Reviewerly/exHarmony huggingface dataset:
The Aided Design of Interior Layout Based on Artificial Intelligence

With the development of science and technology, artificial intelligence technology has gradually matured and has been widely used in the field of computer-aided design. Based on artificial intelligence, a comprehensive interactive management system conforming to the indoor layout and three-dimensional space is constructed. This paper will combine the theoretical knowledge of interior space geometric lines, virtual reality, etc., and use digital modeling methods to analyze the relationship and mutual influence factors of various elements in the two-dimensional CAD model, and establish mathematical models to achieve three-dimensional visual display, and finally complete a computer-based intelligent design environment to improve work efficiency and user experience, and then test the platform, and the test results show that, The operation reliability, safety and stability of the auxiliary tool for indoor layout based on artificial intelligence technology are very high, which can make the indoor layout design tool efficient and low error rate. Based on artificial intelligence, the layout auxiliary system is designed to meet different ages, different regions, and personalized needs. In interior layout design, AI-based layout-assisted design can effectively improve space utilization and reduce costs. Analyze different user needs and functions to determine different sizes, materials or styles. Decide the layout location and method according to customer needs.
Convolutional Radon Transformation Method for Sparse Collective Recognizing

The onboard processing technology based on remote sensing images has become the focus of current research area and received widespread attention. With the increasing amount of onboard data, how to extract effective information from massive data becomes increasingly important. In this paper, a novel sparse collective formation recognizing method is proposed to detect and analyze the formation of the surface ship formation. Firstly, a mobilenet is trained to detect the carrier and single ships to form a binary encoded map, which will be segmented by the DBSCAN method to extract the suspected formation. Then the binary encoded map is processed by the convolutional radon transformation and the result is compared with the standard confidential dataset (SCD) of three formations. Finally the formation type, confidential probability, direction of the surface ship formation was given by the comparison result which has the minimum root-mean-square-error (RMSE) with the SCD. The experimental results show that the proposed method can recognize the ‘Y’, ‘T’ and ‘I’ type surface ship formations with different offsets under more than 60% confidential probability and has a significant feasibility and robustness.
CONDUCTING ENGLISH TEACHING BY USING DIFFERENTIATION INSTRUCTION IN 21ST CENTURY: A STUDENT-CENTERED APPROACH

In one class, there are various students with different characteristics and learning styles. To achieve the learning objectives, the teacher should apply differentiation instruction. In this study, the concept of differentiation instruction is implemented in learning English, a student-oriented approach. The data sources take from learning outcomes conducted in XII MIPA 1 at SMA Negeri 5 Medan in their process of doing the project. The material taught by the teacher in proving this concept is Conditional Sentence Type 2. The learning method used is project based learning. The learning process carried out for this research lasted for four meetings. This research wants to prove that implementing the concept of differentiation instruction can make the students think ingenious while working with groups to produce the original product. In another words, this research aims to prove the teacher's way of conducting the learning process by implementing the concept of differentiating instruction to produce creative and original products. This concept needs to be implemented so the students can apply Conditional Sentence Type 2 into their daily lives. The result shows each group could work together as a team to produce poetries and songs by using Conditional Sentence Type 2. Each group was enthusiastic to perform their best work in front of the class. Also, the learning process became purposeful and meaningful.
Do Digital platforms have positive effects or negative ones on children’s learning a new language?

The research show that digital platforms are found as a useful tool in teaching progress. Therefore, teachers should determine the right educational digital platforms in order to improve teaching quality. Especially when teaching preschool and elementary school students, animations have a great power to catch their interest in learning a new language. In this article, essential features of digital platforms will be revealed with facts and experiments.
The Hypothesis of Cognitive Reagents: Potential Applications

The present study explores the hypothesis of cognitive reagents for early detection of dementia and impairment in various cognitive domains. A comprehensive analysis of task-based assessments using specific cognitive tasks targeting different aspects of cognitive functioning is proposed. Ten cognitive domains, including numerical/alphabetical attention, word/image recall, comparison/differentiation, generalization, numerical reasoning, verbal reasoning, shape recognition, general quantitative reasoning, time/place orientation, and concept description, are investigated as potential biomarkers, with corresponding cognitive tasks acting as reagents for evaluating cognitive impairment. By examining the effectiveness of these cognitive reagents, the study aims to contribute to the development of reliable and efficient methods for assessing cognitive functioning and detecting early signs of dementia.
Experimental Analysis of “A Novel Swarm Intelligence Optimization Approach: Sparrow Search Algorithm”

