Reviewerly/exHarmony huggingface dataset:
Analisis Perencanaan Produksi Padi Terhadap Lahan Panen Di Sumatera Barat Menggunakan Rantai Markov Waktu Diskrit

Rice production is one of the results of farming which is carried out by planting rice seeds, care and maintenance and regular fertilization. While the harvest land is a plant that is harvested after the plant is old enough. Harvested land affects rice production, if the harvested area is decrease then rice production will also decrease. For this reason, it is necessary to predict rice production and harvested land in the province of West Sumatra using a discrete time Markov chain. This research aims to determine the shape of the Markov chain model and the prediction results of rice production and harvested land in the province of West Sumatra for the period January 2021 to December 2021. The results showed that the opportunities for rice production in a row were drastically decreased, decreased, increased and drastically increased by 23,28%, 17,46%, 35,46% and 23,80%. Meanwhile, the opportunities of harvesting land in a row were that drastically decreased, decreased, increased and drastically increased by 23,47%, 16,90%, 38,50% dan 21,13%.
ONE STEP AT A TIME: DEEPENING SOCIO-TECHNICAL LEARNING IN UNDERGRADUATE ICT EXTERNSHIPS TO BRIDGE THE DIGITAL DIVIDE

This paper describes the temporal progression of human and social dimensions that undergraduate information and communications technology (ICT) students realized during an experiential learning externship where they explored digital divide technology solutions for low-income neighborhoods in the surrounding urban community.The described research represents significant adaptation and use of socio-technical integration research (STIR) with undergraduate ICT students engaged in work based experiential learning to promote equity in STEM education, instill a sense of civic responsibility, and practice approaches to tackling complex societal problems.Methods used for the research study included: STIR, semi-structured interviews, and on-site group observations.Using STIR, an embedded social scientist conducted regular one-on-one dialogs with three of four student externs, to collaboratively describe each student's consideration of human and social dimensions as part of their technical work, explore alternative choices and their potential outcomes, and engage in reflexive learning that in some cases, influenced deliberate changes to material and behavioral practices.The on-site observation of group activities within the ICT innovation center situated in the local urban community provided additional ecosystem context during technical solution design and development of the digital divide solution for local high schools and feeder schools.Outcomes for participating undergraduate ICT students showed: 1) Technology learning improvements for all students; 2) Capacity building to reflect, anticipate and respond to sociotechnical interactions for some students; and 3) Each student was able to progress to a new level of socio-technical learning and decision making.Reflexive discourse with participants surfaced cultural assets and consideration of alternative knowledges in collaborative technology design, development, and implementation that can potentially lead to solutions that are more community centered now and in the future as the ICT students transition to the workforce.
Koblitz Curve- A Mapping Technique to Encipher/Decipher the Text message using Elliptic Curve Cryptography

Elliptic Curve Cryptography (ECC) is studied to be very powerful and secured asymmetric technique which uses small key sizes and efficiently uses power and bandwidth. Wired and wireless sensor networks are prone to attacks like node capture, physical tampering, eavesdropping, denial of service, etc. ECC curves being resistant to these kinds of attacks, are used for secured data transmission. ECC uses Koblitz’s curve mapping methodology for encoding and decoding of user’s information over public environment and thus is efficient for secured computations. Koblitz curves are also used for secured exchange and ownership of cryptocurrency which is very popular nowadays. The research paper aims to discuss and implement Koblitz mapping technique on a given ECC curve and it is also proved to be secured to encode and decode the textual information during data transfer. The method, if used with parallel multipliers, does faster computations than other curves and saves time and space.
Creativity and creativity in psychopedagogical considerations aimed at supporting the creativity of the child in the early stages of education (review article)

Creativity is subject of interest of many sciences also pedagogy. Each discipline considers this phenomenon form its own perspective. On the basis of pedagogy of creativity is understood as a discipline of theoretical and practical knowledge. In range of practical knowledge refers to the competence of the modern teacher pupils. Article points to the important issues taking out from definitional and terminological arrangements, concept of creativity as attitude creative human. In connection with it, review individual stances is neither complete nor comprehensive but only focused on establishing place of creativity in pedagogy of creativity and role what performs in sphere education a child.
Rotting Sounds . Artistic Research Practice in Experimental Sound Art

