Reviewerly/exHarmony huggingface dataset:
Application of Fuzzy BP Neural Network to Evaluate Effectiveness of Curriculum Teaching Reform of Nuclear Radiation Detection Technology

In the context of curriculum teaching reform, it is of great significance to evaluate its effectiveness. In the paper, the teaching reform of the nuclear radiation detection technology curriculum is studied and analyzed by using the fuzzy BP neural network model. According to the investigation of the evaluation factors of education reform, four primary evaluation indexes and nine corresponding secondary indexes are selected: teaching ability, classroom order, after school learning, and teaching effectiveness. The preliminary data set is obtained in the form of a questionnaire. The fuzzy theory and analytic hierarchy process are used to construct and calculate the evaluation index to provide samples for the learning of neural networks. On this basis, the fuzzy BP neural network model is constructed by combining BP neural network with a fuzzy system. After testing, the relative error of the output prediction score is less than 0.0002, which well predicts the evaluation results and provides an effective method for the evaluation of curriculum teaching reform.
Analysis of Teaching Influencing Factors and Teaching Reform of Numerical Analysis Course Based on BP Neural Network

Numerical analysis course has important guiding significance for data analysis ability of science and engineering graduate students. Based on BP neural network, we study the teaching influencing factors and teaching reform analysis of numerical analysis course. The teaching quality evaluation of numerical analysis is constructed based on BP neural network. The course of numerical analysis is evaluated from the aspects of classroom teaching, extracurricular development, students' knowledge reserve, and teaching results. 0.820675 is the related coefficient between the predicted value of the neural network and the actual value of questionnaire results, which shows that the constructed teaching quality evaluation model is reliable. Through the related coefficient analysis of the data, the main factors affecting the quality of teaching are obtained to provide new direction and orientation for teaching reform.
Cybercomplexity Metrics

AbstractIt is worth reiterating that commercial IT environments typically contain myriads of elements, and each element likely contains risk factors for information compromise. The presence of numerous risk factors in even modest IT environments suggests any realistic threat scenario is characterized by significant complexity.
Kernel Subspace Possibilistic Fuzzy C-Means Algorithm Driven by Feature Weights

At present, one of the difficulties in the field of fuzzy clustering is the clustering analysis for high dimensional data. Most of the existing fuzzy clustering algorithms are sensitive to initialization, which are greatly affected by noise points and has weak adaptability to high-dimensional data. In order to solve these problems, a kernel space possibilistic fuzzy c-means clustering (KSPFCM for short) algorithm is proposed. Firstly, considering that the fuzzy possibilistic clustering algorithm can deal with the noise points better, the typicality matrix is introduced to weaken the constraint on the membership matrix. Secondly, to refine the granularity of clustering convergence, subspace clustering is introduced to assign each feature weight value to the data, and the feature weight value is obtained by adaptive collaborative iteration. Among them, a greater weight value are given for the important features of the data, which makes the feature weight allocation more reasonable. Thirdly, the Gaussian kernel distance is used as the distance measure between data points to optimize the sensitivity to the data set, and thus the KSPFCM algorithm is proposed. Finally, by comparing with several advanced clustering algorithms on the artificial data sets and UCI data sets in this field, the proposed KSPFCM algorithm performs better in the five clustering effectiveness indicators of ACC, EARI, NMI, CHI and XBI.
The effectiveness of using dictogloss as a method to improve students’ listening achievement at MTs Ma’arif 04 Rumbia

The aims of this research are to find out whether there is significant effect of dictogloss method on the students’ listening achievement and to investigate in what part of speech the students get better achievement after learning through dictogloss method. The sample of this research was the first grade that consisted of 23 students. The instrument of this research was listening test. The researcher used paired samples t-test to analyze the data, in which the significant was determined by p&lt;0.05. The result showed that mean score of pretest (24.56) and posttest (55.65) in which t-value&gt;t-table (9.264 &gt; 2.074) or sig p&lt;0.05 (0.000&lt;0.05). Furthermore, part of speech in listening test that improved the most after learning through dictogloss method was verb. As a result, it can be concluded that dictogloss method is effective to improve students’ listening achievement. Dictogloss method can help the students in understanding the text easier, especially in descriptive text. Keyword: Dictogloss method, Listening Comprehension, Descriptive Text
Corporate governance, transparency and performance: empirical evidence from UAE

The paper uses both the agency theory and the legitimacy theory to provide a complementary framework that links different patterns of disclosures (i.e., transparency) to corporate performance for a sample of 116 United Arab Emirates (UAE) listed firms between years 2008-2016. It investigates the relationship between corporate disclosures (i.e., transparency), organisational commitment to law, a set of governance mechanisms (namely, board size, CEO decision-making power, and foreign ownership) and corporate performance while controlling for corporate specific characteristics such as size, type, age and leverage. The empirical results show that transparency indices have a puzzling pattern across different performance measures - namely return on assets, asset turnover and organisational growth. The paper is one of very few studies that examine the association between corporate transparency and corporate performance in an emerging market economy such as the UAE.
STUDY ON THE APPLICATION OF AUDIT FIRE MANAGEMENT SYSTEM IN RS X DISTRICT Y

