Reviewerly/exHarmony huggingface dataset:
Development Tourism Geographic Information System of Samarinda

This research is motivated by the low level of dissemination of tourism information in the city of Samarinda. Samarinda is one of the cities with very diverse and interesting tourism potentials to explore. The beauty of the urban area and being one of the cities that is crossed by the largest river in the province of East Kalimantan, namely the Mahakam river, makes it one of the tourist destinations that has its own charm, but unfortunately at this time the tourism places in the city of Samarinda have not been widely publicized due to lack of information. About tourism that is given to the public and there are also some places that have not been or have just been opened to become tourist sites. This study uses spatial data in the form of location coordinates and non-spatial data in the form of attribute data including tourist names, addresses, and types of tours, descriptions and pictures. Making the Samarinda City Tourism Geographic Information System website using the Leaflet API as a base map. The database created using PHPMyAdmin on the Samarinda City Tourism Geographic Information System is based on collecting secondary data on tourism information at the Samarinda City Tourism Office and also collecting primary data by interviewing tourist objects that have not been recorded at the Samarinda City Tourism Office. The system and appearance of the Samarinda City Tourism Geographic Information System website was built with the CodeIgniter 3 framework using Visual Studio Code as a text editor. The results of this study are the Samarinda City Tourism Geographic Information System which provides information on tourist names, addresses, types of tours, location coordinates, descriptions, images and is equipped with search features and also road routes to tourist sites. It is hoped that the Samarinda City Tourism Geographic Information System can provide adequate information about tourism information in the city of Samarinda so as to facilitate the delivery and acceptance to the public, especially prospective tourists.
Basics of a General Spectral Theory of Banach Modules

When solving the problem of the multiplication of generalized functions, physicists and mathematicians regard a generalized function as an equivalence class of sequences of C∞-functions. A general method of constructing such algebras was obtained by A. B. Antonevich and Ya. V. Radyno. This chapter reintroduces the topology on the space in a different way. It has been found that this method can be applied not only to generalized functions but also to objects of different character, for example, to unbounded operators. The chapter describes that the proposed ideas and approaches will permit one to solve nonlinear problems and in particular, certain problems of Quantum field theory.
IoT based Distributed Security System

Motion detection is one of the key techniques for automatic video analysis to extract crucial information from scenes in video surveillance systems. The method of foreground and background detection start from second frame onwards it employs new object tracking method which detects and remove ghost objects rapidly while preserving abandon objects from decomposing into background. To detect motion and tracking of human presence and gave alarm, we used an internet of things (IOT) based method with Hidden Markov model. The Raspberry Pi is a minuscule device emblazoned with sentient to monitor on its own when the own camera board is slotted into it. The motion detector aids the camera to detect and save. Capture in-real-time is also a notary feature of this device. At the core of it, a notification is pinged every time the detection picks up noise. It's directed by a pre-coded python script. This also collects the average coordinate of points. In this way, a cost-value system is proposed into place. Given that the application sends data over the internet, it's a well thought out solution to the theft issue.
Deep Neural Networks Algorithm for Vietnamese Word Segmentation

Traditional Vietnamese word segmentation methods do not perform well in the face of Vietnamese ambiguity, in response to the enormous challenge posed by the scarcity of the Vietnamese corpus to language processing. We first investigated the most advanced deep neural network method. According to the ambiguity problem of Vietnamese word segmentation, we then proposed a Vietnamese word segmentation processing technology based on an improved long short-term memory neural network (LSTM), which is made up of an LSTM encoding and a CNN feature extraction portion. The previous important information is kept in the memory unit; the word segmentation processing task is refined into a classification problem and a sequence labeling problem, which can gain the useful features of the word segmentation character and word level automatically. The limitation of the local context window size is avoided, and the word segmentation processing task is refined into a classification problem and a sequence labeling problem. Finally, validated by a homemade Vietnamese news website crawler dataset, the experimental results show that, compared with the single LSTM, single CNN methods, and traditional methods, the performance improvement of our proposed method is more obvious. In the Vietnamese word separation task, the accuracy reaches 96.6%, the recall reaches 95.2%, and the F1 value reaches 96.3%, which is significantly better than the traditional methods CNN and LSTM.
Reframing The Siop Model To Boost Teachers' Self Efficacy In Bilingual-Like Program: A Practical Concept Of An Alternative Model