The majority of today’s media is produced in the digital domain. Although digital data are adorned by a myth of perfection, everyday experience does provide evidence for the existence of degradation and, ultimately, data loss in various forms. The multi-year artistic research project Rotting Sounds has investigated the causes, mechanisms, and effects of such deterioration, specifically in the context of digital audio. This report gives a condensed account of some of the theoretical foundations and methodical approaches chosen. The digital-analog interface, information encoding, as well as the deep time perspective are specifically highlighted. We present a number of artistic works that have been developed as experimental systems to co-generate questions and finally lead to various conclusions. These concern the controllability of such experiments and the interrelationships between (sound) information and its environment. The term of digital patina was introduced to characterize observed aesthetics in permanent transformation and to open up a new perspective on the existence of the digital in a material context. Der überwiegende Anteil heutiger Medien wird in digitaler Form produziert. Digitale Daten sind von einem Mythos der Perfektion umrankt, obwohl die Alltagserfahrung Evidenz für die Existenz von Degradation und letztendlich Datenverlust in verschiedener Weise liefert. Das mehrjährige künstlerische Forschungsprojekt Rotting Sounds untersuchte die Ursachen, Mechanismen und Auswirkungen solcher Verfallserscheinungen, speziell im Kontext von digitalen Audiodaten. In diesem Bericht werden einige der gewählten theoretischen Grundlagen und methodischen Ansätze in komprimierter Form dargestellt. Besonders hervorgehoben werden die Digital-Analog-Schnittstelle, die Kodierung von Information, sowie die Perspektive der ›tiefen Zeit‹. Wir präsentieren eine Reihe von künstlerischen Arbeiten, die als experimentelle Systeme entwickelt wurden, um Fragen zu generieren und letztendlich zu verschiedenen Schlussfolgerungen zu gelangen. Diese betreffen die Kontrollierbarkeit solcher Experimente und Zusammenhänge zwischen (Klang-)Information und ihrer Umgebung. Der Begriff der ›digitalen Patina‹ wurde eingeführt, um beobachtete Ästhetiken in permanenter Transformation zu charakterisieren und eine neue Perspektive auf das Wesen des Digitalen im materiellen Kontext zu eröffnen.
Planning of Clean Water Distribution System to the Needs of the Community with the Utilization of Water Sources of Artesic Water Sources, Way Hula Hamlet, Liang Village, Salahutu District

The need for clean water is one of the necessities that cannot be separated from the life of living things on earth, especially humans, animals and plants. In general, clean water is an important component for the life processes of creatures on earth. Water is one of the village needs for living creatures which is very vital, which if managed properly will bring many benefits to living things. With regard to the results of research, surveys, interviews and observations with both village officials and local communities, the source of the spring has not been utilized because there is no piping network and reservoir tank in the construction process so that it is used daily for washing cars, washing clothes and people using buckets / buckets. gene to take water for daily needs in Way Hula Hamlet. The author aims to determine the availability of clean water discharge that enters the reservoir and is distributed to the community, the diameter of the pipe and the distribution system that will be used for the next 5 years projection for the people of Way Hula Hamlet, Liang Village. Then a research study was carried out through the analysis stage, the results obtained were that the water discharge entering the reservoir was 0.26 m3/second and channeled to the public faucets of the Way Hula Hamlet 0.015 m3/second, the diameter of the galvanized pipe according to the planning and calculations is a galvanized pipe diameter 6 inches is used from the well/source to the reservoir, galvanized pipes with a diameter of 2 inches, 1 inch and 1/2 inch are used from the reservoir to the public faucet for the clean water needs of Way Hula Hamlet for the next 5 years from 2020 to 2025 of 0.01m3/ seconds can be met.
A Comparative Analysis of AWS Cloud-Native Application Deployment Model

Application deployment in cloud computing has become a widely used system where we follow some specific models. For a long time, we have deployed our application in virtual machines. Nevertheless, nowadays the Docker container model is gaining popularity due to its important features. Therefore, we need to know which model is better in terms of request–response, and which modelis error-prone and gives better throughput. In our paper, we have done a comparative study between these two native cloud application deployment models. The main parameters of this study are HTTP response in a fixed time, error percentage, and throughput. We have used the Amazon EC2 service for the Virtual Machine model and Amazon ECS service for the Docker Container model in the implementation part and the Apache JMeter tool in the test part. In our study, we have found that the docker container has performed better in terms of total and average responses to the HTTP request and throughput.
AUDIT STRATEGI TATA KELOLA IT PADA STMIK BINA NUSANTARA JAYA LUBUKLINGGAU MENGGUNAKAN FRAMEWORK COBIT 5

