks (CNNs), an important deep learning model, has good performance in recognizing actions in videos. When recognizing actions from videos, 3D CNNs usually down-sample in temporal dimension, leading to loss of the temporal information. To obtain more temporal information from the videos, this work proposed a new model based on the Inflated 3D ConvNet (I3D), named as I3D-T. Instead of using down-sample in temporal dimension, the proposed model applied the dilated convolution in temporal dimension to enlarge the receptive field. At the same time, a non-local feature gating block was designed in the model to learn the correlations between different feature maps. The experimental results showed that the proposed I3D-T has the state-of-art performance. Using RGB frames as input, the action recognition accuracies are respectively 95% and 74.8% in public dataset of UCF101 and HMDB-51.
Conceptual Cartography of School Safety: School Experiences in Managing the Covid-19 Pandemic in Mexico

This article analyses through a conceptual cartography, school safety, and its association with the management of the COVID-19 pandemic in Mexico. The qualitative methodology allowed the identification of a model of safe learning space in Higher Education, which emerges as a proposal to establish safe learning spaces and manage the pandemic. Once this model implemented, it was possible to inform, mobilize, attend to school content and be in confinement, which meant raising awareness of learning in Higher Education in an increasingly changing knowledge society.
Hiding the Type of Skin Texture in Mice based on Fuzzy Clustering Technique

A substantial matter to confidential messages' interchange through the internet is transmission of information safely. For example, digital products' consumers and producers are keen for knowing those products are genuine and must be distinguished from worthless products. Encryption's science can be defined as the technique to embed the data in an images file, audio or videos in a style which should be met the safety requirements. Steganography is a portion of data concealment science that aiming to be reached a coveted security scale in the interchange of private not clear commercial and military data. This research offers a novel technique for steganography based on hiding data inside the clusters that resulted from fuzzy clustering. The approach has been employed to use Fuzzy C-Mean clustering (FCM) to find the robust image regions for hiding the type of skin texture features in mice. The steganography was implemented using Least Significant Bit (LSB) method.
GPU-Based Self-Organizing Maps for Post-labeled Few-Shot Unsupervised Learning

Few-shot classification is a challenge in machine learning where the goal is to train a classifier using a very limited number of labeled examples. This scenario is likely to occur frequently in real life, for example when data acquisition or labeling is expensive. In this work, we consider the problem of post-labeled few-shot unsupervised learning, a classification task where representations are learned in an unsupervised fashion, to be later labeled using very few annotated examples. We argue that this problem is very likely to occur on the edge, when the embedded device directly acquires the data, and the expert needed to perform labeling cannot be prompted often. To address this problem, we consider an algorithm consisting of the concatenation of transfer learning with clustering using Self-Organizing Maps (SOMs). We introduce a TensorFlow-based implementation to speed-up the process in multi-core CPUs and GPUs. Finally, we demonstrate the effectiveness of the method using standard off-the-shelf few-shot classification benchmarks.
UTILIZING COMMUNICATIVE LANGUAGE GAMES TO IMPROVE STUDENTS’ SPEAKING ABILITY

This study is aimed at finding the utilizing of communicative language games in improving students' speaking ability at second grade students of SMPN 4 Praya Barat Daya. This study was an action research which comprised two cycles. It involved an English teacher and 24 students of second grade at SMPN 4 Praya Barat Daya. The steps of this study were reconnaissance, planning the actions, implementing and observing the actions, and reflecting the actions done. The data of this study were qualitative and quantitative. The qualitative data were obtained by observing the teaching and learning process during the implementation of the actions and interviewing the students and the English teacher. The data were collected using field notes and interview transcription. The quantitative data were taken by assessing the students speaking ability using pre-test and post-test in the form of students' scores. The research finding shows that the use of the communicative language games is effective to improve students' speaking ability. The games are accompanied with other actions such as using classroom English, applying varied themes, using adequate media, doing language form activities, giving feedback, giving rewards, doing group works and rearranging the students seating arrangement. Therefore, it can be concluded that the use of communicative language games is able to improve students' speaking skills at second grade students of SMPN 4 Praya Barat Daya.
Implementation of Best First Search Algorithm in Determining Best Route Based on Traffic Jam Level in Medan City