The need to communicate through English and the desire to practice English in the teaching process has turned a public junior high school in Wonosobo, Indonesia, into one of the schools that hold an "English on Wednesdays" program to implement bilingual-like nuance. This conceptual paper highlights a natural phenomenon that occurs in that institution dealing with the desire to improve the competence of teachers and students in communication by programming "English on Wednesdays." The dilemmas related to teaching are felt by teachers, especially non-English teachers who do not have an English background, yet they are enthusiastic about this program. Thus, this paper will propose a framework called "The Alternative SIOP Model" that will help teachers overcome the dilemmas in teaching the "English on Wednesdays" program that emphasizes self-efficacy to develop teachers' competencies on lesson preparation and communication. This conceptual paper used the systemic review to gain information from theories and research findings related to the topic.&#x0D; Keywords: teachers' dilemmas; teachers' self-efficacy; the alternative SIOP Model
Perancangan Sistem Kenaikan Gaji Berkala Berbasis Java Pada Sekretariat Daerah Kabupaten Aceh Tengah

Purpose: To create a model of a periodic employee salary increase system that is useful for simplifying the fast, good, and efficient processing of employee rank and salary reports in this application, facilitating all types of administration (Wijaya, 2019). Research Methods: what is needed to apply for a periodic salary increase which is included in the KGB Submission menu which contains the requirements and files that must be completed for the progress of the salary increase, (Wardhani, Trinoto, &amp; Kuncoro, 2021). Results: to find out the process and results of submitting periodic salary increases for employees at the Regional Secretariat of Central Aceh Regency (Setdakab) with the validation and results menu, users can easily monitor the submission of periodic salary increases that have been submitted, can quickly determine to what extent the process has been running so it works.
A New Information Hiding Scheme Using Discrete Wavelet Transform at Physical Layer

The discrete wavelet transform (DWT) separates a signal into different frequency components with less arithmetic operations, and it is widely applied in information encryption. In this paper, we use DWT to embed and retrieve secret information at the physical layer, with small affection in the performance of the wireless communication system. The new scheme allows the secret signal to be transmitted to the intended receiver. The hidden secret can be considered as Gaussian noise superimposed on the original message signal. Simulation results illustrate stealth and robustness of our scheme in AWGN and Rayleigh fading channels. With the results, it is found that the proposed scheme is suitable for message watermarking and authentication.
Digital Risk Management: Investigating Human-Factor Security with a Behaviorist Approach

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Georgian Online Exercises for the Foreign Students − the principles of construction

Difficulties in the Georgian language learning are conditioned by the complexities of the language itself and by its otherness in comparison with the European languages. After the reading and writing skills are obtained, the complexities of the Georgian grammar remain to seem impossible to overcome multiple diversifications of the forms of the parts of speech, abundance of affixes, polypersonality of verbs – all those factors originate several problems for the foreign learners. It is already several years that the program “Irbakhi” has been working on in the Ministry of education and science of Georgia (prof. Marika Odzeli − the author and coordinator of the program), website www.geofl.ge is created and is provided by the learning and methodological material, containing manuals, working sheets, reading material, methodological papers, reference material in grammar, grammar guide books and all the materials correspond to the Common European Framework of Reference for Languages (CEFRL). Learning a foreign language only from the manuals is not easy. As time passes, the distance learning methods and exercises are being worked on throughout the world and correspondingly, the abilities to fulfill independently several grammar exercises are also growing. In response to this, on the given stage, within the “Irbakhi” program, a number of the online grammar exercises were compiled containing learning activities for the several stages such as: listening, writing, reading, lexis and grammar. There are several types of the useful exercises, whenever it is necessary for the learners, listening to some words, phrases and texts is also available which helps to fulfill the grammar exercises. The grammar exercises are based on the basic dictionary and abstracts of the literature texts, the fundamental issues of which are given in the text books, work books and reading material. The online grammar exercises represent the convenient additional learning material. When compiling them, we had to solve some problems: choosing the essential problems and systematizing them by the levels, using vocabulary as the base, creating systemic menu and using large varieties of the exercises themselves. The drop-down menu shows the Georgian grammar system through its morphology and syntax (i.e. parts of speech, grammatical categories and others). The issues related to the verbs are especially diverse, including person, number, mood, conjugation forms, preverb, special types of conjugation and so on. Some types of the grammar exercises are used: marking the correct answer out of 3 or 4 given; inserting a right answer into the right space of the table or scheme, also the type of exercise as drag and drop, choose the proper words or the endings in the given full texts. The exercises are simple in use, oriented on practical knowledge, self-checking and improving the level of knowledge.
Towards the Conceptualization of Occupations and Professions’ Explosion

