Reviewerly/exHarmony huggingface dataset:
Strategi Kreatif Pesan Iklan Brimo Edisi Septian David Maulana

The habits of consumers in the digital era encourage advertisers to innovate to make more creative advertisements so that product messages can be conveyed effectively and efficiently to the public. BRImo's latest advertisement uses professional soccer players in the Liga 1 competition and Indonesian National Football team players Septian David Maulana and sportcaster Valentino Simanjuntak as voice overs. creative messages from football players and sportscasters into a strategy to sell products to consumers. Ads are made funny in order to attract the attention of the audience. the semiotic method is used to see the signs in the Septian David Maulana edition of BRImo's advertisement.
A Sentimental Analysis of Legal Documents using Deep Learning Approach

Automatically identifying logical patterns from complicated legal documents can improve the efficiency of legal systems by enhancing case processing time and case clearance rate. The most important job in accomplishing this is automatically categorizing sentences in legal documents depending on their substance. This research proposes a deep learning model for breaking down the legal text and generating judgments based on sentiment analysis. Sentiment analysis is the practice of analyzing natural language to identify emotions associated with a text. Sentiment analysis is commonly used to monitor consumer opinion on social media and brand and campaign monitoring. The automated treatment of text’s opinions, sentiments, and subjectivity is called SA. Bi-directional Long Short Term (Bi-LSTM), Long Short-Term Memory (LSTM) and Gated Recurrent Unit (GRU) are three of the most prominent deep learning approaches used in the Sentimental analysis legal document. These techniques are used in aggregate or stand-alone based on sentimental analysis of legal documents. This working point of interest is the diverse flavors of the deep mastering methods used in special sentiment analysis programs at the sentence stage and goal level. Moreover, the advantages and downsides of strategies are discussed alongside their overall performance parameters. Basically, the determining patterns from the numerical findings is more difficult in text analytics than it is in text analysis because of the difficulty of human language. In Sentiment analysis, Machines must be programmed to evaluate and comprehend emotions in precisely the same way that even the human brain does. Utilizing this type of method such as LSTM, GRU, Bi-LSTM makes it much easier to identify the output.
Robustness Trend of Power Transmission and Transformation Monitoring System based on Multidimensional Data Anomaly Detection Algorithm

A data anomaly detection method based on fuzzy isolated forest algorithm is proposed. By selecting some valuable attributes and building them into isolated forests, starting from multiple dimensions, the membership degree of the detection results of each dimension attribute is judged. The influence of several key factors on CPPS was investigated. The proposed weak interdependence model considers protection mechanisms such as realistic redundancy backup, which makes the model more close to the actual system operation. Great trend of change. Subsequently, the strategy of edge-break protection is further proposed to improve the robustness of the power grid, and the simulation results are shown by computer graphics, which show that it has practical value for the analysis of optimal control systems with accurate mathematical models.
A Bibliometric Review of The Development of Geotourism Research in The Last Five Years

Geotourism research is a tourist activity that is in direct contact with nature and has a variety of characteristics and uniqueness. On the other hand, we must protect nature so that it is not damaged by tourism activities. Therefore, it is important to know the development of research that has been done about geotourism. This study aims to determine the map of the development of research on geotourism. The application used to collect Scopus-indexed research metadata on geotourism using Harzing Publish or Perish application. Furthermore, the Vosviewer application is used to map research related to geotourism in the period 2018 to 2022. In the last five years, topics related to geotourism that have been widely researched are geoheritage, geosites, and geopark.
TOURISM IN BAKA STUPAS AND SURROUNDING WITH HAHSLM PERSPECTIVE

