Reviewerly/exHarmony huggingface dataset:
Peramalan Curah Hujan dengan Pengelompokan Bulan Menggunakan Metode Double Exponential Smoothing dari Brown

It is important to know the future rainfall, the way is to predict rainfall. By knowing future rainfall, development strategies such as irrigation, dams, urban drainage, harbour docks, agriculture, and even disaster mitigation strategies will be right on target. The purpose of this study is to predict the rainfall for Boyolali Regency and Surakarta City, Central Java in 2020-2021 with Brown's double exponential smoothing method. The type of data used is secondary data, which is obtained from the Meteorology, Climatology and Geophysics Agency of Semarang Climatology Station. The smoothing value, alpha, used in each month was varies, because the rainfall data is grouped first based on the same month, before it was forecasted. The results showed that the highest rainfall in 2020 was 490.73 mm (April) and the lowest was 3.25 mm (August). While for 2021, the highest rainfall was 521.37 (April) and the lowest was 3.25 mm (August), with an MSE of 14731.56, RMSE of 121.37, MAD of 97.42, and SSE of 176778.69.
Contrast Enhancement in Infrared and Color Images by Homomorphic Filtering and Cluster-Chaotic Optimization (CCO)

Image contrast enhancement is a technique used in image processing to extract more information from an image, which can be used in complex image analysis systems. This study proposes a new approach to enhance image contrast using homomorphic filtering (HF) and the cluster chaotic optimization metaheuristic algorithm, an alternative to conventional methods. Chaotic algorithms are based on chaos theory, which defines chaos as the behavior of nonlinear systems that are unstable and nonperiodic. HF is a technique that enhances images with non uniform lighting and removes multiplicative noise. Unlike histogram equalization, commonly used in conventional methods, HF uses generalized superposition. To evaluate the effectiveness of this approach, we conducted several tests.
Сontemporary Medical Decision Support Systems Based on Artificial Intelligence for the Analysis of Digital Mammographic Images

The relevance of implementing artificial intelligence (AI) technologies in the diagnosis of breast cancer (BC) is associated with a continuing high increase in BC incidence among women and its leading position in the structure of cancer incidence. Theoretically, using AI technologies is possible both at the stage of screening and in clarifying BC diagnosis. The article provides a brief overview of AI systems used in clinical practice and discusses their prospects in BC diagnosis. Advances in machine learning can be effective to improve the accuracy of mammography screening by reducing missed cancer cases and false positives.
Addressing Human Speech Natures in Single-Channel speaker Extraction Network

&lt;p&gt;The purpose of single-channel speaker extraction is to distill the pure speech of the target speaker from a multi-talker speech mixture. Typically, an auxiliary reference network is employed to obtain the voiceprint features of the speaker’s speech as the input stimulus for the main speech extraction network, improving the robustness of the speech extraction. However, current research has paid little attention to the time-series characteristics of speech signals, resulting in a mismatch between the receptive field and signal features. Additionally, commonly used speaker extraction models do not consider the spectral distribution characteristics of speaker speech. In this paper, we address these issues by extending the ConvNeXt model in image processing to TD-ConvNeXt model and combining it with TCN block to form the main body of our speech extraction network. We also revamp the ConvNeXt model to a new Spk block for the auxiliary network, which learns speaker identity information features from reference speech as embedding vectors. By utilizing this approach, we have achieved better results in speaker identification without compromising the quality of speech extraction. We also use multi-task learning to jointly train the extraction network and auxiliary reference network. Extensive experiments have been conducted to verify the significant single-channel target speech extraction performance improvements of our proposed model.&lt;/p&gt;
Evaluation of irradiance variability adjustments for subhourly clipping correction

&lt;p&gt;Subhourly changes in solar irradiance can lead to energy models being biased high if realistic distributions of irradiance values are not reflected in the resource data and model. This is particularly true in solar facility designs with high inverter loading ratios (ILRs). When resource data with sufficient temporal and spatial resolution is not available for a site, synthetic variability can be added to the data that is available in an attempt to address this issue. In this work, we demonstrate the use of anonymized commercial resource datasets with synthetic variability and compare results with previous estimates of model bias due to inverter clipping and increasing ILR.&lt;/p&gt;
An Accessible Python based Author Identification Process

identification also known as 'author attribution' and more recently 'forensic linguistics' involves identifying true authors of anonymous texts.The Federalist Papers are 85 documents written anonymously by a combination of Alexander Hamilton, John Jay, and James Madison
Analysis of library resources and services in developing confidence for language use