The sparrow search algorithm (SSA) is the latest swarm optimization technique. SSA was invented not only to solve complex global optimization problems but also to obtain the best optimal solution with respect to convergence rate, preciseness, completeness, and reliability in comparison with existing Heuristic, Metaheuristic, and other algorithms. SSA was tested on 19 benchmark functions by Jiankai Xue and Bo Shen in their own paper and it was found that the output of SSA was much better in relation to convergence speed, accuracy, robustness, and stability as opposed to PSO, GWO, and GSA. After the invention of SSA, many researchers emphasized its steady convergence, deficiency of drop within local optimum together with poor accuracy, and to make its complete improvement, they modified it. In this paper, to check that the convergence rate of SSA is really slow, and it is implemented on 10 benchmark functions which are different from the 19 benchmark functions which were used in the sparrow search algorithm’s paper. After the comparison of experimental results of SSA with GWO, BBA, and PSO, it is obtained that the convergence speed of SSA is slow in some benchmark functions.
Hyperparameter Optimization of CNN Using Genetic Algorithm for Speech Command Recognition

Identification or recognition of speaker uttered short speech commands, known as speech command recognition (SCR), is a challenging problem in digital speech processing. It plays a vital role in various real-life applications such as Internet of things (IoT) devices and assistive technology to name a few. The deep learning models like convolutional neural networks (CNNs) have shown the potential ability to solve SCR tasks. However, these models' performance heavily depends on the appropriate choice of associated hyperparameters values, which are very labor-intensive and time-consuming. This paper proposes a genetic algorithm (GA)-based hyperparameters optimization approach to fine-tune CNN hyperparameters for performing SCR tasks. The proposed method is trained and tested with the google speech command (GSC) dataset by considering eight speech commands. The experimental results demonstrate the efficiency and effectiveness of the proposed method for solving speech features-based classification problems like SCR.
Online Unsupervised Video Object Segmentation via Contrastive Motion Clustering

Online unsupervised video object segmentation (UVOS) uses the previous frames as its input to automatically separate the primary object(s) from a streaming video without using any further manual annotation. A major challenge is that the model has no access to the future and must rely solely on the history, <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">i.e</i> ., the segmentation mask is predicted from the current frame as soon as it is captured. In this work, a novel contrastive motion clustering algorithm with an optical flow as its input is proposed for the online UVOS by exploiting the common fate principle that visual elements tend to be perceived as a group if they possess the same motion pattern. We build a simple and effective auto-encoder to iteratively summarize non-learnable prototypical bases for the motion pattern, while the bases in turn help learn the representation of the embedding network. Further, a contrastive learning strategy based on a boundary prior is developed to improve foreground and background feature discrimination in the representation learning stage. The proposed algorithm can be optimized on arbitrarily-scale data ( <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">i.e</i> ., frame, clip, dataset) and performed in an online fashion. Experiments on <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">DAVIS<sub>16</sub>, FBMS</i> , and <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">SegTrackV2</i> datasets show that the accuracy of our method surpasses the previous state-of-the-art (SoTA) online UVOS method by a margin of 0.8%, 2.9%, and 1.1%, respectively. Furthermore, by using an online deep subspace clustering to tackle the motion grouping, our method is able to achieve higher accuracy at 3× faster inference time compared to SoTA online UVOS method, and making a good trade-off between effectiveness and efficiency. Our code is available at https://github.com/xilin1991/CluterNet.
Impact of Digitalizing Healthcare Business Operations on Cybersecurity Landscape

