Reviewerly/exHarmony huggingface dataset:
Sentiment Classification on tweets Based on LSTM with variants and BERT finetune

Covid-19 is a new type of epidemic, we performed sentiment classification tasks on Covid-19 tweets using different machine learning models. The famous pre-training models are not trained with the text relevant to COVID-19, a new kind of virus appearing at December 2019. The twitter posts with such a topic also have not been applied to test the performance of existing pre-training models and neural networks well. In our experiment, we used LSTM and Transformer to do the sentiment analysis (quinary classification) with a dataset including those twitter posts and tried different hyperparameters and models to improve the performance of classification. We finally found that the Transformer performs better than LSTM with an extra softmax layer in the encoder part, and the bidirectional transformer with 4 hidden layer and dropout 0.2 provides the best results among all hyperparameters we have tested. With the finetune of BERT,we got the best performance with the accuracy over 85%.
Improved time-aware debiasing models for recommender systems

Recommender systems are affected by user selection bias during user interactions. Previously, Huang, Jin et al. proposed the TMF-DANCER model to deal with the fact that selection bias is dynamic, and the popularity of an item and user preferences may change drastically over time. However, the previous time-aware methods did not consider the continuity of time, and performing collaborative filtering with matrix factorization may not be able to capture the complex structure of user interaction data. Our methods enhance the effectiveness of time-aware debiasing by utilizing the time-varying sequential method to alleviate the discontinuity of time-based on the frequency-based method, Replacing the matrix factorization with neural collaborative filtering (NCF). We used movie lens 100k as the data for training. The experimental results indicate that methods incorporating the time-varying sequential method and NCF have better performance in rating prediction than debiasing methods without.
New encoders based on depthwise separable convolution for SteganoGAN to improve steganography efficiency

In recent years, deep learning has developed vigorously, including many applications in the field of image steganography, of which steganogan is a representative. However, its network structure is a generative countermeasure network based on convolutional neural network (CNN). Because the generative adversial network (GAN) is difficult to train, there are problems such as mode collapse and gradient disappearance. Training the generative countermeasure network often requires many rounds of training, consuming a lot of computing resources. In this paper, the idea of deep separable convolution of mobile net is used for reference, and the encryption and generator in the generation countermeasure network for encryption is changed into a depthwise separable convolution encoder, which is compared with the original model, improves the speed of training and reasoning, and facilitates steganography on mobile devices and some low-performance devices.
The COVERED FACE: FaceNet-based partially occluded person recognition - on attention mechanism

This paper investigates the problem of improving the recognition accuracy of partially occluded faces. We aim to insert the attention mechanism blocks into the FaceNet to improve its recognition capability. FaceNet has excellent performance as a general-purpose face recognition system. However, recognizing faces with incomplete facial features is a challenge for feature extraction networks. To overcome this weakness and improve the recognition range of FaceNet, this paper proposes to incorporate the attention mechanism in the feature extraction network so that the attention of the model will be focused on the face features that are not occluded. The addition of the attention mechanism makes the application scenario of FaceNet more flexible and improves the anti-interference ability and robustness of the model. The results show that FaceNet trained by non-specific target dataset can improve the performance after adding the attention mechanism. In detail, the improvement in recognition for regular datasets is small. Nevertheless, the performance of the model is significantly improved for certain datasets with extreme conditions, such as face images with occlusions. In general, inserting the attention mechanism blocks in FaceNet can improve its value and expand its usage environment.
Does the VR Experience Influence Visit Intentions? Case Study of Ijen Crater in Indonesia