Reading is a form of social activity that connects the readers to transformational learning. Library resources offer an opportunity to build competence in language use. In essence, the library resources can impact how students perceived reading as a channel to academic success, which in turn—develops a lifelong learner. This study was an exploratory study that analyzed how library resources and services develop confidence in language use. Eight (8) college students were purposively selected for one-on-one interview. The data gathered were narrative from college students on how they utilized resources from their local library. The findings suggested that college students considered their local library as a reliable site to search for information. In-depth analysis showed that students were confident in language use because their resources were reliable and accurate. Language use covered mostly phonological and morphological aspects of language, including lexicons, writing styles, and writing formats. Librarians had the role of encouraging the students to read contents from the library and assisting them in utilizing in-print and online contents. Library assistance enabled the students to build their ideas into meaningful developmental contents. This study provided an angle for language confidence, language success, and language competence. These components of language learning were essential in predicting the linguistic capacity of students.
Exploring the potential of an Augmented Reality sandbox for geovisualization

Abstract. Geovisualization provides theories, methods, and tools for visualizing processes on the earth’s surface. One of the key challenges of the field is to find interesting and engaging ways to display geographical data. In this paper, we focus on the Augmented Reality (AR) Sandbox. An AR Sandbox combines a box filled with sand with a 3D camera and a projector to explore the topography of the sand terrain in real time and allow water flow simulations. This direct interaction between user and topography makes the AR sandbox a fascinating, explorative tool in the field of geovisualization.In this paper, we give an overview about how an AR Sandbox is built, what components are required, and how configuration, calibration or adding additional features work. We also discuss ways to improve the usability of the AR Sandbox or change its appearance to make it more suitable for specific use cases in geovisualization. Of particular importance is the DEM tool, which allows real-life data to be remodeled in the AR Sandbox to explore the terrain, create rainfall simulations, or export the current terrain as a DEM. Further advantages of using an AR sandbox for geovisualization are the hands-on methodology and gamification aspects, which motivate people to interact with topography and improve learning effects in the geosciences.
Novel machine learning based authentication technique in VANET system for secure data transmission

&lt;p&gt;Adaptive transport technologies based on vehicular ad hoc networks (VANET) has proven considerable potential in light of the developing expansion of driver assistance and automobile telecommunication systems. However, confidentiality and safety are the vital challenges in vehicular ad hoc networks which could be seriously impaired by malicious attackers. While protecting vehicle privacy from threats, it is imperative to stop internal vehicles from putting out bogus messages. Considering these issues, a novel machine learning based message authentication combined with blockchain and inter planetary file system (IPFS) is proposed to achieve message dissemination in a secured way. Blockchain is the emerging technology which attempts to solve these problems by producing tamper proof events of records in a distributed environment and inter planetary file system used in the framework is a protocol designed to store the event with content addressability. Along with this combined technology, the source metadata information collected from the inter planetary file system is stored via a smart contract and uploaded to the distributed ledger technology (DLT). For performing event authentication, K-means clustering and support vector machine (SVM) classifier is employed in this framework. K-means clustering performs clustering of vehicles and it is marked malicious or not malicious. After clustering, support vector machine classifier detects the malicious event messages. By this way, the malicious messages are identified and it is dropped. Only the secure messages are forwarded in the network. Finally, our approach is capable of creating a safe and decentralized vehicular ad hoc network architecture with accountability and confidentiality through theoretical study and simulations.&lt;/p&gt;
The Web-Based Sales Information System for A Store in Tegal District

The development of information systems in the age of digital reform is very rapid, as the development of science and technology changes with the age of time. In mankind's lives, information systems play a crucial role in the quality of resources, both human resources, and natural resources, and can increase productivity in both services and goods. The development of the web-based information system application in the regional planning system is conducted using waterfall development methods. With the original shop website online, the owners make more money because the COVID-19 pandemic has felt the income is rapidly falling. With the website of the original store online, the original store owner is happy and content to increase income before there was no website.
Pembangunan Dashboard Inventory Pada Bisnis Ritel

In this study, it will be explained how to create a data mart in a retail business to answer the KPI (Key Performance Indicator) inventory of goods which will be visualized in the form of a dashboard to make it easier for company executives to see the condition of inventory in stores. In making a data mart, it will be explained how the ETL (Extraction, Transformation and Loading) process from a transactional database from 9 stores becomes a data mart. The data mart in this study was built using a star schema and produced 4 dimension tables and 1 fact table. Star schema is used to simplify the query process when you want to display data on the dashboard. After the dashboard has successfully visualized the data, then testing is carried out on users using the UEQ (User Experience Questionnaire) method to find out how the user experience when using the dashboard. From this study, it was found that the dashboard was able to visualize the total inventory of goods, consigned goods inventory, non-consigned trunk inventory in monthly, semester, quarterly, and annual periods. And excellent results on 6 scales of User Experience Questionnaire (UEQ).
A Phonemic Analysis Between English And Indonesian In English Conversation

