Reviewerly/exHarmony huggingface dataset:
Tree Box: Designing embedded and embodied interaction for contemplative experiences in nature-rich environments

We present Tree Box, an interactive artefact designed to connect users to nature-rich environments through contemplation.The object draws on recent debates that juxtapose the benefits of meditation and mindfulness practices with exposure to nature-rich environments.Combining both embedded and embodied interaction, we hope to add to the growing importance of designing for human well-being and planetary health.Technically, Tree Box uses Bluetooth wireless technology to locate spots for contemplation in natural surroundings.The prototype also uses a vibrating motor and an accelerometer sensor to invite users to stop in each location.By drawing on the literature that informed our prototype, we consider how design research and practice might help promote mental health alongside preserving green spaces and biodiversity hotspots.Theoretically, Tree Box draws on key literature covering digital mindfulness, environmental sustainability, and the relationship between nature, culture, and the mind from the standpoint of critical theory.
Sustainability Analysis of Landscape Bamboo Architecture Status Based on Multi-Sensor Network and Telematics Transmission Under the Background of Carbon Neutrality

By analyzing the current situation of domestic building energy under the background of carbon neutrality, the importance of landscape bamboo structure to building energy saving is expounded, and the significance of EPS external wall thermal insulation system for building energy saving is proposed, and some existing problems are analyzed. IEEE802. 15.4 The test and analysis of the network in the vehicle mobile environment is the starting point to develop the key application of the wireless sensor network in the vehicle networking environment. The application status of bamboo in building structural components and the development direction of the modern bamboo structure system, and put forward the bamboo structure. Views on further research topics and new research directions for bamboo structures.
An EM Algorithm for Mixtures of Hyperspheres

This paper studies a new expectation maximization (EM) algorithm to estimate the centers and radii of multiple hyperspheres. The proposed method introduces latent variables indicating to which hypersphere each vector from the dataset belongs to, in addition to random latent vectors having an a priori von Mises-Fisher distribution characterizing the location of each vector on the different hyperspheres. This statistical model allows a complete data likelihood to be derived, whose expected value conditioned on the observed data has a known distribution. This property leads to a simple and efficient EM algorithm whose performance is evaluated for the estimation of hypersphere mixtures yielding promising results.
Runtime Application Self Protection

This paper explains the fundamental concepts of Runtime Application Self-Protection Technology (RASP), a relatively new security method whose widespread use is envisaged in the near future. The ongoing focal point of this innovation is on Java and.NET stage weaknesses. In addition to typification, the paper discusses RASP's benefits and drawbacks. Despite its undeniable benefits, it is not an independent and comprehensive solution for software security. RASP provides an effective solution to avoid harmful actions when used in conjunction with tried and true traditional methods. In powerful web-based applications, script infusion weaknesses are exceptionally normal. To provide protection against distinct injection types, the necessary conditions for the production and exploitation of script injection vulnerabilities were examined. The statements were located with their types in the HTML statements using a combination of the host language and object language analysis. The information reliance connection subgraph with source and sink focuses was produced in light of the control stream diagram. For this sub-graph, a filter insertion technique is used to define multiple input data type filtering strategies. Then, using data flow analysis and intelligent filtering before important sink statements, a solution was built.
A GRAPH BASED APPROACH TO LEARNER PROFILING IN AN INTELLIGENT TUTORING SYSTEM

Learner profiling lays the foundations of the personalization that happens in adaptive educational applications and Intelligent Tutoring Systems (ITS).A learner's level of knowledge on a topic is estimated from their performance on certain activities related to the topic.For this, researchers have devised many model extensions throughout the years that incorporate specific cognitive features into student profiling.In this paper, a new graph-based algorithm for learner profiling has been proposed that is able to adapt the course to the current knowledge level of the learner using the topic dependencies fed in by the subject experts and the past response data of learners who have taken this course in the past.This results in learner profiling with minimum number of assessment activities in the best case.
Hard Anchor Attention in Anchor-based Detector

In the anchor-based object detector, the redundancy introduced by the symmetry of anchor generator will be harmful for the diversity of positive anchors and cause performance drop. A simple yet effective sampling strategy called Hard Anchor Attention (HAA) is proposed in this paper. First, the anchor generator is re-examined by studying the contribution of different samples to the overall performance. It is verified that the harder positive anchors play an important role in the training of the detector. Then the HAA is introduced to evaluate the difficulty of refining anchors, and direct the focus of the training process to such harder anchors. The experimental results demonstrate that HAA can bring performance gains to RetinaNet and further releases the subsequent branches. Particularly, without fine-tuning, on the Pascal VOC dataset, HAA outperforms the random sampling and all-in baseline.
Solar Filament Detection Based on Improved DeepLab V3+