Background: According to the Indonesian National Standard number 03-3985-2000, fire is a phenomenon that occurs when a material reaches a critical temperature and reacts chemically with oxygen to produce heat, flames, light, water vapor, carbon monoxide, or other products and effects. Fires are caused by various factors, either due to human factors or technical factors.Objective: This study aims to determine the application of fire management system audits in RS X Regency Y. Method:With a qualitative method through a case study approach.Determination of informants using the snowball method. Data collection was carried out by observation and in-depth interviews which were processed using content analysis, and triangulation of sources and methods was carried out.Result:The results showed that RS X had formed a fire organization by-laws and regulations, fire procedures did not run well when a fire broke out, and during the simulation, there were still technical obstacles when using fire tools.Conclusion:It is hoped that the management of X Regency Y Hospital will pay more attention to planning, training, and providing fire disaster preparedness.
Design Intents Disentanglement: A Multimodal Approach for Grounding Design Attributes in Objects

Language is ambiguous; many terms and expressions convey the same idea.This is especially true in design fields, where conceptual ideas are generally described by high-level, qualitative attributes, called design intents.Words such as "organic", sequences like "this chair is a mixture between Japanese aesthetics and Scandinavian design" or more complex structures such as "we made the furniture layering materials like a bird weaving its nest" represent design intents.Furthermore, most design intents do not have unique visual representations, and are highly entangled within the design artifact, leading to complex relationships between language and images.This paper examines an alternative design scenario based on everyday natural language used by designers, where inputs such as a minimal and sleek looking chair are visually inferred by algorithms that have previously learned complex associations between designs and intents-vision and language, respectively.We propose a multimodal sequence-to-sequence model which takes in design images and their corresponding descriptions and outputs a probability distribution over regions of the images in which design attributes are grounded.Expectedly, our model can reason and ground objective descriptors such as black or curved.Surprisingly, our model can reason about and ground more complex subjective attributes such as rippled or free, suggesting potential regions where the design object might register such vague descriptions.
Toward a Transatlantic Philosophy of Nature

In “Toward a Transatlantic Philosophy of Nature,” Samantha C. Harvey demonstrates how British Romantic poets like Wordsworth and Coleridge articulated a philosophy of nature in poetic form that would be reinterpreted in two central prose works of American Transcendentalism: Emerson’s Nature (1836) and Thoreau’s Walden (1854). Through detailed analysis of the works of Wordsworth and Emerson, Harvey suggests that nature’s vital role in the nineteenth century becomes particularly pronounced when Romanticism is considered as a transnational movement that flowed beyond national boundaries. Harvey shows how a transcendentalist philosophy of nature crossed, recrossed, and crisscrossed the Atlantic in various directions, undergoing continual transformations along the way.
Optimizing the Use of E-Worksheet and PHET Simulation in Science Learning during the Covid-19 Pandemic

This study examines the use of e-worksheets and PHET Simulation as virtual laboratories in science. This study aims to determine whether the use of PHET Simulation with e-worksheet guidance can optimize online learning to minimize learning loss due to the Covid 19 pandemic. E-worksheets are used as scaffolding media that are used to help guide students to do online practicums. The research was conducted in two stages. The first stage is conducting a direct trial of learning using PHET Simulation and e-worksheets through Google Classroom. For the second stage, the activities include collecting data using an accessibility questionnaire using a google form. The data were then analyzed by usability test covering aspects of usefulness, ease of use, ease of learning, and satisfaction. The usability test results show that the percentage of respondents to the questions given is dominated by the Agree (S) and Strongly Agree (SS) statements on all usability test indicators. This shows that the use of e-worksheets and PHET Simulation as a virtual laboratory fulfils the element of usability.
An asymmetric encryption method for 3D mesh model using elgamal with elliptic curve cryptography

The 3D mesh &lt;span lang="EN-US"&gt;(Polygon mesh) model has been widely used in multiple computer technology fields such as computer graphic design and modern 3D animation. 3D mesh repositories were created to support the contribution of many 3D artist-designers and have become an important data source. This research is aimed at introducing asymmetric encryption for a 3D mesh model to improve encryption using elgamal elliptic curve cryptography with Fischer-Yates shuffling. The researchers evaluated the performance of the proposed model using Entropy, mean squared error (MSE), and peak signal noise ratio (PSNR) as evaluation matrices. The results of a decrypted model using our approach with a double-precision floating point showed zero means squared error and infinite value of PSNR&lt;/span&gt;.
An interpolation based steganographic technique with least-significant-bit and pixel value differencing in a pixel block

