Reviewerly/exHarmony huggingface dataset:
SATUAN PEMELIHARAAN 220th AIRLIFT WING DAN MODERNISASI ANGKATAN BERSENJATA FILIPINA

In the ever-changing global security landscape, the Philippines is dedicated to modernizing its Armed Forces (AFP). The 220th Airlift Wing, a crucial component of the Philippine Air Force, plays a vital role in air mobility operations. However, the Wing faces challenges in maintaining optimal operational readiness, particularly in intermediate level maintenance capabilities. This research aims to develop strategies to strengthen intermediate level maintenance within the Wing, enhancing operational readiness to support the AFP effectively. A comprehensive approach based on the DOTMPLF framework is proposed to address the issues. The study's findings will provide valuable insights to improve aircraft maintenance, bolster operational readiness, and support the Philippines' defense and socio-economic endeavors. Furthermore, the study uses a qualitative method with descriptive analysis as its methodology. Collecting data will be through field research, enabling direct information gathering from the source. Additionally, formal interviews and desk research utilizing internet resources will be conducted and employed. In conclusion, the further development of the intermediate level maintenance is needed to improve operational readiness of the 220th Airlift Wing. This will result in benefits not only for the PAF but to the whole Filipino nation as well.
Measuring Customer Satisfaction Using Multi-Criteria Analysis Model of Customer Satisfaction to Evaluate Product Lines

Today, customer retention and growth is the first goal. Companies have taken a heavytoll on each customer, and competitors are constantly seeking to steal them. Satisfiedcustomers have many benefits for the company, they are less sensitive to prices, will bea customer for a long period of time, and give a favorable view of the company and itsproducts and services to others. Paying attention to the factors that are less importantfrom the customer's point of view and evaluating these factors leads to spendingresources in areas that have less impact on customer behavior, so understanding thefactors that have the greatest impact on customer satisfaction to the organization tomove in this will help. In this study, we intend to use the operational data of the linesand customer satisfaction scales to evaluate the relative efficiency of product lines usingthe network data envelopment analysis method. In order to achieve this goal andquantify the data obtained from the questionnaire, another linear programming methodcalled multi-criteria satisfaction analysis will be used. Another innovation of thisresearch is the application of customer expectations in the data envelopment analysismole because most researchers that focus on quality do not consider this component intheir evaluation model. The results indicate that the distribution system is the mosteffective factor and resources and supply is the most effective factor affecting customersatisfaction.
Towards a Combination of Metrics for Machine Translation

In this scholar, we compare three metrics for machine translation, from English toFrench and vice versa, and we give some combination formulas based on someschemes, algorithms, and machine learning tools. As an experimental dataset, weconsider 10 English and French theses abstracts published in the web with four free incharge machine translation systems. Five combinations, with the same implicit weights,are considered namely: (BLEU+NIST), (BLEU+ (1-WER)), (NIST+(1-WER)),(BLEU+NIST+(1-WER)), and (FR(BLEU)+FR(NIST)+FR(WER)). Thesecombinations are also considered differently through generating weights parameters onthe basis of regression. The results of 12 formulas are computed and compared then intotal. According to the obtained results, average regression combinations based onmachine learning step are the best, especially with the three basic metrics, followed byaverage WER metric in the case of English to French. For French to English,(FR(BLEU)+FR(NIST)+FR(WER)) combination is the best followed respectively bythe average regression combination with both first parameters (Reg(α,β)) and averageBLEU basic metric. Another performance criterion is considered here, in the secondposition, namely: the number of times, over the 10 abstracts, where the formula is thebest. Based on the obtained results, combination with regression based on the first andthe last parameters (Reg(α,γ)) outperforms the others, in the case of English to French,with 3 times followed by Reg(β,γ), Reg(α,β,γ), NIST+(1-WER), and the basic metrics(BLEU, NIST, and WER) with 2 times for each of them. For French to English, thebasic WER metric outperforms the others with three times followed by BLEU, (BLEU+(1-WER)), (FR(BLEU)+FR(NIST)+FR(WER)), and Reg(α,γ) with 2 times for each ofthem. To note that there is a room of improvement for the combinations with1.0914 inthe case of English to French and 1.01 in the case of French to English.
Relevance of GDL Properties Regarding GDL Quality Assurance

