Reviewerly/exHarmony huggingface dataset:
Criteria Rating Prediction with Aspect Representation Learning for Multi-Criteria Recommendation

Multi-criteria recommendation system refers to a recommendation system that takes multi-criteria or multi-aspect ratings into consideration when learning user preferences. The core of the multi-criteria recommendation system is predicting the criteria ratings leading to overall rating estimation. The existing approaches rely on either 1) using collaborative filtering to predict the criteria ratings based on historical criteria ratings, or 2) extracting latent aspects and predicting ratings from the review. The latter approach ignores the explicit ratings and the inferred ratings from the review may not be accurate. In the former approach, historical criteria ratings can be scarce (users may only provide ratings to a few criteria), which could affect the prediction accuracy. In this work, we introduce a novel multi-criteria recommendation model that predicts the criteria ratings from the review and then uses an aggregation function to estimate the overall rating. Multi-criteria ratings are predicted by an aspect representation learning layer followed by a BERT-based sequence embedding. Finally, the overall ratings are computed using a deep neural network-based aggregation function. The performance of our proposed model is evaluated with three different datasets including Tripadvisor, RateBeer, and BeerAdvocate. Our method outperforms several competitive baselines.
Expanding the Methodological Toolbox: Machine-Based Item Desirability Ratings as an Alternative to Human-Based Ratings

The accuracy of self-reported data in the social and behavioral sciences may be compromised by response biases such as socially desirable responding. This has led researchers and scale developers to obtain item desirability ratings, in order to maintain item neutrality, and parity with alternative options when creating forced-choice items. Gathering item desirability ratings from human judges can be a time-consuming and costly task, with the added potential issue of inter-rater inconsistency. However, recent advancements in natural language processing have yielded large language models (LLMs) with exceptional abilities to identify abstract semantic attributes in text. The presented research highlights the potential application of LLMs to estimate the desirability of items, as evidenced by the re-analysis of data from 14 distinct studies. Findings indicate a significant and strong correlation between human- and machine-rated social desirability of .80, across 521 items. Results furthermore showed that the proposed fine-tuning approach of LLMs results in predictions that explained 19% more variance beyond that of sentiment analysis. These results demonstrate the feasibility of relying on machine-based item desirability ratings as a viable alternative to human-based ratings and contribute to the field of personality psychology by expanding the methodological toolbox available to researchers, scale developers, and practitioners.
Multi-View Multi-Label Learning for Label-Specific Feature Via Glocal Shared Subspace Learning

In multi-label learning (MLL), label-specific feature (LSF) learning considers that the label is determined by inherent characteristics of its own. However, in multi-view multi-label learning (MVMLL), the heterogeneity problem persists in the feature space. Existing algorithms only extract LSF for each view separately, and suffer from inadequate communication of LSF and poor classification accuracy. The subspace learning method can extract the shared subspace of each view as a feature representation space substitute for the original view feature space, and the richer the information in the shared subspace the better it represents the original view feature. Based on the above analysis, we propose a multi-view multi-label learning for label-specific feature via GLocal Shared Subspace Learning algorithm (GLSSL). Firstly, the label groups are obtained via spectral clustering. The correlation of the label groups to the feature is fully considered and the specific set of relevant view feature corresponding to the label groups is obtained. Secondly, the feature representation space (global shared subspace) and local subspace (local shared subspace) are extracted according to the original feature space and feature sets respectively. Finally, the local subspace is complemented with the feature representation for LSF learning. The algorithm in this paper is validated by comparing experiments with several state-of-the-art algorithms on several benchmark multi-view multi-label datasets.
Enhanced Information Security Over Cloud Computing Environment using Modified Data Cipher Policies

The need for safe large data storage services is at an all-time high and confidentiality is a fundamental need of any service. Consideration must also be given to service customer anonymity, one of the most important privacy considerations. As a result, the service should offer realistic and fine-grained [11] encrypted data sharing, which allows a data owner to share a cipher text of data with others under certain situations. In order to accomplish the aforesaid characteristics, our system offers a novel privacy- preserving cipher text multi-sharing technique. In this way, proxy re-encryption and anonymity are combined to allow many receivers to safely and conditionally receive a cipher text while maintaining the confidentiality of the underlying message and the identities of the senders and recipients. In this paper, a logical cloud security scheme is introduced called Modified Data Cipher Policies (MDCP), in which it is a new primitive also protects against known cipher text attacks, as demonstrated by the system.
An Attention Graph Stacked Autoencoder for Anomaly Detection of Electro-Mechanical Actuator Using Spatio-Temporal Multivariate Signals