Over the &lt;span lang="EN-US"&gt;past few years, in order to improve the hiding capacity and the peak signal-to-noise ratio (PSNR) value, several steganographic techniques have been developed. Steganography has become a popular technique to transmit secret data through any medium. In image steganography, the human eye cannot easily identify the hidden data which is embedded into the image. Small changes are also not detected by the human eye. High hidden capacity along with high visual quality is provided by the pixel value differencing (PVD) method. This paper first proposes the method of interpolation between the pixel blocks and then applies the least-significant-bit (LSB) substitution technique with the PVD method. At the starting phase, the original image is fixedto a 2x2 block, then the nearest neighbor interpolation (NNI) technique is implemented. In the next phase, the upper left pixel isembedded by the k-bit LSB substitution method along with hidden data. The newly generated neighbouring pixel value is measured. Thus, data is hidden from three directions. Through this paper using two different range tables, the new algorithm is proposed. We observed that in both cases, PSNR and the hiding capacity are improved.&lt;/span&gt;
Application of advanced encryption standard in the computer or handheld online year-round registration system

&lt;span lang="EN-US"&gt;With various severe security threats for web applications, ensuring security on the database layer itself is imperative. Hence, this study aims to protect data saved on the computer or handheld online year-round (CHOY) registration system using the advanced encryption standard (AES) to strengthen data security within the app so that even potential attackers gain access to the app's database; they cannot obtain valuable information because it is scrambled and unreadable. The proponents based the study's conceptual framework on the symmetric and asymmetric key algorithms and procedures manual on enrollment of Southern Isabela College of arts and trades (SICAT) and ISO 25010. The study consists of three elements: developing the CHOY web app imbued with AES, testing it in terms of online registration and spam prevention, and evaluating it using the ISO 25010 in terms of compatibility, reliability, and security. The evaluation results show that implementing the AES in the CHOY web app meets the ISO 25010 criteria mentioned above.&lt;/span&gt;
Comparison of principal component analysis and ANFIS to improve EEVE Laboratory energy use prediction performance

The energy use that is in &lt;span lang="EN-US"&gt;excess of practicum students’ needs and the disturbed comfort that the practicum students experience when conducting practicums in the Electrical eengineering vocational education (EEVE) laboratory. The main objective in this study was to figure out how to predict and streamline the use of electrical energy in the EEVE laboratory. The model used to achieve this research’s goal was called the adaptive neuro-fuzzy inference system (ANFIS) model, which was coupled with principal component analysis (PCA) feature selection. The use of PCA in data grouping performance aims to improve the performance of the ANFIS model when predicting energy needs in accordance with the standards set by the campus while still taking students’ confidence in conducting practicum activities during campus operating hours into consideration. After some experiments and tests, very good results were obtained in the training: R=1 in training; minimum RMSE=0.011900; epoch of 100 per iteration; and R=0.37522. In conclusion, the ANFIS model coupled with PCA feature selection was excellent at predicting energy needs in the laboratory while the comfort of the students during practicums in the room remained within consideration.&lt;/span&gt;
In-depth analysis of dynamic degree load balancing technique in public cloud for heterogeneous cloudlets

&lt;span lang="EN-US"&gt;Load &lt;span lang="EN-US"&gt;balancing is one of the challenges of the distributed computing worldview. With the enormous development in clients and their interest for different administrations on the distributed computing stage, compelling or productive asset usage in the cloud climate has turned into an urgent concern. Load balancing is critical to keeping cloud computing running smoothly. This study examines the research using four scheduling algorithms: dynamic degree balance CPU based (D2B_CPU), dynamic degree balanced membership based (D2B_Membership), dynamic degree memory balanced allocation (D2MBA) and hybrid dynamic degree balance (HDDB) algorithm. Central processing unit (CPU) utilisation, bandwidth utilisation, and memory utilisation are used as performance measures to verify the performance of these algorithms. The CloudSim simulation programme was used to simulate these algorithms. The primary goal of this work is to aid in the future construction of new algorithms by researching the behaviour of various existing algorithms.&lt;/span&gt;&lt;/span&gt;
CBP2P: Cooperative Electronic Bank Payment Systems Based on Blockchain Technology