This study compares and contrasts the phonetic systems of English and Indonesian in the "English Conversation" In order to teach students how to pronounce English with Indonesian phonemes, the research aims to compare and contrast the phonemes in the English Conversation. Ten English consonant phonemes and ten Indonesian consonant phonemes are the focus of this study. A qualitative technique is used in the descriptive-contextual research methodology. Based on the types of phonemes, the technique design compares the phonemes in Text Conversation written in English and Indonesian. The "English Conversation ", which are made up of 10 consonant phonemes, were discovered to share commonalities between the English and Indonesian phonemic systems. Ten consonants in the English Conversation represent the distinctions between the English and Indonesian phonetic systems.
An Efficient Data Structure Providing Maps of the Frequency of Public Transit Service Within User-Specified Time Windows

Abstract. To understand the quality of a public transportation network, map-based visualizations are the first choice. Since the network quality depends on the transportation schedule, the visualization interface should incorporate time. In this work, we provide such an interface where users can filter the data for time windows. When a user queries for a certain time window, we display all network segments that are traversed by at least θ means of public transportation, e.g., buses in the time window on the map. This gives insights into the frequency of the public transit service.Since such transportation networks can contain a high number of network segments, testing each network segment at the moment when the user specifies the time-window query is not fast enough. We investigate an approach to provide the query result in real time. Our contribution is a data structure that answers such arbitrary time-window queries from the user interface. The data structure is based on a tree structure which is augmented with further information. To evaluate our data structure, we perform experiments on real-world data. With our data structure, we answer time-window queries in at most 25 milliseconds whereas testing each network segment on-demand takes at least 60 milliseconds for the data set that has 102599 road segments.
Rapidgzip: Parallel Decompression and Seeking in Gzip Files Using Cache Prefetching

Gzip is a file compression format, which is ubiquitously used. Although a multitude of gzip implementations exist, only pugz can fully utilize current multi-core processor architectures for decompression. Yet, pugz cannot decompress arbitrary gzip files. It requires the decompressed stream to only contain byte values 9-126. In this work, we present a generalization of the parallelization scheme used by pugz that can be reliably applied to arbitrary gzip-compressed data without compromising performance. We show that the requirements on the file contents posed by pugz can be dropped by implementing an architecture based on a cache and a parallelized prefetcher. This architecture can safely handle faulty decompression results, which can appear when threads start decompressing in the middle of a gzip file by using trial and error. Using 128 cores, our implementation reaches 8.7 GB/s decompression bandwidth for gzip-compressed base64-encoded data, a speedup of 55 over the single-threaded GNU gzip, and 5.6 GB/s for the Silesia corpus, a speedup of 33 over GNU gzip.
On the Simplest Entangled Mixed States

Quantum entanglement is a fascinating topic with both theoretical and technological impacts. Yet, even in the simplest scenarios, there are still various open questions involving pure state and mixed state entanglement. Here we present the simplest entangled mixed states. We consider both qubits (quantum bits) and qudits (quantum digits). We first provide our simplest yet most important result for rank-2 bi-partite states, and we then generalize our results to go beyond rank-2 and to go beyond bi-partite states.
Design and Implementation of VDES Data Gateway Applied to Maritime Communication

In order to realize and expand the data exchange function of VDES, the VDES data gateway for maritime communication is designed according to the VDES standard and the data transmission characteristics of the VDES system. VDES data gateway can realize the functions including resource management and allocation, packet data filtering and packet data forwarding in ship-to-shore communication. The VDES data gateway is developed on the Linux platform, and the VDES testing environment is built. The functions of VDES data gateway is verified, which provides reference for the development and application of VDES system.
Performance analysis according to segment length and buffer length in adaptive video streaming

In this paper, we review several MPEG-DASH’s adaptive streaming algorithms that dynamically change the video bitrate with respect to network and watching environment. Then, the performance of each algorithm according to the video segment length and buffer length was analyzed on the video bitrate, rebuffering time, and viewing quality change rate, and finally compared with the QoE score.
Adversarial Attack of ML-based Intrusion Detection System on In-vehicle System using GAN