&#x0D; &#x0D; &#x0D; &#x0D; Tourism activity is a sector that plays an important role in regional development and development efforts by contributing to the income of an area. One of the areas that has developed due to the contribution of the tourism sector is Magelang Regency, Central Java. The existence of the tourist area of Borobudur Temple which has an international scale contributes greatly to the income of the people around it. 72 Borobudur stupas which are a reflexivity of the interference quantum physics pattern based on the Hahslm constant 472319 approach in the Covid-19 economic era. Modern physics is phenomenal in quantum reality with its wave interfer-ence. Similarity is found in the meaning of 7 waves and 2 gaps in the interference physics process, then reflected in the code of the 72 stupas that were built. The conclusion of the research is that 72 Borobudur stupas are a reflection of the interference part of the Hahslm 472319 constant in the Covid-19 economic era. The method used is the Hahslm 472319 equation which refers to QS. Al-Hijr [15]: 87. The result obtained is that the largest historical temple building in the world, namely Borobudur has 72 stupas, refer-ring to phenomenal events with absolute and differentiation.&#x0D; &#x0D; &#x0D; &#x0D;
Distance Estimation for Collision Avoidance of Micro Aerial Vehicles using LiDAR Sensor

This research work proposes a novel method to prevent collision in the micro aerial vehicles by calculating the distance of the obstacle prior to the collision. For distance measurement we have used the LiDAR sensor which uses the time of flight principle and, identified its operating ranges that works perfectly for the micro aerial vehicles and analyzed the errors in various operating ranges. Determining accuracy using the Root Mean Square Error and Absolute Mean Error as two parameters for three types of data classified as All calculated data, very close values and deviating range of the Result plotting graphs and calculating errors for the same. This proposed research helps in understanding the LiDAR Sensor in better way for the exploration of the range of operation of the LiDAR sensor and its applications in collision avoidance. Though the algorithm that we have done is in the Arduino UNO the same can be implemented in Pixhawk module and the control signal can be used to change the direction of the micro aerial vehicle where ever necessary.
Pattern Based Image Retrieval System by Using Clustering Techniques

Nowadays, the image database is growing in enormous size with heterogeneous categories. Similarly, there is rising demands from users in various ways. The most demanding domains in society are health care, Agriculture, commerce, and security. Healthcare domain is concerned with diagnosing the disease. Security domain is involved in investigation of the Criminals. Commerce domain needs analysis to recognize the right product. Agriculture domain requires processing of disease affected fruit images. The PBIR system that combines evidence from multiple digital image domains can reduce those problems of existing image retrieval systems. The PBIR system is used to find uncertain parts of the image during augmentation steps. The result is identified with various parameters (e.g., accuracy, precision, distance, sum of distance), showing that the performance of the k-medoids pam algorithm better than the existing iterative clustering algorithms
Software Defect Prediction Using Machine Learning Techniques

Software defect prediction provides development groups with observable outcomes while contributing to industrial results and development faults predicting defective code areas can help developers identify bugs and organize their test activities. The percentage of classification providing the proper prediction is essential for early identification. Moreover, software- defected data sets are supported and at least partially recognized due to their enormous dimension.
Concept of the Second Cybernetics Influences all Areas of Scientific Knowledge: Scientometric Study from 1963 to 2021

The concept of the Second Cybernetics, exhibit in 1963 by Magoroh Maruyama, proposed a different way of evaluating the relationship between the variables existing in a system, postulating that there is a permanent imbalance between them, opposing the "first" cybernetics of static equilibrium, therefore, the relevance of this study is to demonstrate that the paradigm of contemporary information science has the aforementioned concept in its epistemology. This scientometric research analyzed to what extent the Second Cybernetics permeates contemporary science, through the identification of scientific publications that use it as a reference. Data were obtained from the Web of Science, SCOPUS and JSTOR databases, considering the years 1963 to 2021. The compilation of this corpus was carried out using the Bibliometrix software version 4.0.0 and the collection and extraction was carried out directly with resources available in the indicated databases. The results of the study showed that the concept of the Second Cybernetics is referenced in 980 articles, generating influence in the scientific environment with new publications every year; indexed articles in the areas of Social Sciences and Human Sciences account for 69.1% of the research carried out under this influence; the concept is present in all eight areas of knowledge defined by Coordination for the Improvement of Higher Education Personnel (CAPES).
A MONOPOLIZAÇÃO DE UMA CONVERSA INFORMAL: UMA DESCRIÇÃO DOS MOVIMENTOS DE CONTINUAÇÃO A PARTIR DA LINGUÍSTICA SISTÊMICO-FUNCIONAL