Traffic congestion is a problem for almost everyone in big cities. Based on the 2017 traffic condition report released by Inrix, a transportation analysis company, on average, Indonesians were wasting time about 51 hours a year stuck in traffic congestion. Therefore, one of the solutions to overcome this traffic jam problem is by creating an application or system which can find routes with the lowest possible level of a traffic jam from the origin location to the destination. Best First Search algorithm works by selecting the best nodes (with the most economical cost) among other generated nodes from the initial node to the goal node. The route generated by the system will be shown on the map, along with the distance, travel time, algorithm running time, and traffic flow condition of the route. The implementation and testing on the system showed that the distance traveled by walking was less than or equal to the distance traveled by driving. On the other hand, using the same travel mode, the route from origin to destination had different distances and travel time than the vice-versa because of the Best First Search algorithm itself. Nevertheless, in some cases, the distance from the origin to the destination may be the same as from destination to origin because both of them are closed together. The average distance, travel time, and algorithm running time generated from the testing were 2.8 km, 20.375 minutes, and 0.182 seconds. However, the routes generated by the system weren't always optimal because the Best First Search algorithm wasn't taking into account the total travel time taken.
The design and implementation of a campus web information system based on micro-service architecture

Abstract In the development of Web information system, the traditional monolithic application architecture is simple and effective for small-scale projects. Because all business logics are combined together in those projects, secondary development and maintenance become very difficult. In recent years, there are methods to solve this problem, which are popular Web distributed architecture solution. The first step of the solution is to separate front-end and back-end of Web system and the second step is to decompose system’s services into micro-services. Micro-service architecture splits application into smaller scale services and each service completes only performs special function. Through service registration centre, micro-service architecture provides unified mechanism of service discovery and registration, it provides unified interfaces for calls from front-end through gateway technology; it protects stability and fault tolerance via back-off mechanism and circuit-breaker mechanism. We have developed a campus Web information system, which adopts two techniques, the separation of front-end and back-end and micro-service architecture By using Spring Cloud framework as back-end developing architecture, the solution of splitting application to micro-services is obtained, and then problems in monolithic application architecture are solved. The high reusability of back-end services is realized and the advantages of micro-service architecture are tested in our system.
Analysis of commercial drone sounds and its identification

The usage of quadcopter types of drones is now on mature and a practical stage and many major manufacturers are expanding its applications into various regions with it. Considerable characteristic of this type of flying object as its maneuverability and practicality is now being focused on how we control this among our urban life from the possibility of any offensive usage. Most of them are either small enough to avoid many current airborne detection methods and cheap enough to use them as disposable. In this paper, we tried to analyze the recorded sounds of a subset of commercial quadcopter types of drones and built a trained simple non-linear neural network filter to classify them among the given sound samples. We borrowed Mel-frequency cepstral coefficients as the well-known methodology of sound analysis process but including some of the parameter adjustments for this research, and applied LeNet neural network filter structure for the following classification test. To maintain the information of adjacent samples among the series of wave samples, 2-D spectrogram planning was applied as for the input signal preprocessing. Most of the frequencies from drones were observed as gathered around 3 to 5Khz, up to around 10Khz, and adjusted LeNet architecture could classify over 10 types of drone categories with over 95% of accuracy.
Media Coding Industry Forum Progress Report

The Media Coding Industry Forum (MC-IF) was formed in September 2018 after several months of preparatory activities. With a fundamental goal of complementing Moving Picture Experts Group (MPEG)’s technical work, the MC-IF has quickly become the focal point for discussions around deployment and licensing of the upcoming next-generation video coding standard, versatile video coding (VVC). The MC-IF gathers industry leaders from the entire media technology ecosystem and currently includes more than 30 member organizations.
Generalized eigenproblem of interval max-min (fuzzy) matrices

In this paper we consider the generalized eigenproblem in max-min (fuzzy) algebra, i.e. given matrices A, B find a vector x and a constant λ such that Ax=λBx where the standard pair of operations, plus and times, have been replaced by the operations maximum and minimum. The entries of the vector or matrix are, in practice, usually not exact numbers and can rather be considered as values in some intervals. In this paper the properties of matrices and vectors with inexact (interval) entries are studied and complete solutions of the strong, the universal, the L-controllable and the R-controllable generalized eigenproblems in max-min (fuzzy) algebra are presented. As a consequence of the obtained results, efficient algorithms for checking all equivalent conditions are introduced.
Publications on book science and history of the book, used in the educational process abroad. Part 1. Study materials