Health monitoring of electro-mechanical actuator (EMA) is critical to ensure the security of airplanes. It is difficult or even impossible to collect enough labeled failure or degradation data from actual EMA due to the fact that EMA has high reliability. The autoencoder based on reconstruction loss is a popular model that can carry out anomaly detection with only considering normal training data, while it fails to capture spatio-temporal information from multivariate time series signals of multiple monitoring sensors. To mine the spatio-temporal information from multivariate time series signals, this paper proposes an attention graph stacked autoencoder for EMA anomaly detection. Firstly, an attention graph convolution is introduced in the autoencoder model to convolve temporal information from neighbor features to current features based on different weight attentions. Secondly, stacked autoencoder is applied to mine spatial information from those new aggregated temporal features. Finally, based on the benchmark reconstruction loss from normal training data, different health thresholds calculated by several statistic indicators can carry out anomaly detection for new testing data. In comparison with traditional stacked autoencoder, the proposed model can obtain a higher fault detection rate and lower false alarm rate in EMA anomaly detection experiment.
Membangun Keberanian sebagai Tourism English Public Speaker untuk Generasi Muda Bulukumba

This community service aims to respond to the conditions of tourist visits to train young peopleto have the courage to communicate with International tourists using foreign languages,especially English. It is also time for the government and the private sector related to tourism toprepare themselves, design, and develop tourist objects to make them attractive. Theimplementation method used is a hybrid. 20% were indoors training and the rest 80% wereoutdoors practicing. The implementation stage began with the socialization stage, theregistration, and the final stage was implementation. The team conducted outreach to explainthe importance of mastering English in increasing tourist visits. The training provided was topractice composing ideas about images (building perceptions) by utilizing image media in theform of tourist objects. Furthermore, participants were trained to map their concepts andthoughts before speaking to make it easier to express ideas (mind mapping). Then, they try topractice speaking skills by telling stories (practice). Applying the 3:2 concept so thatparticipants add vocabulary can help increase participant competency.
Pelatihan Penggunaan Repositori Arsip Digital Manuskrip Bagi Pegawai Museum Sang Nila Utama

The current target community service partners are Sang Nila Utama Museum employees. This service is a continuation of research activities regarding the design of the manuscript repository for the Sang Nila Utama Museum collection. Currently, all manuscript collections have been recorded, however, the public still cannot access these digital manuscripts easily, this is because the person in charge of the museum and their employees do not yet have an understanding of the advantages of using a repository. Seeing these conditions, it is necessary to conduct training for employees regarding the use of the repository. The purpose of this activity, namely (1) to provide knowledge to employees about the repository; (2) to Employees have knowledge and understanding of the use of repository services. In order to achieve the above objectives, it is necessary to hold activities, including (1) Counseling related to the museum collection repository and manuscripts; (2) brief training on using the repository service. Participants who took part in the activity totaled 5 people. The results of the service show that at first, the participants did not have an understanding of repository services, but after counseling, the participants understood the meaning and function of repository services. It is hoped that in the future, this repository service can be applied to all collections, not only manuscripts but other museum collection objects.&#x0D; Keywords: training, repository, digital manuscripts.
Bias Present in Computerized Algorithms

Abstract: Automation biases stemming from deep-rooted computer algorithms are blamed for the false results and misinterpretations it presents; However, algorithmic biases in machine learning models are based on user interpretation and input, and therefore the machine's output may not correspond with the input's attitude. This stems from the variety of information that is fed in machine learning models and possible faulty glitches within computers themselve
THE EFFECT OF PARAPHRASING ON EFL STUDENTS' WRITING AT INDONESIAN HIGHER EDUCATION

The paper intends to enquire about the effectiveness of paraphrasing in evolving the EFL students' writing ability for Indonesian Higher Education. The study was quasi-experimental research, and it was conducted in the 4th semester of the English students at Universitas Sulawesi Barat. The research instrument was a writing test, and the student’s scores were gathered through paraphrasing rubric scores. Statistical inferential analysis was performed on the data. It is possible to conclude that The Ha (Alternative) Hypothesis was established hence the paired samples test result carried out with SPSS performed that the sig. rating on the value obtained from the T-test was lower than Sig. value, so theory Y assumptions (Ha) were approved, and both the pilot testing and post-intervention results of the study demonstrated Sig. (2-tailed = 0.000) has been less than 0.05. In other words, this indicates that there is a consequence. The research finishes with pedagogical recommendations for trying to better the paraphrasing skills of novice student writers, and paraphrasing has a medium effect on the EFL students’ writing ability in Indonesian higher education.
A comparison of syntactic patterns of Brazilian Portuguese and English: using comparable corpora of museum texts