In the implementation of academic and non-academic activities STMIK Bina Nusantara Jaya Lubuklinggau has integrated and implemented the use of information technology through SIAKAD ( Academic System) . To be able to carry out the implementation of information technology according to service quality orders and a framework which later can help an organization to be able to improve or improve technology governance in accordance with IT governance standards. Information technology governance, in its role, has many tools to carry out assessments and measurement indicators to help universities. In this study, the author uses cobit 5 famework as an IT governance standard. In the COBIT 5 process, the author only uses the APO 11 and MEA 01 processes. The APO11 (Quality of Service) process has 6 attributes that are used and MEA (Monitor, Evaluate, assess conformance and Conformance) has 5 attributes that are used. There is a gap value between attributes, current conditions and what is expected. The results of the gap analysis obtained in the APO11 and MEA processes still have numbers 1 and 0. The results of the gap number 1 indicate that the current condition is still not good with the expected conditionsKeyword- Audit,Governance, Cobit 5, APO,MEA
Superposition Display of Liver Model using Mixed Reality Technology for a Laparoscopic Surgery Support System

In laparoscopic surgery, the problem is that endoscopic cameras have a narrow field of view and are often overlooked even if organs outside the field of view are damaged. As support, surgical navigation systems present the entire organ. However, because the navigation system uses preoperative medical images, the difference between the actual situation and the information presented by the navigation system increases as the surgery progresses. To solve this problem, in this study, a system of superimposing a deformed intraoperative organ virtual model onto an endoscopic image using mixed reality technology is proposed. In the proposed system, the movement of the surgical instrument is tracked by a motion capture (Mocap) system, and the dynamic deformation of the organ due to contact with the surgical instrument is calculated by a dynamic simulation. In the experiment, a liver model made of urethane resin was placed in a mannequin. The superposition of the endoscopic image of the liver model and the deformed virtual liver model was confirmed.
Machine Learning based Sentiment Analysis Using Django

Before purchasing a product or service, People typically analyse the information about the product such as cost, warranty, quality etc.Only after getting satisfaction about such things, People try to buy that product based on the quality of service received.Since this process takes time and a chance of being duped by the dealer are higher, Sentiment analysis (SA) is necessary to purchase a product without any hesitation.Sentiment analysis examines reviews and comments of the products, which are in the form of text that requires several processes for providing the desirable information to the People.Moreover, SA is a significant research direction of Natural Language Processing (NLP).In this paper, a novel sentiment analysis model is developed based on the Machine Learning (ML) Algorithm, which provides an accurate sentiment information for the texts having different perspectives.The method of Stop words are used for data pre-processing.By using count vectorizer, the text data is converted into the form of vectors for extracting the desired features.Finally, the type of sentiment whether it is positive, negative or neutral is determined based on the ML classifier namely, Naive Bayes classifier.This model is developed using Django web framework that provides an accurate sentiment classification to the people or the industries who need the sentiment analysis.
Toward Secure and Timesaving Data Sharing: Cloud Encryption of RSA-co-ABE

Attribute-Based Encryption(ABE) has been a promising technology without authority sending keys in advance, depending on attributes to encrypt and decrypt. However, most of the existing Attribute-Based Encryption algorithms are time-consuming and complex. To address this issue, we apply the structure of the access tree to accomplish Attribute-Based Encryption. Combined the security of RSA with the convenience of Attribute-Based Encryption, we proposed cloud encryption of RSA-co-ABE algorithm, realize the safe and efficient encryption process on a cloud server. The findings of the security verification based on the game process between the challenger and the attacker reveal that the attacker cannot be identified if there is no polynomial time, and the polynomial time would demolish the security model in a non-negligible range. Finally, A lot of experiments proved that the RSA-co-ABE algorithm greatly saves time overhead, storage space and computing resources.
A Novel Method for Generating Apparent Panoramic Image of Real Texture of Concrete Bridge Based on Multi-View Registration

&lt;p&gt;With the improvement of the informatization and digitization of bridge structures, the importance of technologies such as Building Information Modeling(BIM) and computer vision is constantly increasing. This type of technology all relies on a scan of the structure's appearance. However, based on the principle of optical imaging, there is a contradiction between imaging field of view(FOV) and pixel resolution. Therefore, the existing apparent detection or scanning technology either uses lower pixel resolution to obtain the structured apparent image at the panoramic scale, or a series of scattered high-resolution images in a local area, which has caused two aspect of defects in the detection of apparent damage. On the one hand, low-resolution image data has an adverse effect on the accuracy of deep learning or machine vision models. On the other hand, due to the single surface texture of concrete materials, the number of feature points is scarce in image processing, which reduces the stability of the image stitching algorithm based on feature points. These problems make the apparent images collected in the current inspection work cannot be well applied to the long-term evolution analysis of apparent damage. In order to achieve high-resolution imaging within the panoramic range of the structure, we propose a panoramic image stitching method. Firstly, the traditional single-view imaging is extended to multi-view imaging, and the result images are used for panoramic stitching. Because the feature information in a single image is greatly increased, the stability of the image stitching algorithm based on feature point matching has also been greatly improved. Secondly, through experiments, we determine the number of cameras with the highest efficiency for this novel panoramic image stitching method. Lastly, based on real bridge image data, we evaluate and compare several image stitching algorithms in terms of accuracy, efficiency, and robustness. The experimental results show that this panoramic image stitching method can be well adapted to the apparent scanning task of large-scale components in concrete bridges, and is meaningful for the standardization and automatic acquisition of structural appearance images.&lt;/p&gt;
Highly Integrated Photonic Tensor Core for imagining processing

