Reviewerly/exHarmony huggingface dataset:
ANALYSIS OF WI-FI NETWORK QUALITY IN TANJUNGPURA UNIVERSITY LIBRARY BUILDING

Tanjungpura University Library Building as a place that is often crowded with students who use Wi-Fi networks, requires good Wi-Fi signal quality to support smooth and efficient internet access to various digital resources.Wi-Fi data retrieval is inside the Tanjungpura University Library Building, Measuring RSSI (Received Signal Strength Indicator) parameters in the Tanjungpura University Library Building area using the application G-NetWi-Fi, where measurements are carried out by the walk test method using the G-NetWi-Fi application, Make data analysis and conclusions from the results of measuring RSSI (Received Signal Strength Indicator) parameters at the Tanjungpura University Library Building.Analysis of the results to be carried out is to analyze measurement data to compare measurement results with RSSI (Received Signal Strength Indicator) quality standards. Based on the measurements made, there are many measurement data that show the quality of RSSI ranging from good, normal and bad, from the Wi-Fi of Tanjungpura University Library on each route. For the RSSI value obtained by each route, the point and time will certainly vary. Measurement results This depends on the route passed by the user from the Tanjungpura University Library Wi-Fi. Because the more users, the greater the RSSI value that will be obtained.
Rancang Bangun Alat Pengembalian Buku Perpustakaan Secara Mandiri Berbasis Single Board Computer

the process of borrowing and returning library books usually requires a librarian to go through this process, of course this requirement can cause delays in returning books due to library holidays and the difference in free hours from the library and library members. so this research aims to make it easy for library members to be able to return books independently using a storage box that can be done by the system. in this book return box using a raspberry pi 3b+ as a data processing center and using the pi camera to capture the book cover made on the book return box. the security system in this return box uses a selenoid door lock as an automatic door lock which will be routed by a relay and uses rfid as the identity of books, members and librarians. in this study the system can store and return books using the K-Nearest Neighbor (KNN) method with an accuracy of 95% with a processing time of 6.9s
Rancang Bangun Kotak Obat Pintar Berbasis Mikrokontroler

The increase in the number of chronic diseases and their complications to the increase in mortality (death) caused by the low level of discipline in taking drugs. Errors in taking medication that often occurs are not on time and dose, one way to improve compliance in taking drugs is by using compliance aids such as multi-compartment or the like, based on this, a smart medicine box is made with a system designed using RTC (Real Time Clock) which allows to set the scheduling time which can later be displayed on the device, notifications on the device in the form of reminder alarms and also messages that will enter when the schedule is fulfilled, the system is able to find out whether the drug has been taken or not by utilizing infrared sensor, to find out the drug has run out through the frequency value of the drug set by the user, and also the system can provide notification of the drug running out via message notification. The data obtained from the overall test shows that the system can work according to a schedule set using, the fastest time for sending SMS is 5 seconds with an average delivery time of 9 seconds, the percentage of infrared sensor performance on the device is 91.6%. . The system is capable of storing the set data after the power supply is turned off by accessing the EEPROM memory. So it can be said that this system can work well.
Sistem Penentuan Jenis Promosi Berdasarkan Tingkat Loyalitas Pelanggan di CV. XYZ

CV. XYZ is a company engaged in selling fabrics. The company's current customers are around 372 customers, of which 81% or around 301 customers only make transactions less than 10 times and 19% or around 71 customers make transactions more than 10 times, this shows a low level of customer loyalty towards the company. Company owners currently have difficulty determining the type of promotion that will be given to each customer based on their level of loyalty. The method used to segment customers is the Recency, Frequency and Monetary (RFM) method and delivering promotions to customers using WhatsApp API Gateway Services. The results of this RFM method can make it easier for company owners to determine the type of promotion that will be given to each customer as well as the delivery of the promotion in an effort to increase customer loyalty to the company. Of the 24 customers used as sample data, the Most Valuable Customer group has 4 customers, the Most Growable Customer group has 15 customers, the Migrator group has 5 customers and the Below Zeros group has 0 customers.
Geostandards and Geoanalytical Research Bibliographic Review 2022

