Reviewerly/exHarmony huggingface dataset:
STUDI EKSPERIMENTAL PENGARUH JUMLAH SUDU DAN PENGGUNAAN END PLATE TERHADAP CUT IN SPEED TURBIN ANGIN SAVONIUS HELIKS

&lt;p class="abstrak"&gt;This study aims to analyze the effect of variations in the number of blades and the use of end plates on the cut in speed of Helical Savonius wind turbine. The method used in this research is the experimental method. The variables used in this study are variations in wind speed from 1 to 5 m/s with intervals of 0.5 m/s. Variations in the number of blades are 2,3, and 4 blades. Variations in the use of end plates and without end plates. The results of this study was found that variations in the number of blades and the use of end plates affect the cut in speed of helical Savonius wind turbine. The fewer the number of turbine blades, the better the turbine's cut in speed will be. 2 blade’s Helical Savonius wind turbine with end plate is turbine variation that is able to produce best cut in speed of 1.97 m/s, compared to other variations.&lt;/p&gt;
The Role of Leadership Style in Improving Employee Satisfaction and Performance in Etisalat

Purpose: study the impact of leadership styles on employee satisfaction and organizational performance in Emirates Telecommunication Corporation (Etisalat),&#x0D; Methodology: primary data was gathered from interviews with Etisalat staff, while secondary data was gathered from the Etisalat website and online articles.&#x0D; Findings: Although Etisalat has both transactional and transformational leadership styles it appears that the satisfactory job terms of the company's departments vary, whereas some are very satisfied, but others have reached a medium level of satisfaction. it has been concluded that leadership plays a critical role in inspiring employees, and lack of leadership guidance discourages their creativity&#x0D; Unique Contribution to Theory, Practice and Policy: The study recommends that Etisalat should build a balanced leadership style that focuses on employee productivity and mental health. It also recommends that that employees need to be provided with a comprehensive platform to participate, communicate, and interact with their colleagues and managers.
Research on Chinese Emotion Classification using BERT-RCNN-ATT

Emotional classification is the process of analyzing and reasoning subjective texts with emotional color, that is, analyzing whether their emotional tendencies are positive or negative. Aiming at the problems of massive data and nonstandard words in the existing Chinese short text emotion classification algorithm, the traditional BERT model does not distinguish the semantics of words with the same sentence pattern clearly, the multi-level transformer training is slow, time-consuming, and requires high energy consumption, this paper proposes to classify users' emotions based on BERT-RCNN-ATT model, and extract text features in depth using RCNN combined with attention mechanism, Multi task learning is used to improve the accuracy and generalization ability of model classification. The experimental results show that the proposed model can more accurately understand and convey semantic information than the traditional model. The test results show that compared with the traditional CNN, LSTM, GRU models, the accuracy of text emotion recognition is improved by at least 4.558%, the recall rate is increased by more than 5.69%, and the F1 value is increased by more than 5.324%, which is conducive to the sustainable development of emotion intelligence combining Chinese emotion classification with AI technology.
DEEP LEARNING-BASED SURVEY OF AUTOMATIC EYE DISEASE CLASSIFICATION

This survey paper discusses a proposed deep learning-based approach for the automatic classification of eye diseases.The eyes are one of the most important organs in the human body, responsible for vision and many critical functions.Timely and accurate diagnosis and treatment of eye diseases are essential to prevent vision loss and related complications.However, traditional methods of eye disease detection are time-consuming, costly, and often require trained professionals, making them inaccessible to many people.In this paper, we will explore how the proposed approach utilizing deep learning techniques can classify eye diseases accurately and efficiently, leading to early detection and effective treatment.
Some Results Related With Type Of Family Of Sets

Results Related With Type Of Family Of Sets 1.IntroductionThe concept of a fuzzy integral with respect to fuzzy measure was introduced by Sugeno [4] , and the definition of a fuzzy -field on fuzzy set provided by [3], [7] , in 2019 Ibrahim and Hassan introduced some concepts such as --field and --field which represent the generalizations of -field [1], in this paper we will introduced the concept of fuzzy -field , fuzzy --field ,fuzzy -field , fuzzy --field ,fuzzy -field and the relation between them . FuzzySetsThis section deals with the concepts of fuzzy set, complement , and operation on fuzzy sets.
PALATALISATION IN THE TIV PHONOLOGY