Here we present a highly integrated architecture to perform Matrix-Vector Multiplication. By using the GEMM compiler, we can process images for 3-bits edge detection and 5-bits blur filter, with an error rate lower than 5.1%.
The features of independent work of students in conditions of digital transformation of pedagogical education

The purpose of the study is to determine the features of independent cognitive activities of students of pedagogical universities in the context of digitalization of education. The article discusses the place and role, planning and organization of independent learning activities in the educational process, built according to the Federal State Educational Standard of Higher Education (3++). The scientific novelty lies in the study of the specifics of independent learning activities in the context of the digital transformation of pedagogical education. As a result, organizational, methodological and personal problems of independent learning activities complicated the effectiveness of the training of bachelors of pedagogy are established, the need to use information and communication technologies to solve them is substantiated.
Analysis of Complaints in the Comments Section on Air Selangor's Facebook Page

The speech act of complaints has often caught the attention of researchers in many perspectives. Most previous studies on complaints relied on discourse completion task (DCT) data, and some used ethnographically obtained data. Nowadays, with the widespread use of the Internet, many human affairs have also shifted to online, including complaints. However, there is still not much research done on complaint speech act in an online setting. Therefore, this study has utilized the data of complaints in the comments section on the Facebook page of Syarikat Air Selangor. A total of 74 complaints were obtained from 200 comments in the comments section on Air Selangor's Facebook page. Water consumers make complaints as a response to a notification of water supply disruptions in the Klang Valley. The data were analyzed using the framework introduced by Depraetere et al. (2020) and Decock &amp; Depraetere (2018). The results showed that complainers preferred using only one and two components, namely the strategy of complaints and dissatisfaction or a combination of both. The results proved that the complainers employ more implicit complaint strategies and less explicit strategies. Although this study was conducted in an online setting, it was found that the complaints made were not too aggressive and did not use many harsh words. Most complaints only stop as far as component B, which is dissatisfaction and do not escalate further.
Adaptive Neural Networks for Online Domain Incremental Continual Learning

Continual Learning (CL) poses a significant challenge to Neural Network (NN)s, where the data distribution changes from one task to another. In Online domain incremental continual learning (OD-ICL), this distribution change happens in the input space without affecting the label distribution. In order to adapt to such changes, the model being trained risks forgetting previously learned knowledge (stability). On the other hand, enforcing that the model preserves past knowledge will cause it to fail to learn new concepts (plasticity). We propose Online Domain Incremental Networks (ODIN), a novel method to alleviate catastrophic forgetting by automatically detecting the end of a task using concept drift detection. As a consequence, ODIN does not require the specification of task ids. ODIN maintains a pool of NNs, each trained on a single task and frozen for further updates. A Task Predictor (TP) is trained to select the most suitable NN from the frozen pool for prediction. We compare ODIN against popular regularization and replay methods. It outperforms regularization methods and achieves comparable predictive performance to replay methods.
Item-Behavior Sequence Session-Based Recommendation

Session-based Recommendation has become important and popular in Recommendation System, which focuses on leveraging the historic records to predict the next interactive item(s). The previous works only employ the item sequence or process item sequence and users’ behavior respectively. To model session with item sequence and behavior sequence simultaneously, we propose the Item-Behavior Sequence Session-based Recommendation (IBSSR for abbreviation). The Hadamard product of item sequence and behavior sequence is fed into an improved Transformer and behavior sequence is fed into a Gated Recurrent Unit. Representation generated by concatenating these embeddings with soft attention mechanism will be used to predicts the next item. To verify the bound of our model, we conducted experiments on two datasets where there are large differences in ability of behavior contacting context. Experiment proofs that our model can effectively model item sequence whose behavior sequence has strong ability in contacting context based on the session.