Tourism plays a crucial role in the Indonesian economy. However, the Covid-19 pandemic has substantially impacted the tourism industry. One of the destinations that have been heavily affected is the Ijen Crater. Virtual tourism has emerged as a crucial tool for promoting destinations, including the Ijen Crater, and is helpful to both tourists and tourism managers. This study examines the influence of information access, flow, and telepresence, representing the virtual reality (VR) experience of the Ijen Crater, on tourists' intention to visit the site. Hedonic value mediates the relationship between the VR experience and visits intention on the Ijen Crater. The study involved 117 respondents who had experienced Ijen crater virtual reality, and the SEM-PLS method was used for analysis. The research findings indicate that flow and telepresence have a significant influence on hedonic value, and flow itself has an indirect effect on visit intention. While information access does not significantly impact hedonic values, information access and telepresence do not indirectly influence visit intention to the ijen crater. These findings contribute new insights for researchers, stakeholders, and managers of Ijen tourism.
Latent Dirichlet Allocation Utilization as a Text Mining Method to Elaborate Learning Effectiveness

Learning method is a way to explain the lesson materials to students so that the learning process can occur in students as an effort to achieve the goals. Learning methods can be said to be a success if students are active, both physically, mentally, and socially in the learning process, in addition to showing high enthusiasm for learning and having self-confidence. The purpose of this study is to classify the opinions of Indonesian students regarding the existing learning methods and what learning methods they expected. In order to evaluate existing learning methods using the latent dirichlet allocation method. The data used comes from tweets of Twitter users within the range of January to March 2022. The data is taken using the scrapping method through the help of the python twisel library and totaled to 3778 data, then preprocessed through the nltk and Sastrawi libraries. The results of this analysis stated that student opinions can be classified into 3 major topics which state students' opinions regarding effective learning methods, student difficulties in applicable learning methods, and high cross-departmental interest.
DEVELOPING LEARNING MEDIA BY USING BASIC ENGLISH GRAMMAR POCKET BOOK

The objective of this research is to develop learning materials for the precise understanding of Basic Grammar in English, in the form of a Pocket Book, specifically designed for eighth-grade students at MTs Bustanul Ulum, Glagah, Lamongan. The research employed a developmental research approach, consisting of ten stages: Need Survey, product design, design validation, design revision, try out 1, product revision, try out 2, product revision, and final product. The developed product underwent review by a supervisor, Media Expert, and Material Expert, and was evaluated by 15 students from MTs Bustanul Ulum. The research instruments included a questionnaire for the Validators, a questionnaire for student feedback, and an interview guide for the teacher to analyze the students' results. The students' responses were analyzed using both quantitative and qualitative methods, with the quantitative analysis used for calculating the results and the qualitative analysis employed for interviews, critiques, and suggestions. The findings indicated that the students required a supportive book for learning English with simple explanations and comprehensibility. The outcome of this study was the creation of a Basic English Grammar Pocket Book. The researcher suggests that this product can be utilized in the learning process for an extended period as it facilitates easy studying and allows students to carry the book everywhere they go.
Collective Knowledge Tracing: Estimating Average Knowledge Mastery for Students

Once a student has worked on a sequence of exercises in a course, based on whether the answers are correct or not, \emph{knowledge tracing} (KT) aims to estimate the knowledge mastery of the student by predicting the probability that he/she can correctly answer next exercises. The higher the probability is, the better the knowledge mastery is. Different from existing \emph{knowledge tracing}, called \emph{individual knowledge tracing} (IKT) in this study to show distinction, we investigate \emph{collective knowledge tracing} (CKT) which estimates the average knowledge mastery of all students in the course once having worked on a sequence of exercises. \emph{Collective knowledge tracing} has unique values in various applications in the education domain. To optimize \emph{collective knowledge tracing}, we propose a graph-based solution to capture not only the sequence order of exercises but also the repetition of exercises. The experiments on four benchmark datasets demonstrate the effectiveness of the proposed solution against baselines based on the-state-of-art methods originally designed for \emph{individual knowledge tracing}. Also, the case study of \emph{collective knowledge tracing} on three applications in the education domain has been testified and reported in this paper.
General characteristics and research progress of tellurium mineralization

