Reviewerly/exHarmony huggingface dataset:
Incoming And Outgoing Mail Filing Information System Using The View Controller Model At College Institutions

Research aims (1) to improve the filing system that is still manual and can facilitate workmanship in inputting mail data (2) as learning the creation of information systems in the form of Web Base using model view controller programming methods. This research was conducted at a college institution. The method used in this study is the collection of data by observing directly on the research object regarding the workings of college institutions in handling the filing of incoming and outgoing letters. Furthermore, the data that has been obtained will be equipped with interview data about existing archiving.From the results of research that has been carried out it can be concluded that with the information system filing incoming le tters and exit letters can help, facilitate the work in filing at college institutions.
Adaptive obstacle avoidance algorithm of collaborative unmanned vehicles integrated monocular cameras in dynamic scene

The monocular camera is widely used in robots and unmanned vehicles system because it is low cost and easy to calibrate and identify. However, the depth lack of the monocular camera hinders positioning and determining the real size of obstacles in the unmanned vehicle system. To solve the problem, we propose a collaborative structure to accurately acquire the position of static or dynamic obstacles based on the partially observing information from multiple monocular cameras. After that, a reinforcement learning based obstacle avoidance algorithm is proposed for unmanned vehicles under an unknown environment. Specifically, we discuss the influence of obstacles' moving orientations on the performance of obstacles adaptive avoidance. Simulation results verify the feasibility of the proposed algorithm.
Challenges in the Cloud Computing Model of Resource Management Issues Such as Service Level Agreements and Services Models

Cloud computing has recently emerged as a new model for hosting and delivering services over the internet. Cloud computing has many advantages, such as the ability to increase capacity or add capabilities without the need to invest in new infrastructure. It can also fulfil technological requirements in a fast and automated manner. In recent years, cloud computing has changed the IT industry; in fact, it is one of the industry's fastest growing phenomena. However, as more information about people and businesses becomes available in the cloud, concerns about the safety of this environment will increase. In addition, some challenges to the use of this service exist. This paper presents the results of a survey about cloud computing and outlines the main concepts of the technology along with examples of appropriate usage. It also discusses resource management issues such as service level agreements and highlights the challenges faced by users when choosing cloud computing services.
Storyboard: How Is The Effect For EFL Learners In Writing Skiil?

This research aims to know the students’ ability in writing recount text of the eighth grade students’ of SMP Ulul Albab Islamic Full Day School in the academic year of 2018/2019 through storyboard technique. The study used quantitative pre-experimental design. The subjects of the research were 25 students of VIII-C of SMP Ulul Albab Islamic Full Day School. The data were gained through pre-test and post-test. The result of the students’ scoring pre-test and post-test showed that storyboard technique develops the students’ writing ability in writing recount text. It can be seen from the mean score in pre-test were 70.56 and the post-test score were 82.72. The data were analysed by using t-test. The result of calculation showed that in the significance degree of level 5%, the value of t-count is higher than t-table (15.01 &gt; 1.71). It means that there is effect of using storyboard technique in students’ writing ability especially writing recount text. In addition, the use of storyboard technique was able to improve the students’ achievement in writing
Challenge-Response Enabled Identity Based Encryption in Cloud

Cloud computing provides enormous applications to the people in the real world. One of the most commonly used applications is cloud storage. Most of the people uses cloud storage space to reduces the local system overhead and make availability of data on time. The moving of data from user to cloud will raise the security and confidentiality concerns of data. To safeguard the data confidentiality many of the encryptions technologies are used. To achieve security in cloud computing, this paper proposed an Identity Based Encryption (IBE) with access time slot of each and every user. It facilitates the data encrypted by the user identification and additionally a particular access time slot will be mapped with that user ID. For enhancing the security, the encryption key is divided into two parts, one is with the data owner and another part is with the cloud. The data integrity is verified by the integrity auditing method with the challenge-response game. The proposed work ensures the data confidentiality, user verification and effective data integrity checking with low computation cost.
Fine-grained implicit sentiment processing of polar economic events