This work aims to describe continuative sequences in an informal conversation. It uses as corpusthe C-ORAL-Brasil I (RASO; MELLO, 2012) and is configured as a qualitative and descriptive research. It establishes, as categories of analysis, the NEGOTIATIONsystem, especially in the class of continuing moves. The results indicate that, due to the frequency distribution of the occurrences of continuing moves, there is a dominance of the selection of the speaker role by a single interactant, which contains more than half of this type of move. This continuation, above all, aims to develop the topics already produced throughout the conversation.
Improving STS Teaching Practice Through Transversal Competencies Towards Seamless Blended Digital Learning

Improving the teaching practice of Science, Technology, and Society (STS) is the primary goal of this action research and it was done by developing STS Modules that incorporated the frameworks of UNESCO Transversal Competencies and UN Sustainable Development Goals, and Seamless Blended Digital Learning Modality (SBDLM). These modules were utilized to determine its effects on student’s Transversal Competencies, Conceptual Understanding, Sustainable Development &amp; Solution-oriented Mindset, and on the perceptions of STS faculty members. This study utilized action research design to improve the STS teaching practice by developing and implementing STS Modules and evaluating their effects on the above-mentioned variables. Based on the results, the STS module contributed to the improvement of student’s conceptual understanding, inculcation of transversal competencies, and cultivation of sustainable development and solutions-oriented mindset. The modules are perceived by the students and virtual classroom observers as helpful as they assist the students to maximize learning even if there is minimal interaction between teachers and students because of the situations brought by COVID-19 pandemic. The study recommends continuous utilization of these STS Modules for its further improvement, modification of learning activities towards contextualization once these STS modules are adapted by future researchers in designing Seamless Blended Digital Learning Course Plan for flexible, agile, and responsive learning modality.
SCIENTIFIC-THEORETICAL BASIS OF THE ELECTRONIC MONEY SYSTEM

In this article, electronic money includes not only technologies where payments bypass the banking system, but also technologies where the mechanism of operation involves the existence of final settlements through the banking system. It is for this reason that our research allows us to determine the feasibility, advantages and disadvantages of using electronic money systems from theoretically different approaches
Uncertainty-aware transfer across tasks using hybrid model-based successor feature reinforcement learning☆

Sample efficiency, which refers to the number of samples required for a learning agent to attain a specific level of performance, is central to developing practical reinforcement learning (RL) for complex and large-scale decision-making problems. The ability to transfer and generalize knowledge gained from previous experiences to downstream tasks can significantly improve sample efficiency. Recent research indicates that successor feature (SF) RL algorithms enable knowledge generalization between tasks with different rewards but identical transition dynamics. It has recently been hypothesized that combining model-based (MB) methods with SF algorithms can alleviate the limitation of fixed transition dynamics. Furthermore, uncertainty-aware exploration is widely recognized as another appealing approach for improving sample efficiency. An agent can efficiently explore to better understand an environment by tracking uncertainty about the value of each available action. Putting together two ideas of hybrid model-based successor feature (MB-SF) and uncertainty leads to an approach to the problem of sample efficient uncertainty-aware knowledge transfer across tasks with different transition dynamics or/and reward functions. In this paper, the uncertainty of the value of each action is approximated by a Kalman filter (KF)-based multiple-model adaptive estimation. This KF-based framework treats the parameters of a model as random variables. To the best of our knowledge, this is the first attempt at formulating a hybrid MB-SF algorithm capable of generalizing knowledge across large or continuous state space tasks with various transition dynamics while requiring less computation at decision time than MB methods. We highlight why previous SF-based methods are constrained to knowledge generalization across same transition dynamics, present our novel approach on a firm theoretical foundation, and design a set of demonstration tasks to empirically validate the effectiveness of our proposed approach. The number of samples required to learn the tasks was compared to recent SF and MB baselines. The results show that our algorithm generalizes its knowledge across different transition dynamics, learns downstream tasks with significantly fewer samples than starting from scratch, and outperforms existing approaches. We believe that our proposed framework can account for the computationally efficient behavioural flexibilities observed in the empirical literature and can also serve as a solid theoretical foundation for future experimental work.
Upcoming Conferences of Interest to the AHP/ANP Community