This Geostandards and Geoanalytical Research Bibliographic Review 2022 presents an overview of a wide range of publications in 2022 focusing on the characterisation of new geoanalytical reference materials (RMs) as well as studies which published measurement results for established RMs. The development of highly accurate new methods and techniques leads to large new analytical data sets for RMs with improved accuracy and precision, which we present in this review.
The construction of Bert fusion model of speech recognition and sensing for South China electricity charge service scenario

Abstract Electric charge service and management is an important part of electric power work. The effective recovery of the electric charge relates to the smooth development of daily work and continuous improvement of the operation and management of power supply enterprises. With the large-scale implementation of the card prepayment system, the problem of electricity customers defaulting on electricity charges has been solved to a large extent, but some large electricity users still fail to pay electricity charges on time. Therefore, under the current situation of power grid development, it is still necessary to strengthen the service and management of electricity charges to promote efficient recovery of electricity charges. Speech recognition technology has increasingly become the focus of research institutions at home and abroad. People are committed to enabling machines to understand human speech instructions and hope to control the machine through speech. The research and development of speech recognition will greatly facilitate people's lives shortly. The development of 5G technology and the proposal of 6G technology make the interconnection of all things not only a hope but also a reality. To realize the interconnection of all things, one of the key technical breakthroughs is the development of a new human–computer interaction sensing system. Under the guidance of relevant theories and methods, this paper systematically analyzes the user structure, electricity charge recovery management and service system, existing problems and causes in South China, and clarifies the necessity of design and application of electricity charge service system in South China power supply companies. The experimental data and empirical analysis results show that the optimized Bert fusion model can provide more digital support for the power supply companies in South China in terms of electricity charge recovery efficiency, management level system improvement, and electricity charge service.
An Analysis on the Success Factors of Implementation System of Knowledge Sharing Program (KSP)

Purpose: This study provides policy implications for improving the implementation system of the Knowledge Sharing Program by analyzing its success factors.&#x0D; Originality: Little has been known about the essential elements for designing an effective knowledge sharing program. This study identified and analyzed the success factors of the KSP based on the perceptions of the project managers and officers from implementing agency of the program who possess tacit knowledge concerning the planning and operation of such a program.&#x0D; Methodology: A model was derived, consisting of 4 actors, 13 categories, and 55 success factors based on the preliminary interviews. A survey was conducted to investigate the success criteria of the KSP, significance of each success factor, and exemplary cases of both success and underperformance, and their consistency was assessed.&#x0D; Result: While no consensus on the criteria for success was found among KSP experts, the need to define the program’s accountability ceiling was evident. Several success factors were consistently found crucial; the interest and will of high-level officials in partner country, the selection of appropriate projects, and the selection of competent researchers. This means that what determine the performance of knowledge sharing are creating knowledge that meets the development needs of partner countries and delivering it in a way that can be applied by partner countries.&#x0D; Conclusion and Implication: The factors determined in the planning stage are significant for success of the program.&#x0D; Implementing agencies should ensure stable foundation for conducting KSP, so that they can mobilize sufficient resources in project planning. The internal evaluation of KSP should be process-oriented, focusing on observable outputs and short-term outcomes as well as on improvement of quality of knowledge sharing activities.
JNZNBRK: Physical Experiments in Light, Modulation, and Substrate

We requested an interview with the Winnipeg-based JNZNBRK art collaborative upon being curious about their work process. The artwork they present on jnznbrk.com suggested a thoughtful aesthetic involving compelling physical exhibits. As we are always interested in the physicalization of data, we were keen to hear about possible considerations that might contribute as relevant to our, and our readers', practices.
Representation Learning Method for Circular Seal Based on Modified MLP-Mixer