We present experiments on implicit sentiment processing based on a fine-grained event-with-sentiment dataset for the economic domain. In information extraction, events encode factual information about real-world occurrences reported in news text, while sentiment analysis concerns expressions of opinions and subjectivity.We contribute to the under-researched task of `polar fact’ or `implicit sentiment’ processing (Wilson (2008), Toprak et al. (2010)) by combining extraction of events and sentiment to automatically assign common-sense connotational opinion to facts.The SENTiVENT dataset of English economic news articles contains token-level event annotations (event annotation described in Jacobs and Hoste (forthc.)) on which we manually annotate aspect-based sentiment consisting of sentiment expressions (the words expressing implicit/explicit sentiment), targets (the entity to which the sentiment is directed), and polarities (‘positive’, ‘negative’, and ‘neutral’ investor opinion). The sentiment annotations are validated in an inter-annotator agreement study and a series of polarity classification experiments on coarse- and fine-grained sentiment-target representations. For the coarse-grained experiments, we cast implicit polarity categorization as a text-classification task of sentiment expressions with target spans using large-scale pretrained language model embeddings. We fine-tune several models on the classification task and experiment with the integration of existing lexicons comparing performance of in-domain and general sentiment lexicons. For fine-grained experiments, we apply sentiment-target-polarity triplet extraction to test the feasibility of token-level extraction of implicit sentiment. To this end, we apply a state-of-the-art Grid Tagging end-to-end model (Wu et al. 2020) and compare performance to benchmark explicit sentiment datasets.The SENTiVENT dataset fills the need for a manually annotated dataset in financial text mining applications while also being useful for implicit sentiment processing. These experiments validate the data resource and the results suggest best-practices for the creation and natural language engineering of domain-specific implicit sentiment applications.
Knowledge Base, Causative Factors and Challenges of Teenage Mothers’ Re-entry in Senior High Schools

Teenage pregnancy has been a major setback to the overall development of the girl child in various communities in Ghana.The study adopted the qualitative research approach and used case study design to explore the experience of teenage mothers in selected senior high schools in the Abura-Asebu-Kwamankese District.The target population of the study consisted of teenage mothers and their teachers in two senior high schools in the district.Purposive and snowball sampling techniques were adopted to select twenty participants comprised of 16 teenage mothers and 4 teachers for the study.Semi-structured interview schedule and focus group discussion guide were used to collect data from the participants and the data analysis was done through thematic procedure.The study revealed that teenage mothers had fair knowledge on teenage pregnancy before they became pregnant.The study found that poverty, negative peer influence, permissive behaviour of some parents among others were the contributing factors to teenage pregnancy in Abura-Asebu-Kwamankese District.It was also revealed that teenage mothers faced challenges which include financial burden, unfriendly school environment and stigmatization in their bid to continue their education.It is recommended that endowment fund should be established by the district to support girls including teenage mothers who are serious with their academic pursuit.
Building the Foundation of Medical Knowledge Generation

In this talk I will overview the Medical Information Mart for Intensive Care (MIMIC) database, a continuing series of publicly available critical care databases. As of 2021, the latest iteration of MIMIC is MIMIC-IV, which contains 12 years of admissions to critical care units at the Beth Israel Deaconess Medical Center in Boston, MA. MIMIC has also expanded into other domains, including imaging with the MIMIC Chest X-Ray database (MIMIC-CXR), and the MIMIC-IV Emergency Department database (MIMIC-IV-ED). I will discuss our motivations in distributing MIMIC to the world, the challenges in publicly releasing medical data, and the impact the databases have had on the community. A crucial aspect of the safe and privacy preserving use of retrospective clinical data is deidentification, where patient identifiers are removed or replaced with unidentifiable surrogates. I will cover approaches we have created for deidentifying patient clinical data, images, and free-text clinical notes. I’ll conclude with my thoughts regarding the future of healthcare data modeling, including the need for novel data structures which ensure data quality and utility for broad research use.
The Dynamic Deletion and Insertion of Documents With Multi Rank Keyword Search Scheme

