Reviewerly/exHarmony huggingface dataset:
MANAGEMENT OF ENTRY AND OUTCOMES OF GENERAL SUB-SECTIONS OF EMPLOYMENT AND LEGAL AT THE EDUCATION OFFICE OF SOUTH SULAWESI

This research was conducted with the intention of discovering how the management of incoming and outgoing letters is handled in the General, Personnel, and Legal Subdivisions of the Office of the Education Office of the Province of South Sulawesi. This is a qualitative study, with data obtained from direct observations and interviews about the management of incoming letters and letters. The descriptive research methodology was utilized for this study's research design. Field studies by observation (observation) and interviews were used to collect data for this study (interview). The study's findings revealed that the management of incoming and outgoing letters in the General, Personnel, and Legal Subdivisions at the South Sulawesi Province Education Office, based on the results of interviews and observations, employs a combined principle, namely the principles of centralization and decentralization. In terms of archive storage, inactive archives are managed by Archivists, whereas active archives are managed by their respective subsections.
Organization of online learning using the intelligent metasystem of open semantic technology for intelligent systems

Distance learning today allows you to create a system of mass continuous self-learning, universal exchange of information, regardless of the presence of time and space zones. For more effective online learning, it is necessary to introduce artificial intelligence technologies and methods for implementing learning systems. In this paper, the objects of research were: 1) the capabilities of the OSTIS open semantic technology, the capabilities of the IMS.OSTIS metasystem for organizing online learning; 2) machine learning method – classification. Results of the study: 1) an online course was organized using the IMS.OSTIS metasystem of the OSTIS open semantic technology; 2) for the analysis and visualization of training data, a machine learning method is implemented – classification. The results of the implementation of the online course were obtained using the semantic technology for designing an intelligent learning system: the IMS.OSTIS metasystem using the graphical semantic code SCg. The OSTIS kernel requires a machine with the Ubuntu operating system installed, which is a GNU/Linux distribution based on Debian GNU/Linux, an operating system based on the Linux kernel. The paper also shows an example of using the machine learning method – classification. This method allows you to classify data. Intelligent processing and visualization of data were carried out based on the results of testing students in order to classify them into letter categories A, B, C, D according to a set of features: scores and points of the average score. The high-level Python library Pandas was used, this is a library for data analysis. To visualize the results of data processing, the Matplotlib library in Python was used
Direct Nonparametric Predictive Inference Classification Trees

Classification is the task of assigning a new instance to one of a set of predefined categories based on the attributes of the instance. A classification tree is one of the most commonly used techniques in the area of classification. In this paper, we introduce a novel classification tree algorithm which we call Direct Nonparametric Predictive Inference (D-NPI) classification algorithm. The D-NPI algorithm is completely based on the Nonparametric Predictive Inference (NPI) approach, and it does not use any other assumption or information. The NPI is a statistical methodology which learns from data in the absence of prior knowledge and uses only few modelling assumptions, enabled by the use of lower and upper probabilities to quantify uncertainty. Due to the predictive nature of NPI, it is well suited for classification, as the nature of classification is explicitly predictive as well. The D-NPI algorithm uses a new split criterion called Correct Indication (CI). The CI is about the informativity that the attribute variables will indicate, hence, if the attribute is very informative, it gives high lower and upper probabilities for CI. The CI reports the strength of the evidence that the attribute variables will indicate, based on the data. The CI is completely based on the NPI, and it does not use any additional concepts such as entropy. The performance of the D-NPI classification algorithm is tested against several classification algorithms using classification accuracy, in-sample accuracy and tree size on different datasets from the UCI machine learning repository. The experimental results indicate that the D-NPI classification algorithm performs well in terms of classification accuracy and in-sample accuracy.
Peningkatan Hasil Belajar Bahasa Indonesia Madrasah Ibtidaiyah melalui Model Cooperative Integrated Reading and Composition

This study aims to describe the application of the Cooperative Integrated Reading and Composition (CIRC) method in improving the quality of Indonesian language learning outcomes in class III MI Darul Falah Ngembalrejo Kudus. Classroom Action Research (PTK) uses the Kemmis and McTaggart model which consists of four stages, namely planning, implementing, observing, and reflecting. The subjects of this study were all students of class III MI Darul Falah with a total of 28 students. Data collection techniques in this study were interviews, observations, tests, and documentation. The results showed an increase in the average score of the test results and an increase in the number of students who achieved KKM in each cycle. The average score in cycle I was 68.1 with 42.8% completeness and the average score in cycle II was 80.89 with 82.1% completeness. Based on these results it can be concluded that the application of the CIRC method can improve the quality of student learning outcomes at MI Darul Falah Ngembalrejo Kudus.
NODEMCU INTERNET OF THINGS-BASED FIRE AUTOMATION DESIGN WITH BLYNK APPS NOTIFICATIONS