This study proposes Stamp-MLP, an enhanced seal impression representation learning technique based on MLP-Mixer. Instead of using the patch linear mapping preprocessing method, this technique uses circular seal remapping, which reserves the seals’ underlying pixel-level information. In the proposed Stamp-MLP, the average pooling is replaced by a global pooling of attention to extract the information more comprehensively. There were three classification tasks in our proposed method: categorizing the seal surface, identifying the product type, and distinguishing individual seals. The three tasks shared an identical dataset comprising 81 seals, encompassing 16 distinct seal surfaces, with each surface featuring six diverse product types. The experiment results showed that, in comparison to MLP-Mixer, VGG16, and ResNet50, the proposed Stamp-MLP achieved the highest classification accuracy (89.61%) in seal surface classification tasks with fewer training samples. Meanwhile, Stamp-MLP outperformed the others with accuracy rates of 90.68% and 91.96% in the product type and seal impression classification tasks, respectively. Moreover, Stamp-MLP had the fewest model parameters (2.67 M).
Are GNNs the Right Tool to Mine the Blockchain? The Case of the Bitcoin Generator Scam

A Bitcoin Generator Scam (BGS) is a type of cyberattack in which scammers promise to provide individuals with free cryptocurrencies if they pay a mining fee. Although graph neural networks (GNNs) have been used for detecting other cryptocurrency frauds, the usefulness of these methods for BGS detection has not been studied. In this paper, we carry out extensive experiments to assess the use of both standard machine learning (ML) methods and GNNs to detect Bitcoin transactions associated with activities stemming from Bitcoin Generator Scams. We observe that the over-smoothing problem exists in GNNs designed for BGS detection and show that Random Walk Positional Encoding (RWPE) allows representing long-range interactions between far-away transactions in GNNs without causing over-smoothing. We show that the General, Powerful, Scalable (GPS) Graph Transformer with RWPE outperforms both GNN and ML based state-of-the-art fraud detection methods in Bitcoin Generator Scams. We also analyze the effectiveness of Breadth First Search (BFS) for graph sampling and show that it should not be used as it induces bias toward the subnetwork structure. We propose the Random First Search (RFS) sampling alternative and show that this is a more suitable solution.
Avoiding inferior clusterings with misspecified Gaussian mixture models

Abstract Clustering is a fundamental tool for exploratory data analysis, and is ubiquitous across scientific disciplines. Gaussian Mixture Model (GMM) is a popular probabilistic and interpretable model for clustering. In many practical settings, the true data distribution, which is unknown, may be non-Gaussian and may be contaminated by noise or outliers. In such cases, clustering may still be done with a misspecified GMM. However, this may lead to incorrect classification of the underlying subpopulations. In this paper, we identify and characterize the problem of inferior clustering solutions. Similar to well-known spurious solutions, these inferior solutions have high likelihood and poor cluster interpretation; however, they differ from spurious solutions in other characteristics, such as asymmetry in the fitted components. We theoretically analyze this asymmetry and its relation to misspecification. We propose a new penalty term that is designed to avoid both inferior and spurious solutions. Using this penalty term, we develop a new model selection criterion and a new GMM-based clustering algorithm, SIA. We empirically demonstrate that, in cases of misspecification, SIA avoids inferior solutions and outperforms previous GMM-based clustering methods.
ANALISIS PENGARUH VARIABEL PENDUGA CUACA EKSTREM DI KOTA BENGKULU DENGAN MENGGUNAKAN STATISTICAL PRODUCT AND SERVICE SOLUTIONS (SPSS)