碲作为稀散元素,很少形成独立矿床,主要以共伴生形式产出于多个类型矿床中,包括铜镍硫化物和铂族矿床、铁氧化物铜金(IOCG)矿床、块状硫化物(VMS)矿床、斑岩矿床、矽卡岩矿床、造山型金矿、卡林型金矿和浅成低温热液矿床等。研究表明,碲元素可以形成上百种碲矿物,除了自然碲之外,多与Au、Ag、Pb、Bi、Cu等形成碲化物,与S或者Se形成碲的硫化物或硒化物,也可以形成碲酸盐、硅酸盐、磷酸盐、硫酸盐等矿物;此外Te还可以以类质同象形式替换寄主矿物中的元素。在成矿带尺度、矿床尺度及其矿石中碲均表现出极不均匀的分布特征,与主矿种Cu、Au、Ag等具有成因关系。碲具有多来源特征,可以源自地幔,也可以是浅部壳源岩浆或是围岩地层提供。碲矿化一般发生在成矿的中晚阶段,流体可通过混合作用、水岩反应、沸腾作用等改变体系的物理化学条件(如pH值、硫逸度、氧逸度、碲逸度、温度等),导致流体pH值升高、硫逸度和氧逸度降低,碲逸度升高,这是诱发碲矿物富集和沉淀的主要机制。碲由于其受控成矿条件较为特殊,需要着重加强碲富集成矿的关键控制因素、成矿物质来源和富集沉淀机制的研究。
Inclusive Growth and Structural Transformation: The Role of Innovation and Digitalisation Spillover

Structural transformation is a compelling measure of economic progress as it shifts from less productive to more productive sectors, spurred by technological improvement and digitalisation. Despite the benefits of structural transformation in fostering economic growth, it has been contended that it will exacerbate income inequality. Given the critical role of digitalisation over the years in Africa, the current study investigates the pattern and impact of structural transformation on inclusive growth. To accomplish this, we utilised both absolute (poverty) and relative (income inequality) measures of pro-poor growth for all African countries. Using quantiles via moments panel model, we showed that the structural transformation from agriculture to services reduced the incidence of poverty (extreme poverty) while increasing inequality (Gini coefficient). On the other hand, manufacturing had no significant effect on poverty or inequality, indicating the region’s slow pace of industrialisation. Using income share measures, we found evidence of inequality across and within sectors, particularly in the services sector. Finally, we observed that digitalisation and technological processes significantly reduced the incidence of extreme poverty and inequality. Hence, the study recommends that Africa capitalise on its comparative advantage in the agricultural sector by establishing investment and manufacturing zones to develop the industrial sector. Furthermore, gains in the manufacturing sector could be realised through a concerted effort to improve the industrialisation process.
Optimized Encryption Technique for Securing E-Health Images

Medical imaging data must abide by strict confidentiality and data protection standards, much as the bulk of patient data. Due to the aforementioned concerns and the potential for information/data leakage, communicating clinical picture information within an open organization becomes problematic. In the past, methods for concealing data and encrypting photographs were possible fixes. However, these techniques could have problems if you try to recover the original image. In this work, an algorithm for medical picture protection based on the pixels of interest was created. Peaks in medical images are calculated using peak detection in an image histogram. In medical imaging, threshold values were used to process pixels of interest. The average of all peaks in the histogram serves as a marker for the threshold. These pixels are encoded with interest values using a Sudoku matrices. A number of statistical tests will be used to evaluate the suggested plan, and the results will be compared to industry norms. The outcomes demonstrate that the proposed method outperforms competing picture encryption techniques in terms of security.
Elementary pre-service teachers' ambivalent views on the introduction of artificial intelligence education: photovoice analysis