There are three upcoming conferences that would be beneficial for the AHP/ANP community. The first conference is “The 23rd Conference of the International Federation of Operational Research Societies”, IFORS2023 STGO to be held in Santiago, Chile, July 10-14, 2023. Second, the INFORMS Annual Conference will be held in Phoenix, Arizona, USA, October 15-18, 2023. Phoenix is a popular location with INFORMS members. We are expecting some AHP/ANP and extensions scholars to participate in this conference. I am planning to invite our AHP/ANP colleagues from all over the world. In the scientific program, there is a cluster for Multiple Criteria Decision Analysis, in which there will be at least one AHP/ANP invited session: AHP/ANP and extensions (Organized by Birsen Karpak, Ilker Topcu) Last, but not least, is the MCDM 2024 conference. The Tunisian Decision Aid Society is organizing this international conference on Multiple Criteria Decision Making which will be held in Hammamet, Tunisia, June 2-7, 2024.
Validated Models Using EHRs or Claims Data to Distinguish Diabetes Type among Adults

Purpose: Clinical data provides the opportunity for efficient and timely disease surveillance.We developed and validated advanced phenotyping models to classify adult patients with diabetes to type 1, type 2, or other/indeterminate using structured fields from EHR data.To simulate the use of claims data supplemented with medication information, we compared model performance before and after the removal of body mass index (BMI) and laboratory results. Methods:We used 3 years of EHR data from a sample of 2,465 adult patients with diabetes from a health care system's clinical data warehouse.A weighted ratio of type 1 diabetes codes to all diabetes codes was created by down-weighting codes from care settings that do not treat diabetes.We developed two multinomial regression models and a machine learning conditional inference tree to classify patients to type 1, type 2, or other/indeterminate.The models were validated by calculating sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) relative to a gold standard.Results: For all models, the weighted ratio of type 1 diabetes was the strongest predictive factor.The models had validation statistics ≥ 93% for sensitivity; ≥ 87% for specificity; ≥ 88% for PPV, and ≥ 93% for NPV.After removal of BMI and laboratory data from the regression model the largest decline in performance from the full model was in type 2 diabetes specificity (90.8% to 89.2%). Conclusion:Prediction models and machine learning conditional inference trees using either structured fields from EHR data or claims data supplemented with medication data can be used to accurately distinguish diabetes type among adults.The inclusion of BMI and laboratory results improves model specificity for type 2 diabetes.
Discovery Processes and the Kondratieff Cycle: Mathematical Principles

