Reviewerly/exHarmony huggingface dataset:
Penerapan Togaf Architecture Pada Smart Nature Tourism Berbasis Website

&lt;p&gt;Abstrak. Layanan informasi wisata yang tersebar di Kecamatan Kadudampit sangat minimal dan tidak semua tempat wisata terpublikasi dengan baik, akibatnya wisatawan tidak mengetahui detil wisata yang akan mereka kunjungi. Pengelolaan data pengunjung juga masih menggunakan cara manual sehingga memakan banyak waktu dan tenaga. Artikel ini menyajikan model sistem layanan informasi berbasi website. Framework yang digunakan pada perancangan sistem adalah Togaf ADM yang terdiri dari 5 fase yaitu: Preliminary Phase, Architecture Vision, Business Architecture, Information Systems Architectures, Technology Architecture. Hasil uji menunjukkan sistem telah dapat digunakan sebagai media promosi secara luas dan lengkap, dapat melayani penjualan tiket wisata secara online, serta dapat mengelola data pengunjung secara efisien.&lt;/p&gt;&lt;p&gt;Kata kunci: Togaf Architecture, Smart Nature Tourism, Sistem Informasi, Berbasis Web &lt;br /&gt; &lt;br /&gt;Abstract. Tourist information services scattered in Kadudampit District are very minimal and not all tourist attractions are well publicized, as a result, tourists do not know the details of the tours they will visit. Management of visitor data is also still using the manual method so that it takes a lot of time and effort. This article presents a website-based information service system model. The framework used in system design is Togaf ADM which consists of 5 phases, namely: Preliminary Phase, Architecture Vision, Business Architecture, Information Systems Architectures, Technology Architecture. The test results show that the system can be used as a broad and complete promotional media, can serve online tourist ticket sales, and can manage visitor data efficiently.&lt;/p&gt;&lt;p&gt;Keywords: Togaf Architecture, Smart Nature Tourism, Information System, Web-Based&lt;/p&gt;
Results of Research Data Management Survey at Tohoku University

Appropriate design of organizational RDM (research data management) environment is required for each institution in accordance with social demands such as promotion of open science and research fairness. We conducted a survey on research data management using the questionnaire template published on AXIES (Academic eXchange for Information Environment and Strategy) in order to collect data that provide a starting point to understand Tohoku university researcher&#x0027;s needs and concerns regarding research data management. This paper will report the result of the survey at Tohoku university.
Analysis of Answer History Data to Detect Learner's Hesitation When Solving Word-reordering Problems

We are developing a web application to detect the learner&#x0027;s hesitation that occurs when answering word-reordering problems (WRPs). In our web application, the movement distance, number of drags and drops, number of U turns, and the number of times words are grouped, among others, are recorded and calculated from the mouse trajectory information. Machine learning is adopted based on these features. We applied supervised learning (random forest) to detect learners&#x0027; hesitation. Currently, the accuracy of the hesitation prediction is approximately 83&#x0025;. In this study, we focus on the register and grouping functions that can be used by learners in our web application. As a new feature of machine learning, we created features related to registers and grouping, focusing on the semantic chunks of English, and attempted to improve the hesitation prediction accuracy.
TINJAUAN SUNGAI ITEM SUNTER SETELAH DINORMALISASIKAN SEBAGAI PENGENDALIAN BANJIR DI JAKARTA PUSAT

The purpose of this research to review the Item Sunter River which has been normalized as flood control in Central Jakarta. This research was conducted to determine the causes of flooding due to the overflow of the river that occurred in 2020. The review was carried out by analyzing the flood discharge of the river by calculation of the planned flood discharge using the Nakayasu Synthesis Unit Hydrograph method in return periods of 2, 5, 10, 25, and 50 years respectively of 88.44 m3/s, 116.52 m3/s, 137.85 m3/s, 168.39 m3/s, and 193.22 m3/s compared to the calculation river flow rate using the Manning equation of 205.94 m3/s. The calculation result shows that river flow is still sufficient for the planned flood discharge. Then a further analysis is carried out on the factors of waste management, sedimentation, and pump house. The results of the analysis show that the accumulation of garbage occurs in the river basin area, sedimentation is 20% of the flow capacity, and the pump house is inadequate due to flooding. Therefore, it is necessary to prevent and clean up rubbish in river area, routine dredging sedimentation, and maintenance of water pumps must be on standby at all times.
On independence of time and cause