УДК 002.2(100)(
A Novel Ensemble Method for Detecting Outliers in Categorical Data

Outliers are data objects having very important and valuable information, but are rare in their datasets.Several algorithms are developed by various researchers for finding outliers from different types of datasets like multivariate datasets, time series datasets, image datasets and high dimensional datasets.These algorithms are specific to the type of datasets and no general purpose algorithm for detecting outliers in different types of datasets exists in the literature.Moreover most of the algorithms in the literature are capable of dealing with numerical data only.Real world datasets may contain data objects with categorical features in addition to numerical data objects.Here, we propose a novel ensemble learning method for finding outliers in categorical datasets, that ensemble one hot encoder and label encoder together with different outlier detection algorithms such as Local Outlier Factor, One ClassSupport Vector Machine, Elliptic Envelope, Isolation Forest and k-Nearest Neighbor.Experimental results using real world datasets show that the proposed ensemble method for finding outliers in categorical datasets outperforms the other outlier detection techniques.
Formal Perspectives on Conceptualization of Cyberspace

Cyberization gives rise to divergence of cyberspace concepts--cyberspaces to general cyberspace; cybermatics to cyberSciTech; cyber-enabled worlds to cyber-physical-social-thinking hyperspace etc.That is, Cyberspace perception and conceptualization have become more complex with time, due to scalability and as new terms and ideas are added, leading to continues proliferation creating a need for solid characterization.Existing theories are reach and therefore articulated to better understand the physical social thinking hyperspace notion of cyberspace.This paper presents a meaningful inter-disciplinary, transdisciplinary, and multi-disciplinary integration of cyber philosophy, cyber science, and cyber information to present theoretic perspectives on cyberspace--Formal cyberspace.Three main aspects ontology, topological dynamics, and information respectively considered in terms of philosophy, theory in network science, and information theory to define existence of cyberspatial entity.
Efektivitas Penggunaan Aplikasi Daring, Video Conference Dan Sosial Media Pada Mata Kuliah Komputer Grafis 1 Di Masa Pandemi Covid-19

Covid-19 the Impact of application learning patterns in the world of education. This also occurs in the computer graphics 1 corses of Visual Communication Design Program, Trilogi University Jakarta. The process of delivering lecture material switches from offline to perfectly digital online by utilizing educational-based applications by Edmodo, Google Meet, and Instagram as supporters to display the final Exam. The purpose of this study was to determine the level of understanding of students in using the application. The research method used is qualitative by looking at the highest percentage of respondents (students) who use the application. The results of this study are expected to be a benchmark or input in the teaching and learning development process in the coming semester program.
Impact of digital technology in higher education

In the current era, digital technology cannot be overlooked in higher education and other economic factors. Digital technology introduces scopes that expedite blended, e-learning, and online in higher education; suggests a multiple of ways to communicate, learn, correspond, cooperate, and collaborate. Also, digital technology has been more and more widely used in higher education for the continuous development of the economy. This study replicates on the growing importance of digital technology on higher education in Bangladesh over the period 1988-2018. Besides, the study exploits the Johansen cointegration and vector error correction model (VECM) for investigating the positive relationship between digital technology and higher education. The Johansen's cointegration outcomes ascertain that digital technology, higher education, and gross domestic product are cointegrated in the long-run. Furthermore, the VECM outcomes suggest that digital technology can stimulate higher education in both the long run and short run, where learners, educators, and nations are consistently gainer of this country. The study also highlights that higher education consistently contributes to gross domestic product. This research would do twisting up higher education in the kind of digital technology that effectively contributes to educational institutions and countries to remain long-term response. Bangladesh must be beneficial by growing technological development in higher education. For the rapid changes in higher education, the research is advocated that the successful execution of digital technology needs to concentrate on interconnecting structures for transformation: the educator, the educational institutions, and the policymakers. Consequently, public policies would make educational changes in practicing the digital technology of Bangladesh