Discovery processes' are hypothesised as processes in which there is an interplay between innovation activity and exploitation activity.Both require societal resources, in a zero sum game, so that, while innovation is needed to make exploitation possible, exploitation takes effort away from innovation, inhibiting the maintenance let alone expansion of exploitation.Such negative feedbacks, which propagate through the economy with a certain lag, give rise to oscillatory behaviour.Hence economic expansion proceeds in cycles.The cycle duration is linked to the human ageing process, since it is those entering adulthood who are best placed to respond to changed economic opportunities, while older adults are more committed to existing occupations.Since innovation activity is always positive (things are seldom de-invented), the cumulative activity (total inventions) manifests as quasi-logistic pulses, where growth is flatter when society's focus has shifted towards exploitation and steeper when society's focus has shifted back towards innovation.'Complex' discovery processes extend the logic of these 'simple' discovery processes with an additional dynamic whereby high value exploitation processes stimulate competition, which reduces their value, while innovation restores their value.The coupled cycles of innovation, exploitation and competition produce a fluctuation in all three activities, whose phase relationships correspond to those of the Kondratieff cycle and whose duration, given some assumptions about the turnover of generations, can be shown to match the Kondratieff period.The ideas discussed in the paper are applied to manned space exploration and are used to estimate the growth of the human presence in orbit over the next half-century.
THE ANALYSIS OF THE TRANSLATION OF SCIENTIFIC AND TECHNICAL TERMINOLOGY IN AUTOMOBILE RACING

Based on the translation of terms of automobile racing in China, as well as the author’s own translation practice, this paper summarises the characteristics and the translation methods of scientific and technical terms in automobile racing. It also analyzes the relevant examples in order to provide some reference for the translation of scientific and technical terms in automobile racing.
Influence of Students’-Staff Interactions on Academic Delinquency amongst Undergraduate Students in Public Universities in Kiambu and Nairobi Counties-Kenya

Academic delinquency has manifested itself in practices through practices such as: ‘sex for grades,’ sneaking unacceptable materials into examination rooms popularly known as ‘mwakenya’, plagiarism of assignments among other delinquent practices which have greatly affected the quality of university education in Kenya. So, this study sought to answer the research question: what is the influence of students’-staff interactions on academic delinquency amongst undergraduate students in public universities in Kiambu and Nairobi Counties in Kenya? The study adopted both quantitative and qualitative approaches targeting 40 Deans, 12 heads of departments, 120,000 undergraduate students, 2 counsellors, 2 registrars and 2 examination coordinators from Kenyatta University and Jomo Kenyatta University of Agriculture and Technology. Using stratified, multistage and purposive sampling criteria, a total of 414 respondents were sampled to participate in the study. For ethical purposes, the two universities were coded as X and Y in the analysis of data. Questionnaires and structured interview guide with open-ended test items were used to collect data from the students and deans, heads of departments, counselors, registrars and exam coordinators respectively. The study found that students’ interactions with members of staff during lecturers, Class work, sport and social functions was found to influence engagement in academic delinquency amongst students, as supported by more than 60% of respondents from both university X and Y. The study recommends a collaborative teaching and learning practice, where parents, staff and other stakeholder are engaged in ensuring proper ethics are instilled to all earners in universities.
Mancini vs. Manfredini, or the Tril Controversy

Giambattista Mancini and Vincenzo Manfredini, two great masters of the art of singing, engaged in a long-running controversy at the height of the 18th century over the training of the voice, but especially over how to perform the trill. Their dispute, which lasted more than twenty years, demonstrates the growing interest in the method of balancing the inventiveness generated by the use of ornamental formulas with the acquisition of vocal stability based on rigor and competence. The methods of applying these fundamental principles set a precedent for intense controversy, which ultimately proved to be both constructive and creative, with the happy consequence of a significant evolutionary leap in interpretive variety.
Christopher Bochmann´s “Essay XIII for Alto Saxophone Solo”: Proposed Fingerings for Timbre Shifts and Multiphonics

Written in 2001, Christopher Bochmann’s Essay XIII for solo Eb alto saxophone requires the performer to choose the alternate fingerings or Timbre Shifts used at several moments of the piece, as well as for the multiple choice multiphonics proposed by the composer. The principles of use and choice of fingerings supported by the work’s feasibility will be examined based on the literature of different authors. This paper intends to present the information necessary for the execution, bearing in mind the technical difficulties, challenges, and results that the employment of these extensive techniques always represents, whilst respecting the composer’s initial idea. The result was submitted and proposed to the composer Christopher Bochmann and was approved for record release.