The technological evolution and digitalization of business operations contributed to healthcare organizations' constantly changing cybersecurity landscape. It is compulsory and mandated by the covered entities to fully comply with the industry regulatory standards, procedures, laws, and guidelines. The compliance officer must pay attention to the change in the business operations and the laws governing the organization's business operation. Developing an automated cybersecurity team that will track the change in the cybersecurity landscape of healthcare businesses as the business operations move toward digitalization and adoption of artificial intelligence-driven solutions. Adopting AI as a defensive measure requires an organization to monitor and assess the patent application landscape before deploying any AI intellectual property for its risk mitigation strategy or infrastructure protection. The security team must ensure that the usage of AI at the organization complies with the US federal and state antitrust laws. The organization's security team will implement control to identify data retention limits and regulate and permit the use of personally identifiable information within the organization. The enforcement will be via an organization's processes, functions, or approved mechanisms. The security team will implement binding techniques to strengthen the information flow enforcement process. This paper will elaborate on the binding technique that will regulate the number of users accessing the organization's resources or information. Keywords: Digitalization, Artificial Intelligence, Controls, Compliance, Rule &amp; Regulation. Journal Reference Format: Yamcharoen P., Folorunsho O.S., Bayewu A. &amp; Ojo T.P. (2022): Impact of Digitalizing Healthcare Business Operations on Cybersecurity Landscape. Journal of Behavioural Informatics, Digital Humanities and Development Research. Vol. 8.No. 4, Pp 27-34. Available online at https://www.isteams.net/behavioralinformaticsjournal. dx.doi.org/10.22624/AIMS/BHI/V8N4P3
Efektivitas Media Daring Pembelajaran PAI Siswa Kelas VIII Di SMP Pahlawan Toha Kota Bandung

The decrease in the enthusiasm for learning in students shows that students are still less motivated to explore PAI subjects. This habit is because students are not used to using technology as a learning medium. The purpose of this study was to determine the effectiveness of PAI learning in using online media in class VIII students at Pahlawan Toha Junior High School, Bandung City. This study uses a qualitative approach with phenomenological methods. The technique in this study uses triangulation, namely, interviews, observation and documentation. The results showed that the effectiveness of PAI learning using online media was quite effective. It is evident from the achievement of indicators of learning effectiveness with a very high percentage of 77.3%, it can be concluded that PAI learning using online media for class VIII students at SMP Pahlawan Toha City Bandung is effective.
Real Estate Augmented Reality Marketing Media Strategy: Formgiving architectural design

Using real estate agents to advertise home has long been a common practice. Some developers use a scale model to reflect the design results as a physical model however, the production requires components that cost quite a bit of money and are not practical nowadays. Hence, this study attempt to uncover the challenge of using augmented reality in marketing. The design framework for using augmented reality in marketing is determined using User-Centered Design with a protocol design method. Tracking and context identification, sound, one contact, kinesthetic and sensory modalities are the five types of design criteria identified.
EVALUATING BERT AND PARSBERT FOR ANALYZING PERSIAN ADVERTISEMENT DATA

This paper discusses the impact of the Internet on modern trading and the importance of data generated from these transactions for organizations to improve their marketing efforts. The paper uses the example of Divar, an online marketplace for buying and selling products and services in Iran, and presents a competition to predict the percentage of a car sales ad that would be published on the Divar website. Since the dataset provides a rich source of Persian text data, the authors use the Hazm library, a Python library designed for processing Persian text, and two state-of-the-art language models, mBERT and ParsBERT, to analyze it. The paper's primary objective is to compare the performance of mBERT and ParsBERT on the Divar dataset. The authors provide some background on data mining, Persian language, and the two language models, examine the dataset's composition and statistical features, and provide details on their fine-tuning and training configurations for both approaches. They present the results of their analysis and highlight the strengths and weaknesses of the two language models when applied to Persian text data. The paper offers valuable insights into the challenges and opportunities of working with low-resource languages such as Persian and the potential of advanced language models like BERT for analyzing such data. The paper also explains the data mining process, including steps such as data cleaning and normalization techniques. Finally, the paper discusses the types of machine learning problems, such as supervised, unsupervised, and reinforcement learning, and the pattern evaluation techniques, such as confusion matrix. Overall, the paper provides an informative overview of the use of language models and data mining techniques for analyzing text data in low-resource languages, using the example of the Divar dataset.
Perancangan Sistem Informasi Analisa Website Penjualan Mobil menggunakan Metode Webqual 4.0

The existence of the internet is no longer foreign to almost all circles of society. Internet has become one of the important needs in everyday lives, especially in information exchange. Utilization of the internet can’t be separated from the existence of website, a place where the information needed by the user is located. To attract the attention of visitors, a website should have an attractive, communicative, and user-friendly appearance. This research was conducted at PT. Sejahtera Buana Trada – Suzuki Pantai Indah Kapuk (PIK), where the sample used in this study are consumer PT.SBT – PIK totaling 100 people. To determine the sample, Webqual 4.0 method is used in which data is collected through interview and questionnaires. The data analysis technique used validity test and reliability test, then to calculate the data results used quantitative descriptive analysis methods. From the test results based on the usability aspect, the percentage is 96,25%, the Information Quality aspect is 96,77%, the Service Interaction Quality aspect is 85,75%, and Overall Impression is 87,40%. Results The average of the four aspects obtained a percentage of 91,54%. So it can be concluded that the highest aspect is Information Quality, while the lowest aspect is Service Interaction Quality.
The Effect of Task Tepetition on Complexity, Accuracy, and Fluency of Indonesian Maritime Vocational School Students’ Speaking Performance