Palatalisation is a well-known phonological process and a repairing strategy in the Tiv phonology which has not been adequately explored. Palatalisation in the Tiv phonology examines the phonotactic constraints of palatalisation and explores the functions that palatalisation performs in the Tiv phonology. This study has adopted Generative Phonological Model that was jointly co-authored by Chomsky and Halle’s (1968) Sound Patterns of English (SPE). The study used participant-observation instrument in this study. The study used both primary and secondary materials for gathering of data. In this study, the researcher got raw data, transcribed, translated and classed them into phonotactic constraints and functions of palatalisation in Tiv. From this study, it has been discovered that Tiv palatalisation has phonetic and orthographic classes; palatalisation results in consonant clusters, pluralisation, epenthesis, deletion and metathesis; palatalisation is a phonological process, secondary articulation and phonological change. The study is, therefore, recommended to scholars, lecturers and writers who are learning, teaching, researching and writing scholarly works on Linguistics, Nigerian and African Languages and English Language.
Visualization in neuroscience: a case of cortico-subcortical loops

The aim of this paper and poster is to discuss some of the problems occurring in attempts to visualize neurobiological mechanisms. According to the thesis, neurobiological, static schemas should not only depict the order of connections among individual neural structures accordingly, but they have also the potential to present more detailed information about relations within mechanisms, such as patterns of dynamic interactions, their intensity, arrangement and the size of specific components, etc. First I will introduce the problems of visualization in neuroscience, then I am going to discuss these problems with an example of the cortico-subcortical loops (C-SL) mechanism. Finally, I will show my solutions to some visualization problems and discuss the original schemas presented in the poster.
Method for detecting pollution degree of insulator based on Locality Preserving Projections Extreme Learning Machine

The Composite insulator is subjected to environmental influences, its surface can accumulate pollution, which can lead to an increase in flashover accidents. For the measurement of insulator surface pollution, the traditional detection methods have a certain degree of defects. In this paper, we use hyperspectral technology to detect the surface pollution of insulators from the perspective of high accuracy and non-contact. In this paper, firstly, artificially polluted insulator samples are produced, and then the data obtained by hyperspectral technology are subjected to black-and-white correction, standard normal variable distribution (SNV), and Savitzky-Golay convolution (SG) algorithms to reduce the interference of noise in the images and dark inrush current on the hyperspectral imaging results. Finally, we use locality preserving projections extreme learning machine (LPP-ELM) to achieve the classification of insulators with different degrees of pollution with an accuracy of 98.33%.
A preference-based path planning approach for multi-UAV collaborate reconnaissance in static environment

The collaborate path planning of multiple Unmanned Aerial Vehicles (UAVs) for patrolling and reconnaissance in static environment is addressed in this paper. In the application of urgent observation, two objectives are considered simultaneously, i.e., time cost and energy cost. A good plan makes sure that all the targets are observed as soon as possible, and the overall energy consumption as low as possible. The problem is formulated as a multiple traveling salesman problem (MTSP) with multiple depots, known as a nondeterministic polynomial-hard problem. A preference-based multi-objective optimization algorithm is proposed to solve the problem. Preferred range of each objective is used as preference information, and the algorithm aims at Pareto optimal solutions that match the preference. Through computational experiments, the benefit of the proposed algorithm (T-MOEA/D-2opt) is demonstrated by comparing with other existing algorithms. Experimental results show that T-MOEA/D-2opt is effective and efficient in finding preferred Pareto solutions for this path planning problem.
Research and Application of Key Technologies on Cloud DTS based Intelligent Instructor System: Architecture and Functions

With the further deployment of the regulation cloud technology, it has become a trend to migrate DTS to the cloud platform, so as to give full play to the advantages of the cloud platform in resource sharing, efficient computation, etc. However, with insufficient intelligence and automation, dispatching training on cloud DTS still requires the participation of real instructors throughout the process, which seriously restricts the application efficiency and effect. Therefore, this paper firstly analyzed shortcomings of existing DTS and proposed the architecture of the cloud DTS based intelligent instructor system (IIS) integrating with the adaptive learning model in order to meet the personalized and intelligent training needs for random concurrency of multiple dispatchers under cloud training mode. Then the application scenarios and functions of the IIS was described in detail, mainly from three aspects as automatic preparation of training cases before training, intelligent interaction and control of drill process during training and comprehensive evaluation for adaptive recommendation after training. Once fully developed, the IIS can provide continuous support for cloud DTS to become the daily and autonomous training tool for dispatchers at anytime and anywhere.
Research and application of power transformer technical standard retrieval algorithm based on knowledge graph