For two independent, almost surely finite random variables, independence of their minimum (time) and the event that one of them is either greater, equal or less than the other (cause) is completely characterized. It is shown that, other than for trivial cases where, almost surely, one random variable is greater than or equal to the other, this happens if and only if both random variables are distributed like the same strictly increasing function of two independent random variables, where either both are exponentially distributed or both are geometrically distributed. This is then easily generalized to the multivariate case.
APLIKASI PASURUAN CITY GUIDE BERBASIS ANDROID DENGAN MENGGUNAKAN METODE LBS (LOCATION BASED SERVICE)

&lt;p&gt;&lt;span class="fontstyle0"&gt;Abstract: &lt;/span&gt;&lt;span class="fontstyle2"&gt;Smart City is a term in assessing a City that has succeeded in utilizing Information Technology as a means of supporting the government and the community in providing facilities and services. Based on the Smart&lt;br /&gt;City concept, an Android-based "Pasuruan City Guide" application will be made using the LBS (Location Based Service) method, in accordance with the name of the application, the city that will be used as a research is&lt;br /&gt;Pasuruan, the "Pasuruan City Guide" application will display Service information Public, besides that there is also Pasuruan City Event information.&lt;/span&gt;&lt;/p&gt;&lt;p&gt;&lt;span class="fontstyle2"&gt;&lt;br /&gt;&lt;/span&gt;&lt;span class="fontstyle3"&gt;Keywords&lt;/span&gt;&lt;span class="fontstyle2"&gt;: Pasuruan City Guide, LBS, Public, Event, Android&lt;/span&gt; &lt;br /&gt;&lt;br /&gt;&lt;/p&gt;
THE APPLICATION OF MACHINE LEARNING METHODS TO PROBLEMS ON GRAPHS

This article provides an overview of machine learning methods applicable to graph tasks. It also provides a summary of how to represent graphs and a description of the machine learning application to graphs.
Research on collaborative construction of emergency logistics support system and blockchain

Blockchain was once hailed as an important direction of the fourth industrial revolution with its decentralization concept. The logistics industry is the largest application scenario of blockchain after finance. This paper designed the emergency logistics support system which is based on blockschain collaboration. And this system is constructed from material supply and demand management, material scheduling management, etc. In this system, smart contracts are automatically executed throughout the process and highly reliable, providing a shared but non-tamperable distributed logistics database to ensure the real-time query logistics information. Under the joint maintenance of all parties, every logistics transfer is recorded on the blockchain. This will not only improve the efficiency of emergency logistics management in emergencies, but also help enhance transparency. At the same time, the timeliness and adaptability of material allocation have been fully guaranteed.
Coding Challenge Answers: Evaluation and Management Services

The answers to the Coding Challenge are presented.
Detecting Anomalies in Daily Activity Routines of Older Persons in Single Resident Smart Homes: Proof-of-Concept Study (Preprint)

<sec> <title>BACKGROUND</title> One of the main challenges of health monitoring systems is the support of older persons in living independently in their homes and with relatives. Smart homes equipped with internet of things devices can allow older persons to live longer in their homes. Previous surveys used to identify sensor-based data sets in human activity recognition systems have been limited by the use of public data set characteristics, data collected in a controlled environment, and a limited number of older participants. </sec> <sec> <title>OBJECTIVE</title> The objective of our study is to build a model that can learn the daily routines of older persons, detect deviations in daily living behavior, and notify these anomalies in near real-time to relatives. </sec> <sec> <title>METHODS</title> We extracted features from large-scale sensor data by calculating the time duration and frequency of visits. Anomalies were detected using a parametric statistical approach, unusually short or long durations being detected by estimating the mean (μ) and standard deviation (σ) over hourly time windows (80 to 355 days) for different apartments. The confidence level is at least 75% of the tested values within two (σ) from the mean. An anomaly was triggered where the actual duration was outside the limits of 2 standard deviations (μ−2σ, μ+2σ), activity nonoccurrence, or absence of activity. </sec> <sec> <title>RESULTS</title> The patterns detected from sensor data matched the routines self-reported by users. Our system observed approximately 1000 meals and bathroom activities and notifications sent to 9 apartments between July and August 2020. A service evaluation of received notifications showed a positive user experience, an average score of 4 being received on a 1 to 5 Likert-like scale. One was poor, two fair, three good, four very good, and five excellent. Our approach considered more than 75% of the observed meal activities were normal. This figure, in reality, was 93%, normal observed meal activities of all participants falling within 2 standard deviations of the mean. </sec> <sec> <title>CONCLUSIONS</title> In this research, we developed, implemented, and evaluated a real-time monitoring system of older participants in an uncontrolled environment, with off-the-shelf sensors and internet of things devices being used in the homes of older persons. We also developed an SMS-based notification service and conducted user evaluations. This service acts as an extension of the health/social care services operated by the municipality of Skellefteå provided to older persons and relatives. </sec>
CGH-assisted metrology testbed for the Thirty Meter Telescope primary mirror