The aim of this paper is to analyze two corpora (one in Brazilian Portuguese and another English), from PUCRS’ Science and Technology Museum, to unveil which of these languages could be rendered to be more or less syntactically and rhetorically elaborate. The corpora were processed on Natural Language Processing tools, such as NILC-Metrix, Coh-Metrix 3.0 and AntConc. Results point to the feature regarding the higher number of words before the main verb as the main factor rendering syntactic and rhetoric elaboration and, consequently, more complexity in the Portuguese corpus.
Automatic Modulation Recognition in Two- Way Relaying Channel with the Presence of Relay Transceiver Hardware Impairments

Abstract Modulation recognition (MR) is well-known as one of the enabling tools, which aims to further afford efficient and secure communications in cognitive radio (CR) context for 5G and beyond networks. In this Paper, we propose a robust MR approach designed for two-way MIMO cooperative relaying network by specifically taking into account two crucial constraints: hardware impairments at relay transceiver and co-channel interference. To mitigate the effect of these impairments, feature-based artificial neural network (ANN) recognizer combined with a nonlinear design of the relay processing matrix with dirty paper coding (DPC) is investigated in this work. Simulations using two receive criterions, namely DPC-ZF and DPC-MMSE, have been carried out to validate the effectiveness of the proposed approach. It has been proved that both DPC-ZF and DPC-MMSE provide high modulation recognition, whatever the impairments level at the relay transceiver.
Innovation Climate and Attraction and Retention of Human Capital Among Small and Medium Enterprises in Kenya: The Moderating Effect of Founder Characteristics

Past studies on the effect of innovation climate on the attraction and retention of human capital produce mixed results. For this reason, this study aimed to investigate the impact of founder characteristics on the correlation between innovation climate and the attraction and retention of human capital. Criterion sampling was used to select the top 100 SMEs in Kenya. Targeted respondents included founders of SMEs. Out of the targeted 100 SMEs, 59 responded, giving a response rate of 59%. The study used a structured questionnaire to collect data and the partial least squares structural equation modelling technique to analyze the collected data. Since previous researchers have found mixed results on the influence of innovation climate on the attraction and retention of human capital, the current study aimed to ascertain this and thus the moderating variable, founder characteristics. It established that the variable had an insignificant effect on the link between innovation climate and human capital attraction and retention (&amp;beta;eta = 0.230, t = 1.855, p = 0.064). Since talented employees usually desire to work in a conducive workplace environment, SMEs need to create a supportive innovation climate that can assist in attracting, maintaining and retaining human capital. Future scholars can investigate the influence of other moderating variables on the link between innovation climate and the attraction and retention of human capital.
The use of Google Sheets for Specimen Tracking, Pathologists’ Requisitions, Quality Control and Data Retrieving for Statistics, Search and Research in Anatomical Pathology Laboratories in the Absence of Barcoding and/or Anatomical Pathology Laboratory Information System

Background: Many Anatomical Pathology laboratories do not have a barcoding system or an anatomical pathology laboratory information system that allow for better workflow by tracking of specimens and orders, quality control documentation, statistics calculation, search and data retrieval for research purposes. Aim: This paper will show how Google sheet can be used as an alternative using the checkboxes, the electronic edit history and other features. Materials and Methods: Google accounts were created then Google sheets were designed with specific details and the daily quality log was designed to show compliances to national and international standards. Results: Descriptive templates allowed for tracking of specimens and pathologists’ requisitions, quality control documentation, statistics calculation, search and data retrieval for research purposes. Conclusion: Google sheet can be used in the absence of barcoding systems or an anatomical pathology laboratory information system for tracking, documentation, search, research and monitoring of all activities by the supervisor as required by some accreditation body.
Potential Use of Antennas In Rural Areas To Improve Internet Connectivity

This research was motivated by the conditions when the Covid-19 pandemic occurred, at that time there was a very striking change in the social conditions of the community both in terms of economy, and communication, to problems with the quality of education.Long-distance education has been implemented to reduce the viruses spreading, and education which usually took place in the classroom; then shifted to virtual classes.Another challenge that occurs is the low reception quality of the 4G signal, which certainly impacted learning quality.Although today we are about to start the lecture again in the classroom, the problem of signal reception quality is still the biggest obstacle in communicating over long distances.In this study, the author tries to explore how much potential use of an antenna to improve signal reception quality problems and the economic ability of people in rural areas to assemble them.
Implementation of Retention Ponds in Flood Management in Sorong Regency â€“ Southwest Papua