The paper proposes the mainstreaming of the conceptual potential of Yu. M. Lotman (1922–1993) and M. K. Petrov (1923–1987) scientific and philosophical heritage relating to the theory of explosive complexity, increasing diversity and instability, which our society has recently been observing in occupational, vocational and professional spheres and the related social institutions (professional associations, professional education, professional guidance, etc.). Heterogeneous and heteronomic being-in-common (Fr. partage) in light of the works of J.-L. Nancy (b. 1940) is the most important heuristic intuition of the proposed updating. It allows one to think through a single, but flexible, multi-directionally transformable and polysemantic framework for the future theory of rapidly updated professional diversity, its explanation, forecast of likely development scenarios and strategies for self-determination within it and management strategies in relation to it. The authors present the conceptual unfolding of the intuition of being-in-common (partage) to be compatible with both the theoretical provisions of the semiotics of culture of Yu. М. Lotman and the socio-cultural dynamics of M. K. Petrov. Professionology is still searching for a methodological platform that would complement its retrospective generalizations and interdisciplinary discontinuity. The actualization of the potential of the concept of compatibility allows it to consolidate multidisciplinary research and its results and to guide them along the path of careful and, at the same time, bold theoretical construction in accordance with what social processes declare themselves to be. The authors observe the readiness of today’s multidisciplinary discourse to unite on such a methodological platform that allows for not to being lost in it under the influence of priorities and presumptions that are inevitable for the methodology, but, at the same time, focusing the collective efforts of occupational researchers on the most promising and practice-oriented aspects of the subject of their research.
Reliable Photovoltaics Output Power Prediction in Qatar

Renewable energy is gradually becoming the most promising type of power generation that could replace fossil fuels in the future. One of the most widely used form of renewable energy is solar/PV energy. To examine the impacts of different climatic circumstances and maintain solar power converters' optimal performance while meeting peak demand via diverse environmental conditions, accurate PV generating power prediction models are required. Air temperature, relative humidity, Photovoltaics (PV) surface temperature, irradiance, dust, wind speed, and output power are among the environmental parameters examined and addressed in this study. The model suggested in this study optimises and trains three prediction algorithms: the Artificial Neural Network (ANN), the Multi-Variate (MV), and the Support Vector Machine (SVM). To choose the best PV generating power forecast, the model uses three well-known prediction algorithms plus a voting method. Furthermore, given the environmental circumstances, the voting system predicts the output power with great accuracy. The MSE for Artificial Neural Network (ANN), Multi-variate (MV), and Support Vector Machine (SVM) is 98, 81, and 82, respectively. In comparison, the voting algorithm's Mean Squared Error (MSE) is only slightly higher than 53. With respect to the environmental circumstances in Qatar, the suggested PV power generation forecast algorithm produces trustworthy results. The suggested voting algorithm is anticipated to aid in the design process of photovoltaic (PV) facilities when energy output is very predictable.
Identifying Adversaries’ Signatures Using Knowledge Representations of Cyberattack Techniques on Cloud Infrastructure

Advanced Persistent Threats (APTs) have increased in parallel to growing cloud infrastructure and cloud Software-as-a-Service (SaaS) needs, exposing new vulnerabilities within the cloud environment. Moreover, APT groups are becoming more sophisticated and organised which needs to be addressed by the research community to enable faster response and more importantly, prevent threats within the domain. The MITRE ATT&amp;CK Cloud framework offers one of the leading structured inventories within this context. Our research is to expose patterns and signatures of a select group of APT’s on the MITRE Cloud Framework by using Formal Concept Analysis (FCA) to construct a “lattice graph” and an ontology. The goal is to develop a better conceptualisation of the MITRE ATT&amp;CK Cloud Matrix framework for cyber security experts to be able to proactively act upon adversary techniques. The MITRE ATT&amp;CK framework was retrieved, cleaned, and pre-processed to construct the lattice and ontology using data cleaning methods, FCA tools such as Concept Explorer, and the Web Ontology Language (OWL), with additional symbolic reasoning and inference generation. This resulted in knowledge representations/graphs, which are highly efficient representations of this knowledge field. The underlying linkages between techniques and targets specific to those APTs are further exposed and enriched and presented visually and integrated into the ontology. The ontology gives formalisation to associations and implications between techniques, tactics, and APTs – enabling cyber security practitioners to forecast potential targets and techniques based on their scenario, but also to attribute certain technique patterns and signatures to individual APTs. Cyber security practitioners can query from this knowledge graph and formulate strategic proactive measures. From these findings, the applications and constraints of the APTs’ cyber-attack techniques and their associated patterns were determined. The findings provide a guideline for future additional research in the field of AI knowledge representation in cybersecurity, as well as highlighting certain limitations in this field of research.
Pengembangan Fitur Video Pembelajaran untuk Mendukung Meteri Pembelajaran Digital Secara Online pada SMK Miftahul Huda