In view of the difficulty in using unstructured text data and the shallow application of equipment knowledge in the process of transformer equipment operation inspection by power supply companies, this paper proposes a knowledge map technology framework to support transformer intelligent management by using knowledge map, natural language processing and other artificial intelligence technologies. At the same time, this paper proposes a method to screen new knowledge through text error checking and a method to screen degraded knowledge through text path searching. After the knowledge map is updated, the integrity of knowledge is verified through text error checking. Finally, this method is verified in the scenarios of flexible question answering of power transformer equipment information and automatic extraction of transformer fault reports. The experimental results show that this scheme improves the accuracy of the knowledge map, can properly integrate new knowledge into the knowledge map, and effectively improves the application effect of the defect text knowledge map.
Reliable and Efficient Image Processing and Deep Machine Learning for large-scale Digital Image Retrieval

Retrieving relevant photos from a database by analysing their differences and similarities is an essential part of machine vision. Numerous applications exist in areas such as storage, object recognition, localisation, and recognition with limited data. In this study, we take a look at the issue of image retrieval, in which a group of pictures is retrieved from a huge database in order to find ones that are most like the one the user has submitted (the “query image”). This thesis investigates the origins of the issue, as well as its present-day manifestations and potential solutions. To the best of our knowledge, however, there is currently no accessible generic text removal method that can be used to any font, script, language, or shape to remove all or user-specified text sections. The difficulties of multi-lingual and curved text identification and inpainting are carried over into the development of a general text eraser for real-world settings. To the best of our knowledge, however, there is currently no accessible generic text removal method that can be used to any font, script, language, or shape to remove all or user-specified text sections. Creating a general text eraser for use in real-world scenarios is difficult since it takes on the difficulties of both multi-lingual text detection and curved text inpainting. By adhering to these standards, our method significantly outperforms the state of the art on four benchmark datasets. This includes more complicated algorithms with auxiliary components. Furthermore, we offer a qualitative evaluation of our trained representation, which shows that despite its small size, it is able to gather information from highly localised and discriminative regions, much like an implicit attention mechanism.
Design of Portable Sensor Data Storage System Based on Homomorphic Encryption Algorithm

With the development of sensor technology, people put forward a higher level, more diversified demand for portable rangefinders. However, its data storage method has not been developed in a large scale and breakthrough. This paper studies the design of portable sensor data storage system based on homomorphic encryption algorithm, which aims to maintain the security of sensor data storage through homomorphic encryption algorithm. This paper analyzes the functional requirements of the sensor data storage system, puts forward the overall design scheme of the system, and explains in detail the requirements and indicators for the specific realization of each part of the function. Analyze the different technical resources currently used in the storage system field, and dig deep into the key technologies that match the portable sensor data storage system. This paper has changed the problem of cumbersome operation steps and inconvenient data recovery in the sensor data storage system. This paper mainly uses the method of control variables and data comparison to carry out the experiment. The experimental results show that the success rate of the sensor data storage system under the homomorphic encryption algorithm is infinitely close to 100 <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">%</sup> as the number of data blocks increases.
Side-Channel Analysis and pseudo-Boolean functions

The development of classical cryptanalysis makes possible to assess the security of symmetric and asymmetric encryption algorithms. A vulnerability of these algorithms lies in their physical implementations. Indeed during their executions, several physical parameters can be retrieved thanks to the side-channel analysis, and thus provide information about the used encryption keys. The objective of this work is to suggest one or more side-channel attack (or significant improvements), based on the properties of pseudo-Boolean functions modeling the leakage.
Research on the discrepancy distinguishment of the electric power standard clauses based on NLP

To solve the problem of overlapping, repeated and contradictory terms in different kinds of electric power standards, we propose a method of discrepancy distinguishment for the electric power standard clauses based on natural language processing (NLP). The proposed method converts the unstructured text into triples using the entity relation extraction method for power standard terms, and stores them in knowledge graph to reduce the query time and the processing time. Then, the text similarity calculation method is used to compute the similarity of triples. Finally, the discrepancy distinguishment of standard terms can be obtained. Taking power grid equipment technical standard difference clause data as an example, experiments were carried out, and the recall and the precision reached 82.2% and 70.6% respectively. The experimental results illustrate that the recognition rate and adoption rate reached 82.2% and 70.6% respectively. It also shows that the proposed method could provide a solution to the discrepancy distinguishment of standard documents in various industries.
Block Chain Technology Implementations for Secured Financial Transactions using Cloud Environment