This study aimed to investigate the ambivalent views held by pre-service elementary school&#x0D; teachers regarding the introduction of artificial intelligence education using photovoice. The analysis&#x0D; was conducted on a total of 116 photographs and accompanying descriptions, which were carefully&#x0D; selected and contextualized by four of the 29 research participants. The findings can be summarized&#x0D; as follows.&#x0D; First, supportive views regarding the introduction of AI education were derived from seven&#x0D; themes: 1) The familiarity of students with the digital environment, 2) The responsibility of the&#x0D; school education system to prepare students for future society, 3) Opportunities to overcome the&#x0D; limitations of existing teaching methods, 4) The potential of AI as an effective learning tool, 5)&#x0D; The potential for customization of classes and feedback, 6) The potential of AI to spark interest in&#x0D; learning by integrating with the digital learning environment, and 7) The role of AI in providing&#x0D; teaching support and assistance to teachers.&#x0D; Second, opposing views on the introduction of AI education were derived from the following&#x0D; eight themes: 1) Concerns about AI's appropriateness for the development stage of elementary&#x0D; school students, 2) Unpredictable risks and potential side effects, 3) AI’s limitations in fostering a&#x0D; complete learning process, 4) Limitations of the value of direct experience, 5) Emphasis on the&#x0D; importance of teaching value judgment and critical thinking skills prior to AI integration, 6) Fears&#x0D; of losing human relationships, communication skills, empathy, and community spirit, 7) Belief that&#x0D; AI cannot replace professional expertise and assistance provided by teachers, and 8) Reduced&#x0D; thinking skills due to dependency on AI.&#x0D; Third, the study delved into the ambivalent views surrounding the introduction of AI education&#x0D; by interpreting the pros and cons perceived by pre-service elementary school teachers. These&#x0D; ambivalent perspectives were analyzed from the standpoint of their implications for students,&#x0D; teachers, the teaching and learning process, and society at large.
Implementation of Virtual Keyboard Using Hand Gestures

Abstract: Human interaction with computers is increasing everyday with the advancement in Technology. The different ways of interaction with computers have become an important factor in choosing devices. Humans are more interested in lightweight, touchless technologies that can make the work easier and easier. In this Paper, a virtual keyboard and mouse that act as touchless input medium to Computers and eliminates the use of physical keyboard and mouse has been proposed. The virtual keyboard and mouse are designed to execute its functionality by recognizing hand gestures. The project is build using Python, OpenCV, MediaPipe technologies which provides features for hand gesture controls. It requires a computer or laptop with camera. The idea is to display the customized keyboard layout on the computer screen and the built-in camera captures the hands and its movements over the virtual keyboard layout. A forefinger hovering over the keyboard keys highlights those keys and when the tips of forefinger and middle finger met, then that key is clicked, which is taken as input to computer and displayed on the screen. A virtual mouse has been designed to function as a physical mouse based on hand gestures. The virtual mouse recognizes the fingertip of forefinger and movement of that finger is considered as cursor movements. When the forefinger points to the elements on the screen, it is highlighted as if the cursor is placed over those elements. The overlapping of tips of forefinger and middle finger are designed as a click.
Strategies for Organizing Information Domain Contents and Developing Textbook in Response to The 2022 Practical Arts Curriculum Revisions

This study aimed to explore the content organization and textbook development strategies for the&#x0D; information domain of the 2022 Practical Arts curriculum revision. To this end, we examined the&#x0D; features of the organization of the information section of the 2022 Practical Arts curriculum. We&#x0D; delved into aspects such as content structure, achievement standards, teaching and learning&#x0D; methodologies, and assessment criteria that constitute the information section of the 2022 revised&#x0D; Practical Arts curriculum. This analysis enabled us to discuss their distinct characteristics and derive&#x0D; implications from our findings. Subsequently, we selected the content (draft) to be incorporated into&#x0D; the Practical Arts textbook, assessed the appropriateness of this content (draft) for each element of&#x0D; the textbook system, and presented how the information domain should be organized into units. We&#x0D; also identified digital devices suitable for this domain and provided detailed guidelines for writing&#x0D; the textbook content.&#x0D; Based on the study’s findings, the following conclusions were drawn. First, when structuring the&#x0D; content and organization of the information domain in Practical Arts textbooks, it is crucial to have&#x0D; a precise understanding of the unique attributes and relationships among various categories of the&#x0D; curriculum content system, achievement standards, and the functions of teaching, learning, and&#x0D; assessment. An effective organization should ensure that the combined and integrated outcomes of&#x0D; these elements are presented appropriately, all while adhering closely to the curriculum guidelines.&#x0D; Second, in developing Practical Arts textbooks, particular attention should be given to enhancing&#x0D; learners' digital literacy within the information-related aspects of the 'Sustainable Technology and&#x0D; Convergence' domain. Additionally, the Digital Society and Artificial Intelligence section should&#x0D; consider both the 2015 Practical Arts curriculum and insights from prior research on artificial&#x0D; intelligence. Third, the development of Practical Arts textbooks should draw from the findings of&#x0D; this study but should also encourage creativity and flexibility within the framework of the&#x0D; curriculum guidelines.
Ontological and Epistemological Reflections on the Philosophy of Invention