This research is a development from previous research in the form of digital module learning media, the development carried out is in the form of adding features that contain learning videos to support digital learning materials online. This research was conducted at SMK Miftahul Huda, which is located at Jalan Lintas Timur Km 124, Tugu Agung Village, Lempuing District, Ogan Komering Ilir Regency. During the Covid 19 pandemic, the teaching and learning process at many schools was hampered in the delivery of material, because there were no meetings. face to face to convey material. Most of the delivery of material currently only uses WhatsApp in the form of photos of the material and examples of this make students confused in understanding the material, examples and doing their assignments. The method used in the development of the instructional video features to support online digital learning materials at Miftahul Huda Vocational High School is linear sequential model. The solution to the problems faced by SMK Miftahul Huda is by developing learning media in the form of a learning system equipped with videos and online digital materials that can be accessed using a smartphone. This developed learning system can make it easier to get material and examples that are attached with learning videos so that it makes it easier for students to learn and increase interest in learning
The local diagnostic reference levels for breast screening using digital mammography at Songklanagarind Hospital

Introduction: This work aimed to determine local diagnostic reference levels (local DRLs) for screening mammography at Songklanagarind Hospital on digital mammography. Materials and methods: Retrospective data of screening mammography were collected from 400 patients from Songklanagarind Hospital, 200 patients from Tanyawej Breast Center and 200 patients from Premium Diagnostic Imaging Center. The patients were women aged between 40-75 years old with compressed breast thickness between 41-65 mm. and undertaken screening mammogram during 1st January 2019 – 31st October 2020. Patient data and exposure parameters collected were as follows: average glandular dose (AGD), entrance surface air kerma (ESAK), compressed breast thickness (CBT), compression force (CF), peak kilovoltage (kVp), tube current-time (mAs), target and filter (W/Rh, W/Al), and patient age. Results: The result showed that the average glandular dose of FFDM (2D mode) and DBT (3D mode) for compressed breast thickness 41-65 mm were 1.41±0.43 and 1.68±0.39 mGy, respectively and the 75th percentile of FFDM (2D mode) and DBT (3D mode) were 1.65 mGy and 1.89 mGy, respectively. The average ESAK were 4.93±1.96 mGy in FFDM (2D mode) and 5.31±1.55 mGy in DBT (3D mode), respectively. The 75th percentile of ESAK in FFDM (2D mode) and DBT (3D mode) were 6.03 and 6.17 mGy, respectively. There were 24.88 % and 24.63% received the average glandular dose over the 75th percentile in FFDM (2D mode) and DBT (3D mode). Conclusion: Local Diagnostic Reference Levels for FFDM (2D mode) and DBT (3D mode) at Songklanagarind Hospital were 1.65 mGy and 1.89 mGy. The Local DRLs in our study was safe and lower than the standard reference levels reported by the International Atomic Energy Agency at 3 mGy/view.
A large-scale container dataset and a baseline method for container hole localization

Automatic container handling plays an important role in improving the efficiency of the container terminal, promoting the globalization of container trade, and ensuring worker safety. Utilizing vision-based methods to assist container handling has recently drawn attention. However, most existing keyhole detection/localization methods still suffer from coarse keyhole boundaries. To solve this problem, we propose a real-time container hole localization algorithm based on a modified salient object segmentation network. Note that there exists no public container dataset for researchers to fairly compare their approaches, which has hindered the advances of related algorithms in this domain. Therefore, we propose the first large-scale container dataset in this work, containing 1700 container images and 4810 container hole images, for benchmarking container hole location and detection. Through extensive quantitative evaluation and computational complexity analysis, we show our method can simultaneously achieve superior results on precision and real-time performance. Especially, the detection and location precision is 100% and 99.3%, surpassing the state-of-the-art-work by 2% and 62% respectively. Further, our proposed method only consumes 70 ms (on GPU) or 1.27s (on CPU) per image. We hope the baseline approach, the first released dataset will help benchmark future work and follow-up research on automatic container handling. The dataset is available at https://github.com/qkicen/A-large-scale-container-dataset-and-a-baseline-method-for-container-hole-localization .