The advancement of technology has an influence on consumers' decision to switch from executing your financial information in a conventional way to doing so online. Contracts are encouraged by the use of cloud computers or its key feature of accessibility from everywhere. The enormous amount of data handled by the cloud platform used to facilitate money transfers necessitates maintaining a high degree of security for all those important passwords stored there. Although the conventional authentication methods continue to work well in protecting data in cloud, more sophisticated cyber attacks against cloud-based storage of information still exist. Additionally, using typical cryptographic primitives to secure cloud data requires a significant amount of operation time due to the need to execute verification checks for both valid and illegitimate access control.
On the Mechanism of Particle Motion in Space and Time

On the basis of a hypothesis about spiral motion of particles in space and time, It is derived from the theoretical expression for Planck constant and the De Broglie wave formulas and suggested a new physical constant.
Perceptual Space of Action of a Musical Composition

The purpose of the article is to reveal the meaning and peculiarities of the category"perceptual space" in musical art. The methodology of the research is based on theinterdisciplinary integration of the methods of modern philosophy, cultural studies and art history.Scientific novelty of the article is the substantiation of the inseparable interconnection of space andman, which makes it possible to consider this category one of the fundamental forms ofunderstanding the world and thinking about the world in musical art. For a full study of theperceptual space in music, there are means that facilitate the creation of connections of elementsboth within the composition and between objects of art and reality. Conclusions. Continuation anddeepening of the study of spatial means and principles of form formation in music createprerequisites for a deeper understanding of the nature of space in art. This process also contributesto the identification of common psychological, physical, compositional patterns, concentratesspatial perception in music. To such we attribute the following: the value of the unconscious increating conditions corresponding to the activation of sensory channels responsible for visualperception; the operation of general physical laws; the basis of the mechanism of associativity, motor modeling in music; the necessary generality of the stages of understanding is imagesensation, image-perception, image-representation; the basis of the unity of the compositionalprinciples of visual and musical arts; the general effect of the principles of formal composition (theprinciple of simplicity, the influence of geometric forms on emotional perception, the arrangementof musical marks on the plane of the score, such as the relationship between the figure and theplane and other positions in music).Key words: space, space of musical art, perceptual space, composer creativity, synaesthesia
A STUDYING OF WEBCONTENT MINING TOOLS

The web today has become an archive of information in any structure such content, sound, video, designs, and multimedia, with the progression of time overall web, the world wide web is now crowded with different data making extraction of virtual data burdensome process, web utilizes various information mining strategies to mine helpful information from page substance and web hyperlink. The fundamental employments of web content mining are to gather, sort out, classify, providing the best data accessible on the web for the client who needs to get it. The WCM tools are needful to examining some HTML reports, content and pictures at that point, the outcome is using by the web engine. This paper displays an overview of web mining categorization, web content technique and critical review and study of web content mining tools since (2011-2019) by building the table's a comparison of these instruments dependent on some important criteria
Akuntansi Manajemen: Peran Sistem Informasi dan Budaya Organisasi

In the current era, information plays a very important role in various aspects of human life individually or in organizations. Information is able to help an organization reach its optimal point, the effectiveness of information makes it easier to identify competitors and analyze the profits of other competitors. One of the factors that can influence this information system is organizational culture. The quality of an information system is influenced by the organizational culture. The purpose of this study is to determine the role of information systems and organizational culture in management accounting. The type of research used is qualitative with descriptive analysis. The data collection was carried out by means of a literature study. Based on the results of the study, it shows that information systems and organizational culture have a role in management accounting. This information system can provide information related to financial reports that are used in measuring several company activities. Accounting information systems can also play a role as a source of information that is used as a basis for consideration in making decisions for management. Culture within the company is able to influence the effectiveness of implementing accounting information systems, in which corporate culture is able to shape the behavior of managers in making decisions. The successful implementation of accounting information systems needs to pay attention to organizational factors.&#x0D;
ARTIFICIAL INTELLIGENCE IN EDUCATION: THE UAE EXPERIENCE

Artificial intelligence is the present, not the future. This technology is gradually revolutionizing the field of education. The article discusses the experience of the United Arab Emirates in the application of artificial intelligence technologies in school and university education. A SWOT analysis of the strengths and weaknesses of the use of artificial intelligence in education is also presented.