This study aims to examine the complex and multifaceted nature of invention in the ontological&#x0D; and epistemological aspects of the philosophy of invention. The conclusions drawn are as follows.&#x0D; First, the ontological status of invention is complex and multifaceted, encompassing its perception&#x0D; as a product of human subjective action, an objective entity, and a result of the interaction between&#x0D; subjectivity and objectivity. Second, in the ontology of invention, the issue of novelty sparks a&#x0D; debate regarding the criteria for deeming an invention genuinely new. Third, in the ontology of&#x0D; invention, subjective creativity exists in an individual's cognitive and imaginative process, while&#x0D; objective creativity manifests as new inventions and technological artifacts, serving as visible&#x0D; outcomes of the invention process. Fourth, in the epistemology of invention, invention hinges on&#x0D; dynamic interactions involving the acquisition of new knowledge and its integration with existing&#x0D; knowledge. Inventors focus on gathering diverse knowledge from various sources and integrating it&#x0D; to generate innovative ideas. Fifth, in the epistemology of invention, the significance of tacit&#x0D; knowledge and expert knowledge extends beyond explicitly expressed or codified knowledge,&#x0D; playing pivotal roles in the invention process. Sixth, in the epistemology of invention, justification&#x0D; provides the basis for inferences and arguments that support the significance of invention within the&#x0D; context of invention claims and descriptions. Finally, in the epistemology of invention, the social&#x0D; construction of invention underscores that both invention and knowledge are not solely products of&#x0D; individual effort but are also shaped by social and cultural factors.&#x0D; In terms of the implications of exploring the philosophy of invention for invention education, on&#x0D; the ontological side of invention, it is essential for school-based invention education to prioritize the&#x0D; development of creativity as a core competency. On the epistemological side of invention, invention&#x0D; education should recognize the importance of experiential learning. It should provide students with&#x0D; opportunities for hands-on maker experiences, project-based learning, and mentorship from experts in&#x0D; relevant fields to foster the development of students' tacit knowledge.
HEROES: Unreal Engine-based Human and Emergency Robot Operation Education System

Training and preparing first responders and humanitarian robots for Mass Casualty Incidents (MCIs) often poses a challenge owing to the lack of realistic and easily accessible test facilities. While such facilities can offer realistic scenarios post an MCI that can serve training and educational purposes for first responders and humanitarian robots, they are often hard to access owing to logistical constraints. To overcome this challenge, we present HEROES- a versatile Unreal Engine simulator for designing novel training simulations for humans and emergency robots for such urban search and rescue operations. The proposed HEROES simulator is capable of generating synthetic datasets for machine learning pipelines that are used for training robot navigation. This work addresses the necessity for a comprehensive training platform in the robotics community, ensuring pragmatic and efficient preparation for real-world emergency scenarios. The strengths of our simulator lie in its adaptability, scalability, and ability to facilitate collaboration between robot developers and first responders, fostering synergy in developing effective strategies for search and rescue operations in MCIs. We conducted a preliminary user study with an 81% positive response supporting the ability of HEROES to generate sufficiently varied environments, and a 78% positive response affirming the usefulness of the simulation environment of HEROES.