Mariat Subdistrict is one of the villages affected by the floods in Klasuluk Village, with an area of 0.7995 km2, and Klamalu Village, with an area of 1.0479 km2. This research uses experimental, descriptive, qualitative, and quantitative analysis methods. The results of the analysis and simulation, after being run at intervals of 10 years in the future, there are three flood points in the Klamalu village canal, where the most significant total flood volume is at JN64 146,687 m3/s, the smallest is at JN15 21,232 m3/s, and there are 56 flood points in the Klasuluk village canal, where the largest total flood volume was at JN91 1,863 m3/s and the smallest at JN9 and JN37 0.008 m3/s. The volume of wastewater discharge that enters the drainage is only 1%, so it has no effect. From the data on the dimensions of the retention pond, it is obtained that the wet cross-sectional area is about 145.05 m2, the wet perimeter of the retention pond is 101.69 meters, the hydraulic radius is 1.43 m, the flow velocity is 3.168 m/s, the guard height is 1.22 meters, the water discharge that comes out is 459.51 m3/second.
Naming of US Public Libraries

The article considered the development of branding and naming in the marketing of library and information activities in Russia and in the USA. It is noted that in the professional literature of the USA, the problem of the library naming is not covered in detail but general branding issues. The names of the leading branches of American public library systems are analyzed in accordance with the author’s classification of naming (personalized, conceptual and toponymic). It is noted that most public libraries in the USA have a toponymic version of the name. A comparative analysis of the names of the New York Public Library branches was carried out for a comprehensive understanding of the features of American library naming. The prevalence of toponymic naming, when the name contains a direct reference to the location of the cultural institution, is proved by the example of New York libraries. In the process of comparative analysis, single indication of conceptual naming was identified (the name is associated with the reflection of the priority direction of the cultural institution activity, or has a special associative way at its basis). The author showed that a distinctive feature of personalized naming in the USA is the prevalence of libraries with the names of their founders or major patrons. It is concluded that attention to naming will increase as part of the overall marketing strategy of US cultural institutions.
The professionogram of the manager of socio-cultural activities: the meta-competence aspect

The issues of reforming the modern system of higher education in the Russian Federation are considered and the tasks of training professionals in socio-cultural activities are specified. The justified refusal of the Russian Federation from further integration into the European educational space determines the need to rethink the approach to the forms of organization and content of educational practices in the humanitarian field in general, and in the direction of training «socio-cultural activities», in particular. The author believes that the most productive modification strategy is the gradual rejection of the modular approach and the implementation of a subject-centered model of training specialists, the central component of which is the development of creative abilities and the formation of value orientations of the student’s personality. The necessity of developing and implementing metaprofessional competencies in the educational practice of the transition period as a consensual basis of the profession is argued. As meta-competencies, such as: consistency, axiological, socio-cultural leadership are considered.
Historical foundations of the educational activities of the National Library of Russia

The state policy in the field of culture, as a fundamental element in ensuring the cultural sovereignty of Russia, provides for an increase in the role of education and enlightenment. The educational function immanently inherent in libraries, characteristic of all types of their activities, is characterized. The transformation of educational activities over the course of more than two hundred years of the historical path of the Imperial Public - Russian National Library is analyzed. The fundamental difference in the tasks of educational activities in the main library of the Russian Empire and in the period of the Сultural revolution and socialist construction of the 1920s–1930s was determined. The features of the educational activities of the National Library of Russia during the Great Patriotic War are characterized. The forms and methods of its implementation in the national library of the Russian Federation are revealed, their special role in changing historical conditions is shown.
Criteria for evaluating scientific activity and its results in library and information science

The features of the assessment of scientific activity and its results in the library and information sphere are considered. Criteria for evaluating the significance of the activities of a scientist in the library and information sphere and his works by the number of publications using citation and Hirsch indices are highlighted. An attempt was made to identify the attitude of scientists involved in research in this area to the accepted criteria for evaluating the results of scientific activity. The results of an anonymous survey of scientists involved in research in the field of library science, bibliography and book science are presented, the purpose of which is to analyze the effectiveness of various areas of evaluation of scientific activity in the library and information sphere. In the developed questionnaire, quantitative and qualitative criteria for evaluating scientific activity are proposed. The results of the survey showed that the attitude to the evaluation criteria is largely related to the role of a scientist (researcher, head of a scientific department, etc.), as well as to the peculiarities of the development of the field of scientific research itself.