In recent years, research has focused on developing intrusion detection systems (IDS) within vehicle networks to prevent automotive hacking from external cyberattacks. While machine learning (ML) techniques have shown promise in detecting known attacks, their vulnerability to adversarial examples remains a significant challenge. In this study, we introduce a Generative Adversarial Network (GAN)-based method for creating adversarial attacks capable of bypassing ML-based IDS in in-vehicle networks. Our approach involves preprocessing an automotive hacking dataset, training a GAN-based model, and evaluating the generated attacks using accuracy metrics. The results demonstrate that adversarial attacks effectively reduce the detection accuracy of various IDSs to less than 50%, emphasizing the importance of addressing adversarial cases when designing and evaluating ML-based IDSs for in-vehicle networks. Additionally, t-SNE visualization reveals the successful generation of new adversarial attacks, highlighting the need for ongoing research to strengthen the security of in-vehicle systems.
Penegakan Diagnosa Keperawatan pada Pasien Gastroesofagus Reflux Disease dengan Aplikasi Sistem Pakar Forward Chaining

This study aimed to see the use of a computer-based expert system with the forward channeling method for detecting Gastroesophageal Reflux Disease and its application in nursing. The research method used in writing this literature review is based on 25 pieces of literature from 2018-2022. This expert system is run with PHP and MYSQL programs. The results of this study are that the Forward Chaining Expert System program will detect gastroesophageal reflux disease based on the symptoms inputted into the system and display an intervention plan that can be carried out like an expert. Still, this system cannot yet display 100% appropriate disease diagnosis because it requires a series of other tests that have not been prepared. In conclusion, with this expert system technology, health workers and users are increasingly assisted and shorten the time needed for disease diagnosis and treatment.&#x0D; &#x0D; Keywords: Expert System, Forward Chaining, Gastroesophageal Reflux Disease
An Informal Introduction to Semirings for GraphBLAS using Matlab

This paper presents an informal introduction to semirings and their application in GraphBLAS using Matlab. GraphBLAS is a powerful and versatile tool for working with graph algorithms and linear algebra, and its use in education is also discussed. The paper simplifies the mathematical complexity typically associated with semirings and provides an accessible entry point for those who are new to the field of GraphBLAS. The use of Matlab as a tool for implementing GraphBLAS is also highlighted, making it user-friendly and easy to understand. Overall, this paper serves as a useful starting point for anyone interested in learning more about GraphBLAS and its potential applications.
Blockchain based tomato supply chain management

Supply chain in agriculture field is very important as the cultivated goods are sensitive for time and temperature. Most of the time, middlemen act as the price-fixing authorities. The farmer’s profit declines as the number of people increases. Additionally, there is no provision for tracking the status of the farming goods throughout transportation. Tomatoes are one of the many products that are time, temperature, and container sensitive. These parameters could be tracked by a centralized system, which would be more advantageous. Blockchain is a distributed database providing tamper proof storage of data. The management of the tomato supply chain based on blockchain is suggested in this research. Customers can use this method to learn how the produce is grown and how the shipping process works. Here, the farmer uses the smart contract to periodically update the blockchain with the crop status. The farmer grows it and sells it once it is ripe for cultivation. As a result, the proposed system enables the customer to be fully informed about the crop and commodities. Additionally, it helps the farmer keep track of their products and maximize their yield’s profit.
Edukasi Media Video dan Booklet terhadap Motivasi dan Sikap Orangtua dalam Merawat Balita dengan Gastroenteritis

This study aims to determine the effect of providing education using video media and booklets on the motivation and attitudes of parents in caring for toddlers with gastroenteritis. This type of research is a quasi-experimental design with a non-pretest-posttest design. The study's results found a difference in the average score of parents' motivation and attitudes in caring for toddlers with gastroenteritis before and after providing education. In the video media group ρ motivational value (0.01) and perspective (0.00), in the booklet media group with ρ motivational value (0.02) and attitude (0.00), and the video media and booklet combination group with ρ motivational value (0.00) and perspective (0.00). In conclusion, there is a significant effect of the use of educational media on increasing the average score of parents' motivation and attitudes in caring for toddlers with gastroenteritis. The combination of education using video media and booklets gave more effective results than other educational groups.&#x0D; Keywords: Booklet, Video Media, Motivation, Health Education, Attitude
Penggunaan Conventional Ultrafiltration selama Cardiopulmonary Bypass untuk Mencegah Terjadinya Acute Kidney Injury Paska Operasi Jantung

This study aims to identify the relationship between the use of conventional ultrafiltration and the incidence of postoperative acute kidney injury associated with the help of a cardiopulmonary bypass machine. The method used is a systematic review using the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) flowchart to obtain five selected literature. The results showed a relationship between conventional ultrafiltration fluid volume shifts and the incidence of post-cardiac surgery acute kidney injury. In conclusion, ultrafiltration fluid volume displacement &gt; 32 mL/kg will increase the risk of acute kidney injury after cardiac surgery.&#x0D; &#x0D; Keywords: Acute Kidney Injury, Cardiopulmonary Bypass, Conventional Ultrafiltration, Heart Surgery