Cloud computing is gift development as another procedure show in assortment of business zones. Significant amounts of escalated scale workplaces are commencing to move the educational on to the cloud condition. With the face of capability as a company fluctuated adventures are moving their essential knowledge to the cloud, since it prices less, adequately issue and should be gotten to from anywhere at no matter purpose. Dilated explicit multi-watchword situating interest contrive with best key by recommends that of confused cloud knowledge that at the indistinguishable time supports dynamic revive errands as deleting and embeddings records. Prehensile significance starting look computation is suited capability multi watchwords on place and record structure. Cryptography is one in everything concerning setting up trust models. Open security can be a cryptological system to convey up security. In assortment of investigators are cacophonic endlessly at creating security and profitable open coding sorts. We tend to tend to require new unimaginable cryptological frameworks energetic concerning knowledge structures like CRSA and B-Tree to support the part of security. we tend to tend to propose new multi-watchword look question over encoded cloud learning in worn out best k scored records. The vector house model and TFIDF indicate are wont to produce document and request age. This paper bases on multi trademark get eager concerning situating over a confused cloud data. The chase uses the piece of closeness and interior factor alikeness coming up with. We tend to tend to propose to assist the smallest amount complicated k Multifull-content explore for security and execution examination exhibit that the organized model guarantees a high welfare and customary sense and dynamic revive exercises, for instance, eradicating and in addition reports. The check results show that the overhead in calculation and correspondence is low.
E-government and citizen satisfaction in Jordan: EGOVSAT testing using SEM approach

Governments around the world have been in focus to facilitate citizens' access to and adoption of e-services by ensuring that they benefit from digital development. Therefore, ensuring citizens' satisfaction with the provided services is critical for that adoption success. The current study evaluates satisfaction with e-government among Jordanian citizens through testing the EGOVSAT model. Quantitative approach through a descriptive exploratory method was adopted. A self-administered questionnaire was developed for data collection purposes. Through convenience sampling, 483 respondents were included, and structural equation modelling through SMART PLS was utilised to test the model, and the result indicated that the proposed dimensions accounted for 53.2% of the variance in citizen satisfaction with e-government services. Moreover, reliability was identified as the strongest driver followed by efficiency and utility respectively, whereas customisation was identified as a negative driver and flexibility as an insignificant one entailing an issue that needs to be addressed. Following garnered results, implications were discussed.
Density-based spatial clustering of applications with noise using Gower distance

Most clustering algorithms considering spatial characteristics of data have been developed based on the geological location of observations. Density-based spatial clustering of applications with noise (DBSCAN) provides arbitrarily shaped clusters grouping a set of observations which are closely packed together and noise detecting outliers which lie alone in low-density regions. A distance measure for DBSCAN is Euclidean distance, which is the standard measure of distance and especially suitable to handle continuous variables. To handle both categorical and continuous variables simultaneously, other measures are required to compute distance for various types of variables. Thus, we propose DBSCAN algorithm using Gower distance. We provide numerical results on spatial and non-spatial setup comparing DBSCAN methods with Euclidean and Gower distance and we apply this method to land price data and migraine treatments data. DBSCAN using Gower distance has a reasonable method and gives comparably stable results.
Concurrent Signatures from a Variety of Keys

Concurrent signatures allow two entities to produce two ambiguous signatures that become binding once an extra piece of information (called the keystone) is released. Such a signature is developed by Chen et al., but it restricts signers to using the same public parameters. We describe and analyse a new concurrent signature that allows users to sign documents even if they use different underlying hard problems when generating their public parameters.
Action of Finite Group Presentations on Signal Space

The use of finite group presentations in signal processing has not been exploit in the current literature. Based on the existing signal processing algorithms (not necessarily group theoretic approach), various signal processing transforms have unique decomposition capabilities, that is, different types of signal has different transformation combination. This paper aimed at studying representation of finite groups via their actions on Signal space and to use more than one transformation to process a signal within the context of group theory. The objective is achieved by using group generators as actions on Signal space which produced output signal for every corresponding input signal. It is proved that the subgroup presentations act on signal space by conjugation. Hence, a different approach to signal processing using group of transformations and presentations is established.
A Study on Conjunctive Endings with Auxiliary Particle of 'do' for Korean Language Education