&lt;p&gt;The most common consumer behavior was to pay in cash at a physical store in the past. However, with the rapid development and popularization of smart handheld devices and computers, merchants have had many innovative business models in recent years. For example, the digital cryptocurrency Bitcoin has the advantages of decentralization, anonymity, and the inability to tamper with data. If these benefits are combined with the current electronic payment financial operation model, they will be highly innovative. However, blockchain technologies have been applied to decentralized network architectures. As a result, the financial system will face anonymous crime, extensive data synchronization, and time-consuming transaction processes. This paper implements a P2P electronic payment system with a hierarchical structure based on the blockchain architecture, called CBP2P (Cooperative Bank Peer-to-Peer), to improve the defects and realize an accurate electronic payment system. Through the characteristics of the blockchain and cooperation between banks, we will enhance the security and availability of the system.&lt;/p&gt; &lt;p&gt;&amp;nbsp;&lt;/p&gt;
Improving Students’ Reading Comprehension By Using Questioning Techniques In Narrative Text

This study attempts to improve students’ reading comprehension by using questioning technique.This study was conducted by applying classroom action research. The subject of the research wasclass X-4 SMA N.1 Sei Rampah which consisted of 30 students. The research was conducted intwo cycles, cycle I of three meeting and cycle II consisted of three meetings. The instruments forcollecting data were quantitative data namely reading comprehension test and qualitative datanamely, diary notes, observation sheet and questionnaire. Based on reading comprehension testscores, students score kept improving in every test of reading. Based on diary notes, observationsheet and questionnaire sheet it was found that the students were active and enthusiastic in learningreading through questioning techniques. The result of the research showed that questioningtechniques significantly improved students’ achievement in reading comprehension.
A Systematic Comparison of Software Requirements Classification

Software requirements specification (SRS) is an essential part of software development. SRS has two features: functional requirements (FR) and non-functional requirements (NFR). Functional requirements define the needs that are directly in contact with stakeholders. Non-functional requirements describe how the software provides the means to carry out functional requirements. Non-functional requirements are often mixed with functional requirements. This study compares four primarily used machine learning methods for classifying functional and non-functional requirements. The contribution of our research is to use the PROMISE and SecReq (ePurse) dataset, then classify them by comparing the FastText+SVM, FastText+CNN, SVM, and CNN classification methods. CNN outperformed other methods on both datasets. The accuracy obtained by CNN on the PROMISE dataset is 99% and on the Seqreq dataset is 94%.
Differences in the Test Results of Two Test Rubrics in the Yes/No Vocabulary Test

The Yes/No vocabulary test (YN test) is a receptive vocabulary size test that comes in a form of a checklist where learners answer yes to the words they know. However, an inconsistency of the test rubrics has been found. That is, rubric type 1 says: “Write Y (yes) if you know the meaning of the word” while rubric type 2 says: “Write Y (yes) if you think that the word exists in English”. These 2 rubrics seem to require different levels of vocabulary knowledge from test takers. Rubric 1 may need more knowledge of the word meaning while Rubric 2 may need less (i.e. only having seen the word or even guessing). This led to the doubt whether or not the 2 rubrics yield the same YN test results. Therefore, a study was conducted to compare these two rubrics by administering 2 YN test versions, i.e. Rubric 1 YN tests and Rubric 2 YN tests, to 600 first-year students of a university in Nakhon Ratchasima, followed by a translation test as a concurrent validity test. After that, a semi-structured interview of 72 students was conducted in order to gain some insight of how they did the tests. The findings revealed that the results of Rubric 1 YN tests correlated better with the results of the concurrent validity test than those of Rubric 2 YN tests.
Deep CNN Based Hybrid Model for Image Retrieval

The popularity of deep features based image retrieval and classification task has grown a lot in the recent years. Feature representation based on Convolutional Neural Networks (CNNs) found to be very effective in terms of accuracy by various researchers in the field of visual content based image retrieval. The features which are neutral to their domain knowledge with automatic learning capability from their images are in demand in various image applications. For improving accuracy and expressive power, pre-trained CNN models with the use of transfer learning can be utilized by training them on huge volume of datasets. In this paper, a hybrid model for image retrieval is being proposed by using pre-trained values of hyper parameters as input learning parameters. The performance of the model is being compared with existing pre-trained models showing higher performance on precision and recall parameters
The state of systems development methodologies use within the systems development organisations in South Africa

The adoption of the most appropriate systems development methodology (SDM) for a systems developmentproject is one of the most critical decisions in systems development practice. An appropriate SDM for a sys-tems development project is adopted to avoid a misfit of a systems development methodology to the systemsdevelopment project contextual settings. An SDM misfit is caused by an SDM whose basic assumptions havebeen violated by the targeted systems development project contextual settings. A misfit may increase theeffort required for an SDM in use to fit the systems development project contextual settings. The study aimsto investigate the contingent use of SDMs as an approach to minimise SDM misfit in a systems developmentproject. The purpose of the article is to present insights on the contingent use of SDMs derived from a surveyof 155 organisations involved in systems development. The results show that both plan-driven and agile SDMclass instances are in use and that hybrid SDMs characterise most SDM implementations. The findings haveimplications for both research and practice as they unify the use of the two SDM classes under the contingentuse of SDMs approach.