The Bengkulu City area often experiences extreme weather with the potential for flooding and affects various types of human activities. This study aims to determine the effect of extreme weather predictor variables in Bengkulu City by using Statistical Product and Service Solutions (SPSS). Extreme weather indicators are reviewed based on rainfall with estimating variables in the form of air pressure, humidity, air temperature, and wind speed, for 5 years (2017-2021) obtained from the BMKG Station on Baai Island, Bengkulu City. Data processing using SPSS method. Data analysis was carried out statistically and descriptively. Based on the results of the study, the correlation between the estimator variables on extreme rainfall is quite good with r = 0.661, and the error value (RMSE) is 27,124. Furthermore, the homogeneity test between extreme rainfall indicators and extreme weather estimators includes air pressure, air temperature, wind speed, and air humidity, showing homogeneity in 2019. This indicates the predictor variable has the same direction to extreme rainfall, where the error value is obtained tends to be relatively small. The estimator variables, namely air pressure and humidity, have a significant relationship with extreme rainfall. Predictions using data (2017-2021) show that in 2022, extreme rainfall events will occur for a relatively long time, namely in January, March, May, June, July, August, October, and December. The most extreme rainfall intensity occurs in January
Analysis of Flood Vulnerability Levels Using Overlay Method With System-Based Scoring Geographical Information (Case Study: District Tangerang)

This research aims to determine the factors of flood disasters in Tangerang district, which consist of land height, slope, soil type, land use, river density, and rainfall, and to find out the results of flood mapping in Tangerang district. The research method used is the overlay method with scoring. This research uses secondary data consisting of rainfall data for the period 2022-2020, shp Admin data from Tangerang district, watershed data throughout Indonesia, OSM data throughout Indonesia, slope data throughout Indonesia, DEM data throughout Indonesia, DSMW data throughout Indonesia, 2017 landcover data. Data were processed using Microsoft Excel software, Arc GIS 10.8, and QGIS 3.26.0. Based on the results obtained, the flood disaster factors in Tangerang district that are very dominant in influencing the occurrence of floods in Tangerang district are soil type and slope. Meanwhile, the results of flood mapping in Tangerang district are categorized into three classes: not vulnerable, moderately vulnerable, and fragile. Four sub-districts in Tangerang Regency are not prone to flood disasters, including Panongan, Legok, Cisauk, and Pagedangan sub-districts. Meanwhile, the Tangerang district, which is categorized as quite vulnerable, consists of 9 sub-districts, namely the sub-districts of Kelapa Dua, Curug, Cikupa, Tigaraksa, Jambe, Solear, Jayanti, Cisoka, Balaraja. Meanwhile, there are 16 sub-districts in Tangerang Regency which are categorized as very vulnerable, namely Pasar Kemis, Sindang Jaya, Kresek, Gunung Kaler, Sukamulya, Sepatan, Sepatan Timur, Rajeg, Kemiri, Kronjo, Mekar Baru, Mauk, Sukadiri, Pakuhaji, Teluk Naga, Kosambi districts.
PENGARUH MEDIA KATAM (KARTU KATA BERGAMBAR) TERHADAP KETERAMPILAN MENULIS PERMULAAN PADA PEMBELAJARAN BAHASA INDONESIA SISWA KELAS I SDN 01 LUBAI ULU

The background of the problem in this study is that there are still many students' writing abilities which are still lacking, because educators at SD Negeri 01 Lubai Ulu still rarely use learning media which aims to develop students' initial writing skills. This study aims to determine the effect of the use of KATAM media on the initial writing ability of the first graders of SD Negeri 1 Lubai Ulu. The research method used is an experimental method using KATAM media (picture word cards). The subjects of this study were students in class I A and I B of SD Negeri 01 Lubai Ulu, which consisted of 49 students. Methods of data collection using tests and documentation. The test instrument was in the form of essay questions which totaled 10 questions to measure students' writing results. Data analysis technique using Independent Sample T-test. The results showed that the influence of ritatoon media can improve the learning outcomes of elementary school students in Indonesian language material which can be seen from the results of learning to test the hypothesis (Independent Sample T-Test) in the form of a significance value in this study, namely 0.000 &lt;0.05, which means Ho is rejected Ha is accepted&#x0D; Keywords: KATAM Media, Student Beginning Writing
Time course of effective connectivity associated with perspective taking in utterance comprehension