The impact of fires causes quite large losses, often even causing fatalities. The method used in the system is monitoring the fire sensor which is used to detect a fire, the buzzer as a notification output in the form of sound, and the water pump as a fire extinguisher which will function after the fire sensor is on. detecting the presence of fire. to detect fire in realtime and 9 in the event of a fire with a research and development. Monitoring approach on fire sensors used to detect the presence of fire, buzzers as output notifications in the form of sound, and water pumps as a tool to extinguish fires which will function after the fire sensor detect the presence of fire.
Active Voice Amplifier: On-Device Noisy Environment-Aware Solution for Dialogue Enhancement in Real Time

J. Cho, S. Kim, and I. Hwang, "Active Voice Amplifier: On-Device Noisy Environment-Aware Solution for Dialogue Enhancement in Real Time,"
DEEP CONVOLUTIONAL NEURAL NETWORK USING A NEW DATASET FOR BERBER LANGUAGE

Currently, Handwritten Character Recognition (HCR) technology has become an interesting and immensely useful technology. It has been explored with highperformance in many languages. However, a few HCR systems are proposed for the Amazigh (Berber) language. Furthermore, the validation of any Amazighhandwritten recognition system remains a major challenge due to no availability of a robust Amazigh database. To address this problem, we first created two new datasets for Tifinagh and Amazigh Latin characters, by extending the well-known EMNIST database with the Amazigh alphabet. And then, we have proposed a handwritten character recognition system, which is based on a deep convolutional neural network to validate the created datasets. The proposed CNN has been trained and tested on our created datasets, and the experimental tests show that it achieves satisfactory results in terms of accuracy and recognition efficiency.
Query Similarity of Various Linguistic Levels for Hybridized Conversational Agents

The performance of retrieval-based conversational agents is affected by the discrepancy between a user query and a retrieved query similar to the user query. There have been a number of previous studies to cope with this discrepancy, and a skeleton-based response generation is one of the successful approaches. However, it shows some ineffectiveness in that it considers only the lexical similarity in finding a similar query from a database of query-response pairs. Therefore, this paper proposes a CNN-based model which uses the combination of the neural representation of two queries and manually-designed lexico-syntactic features to determine the similarity between the queries. According to the experimental results on a manually-constructed dataset, the proposed model outperforms legacy search engine in finding similar queries from the database, which proves the plausibility of the proposed model.
“Every Dog Has His Day”

This article proposes a competitive-evolving-committee proactive secret sharing. Every participant in the system has the opportunity to become a member of the holding committee and have sufficient anonymity. During the life cycle of serving as the holding committee members, they only send one message in the protocol without excessive interaction, and achieve receiver strong anonymity with a capability-based encryption scheme different from most public-key encryption schemes, at present named RiddleEncryption, which is also proposed in this paper. In RiddleEncryption the sender does not need to pay attention to the specific identity of the receiver but focuses on what kind of capability the receiver should have. Nobody can determine this kind of capability at the beginning of the system establishment. This article aims at depositing a secret in a distributed manner (e.g., blockchain) without excessive trust and to emphasize more anonymity and capability. The scheme can be used in the dynamic groups, authentication management, rights abuse prevention, and so on.
Anomaly detection in internet of medical things with artificial intillegence

Internet of things (IoT) becomes the most popular term in the recent advances in Healthcare devices. The healthcare data in the IoT process and structure is very sensitive and critical in terms of healthy and technical considerations. Outlier detection approaches are considered as principal tool or stage of any IoT system and are mainly categorized in statistical and probabilistic, clustering and classification-based outlier detection. Recently, fuzzy logic (FL) system is used in ensemble and cascade systems with other ML-based tools to enhance outlier detection performance but its limitation involves the false detection of outliers. In this paper, we propose a fuzzy logic system that uses the anomaly score of each point using local outlier factor (LOF), connectivity-based outlier factor (COF) and generalized LOF to eliminate the confusion in classifying points as outliers or inliers. Regarding human activity recognition (HAR) dataset, the FL achieved a value of 98.2 %. Compared to the performance of LOF, COF, and GLOF individually, the accuracy increased slightly, but the increase in precision and recall indicates an increase in correctly classified data and that neither true nor abnormal data is classified wrongly. The results show the increase in precision and recall which indicates an increase in correctly classified data. Thus, it can be confirmed that fuzzy logic with input of scores achieved the desired goal in terms of mitigating cases of false detection of anomalous data. By comparing the proposed ensemble of fuzzy logic and different types of local density scores in this study, the outcomes of fuzzy logic presents a new way of elaborating or fusing the different tools of the same purpose to enhance detection performance
Interactive Computer System Using Hand Gestures