The Thirty Meter Telescope primary mirror consists of 492 1.4 m diameter hexagonal segments. A CGH-assisted interferometric testbed has been developed to quickly and accurately measure surface figure error of the 82 different segment prescriptions. In this paper, technical aspects of the testbed will be described, including interferometer design, techniques to reduce sensitivity to vibration and turbulence, use of CGH phase fiducials for 6 degree-of-freedom alignment of the interferometer to the Test Plate, proximity sensors for segment-to-Test Plate alignment, synthetic extended source technique to mitigate coherent artifacts, characterization of instrument transfer function, and system calibration. A surface figure error map of a "Type 0" full-scale segment will also be presented.
Ecosystem Approach in Education: Foreign and Russian Practices

The article is devoted to the current research in the field of ecosystem approach in education. It examines the main characteristics of educational ecosystems and gives examples of existing innovation and educational ecosystems abroad and in Russia.
Special issue on Performance modeling, benchmarking, and simulation of high performance computing systems

Concurrency and Computation: Practice and ExperienceVolume 34, Issue 20 e7165 EDITORIAL Special issue on Performance modeling, benchmarking, and simulation of high performance computing systems Steven A. Wright, Corresponding Author Steven A. Wright steven.wright@york.ac.uk orcid.org/0000-0001-7133-8533 Department of Computer Science, University of York, York, United Kingdom Correspondence Steven A. Wright, Department of Computer Science, University of York, York, United Kingdom. Email: steven.wright@york.ac.ukSearch for more papers by this author Steven A. Wright, Corresponding Author Steven A. Wright steven.wright@york.ac.uk orcid.org/0000-0001-7133-8533 Department of Computer Science, University of York, York, United Kingdom Correspondence Steven A. Wright, Department of Computer Science, University of York, York, United Kingdom. Email: steven.wright@york.ac.ukSearch for more papers by this author First published: 15 July 2022 https://doi.org/10.1002/cpe.7165Read the full textAboutPDF ToolsRequest permissionExport citationAdd to favoritesTrack citation ShareShare Give accessShare full text accessShare full-text accessPlease review our Terms and Conditions of Use and check box below to share full-text version of article.I have read and accept the Wiley Online Library Terms and Conditions of UseShareable LinkUse the link below to share a full-text version of this article with your friends and colleagues. Learn more.Copy URL Share a linkShare onFacebookTwitterLinkedInRedditWechat No abstract is available for this article. Volume34, Issue20Special Issue: Performance Modeling, Benchmarking and Simulation of High-Performance Computing Systems (PMBS2020). International Conference on Innovations in Intelligent Systems and Applications (INISTA 2021). Recent advances in quantum computing and quantum neural networks10 September 2022e7165 RelatedInformation
An efficient heuristic approach combining maximal itemsets and area measure for compressing voluminous table constraints

Constraint Programming is a powerful paradigm to model and solve combinatorial problems. While there are many kinds of constraints, the table constraint is perhaps the most significant—being the most well-studied and has the ability to encode any other constraints defined on finite variables. However, constraints can be very voluminous and their size can grow exponentially with their arity. To reduce space and the time complexity, researchers have focused on various forms of compression. In this paper, we propose a new approach based on maximal frequent itemsets technique and area measure for enumerating the maximal frequent itemsets relevant for compressing table constraints. Our experimental results show the effectiveness and efficiency of this approach on compression and on solving compressed constraint satisfaction problem.
Readability and letters

In the present, there are different indices that measure the difficulty level of reading a text, i.e. the readability of a text. Different studies have been made on the frequency of occurrence of letters in several languages, but as we know there are not thorough studies on the occurrence of letters according to the readability of a text. The main objective of the present work is to study the frequency of occurrence of letters in a text according to its legibility. This occurrence will be approached from two points of view. First, through the so-called power indices of game theory. To the best of our knowledge, it is the first time that a game is associated with a text and the influence or power of each letter will be analysed by means of the so-called power indices of the game theory. Thus, we present a new application of game theory. Second, by means of basic statistics to study relative frequency of letters in a text.
Faciem - Microservice-based application for face recognition in mobile devices