Abstract A novel solar filament detection method based on an improved DeepLab V3+ is proposed to address the low detection accuracy of small solar filaments in H α full-disk solar images. First, the Xception structure of the backbone network is fine-tuned, and the low-level feature information of the filaments is added to the decoder module of the network to improve the utilization of the solar filament features. Second, the receptive field of dilated convolution is expanded, and the information utilization rate is increased via cascaded dilated convolution to improve the detection accuracy of the small solar filaments. In the decoder module, two depthwise separable convolutions are used instead of ordinary convolutions to reduce incomplete detections. Finally, a dense conditional random field is added to optimize the edge of the detection results. Experiments on a public data set comprising full-disk H α images show that compared with the original Deeplab V3+ algorithm, the proposed method improves the mean pixel accuracy, mean intersection over union, and F 1-score by 1.86%, 1.95%, and 2.18%, respectively, which also demonstrates its superiority over other existing solar filament detection algorithms.
Retraction notice to “The development of a systems mindset in the first-year students studying online at a vocational pedagogical university while mastering the basics of working with digital technologies”

This article has been retracted: please see Elsevier Policy on Article Withdrawal ( https://www.elsevier.com/about/our-business/policies/article-withdrawal ). This article has been retracted at the request of the Editors-in-Chief. After a thorough investigation, the Editors have concluded that the acceptance of this article was based upon the positive advice of one unreliable reviewer report. The report was submitted from an email account which was provided to the journal as a suggested reviewer during the submission of the article. The reviewer account did not respond to the journal request to confirm the reviewer identity, and the Editors decided to retract the article. This manipulation of the peer-review process represents a clear violation of the fundamentals of peer review, our publishing policies, and publishing ethics standards. Apologies are offered to the readers of the journal that this deception was not detected during the submission process.
Construction and Application of YOLOv3-Based Diatom Identification Model of Scanning Electron Microscope Images.

To construct a YOLOv3-based model for diatom identification in scanning electron microscope images, explore the application performance in practical cases and discuss the advantages of this model.A total of 25 000 scanning electron microscopy images were collected at 1 500× as an initial image set, and input into the YOLOv3 network to train the identification model after experts' annotation and image processing. Diatom scanning electron microscopy images of lung, liver and kidney tissues taken from 8 drowning cases were identified by this model under the threshold of 0.4, 0.6 and 0.8 respectively, and were also identified by experts manually. The application performance of this model was evaluated through the recognition speed, recall rate and precision rate.The mean average precision of the model in the validation set and test set was 94.8% and 94.3%, respectively, and the average recall rate was 81.2% and 81.5%, respectively. The recognition speed of the model is more than 9 times faster than that of manual recognition. Under the threshold of 0.4, the mean recall rate and precision rate of diatoms in lung tissues were 89.6% and 87.8%, respectively. The overall recall rate in liver and kidney tissues was 100% and the precision rate was less than 5%. As the threshold increased, the recall rate in all tissues decreased and the precision rate increased. The F1 score of the model in lung tissues decreased with the increase of threshold, while the F1 score in liver and kidney tissues with the increase of threshold.The YOLOv3-based diatom electron microscope images automatic identification model works at a rapid speed and shows high recall rates in all tissues and high precision rates in lung tissues under an appropriate threshold. The identification model greatly reduces the workload of manual recognition, and has a good application prospect.目的: 基于YOLOv3模型构建硅藻电子显微镜图像识别模型，测试在实际案例中的应用效果，探讨该模型在法医学硅藻鉴定中的优势。方法: 选取25 000张1 500×的硅藻电子显微镜图像作为初始图像集，经专家标注和图像处理后，输入YOLOv3网络训练识别模型。收集8例溺死案例肺、肝、肾组织样本的硅藻电子显微镜图像，分别在0.4、0.6、0.8的阈值下利用该模型识别硅藻，同时进行人工识别，以识别速度、召回率和查准率评价该模型的实际应用效果。结果: 模型在验证集和测试集上的平均精度均值分别为94.8%和94.3%，平均召回率分别为81.2%和81.5%。实际应用中，该模型识别速度是人工识别速度的9倍以上。阈值为0.4时，肺组织硅藻总体召回率均值达89.6%、总体查准率均值达87.8%；肝、肾组织硅藻总体召回率达100%、查准率低于5%。随着阈值的增加，各组织硅藻召回率下降、查准率上升；模型在肺组织的F1分数随着阈值升高而降低，在肝、肾组织的F1分数随着阈值升高而升高。结论: 基于YOLOv3的硅藻电子显微镜图像识别模型能够快速识别硅藻图像，并能在一定的阈值下取得良好的硅藻召回率和肺组织较高的硅藻查准率，显著减少了人工识别的工作量，具有良好的应用前景。.
Character recognition of Tibetan Historical document in Uchen font: Dataset and bench mark