Abstract: This paper proposes a way to control the position of cursor with the bare hands without using any electronic device. While the operations like clicking and dragging of objects will be performed with different hand gestures. Only authorized persons can access the system by using facial recognition. Face recognition tracks target objects in live video images taken with a video camera. This application is based on face detection, feature extraction and recognition algorithms, which automatically detects the human face when the person in front of the camera recognizing the person. If the person is authorized then he can access the computer. We used transformational algorithm, K-cosine algorithm in face detection and finger detection.
“For Free and Useless Studies”: Critical Reflections on Work, Study, and Security*

Revisiting André Gorz’s Destroy the University (1970) offers an opportunity to reconsider the concept of edu-factory explained by the respective authors of the Edu-factory Collective and Toward a Global Autonomous University (2009), which considers the political implications of asserting, “What was once the factory is now the university,” critical university studies’ critique of the neoliberal university (2012), and abolition university studies (2019), which asks, “Are prisons and universities two sides of the same coin?” The community college in the United States is arguably situated most directly between the factory and the prison. Most community college students are first generation, full-time students, workers, and often parents. They face severe time constraints, which are under-theorized and under-politicized to their own detriment. The COVID-19 pandemic compelled most people, including students, to transform previously private spaces to public spaces to accommodate work, school, and care-giving responsibilities. As a result, spatial and temporal distinctions between these different modes of being collapsed, allowing economic rationality to inform the most intimate settings of home, a Gorzian nightmare.
A Comparitive Study of Detection of Serum Total and Direct Bilirubin by Jendrassik &amp; Grof and Automated Method

Background: Bilirubin is one of the major bile pigments, clinically and biologically important among the bile pigments present in the mammals. Material and Methods: The cross-sectional study was conducted in department of biochemistry in the collaboration with department medicine in Civil Hospital Tarn Taran. Out of 90 patients, 54 were males and 36 were females. Result: The comparison of Serum Total and Direct bilirubin by Jendrassik &amp; Grof and Automated method was non-Significant with p value = 0.7788and 0.5394 respectively. The comparison of Serum Total and Direct bilirubin by Malloy Evelyn and Automated method is Highly Significant with p value =0.0002 and 0.0003 respectively. The mean difference of malloy with jendrassik &amp; grof and automated was 2.394 and 2.162 respectively and the mean difference of jendrassik &amp; grof with automated methodwas -0.231. Conclusion: It was concluded that a good correlation is found between bilirubin detection by manual and automated method. Non-significant mean difference between Jendrassik &amp; Grof and Automated makesit better than Malloy Evelyn.
X-ray fluorescence (XRF) fingerprinting of Palaeogene deposits in Denmark

In this study, we test if cost-efficient X-ray fluorescence (XRF) analyses can be used to fingerprint Palaeogene clay and marl deposits in Denmark. A total of 67 samples from key sites in Denmark have been analysed. Our preliminary results indicate that it is possible locally within 10–30 km to distinguish between most of the Palaeogene units, but on a regional scale across Denmark, the units are not unique, and this probably reflects variations in clay mineralogy, grain size and calcareous content. Accordingly, we suggest that a comprehensive reference database is now needed if the full potential of the method is to be utilised, and this will ultimately result in more reliable geological models.
Assistance in The Planning of Irrigation Channels for Farmers Using Water in Iwoi Sangia Area

The water for the rice fields comes from the Iwoi Sangia spring. The water flows in irrigation canals that are not feasible so that a lot of water is wasted. Water flows out of the canal through cracks in the walls. This resulted in water not being distributed optimally to the farmers' paddy fields. Through this program, we took the initiative to repair damaged irrigation canals. It is hoped that after the existence of good irrigation canals, water will no longer seep in vain so that irrigation coverage can be wider, irrigation canals become cleaner, and can initiate program plans with government assistance. The method of implementing this activity contains steps to realize the objectives of the community service PKM proposal. Community Service activities, especially the planning of tertiary irrigation channels, were carried out very well and smoothly in accordance with the previous planning activities. This activity begins with interaction with the Village Government and continues with site inspections and field measurements. The result of this community activity is the delineation of irrigation canal plans and budget plans, which will facilitate irrigation work for the Village Government.
DIGITAL INITIATIVE FOR FARMERS: REBOOTING PUBLIC LIBRARIES