이 글은 조사 ‘도’가 결합한 양보 관계 접속어미의 특성을 밝혀 한국어교육에서의 문법 설명력을 기술하고자 한 것이다. 한국어교육에서 양보 관계를 드러내는 문법형태로 기술되어 있는 ‘-아도’, ‘-고도’, ‘-는데도’, ‘-으면서도’는 ‘접속어미+도’의 구성을 보인다는 것이 특징이다. 그리고 이들 양보 관계 접속어미는 대개 중급단계의 교수요목인데 조사 ‘도’가 결합하지 않은 ‘-아’, ‘-고’, ‘-는데’, ‘-으면서’는 초급단계의 교수요목이라는 것도 특징이다. 이 연구에서는 이러한 특성에 주목하여 한국어교육에서 조사 ‘도’ 결합형 양보 관계 접속어미를 효과적으로 교육할 수 있는 이론적 특성에 대해 고찰하고자 한다. 이 연구는 한국어교육에서 양보 관계 접속어미 교육 방안 마련의 이론적 토대가 될 수 있다는 데 그 의의가 있다.This study aims to describe the grammar explanation in Korean language education by investigating the characteristics of concessive conjunctive endings with ‘do’. It is characterized in that concessive conjunctive endings such as ‘-ado’, ‘-godo’, ‘-neundedo’, ‘-eumyeonseodo’ are composed of ‘conjunctive endings+do’. In addition, it is characterized in that these concessive conjunctive endings with ‘do’ are usually dealt in intermediate-level education even though concessive conjunctive endings without ‘do’ are dealt in beginner level. This study aims to examine the theoretical characteristics with which concessive conjunctive endings with ‘do’ can be effectively educated in Korean language education by focusing on these characteristics. This study is significant in that it can serve as a theoretical foundation for the education plan for concessive conjunctive endings in Korean language education.
3D Gesture Estimation from RGB Images Based on DB-InterNet

The booming of deep learning has made it possible to estimate 3D gestures from ordinary color images. However, the high accuracy of inferring 3D hand postures from RGB images is still not available due to the high flexibility of the gestures themselves. This paper aims to address the problem of low accuracy of keypoint coordinates position in InterNet gesture estimation network, by means of improving the confidence coordinate function, and selecting different suppression factor &amp;beta; according to different keypoints to fit t interacting hand estimation. By doing so, the maximum position coordinates are more precise and the keypoint prediction is more accurate. With respect to good measures, enhancing the representation capability of the model and employing dynamic activation function at different locations of the network to learn features in a dynamic way so as to boost the learning of hidden joints. In this way, different layers dynamically adjusted the segmental activation function according to the input to improve the performance of the model by dynamically learning features in a more flexible way. The experimental results indicate that compared with the baseline algorithm, the MPJPE and MRRPE of this algorithm are reduced by 0.73% and 2.04%, respectively, and the accuracy of single hand estimation is higher while the accuracy of interacting hand estimation is also effectively improved.
VR TECHNOLOGY APPLICATION IN PSYCHOLOGY, SOCIAL SCIENCES AND BUSINESS: AN INTERVIEW WITH BOYAN MILUSHEV

In this interview are presented some terms related to the simulated environment and virtual reality (VR), augmented reality (AR), mixed reality (MR). Some peculiarities of VR immersion are discussed and its use for psychological, scientific, educational, and business purposes. Boyan Milushev revealed the benefits of VR application in different life areas.
Automatic camera calibration method based on projective transformation

The precise parameter calibration of the camera is the prerequisite for computer vision applications. A fully automatic camera calibration method based on projective transformation is proposed. A calibration board containing two kinds of circles is used to calibrate the camera. Firstly, perform threshold segmentation on the calibration image to obtain the area where the calibration board is located. Secondly, extract the circles on the calibration board and perform ellipse fitting to identify 5 large circles to determine the direction of the calibration board. Then, use the projective transformation to accurately sort all the circles to obtain a correspondence between the coordinates of the circles' center in the image and the known coordinates of the calibration board. Finally, use the image coordinate values of all the circles' centers to calibrate the camera parameters. The actual experiment verifies that the recognition method is fast, effective and accurate. The automatic calibration of the camera can be completed without manual intervention.
Physecology:A Conceptual Framework to describe Data Physicalizations in their Real-World Context

The standard definition for ‘physicalizations’ is “a physical artifact whose geometry or material properties encode data” [47]. While this working definition provides the fundamental groundwork for conceptualizing physicalization, in practice many physicalization systems go beyond the scope of this definition as they consist of distributed physical and digital elements that involve complex interaction mechanisms. In this paper, we examine how ‘physicalization’ is part of a broader ecology – the ‘physecology’ – with properties that go beyond the scope of the working definition. Through analyzing 60 representative physicalization papers, we derived six design dimensions of a physecology: (i) represented data type, (ii) way of information communication, (iii) interaction mechanisms, (iv) spatial input-output coupling, (v) physical setup, and (vi) audiences involved. Our contribution is the extension of the definition of physicalization to the broader concept of ‘physecology’, to provide conceptual clarity on the design of physicalizations for future work.
Two-Parameters Log-Normal Distribution

If y = Ln(x) is normally distributed, then the random variable x has a Two-parameters Log-Normal (LN2) distribution.