. A offline character dataset of Tibetan Historical document in Uchen font, THCU, is presented to facilitate the research of Tibetan Historical document recognition. The dataset THCU includes two subsets: THCU-M and THCU-S. The THCU-M is annotated manually in original document images, including 121214 character samples and 238 character categories. The subset THCU-S is a simulation dataset, and its samples are generated based on the idea of component combination. There are four subsets in THCU-S, in which the numbers of character category are 7238, 2908, 562 and 245 respectively, and the numbers of sample in each category are 5000, 3000, 600 and 600 respectively. We also evaluate THCU dataset using a CNN based model as a baseline performance. The experiment shows that the performance of the model on the real data is greatly improved by adding the generated samples.
Overview of Blockchain Technology and Its Application in Healthcare Sector

A blockchain is distributed ledger technology (DLT) which is used to store data securely. In the blockchain, data is stored as a peer-to-peer network. In this digital era, most of the business wanted to convert their data centers from centralized to decentralized. Blockchain can secure their data through a specific algorithm. The blockchain ensures data transparency, data security, and data integrity. Blockchain is known for cryptocurrencies, but it is beyond cryptocurrency. This paper aims to overview the architecture of blockchain, features of blockchain, and application of blockchain in the healthcare sector. The main goal of applying blockchain in the healthcare sector is for security and to achieve interoperability. Patient data is very sensitive and very crucial to provide security features. Due to COVID-19, most of the medical data is stored in electronic format, and storing their data in the blockchain is the best thing to make data secure and transparent.
AWARENESS GENERATION AMONG THEMASSES THROUGH COMMUNITY PARTICIPATION: CASE STUDY OF NIZAMPUR VILLAGE, MEWAT AREA

Environmental awareness generation is the most effective tool to bring about a change in society with respect to cleanliness, environmental health, hygiene, social stigmas stigmas, taboos and so on.For bringing about environment awareness in the society, programs can be executed through "folk songs, nukkad-natak, folk dance, and pamphlet distribution, advertisement vehicles, creating and distributing appropriate information, education and communication (IEC) material to targeted beneficiaries.Awareness generation can be of various types.It depends primarily on the theme which it focuses on.They include the following: Behavioral Change programs, social stigmas redressal, personality development programs, environmental awareness, and financial literacy programs.Behavioral change programmes primarily aim to change the beneficiaries' attitudes or behaviours.Maintaining a clean environment, for example, and changing the practise of defecating in the open.We have dealt with such groundlevel awareness efforts in our research.The study presents its findings in the form of case studies.Social stigma redressing programmes are frequently linked to discrimination and exclusion, as well as a lack of education and awareness among the general public.Stigma can be a danger and a roadblock to a country's growth.Health emergencies, such as the Covid-19 outbreak, have resulted in social stigma and discrimination against persons of various ethnic backgrounds.Similarly, awareness programs focusing on environmental issues, financial literacy, and personality development (Skill development) basically involve active participation of community as well as the trainers or facilitators to get the best results.Some awareness programmes were held on a regular basis in the village in question.Further research reveals a shift in community behaviour.Because the process of raising awareness is inclusive, it engages people from all walks of life.Meanwhile, adolescent girls, children, mothers, and the elderly are the true beneficiaries.Changes in behaviour, cleanliness of the environment (environment), lower disease transmission rates, reduced social stigmas and taboos, lower school dropout rates, and effective menstrual hygiene management are all examples of the effects.In a word, we can state that successful implementation of environmental awareness programmes requires active community participation.
MENINGKATKAN KOMPENTENSI PESANTREN MAHASISWA (PESMA) MELALUI PELATIHAN MICROSOFT OFFICE

The purpose of this training is to improve the ability of students in student boarding schools (pesma) in mastering Microsoft office, Microsoft office training is attended by all students who are members of student boarding schools (pesma) totaling 16 people. The steps taken in this training are the preparation of activities to determine the readiness of the training implementation, the implementation of training activities carried out in stages and evaluation to measure the mastery of the training participants. The results of the service activities showed that the training participants had understood all the material well about Microsoft word, excel and power point, although there were still certain parts that had to be understood correctly and in depth. Thus, the existence of Microsoft office training activities for PESMA is very important in order to improve and develop Pesma's abilities and creativity in the computer field.
Present and Future QIS and QC

Abstract Alice and Bob describe currently available physical systems to be used as quantum qubits. While the quantitative physics is beyond the scope of this book, they give a brief qualitative explanation of the physics of those qubits. The difference between QC and QIS is briefly delineated, including the possibility of a quantum internet. They also explain a variety of other QC and QIS issues including programming quantum computers, future qubits, new QC architectures, machine learning, and AI. They also raise several ethical issues facing QC and QIS and point to information about careers in QC and QIS.
[Research progress of in-hospital mortality risk model in patients with acute myocardial infarction].