This paper is all about the public library digital initiative for farmers with much emphasis onthe concept of digital library, digital library services, advantages of digital library, disadvantages of digital library, use of digital library, digital technologies in agriculture and rural area, condition for digital transformation, challenges, conclusion and recommendations.It was found that Public Libraries so far done nothing for the farmers who have been potential users of Public Libraries. Library timings do not suit the farmers. So, Public Libraries should take immediate initiatives to reboot its importance among the rural communities. Public Library should plan to start to provide above mentioned services without any delay. In addition to these services some new and innovative technology-based services like, Computer literacy for farmers, Webinars for farmers, SMS alert on new issues like crop diseases and plant protection in local language etc., should be started.
Performance analysis of least squares algorithm for multivariable stochastic systems

In this paper, we consider the parameter estimation problem for the multivariable system.A recursive least squares algorithm is studied by minimizing the accumulative prediction error.By employing the stochastic Lyapunov function and the martingale estimate methods, we provide the weakest possible data conditions for convergence analysis.The upper bound of accumulative regret is also provided.Various simulation examples are given, and the results demonstrate that the convergence rate of the algorithm depends on the parameter dimension and output dimension.
Quantum electrodynamics of non-demolition detection of single microwave photon by superconducting qubit array

By consistently applying the formalism of quantum electrodynamics, we developed a comprehensive theoretical framework describing the interaction of single microwave photons with an array of superconducting transmon qubits in a waveguide cavity resonator. In particular, we analyze the effects of microwave photons on the array’s response to a weak probe signal exciting the resonator. The study reveals that high quality factor cavities provide a better spectral resolution of the response, while cavities with moderate quality factors allow better sensitivity for a single-photon detection. Remarkably, our analysis showed that a single-photon signal can be detected by even a sole qubit in a cavity under the realistic range of system parameters. We also discuss how the quantum properties of the microwave radiation and electrodynamical properties of resonators affect the response of qubits’ array. Our results provide an efficient theoretical background for informing the development and design of quantum devices consisting of arrays of qubits, especially for those using a cavity where an explicit expression for the transmission or reflection is required.
Design of Dynamic Network for Parallel Processing on a Distributed System

Modern computation systems involve multicomputer configurations.Multiple computers enable multiple threads to be executed simultaneously, with the ability to perform the same operations on different processors (computers) at the same time.This paper addresses the building of a software application to be implemented on 8*8 dynamic multistage network exchange depending on the client/server principles so that one can select one type of different topologies that is suitable to the type of application.The network can serve any number of nodes.Two different applications were examined, convolution operations and matrix multiplication.The goal of this paper is to explore the different ways, in which the multistage network topology can simulate supercomputer systems employing large-scale parallel processing.This paper proposes designing parallel systems on a distributed system, running different topologies such as linear systolic, mesh, and hypercube topologies of the parallel processor's networks, and also a dynamic selection of the appropriate network topology based on the nature of the solved problem.Simulation of parallel processing systems on distributed environments mainly done through Socket programming based on JAVA threads.
Interactive Media Introduction to 10 Most Famous Historical Buildings in Medan City as a Media for Learning History

Medan City is one of the cities that has a number of diverse historical heritage, one of which can be seen clearly are the historical buildings. Preservation of history, including the heritage of buildings, is an important way for humans to convey an understanding of the past to future generations. In getting to know historical buildings, we can learn through the use of technological media, one of which is using an Android smartphone. The media referred to here is interactive multimedia learning that is intentionally provided to increase student interest in learning, increase student interest in participating in learning during the learning process and to improve student learning outcomes, especially in learning history about historical buildings in Medan City.
Infrastructure project selection automation using non-structural fuzzy decision support system II

In this study, we develop a web-based Decision-Making Tool (DMT) based on a four-year research project in building the proper multiple criteria Decision-Making Framework (DMF) for infrastructure project selection automation. Several challenges in selecting and prioritizing infrastructure projects include poor front-end planning, lack of project funding, improper investment, unsustainable development, regulatory barriers, and poor coordination among stakeholders. The Non-Structural Fuzzy Decision Support System II (NSFDSS-II) is chosen as the main method applied in the proposed DMF since it could resolve complex multi-criteria problems, even without sufficient information provided. When developing the DMT, Agile software development method is used since the development cycle can be run in a light and fast manner with iterative and incremental processes. The DMT is successfully developed by using PHP, HTML, and JavaScript which implement the proposed NSFDSS-II method. We further tested the decision results from the DMT by using eight real past infrastructure projects from relevant infrastructure agencies in Indonesia, such as the Ministry of Public Works and Housing (MPWH), the Ministry of Transportation, and the Local Government. The DMT outcomes were compared with the actual implementation status and evaluated by an independent expert. It was found that the decision results from the developed DMT are in accordance with the real implementation status of evaluated projects. The DMT is recommended to be used for infrastructure project selection automation. However, despite of its fast and accurate result, the DMT should be tested on larger number of infrastructure projects in the future