Nowadays, mobile devices offer a varied range of sensors that can be simultaneously used in diverse applications and contexts. Faciem is a platform conceived to explore these characteristics and to validate the presence of a distinct person in specified circumstances, according to the application data. The verification is performed by the mobile device, integrating GPS – Global Positioning System localization and user face recognition. The system architecture is based on microservices to optimize the application and allow a lot of diversity of mobile devices, with diverse characteristics such as processor and memory capacity, to execute the application. The analysis of a use case, where students attendance is verified, shows promising results and validates the proposed implementation.
AI Coach for Badminton

In this competitive world of sports, to become an ideal player, one must maintain his nutrition and physique. Every motion involved in the sport must be efficiently carried out to employ the active muscles and eventually sustain energy depletion levels. Badminton is one sport where player movements are relatively easier to track using video analytics. The stroke movements captured through the camera can be used to examine the hand and hip coordination, placement of the leg and the varied upper bound and lower bound angles of the strokes. The prediction of a much better stance and orientation of the muscles, erroneous playing techniques, joint fatigue and several such aspects can be forecasted through an intelligent system as a recommendation. This research focuses on various techniques of neural networks to analyse the image retrieved from a badminton game. Ideal and efficient data is vastly available on the World Wide Web, and a series of data is then be taken down as per the requirements of the subjects, i.e., taking into consideration, player’s body type and consecutively keeping the subjects diet and physique under observation while noting down the muscles which get activated during the execution of the said stroke.
A Fully Integrated 1.7mW Attention-Based Automatic Speech Recognition Processor

This brief presents a low-power attention-based automatic speech recognition (ASR) processor achieving real-time recognition capability. The proposed attention window algorithm, compact end-to-end neural-network topology, and efficient computation dataflow effectively minimize the hardware complexity and power consumption, enabling a fully integrated low-power ASR processor solution without the necessity of any off-chip memory resource. The proposed design techniques reduced 98.9% weight memory and 92.1% power consumption with minimal degradation of 2.24% in recognition accuracy. The proposed ASR processor operates at 100MHz with 1.7mW at 0.9V, demonstrating 2x and 1.68x performance improvements in speed and power, respectively, compared to the previous ASR designs that require additional supports of off-chip memory or external decoder.
The activation of the focal attention sub-system as a product of a hierarchical process during the interaction with virtual products

In studies related to the behavior patterns that are generated from the interaction processes of a group of users with virtual products., It was detected that the acti-vation of Focal Attention sub-system is a constant not only for persons with normal vision also for persons with vision weakness. However, there are behav-ioral differences depending on the user´s dominant sensory mechanism related with physio-anatomical and cognitive characteristics of the user. The effects are observed in the time of execution of the tasks, number of sensory mechanisms used during the process, stress responses generated by the fulfillment of objec-tives among others.The aim of these studies is to promote reflections on the attentional processes that are carried out from the interaction of a user with virtual products and their work systems. And explore how Focal Attention processes change with the personal characteristics of a person.
Application of Digital Data Analysis Technology in Education

The main directions of digitalization of the education system are considered, the infrastructural and technological aspect of new strategic directions of development is analyzed. The author analyzed information systems and services in education, taking into account the possibility of using technologies for analytical data processing. The problem of using data analytics tools in education at present is the lack of uniform formats and tools for integrating information systems. Data in education accumulates in various solutions that do not share the results of the educational process. Based on this, it is impossible to build a clear system of end-to-end interaction between systems on common platforms. The author aims to solve this problem by modeling an integrated solution for data analysis at all levels of education. The article proposes technical and organizational solutions for the creation of integrated analytics services that allow accumulating and transmitting data on educational results during the transition of a student between learning levels. The analysis tools are based on the use of big data technologies.
Development of a low-cost remote sensor for ground-based solar radiation and related data measurement

Over the past three decades, solar energy has gained a lot of attention because of its energy potential and environmental-friendly aspect. To estimate its energy potential, most researchers use satellite approximation solar radiation data or imagery as their only data source, which is not sufficient as the images are taken high above the ground which results in the loss of the part of the resolution, and besides that, they also lack the hourly or daily variations, which is a critical component for an accurate estimation. This paper aims to provide the renewable energy research community with a low-cost and portable remote sensor for ground-based solar radiation and related data measurement. The remote sensor comprises a series of low-cost and accurate sensors, a single board computer, two Arduino micro-controllers, two Real Time Clocks, two mini-solar panels, an internet modem, two onboard batteries and six (6) relays, all interfaced in the Python Programming Language. The operation of the remote sensor is discussed in this paper along with a survey of its energy consumption. Data validation was done by comparing our recorded data with the Japan Weather Station data, and the result showed an accuracy of about 90%.