The incidence of in-hospital death in acute myocardial infarction (AMI) is high, which seriously threatens the life and health of patients. At present, many countries and regions have established a variety of objective assessment models for predicting the in-hospital mortality of patients with AMI, providing important decision-making support for patients with different risk levels when formulating treatment plans. With the rise of artificial intelligence, many new modeling methods also show certain advantages over the traditional models. This article systematically introduces the commonly used and newly constructed risk prediction models for in-hospital mortality of AMI, in order to provide help for medical staff to assist decision-making in clinical practice, and provide reference for the establishment of a safe and more effective risk prediction model in the future.
PERAN PENYULUHAN METODE SISTEM PAKAR TERHADAP KEBUTUHAN PERANCANGAN APLIKASI CUSTOMER DI CV SOLIDTECH

Counseling on expert system methods has a strategic role in helping to increase the production needs of application design at CV Solidtech. Counseling on expert system methods at CV Solidtech aims to provide training in order to introduce some material related to expert system methods that can be used for designing expert system applications. With this counseling, CV Solidtech can efficiently and effectively increase target customers in the field of application design based on an expert system. CV solidtech is one of the businesses engaged in the field of technology services is a small company that only handles Software Development or better known as Software House which handles software development. The company received more attention in this outreach activity. This activity aims to introduce the expert system in depth and to give CV Solidtech a significant impact on the production level of application design for customers. The service method used is the technique of delivering material directly to 10 Solidtech employees. The results of this counseling show that the average value of knowledge before giving nutrition counseling (pretest) is 73.00. In knowledge after intervention (post-test) the average value of knowledge before giving counseling (Pretest) was 1.30. In knowledge after intervention (Post-test) the average value was 5.80. The average score on the post test increased by 4.5 points. Therefore, it can be concluded that there are differences in the pretest and posttest scores after counseling on CV. Solidtech and the results of this counseling show that the role of expert system method extension is categorized as having a significant influence as a facilitator in increasing customer targets at CV Solidtech
Parallel Implementation of 3D Model Reconstruction of Monocular Video Frames in a Dynamic Environment

Real-time three-dimensional (3D) reconstruction has been widely explored in several domains in motion capture, robot navigation, augmented reality, and autonomous driving.It is considered one of the most efficient solutions to overcome several problems, such as occlusion and collision in computer vision and computer graphics.This process is computationally intensive and it considers a bottleneck for real-time realistic interaction applications which need a quick response to achieve action in real-time.The Monocular 3D model reconstruction (M3DMR) is considered one of the possible solutions to build an accurate 3D reconstruction in a dynamic environment.However, the proposed framework needs a high computational power to create a single frame.Graphics processors unit (GPU) architecture is used to improve the computational time of M3DMR.This study discussed how to maximize the benefits of using GPU resources by using several optimization techniques that enable GPU architecture to achieve the best possible performance for the M3DMR.Different multicore heterogeneous systems are used to evaluate the performance of the proposed framework.Experimental results confirm that our parallel implementation of 3D Model Reconstruction of Monocular Video Frames is valid for different GPU architectures.The proposed parallel implementation can execute 28 FBS compared with the serial version that executes one frame in 30 min.
Electronic Resources for Children Explaining COVID and Vaccinations

Abstract As parents are forced to become experts of a new virus, it is helpful to know there are resources to help navigate the conversation with children. There are now countless e-books for all ages explaining the virus, illness, social distancing, and even the vaccine. Below are suggestions for especially helpful and fun e-books to aid parents in having these conversations.
A new index‐based hyper‐heuristic algorithm for global optimisation problems

In this research study, a new combination search algorithm, based on indexing its constituent processes, is proposed to solve global optimisation problems. As optimisation problems become more complex, especially real-world problems, the use of higher-performance algorithms has become essential. One of the techniques that lead to design of an algorithm with stronger strategies in exploration and exploitation, as well as a better balance between these two strategies, is the appropriate combination of parent algorithm processes. The proposed algorithm was developed using a new innovation with the help of the supply-demand-based optimisation and the Harris hawks optimisation algorithms processes as parent algorithms. In this algorithm, the local and global search sections of its parent algorithms, are separated, and then based on a new indexing method in each iteration, according to the current population indexing, a global search and a local search are selected from the processes of its parent algorithms, and then the current population is updated with two selected sections. The performance and effectiveness of the proposed algorithm in solving well-known standard benchmark problems and in solving real-world engineering problems have been tested and validated by statistical tools. The results of the research study show that the proposed algorithm can provide very effective results compared to other competing algorithms as well as its parent algorithms in many tests. The results show that the proper combination of optimisation algorithm processes can be used as a technique to design more powerful algorithms to solve global optimisation problems, especially complex real-world problems.