Developments in the area of task-based language teaching (TBLT) research have focused on the task implementation factors in that they effectively promote successful language performances. The present study aimed to examine the effect of task repetition on the speaking performances of students who studied English Specific Purposes at an Indonesian Maritime Vocational School. To this end, a pre- and post-test quasi-experimental design was applied that involved 43 participants, who were non-randomly selected and considered as two groups of the experimental and control ones. Both groups took a pre-test to ensure their homogeneity in speaking skill. For 12 sessions, the experimental group was engaged in repetitive practice of speaking tasks. Three weeks after the end of the treatment, both groups performed the two post-tests. The results of independent samples t-tests showed that the experimental group significantly outperformed their counterparts in the control group in terms of task complexity on the two post-test phases (p&lt;.05). However, they did not differ significantly in terms of accuracy.
Interest of the Students in the Lecturer's Teaching Performance in the Hybrid Classroom

Abstract. This study sought to determine whether students in the English Language Study Program are interested in the lecturer's teaching performance in learning English for Tourism subject for hybrid classroom, as well as the impact of the lecturer's teaching performance on students' interest in learning English for Tourism subject. This study employed a combination of quantitative and qualitative studies In the academic year 2021/2022, the population consisted of students of English Language Education (ELE) study program. There were 260 ELE students as the population. By addressing purposive sampling, which has some categories namely: the students who were enrolling in English for Tourism subject; the students were eager to participate in this study. There were 52 students involved as the subject. In order to obtain the data, the researchers utilized the survey questionnaires and semi-structured interview as research tools. Testing the hypotheses provided information on the relationship between lecturer’s teaching performance and students’ interest in learning English for Tourism subject. SPSS version 26 for Windows was utilized by the researcher to handle and analyze the data for this study. The findings of this study demonstrate that the majority of questionnaire computations result in. According to the findings of the interviews, the majority of students believe that the teacher's teaching performance has an impact on students' interest in learning the English for Tourism’ subject. Some implications has been proposed by the researchers namely: the beginning to build effective plans, well-prepared lecturers need to have a thorough understanding of the work at hand, they are: the language appropriate for the level; the appropriate skills; the appropriate learning resources; the appropriate teaching stages and methods; A variety of activities; Classroom management abilities; grab your online and offline studentsKeywords: Students’ Interest; Teaching Performance; Hybrid Classroom
ADMINISTRATIVE ACTIVITIES IN AN OUT-OF-SCHOOL EDUCATION INSTITUTION IN TODAY'S CONDITIONS

Management activities in today's conditions face new challenges every day, which require an immediate response and the construction of a strategy for their solution. Management of after-school education institutions is a difficult and responsible task, especially in the current conditions. At the same time, this task is extremely important, because after-school education plays a vital role in preparing the rising generation for success in today's economy. A review of the existing literature revealed that challenges faced by out-of-school education institutions include funding, organizational challenges, and the need for appropriate educational content. To address these challenges, the paper recommends innovative solutions such as public-private partnerships, staff development programs, and investment in modern infrastructure and equipment. In addition, post-secondary institutions must focus on providing relevant, practical education that prepares students for success in today's economy. Management of out-of-school education institutions in today's environment faces numerous challenges, including funding, infrastructure and educational content. These challenges can hinder institutions' ability to provide quality education to students, potentially affecting their success in today's economy. The COVID-19 pandemic also made adjustments to modern out-of-school education, which in turn created new challenges for management, including the need to adapt to distance learning and ensure a safe and healthy learning environment. Effective management of out-of-school education institutions requires a willingness to address the challenges facing these institutions through innovative solutions and a focus on providing quality education to all students. Collaboration between post-secondary institutions, schools and community organizations can help solve funding, staffing and infrastructure challenges. If effectively managed, after-school institutions can continue to play a critical role in shaping the future of education and preparing students for success.