This study discusses the effective connectivity in the brain and its time course in realizing perspective taking in verbal communication through electroencephalogram (EEG) associated with the understanding of Japanese utterances. We manipulated perspective taking in a sentence with the Japanese subsidiary verbs -ageru and -kureru , which mean “to give”. We measured the EEG during the auditory presentation of the sentences with a multichannel electroencephalograph, and the partial directed coherence and its temporal variations were analyzed using the source localization method to examine causal interactions between nineteen regions of interest in the brain. Three different processing stages were recognized on the basis of the connectivity hubs, direction of information flow, increase or decrease in flow, and temporal variation. We suggest that perspective taking in speech comprehension is realized by interactions between the mentalizing network, mirror neuron network, and executive control network. Furthermore, we found that individual differences in the sociality of typically developing adult speakers were systematically related to effective connectivity. In particular, attention switching was deeply concerned with perspective taking in real time, and the precuneus played a crucial role in implementing individual differences.
High-precision binocular optical tracking method based on transformation constraints

Binocular optical tracking systems are an important component in the field of 3D measurement and reconstruction, and the calibration of objects with reflective marker points attached, hereafter referred to as marker object, is a key factor in the overall measurement accuracy. In response to the challenge of using more sophisticated and expensive instruments such as CMM for the calibration of traditional marker object, this paper proposes a short baseline, high-precision, fast, and low-cost marker object calibration method based on transformation constraints. A binocular calibration system with a short baseline and small field of view is designed to improve the initial spatial resolution accuracy. The multi-angle projection of marker points on the marker object under known fixed transformation constraints is collected through precision servo rotary stage control, and a global error optimization method based on Newton's iterative method is proposed to reduce the estimation error of the initial marker points. The marker object calibration system built in this paper enables a spatial position accuracy resolution of 0.15mm between marker points on the marker object, realizing the need for low-cost, fast and high-precision calibration, and achieving high-precision tracking of binocular optical tracking systems.
DEVELOPMENT OF LEARNING MODULES WITH DATA PRESENTATION MATERIALS TO INCREASE STUDENTS' INTEREST IN LEARNING

The aim of the research is to develop a data presentation module to increase students' interest in learning. This type of research is research and development (R&amp;D), with the ADDIE model. Qualitative and quantitative data analysis techniques. Validation results of the material section 4.26 valid category. The validation of media experts is 4.50 valid categories and the validation of linguists is 4.87 categories which are very valid. Practical results in confined classes and fields. The results of practicality in the limited trial using a student response questionnaire and a questionnaire of initial and final student learning interest, the results of the practicality percentage obtained a maximum value of 2.72 in the very practical category, the practicality test using a final learning interest questionnaire with a value of 4.9 in the very practical category. The practicality result in the field trial was 4.72 in the very practical category. The results of the effectiveness of the test module obtained an average score of 75 in the complete category. Hopefully the results obtained above can make further researchers easier to understand so as to increase student learning interest
Meningkatkan Kemampuan Menulis Teks Deskripsi Menggunakan Model Pembelajaran Think Talk Write (TTW) dengan Media Lingkungan Alam

This research is Classroom Action Research (PTK) with the aim of improving the ability to write descriptive text using the Think Talk Write (TTW) learning model with natural environmental media. The natural environmental media used as objects of observation are those in the school environment. Subeyek, in this research, were 32 students at SMP 1 Pandak Bantul class VII. Data collection techniques in this research were interviews, tests and documentation. This research carried out two cycles, with the stages in each cycle being planning, action, Observation, and reflection. The results of student completion in the cognitive domain of cycle I were 50% and increased in cycle II to 84.37%; the affective domain in cycle I was 68.75%, increased in cycle II by 93.75%, Observation of student activities in cycle I was 60 .63 increased in cycle II by 90.71, Observation of teacher activities in cycle I was 68.35, increased in cycle II by 91.40. These results show that applying the TTW learning model with natural environment media can improve the ability to write descriptive text in class VII A students at SMP 1 Pandak Bantul.