Gas diffusion layers are an important part of all types of polymer electrolyte membrane fuel cells (LT-PEMFC, HT-PEMFC or AEMFC). Albeit the conversion reaction is not taking place in the GDL the contributions of the GDL to the function of the cell are essential. So, the GDL needs to homogenise the distribution of reacting gases over the electrode area compensating inhomogeneities created by the channel fin structure of the flow-field of the bipolar plate and at the same time cause a focussing of product streams towards the channels. The GDL needs to conduct electric current between the catalyst layer and the bipolar plate at high current density and transport released thermal energy. The GDL also needs to distribute mechanical pressure of the stack compression. In order to accomplish all those tasks, the GDL needs to feature the right properties with high homogeneity through-out its area and with high reproducibility batch to batch. Unfortunately, a rather high number of properties can be assigned to a GDL. So, the review paper by Yuan et al. on properties for different LT-PEMFC components 1 lists about 15 different properties for GDL which influence their function. As many of these properties are difficult to measure measuring all of them is not a viable approach to the quality assurance of GDL as part of their industrial production. Within the project QM-GDL Fraunhofer ICT together with the other partners of the project is analysing the relevance of the different properties, comparing the expected impact of deviation from the designed values and the effort, and determining the actual values. The goal is to determine the most relevant parameters which will allow to assure proper functioning of the GDL if their values are controlled keeping the effort for measurements at a reasonable value. In the presentation the approach for the selection of relevant parameters will be explained at a number of examples. Also, a tentative list of parameters will be presented and discussed. The presented work is part of the project QM-GDL which receives financial support by the German Federal Ministry of Digital Infrastructures and Traffic under Grant Agreement 03B11016E. The content of the presentation is in the sole responsibility of the author. X.-Z. Yuan, C. Nayoze-Coynel, N. Shaigan, D. Fisher, N. Zhao, N. Zamel, P. Gazdzicki, M. Ulsh, K. A. Friedrich, F. Girard and U. Groos, Journal of Power Sources, 491 ( 2021).
Electrochemical Framework for Dynamic Tracking of Soil Organic Matter (SOM)

Soil Health parameters serve as excellent surrogate measures towards assessing environmental quality and understanding effects of climate change mitigation via carbon sequestration. Soil health monitoring in the near past has been highly qualitative and speculative with more recent advancements still trying to fill the void of determining a holistic soil profile through phantom based measurements. In fields and crop-circles, testing methods to perform in-situ profiling however from one lab is likely to vary with another and hence results are not universally compatible. Additionally, these normalized techniques ideally involve empirical approaches, extensive sample preparation which adds on to a temporal factor along with equipment for extraction and subsequently-analysis. Even with the upcoming research breakthroughs in non-destructive approaches like spectroscopy and tomography-based models, there is a barrier in-terms of equipment complexity and availability as well as high costs and high logistical overhead. There are a wide number of redox systems present in soil that exist in reduced state under ideal conditions (submerged). While Carbon monitoring would be highly beneficial in the field, an overall sense of the organic matter nutrients present in soil denoted as soil organic matter understanding would offer a wholistic manner of surveying soil and environmental health. In this work, faradaic and non-faradaic measurements are utilized to determine threshold changes in soil electrochemical activity due to presence of various electroactive substances present in the matrix. First, a galvanostatic approach using the chronopotentiometry modality was applied to a soil slurry system- ‘test’ sample to which different levels (w/v %) of the following amendments were added to see how the effective charge modulation can be visualized. Utilizing this experimental framework as preliminary information- A hypothesized mechanism of interaction between the RTIL (Room Temperature Ionic-Liquid) modified electrode and the OM functional moieties based on hydrogen bonding and pi-pi interactions captured using charge-based (chronocoulometry) and interfacial mapping-based (electrochemical impedance spectroscopy) method is utilized to design and test a first-of-a-kind electrochemical soil organic matter (SOM) sensor. Figure 1. Chronopotentiometric characterization of soil organic matter using an RTIL modified electrode. Figure 1
(Invited) Smartphone Diagnostics Meets CRISPR

Smartphone-based optical imaging and sensing devices are among the next-generation biosensors that have shown great potential to transform the field of point-of-care (POC) diagnostics. With the rapid improvement of hardware (e.g., lens, image sensor, and CPU), smartphone has become a transformative microscopy and sensing platform that can support various detection or biomedical measurement applications, especially for resource-limited settings. On the other side, smartphone diagnostics can maximize its potential for early disease detection by coupling with specific molecular assays, such as nucleic acid amplification tests and immunoassays. This talk will highlight our recent effort in creating advanced field-portable biosensor platforms based on smartphones and the integration of smartphone device with CRISPR assay to generate a new functional POC diagnostic platform. An unexpected trans-cleavage behavior of Cas12a against double-stranded DNA substrates is discovered, which greatly eases the design of CRISPR-Dx reporter molecules. Promising applications ranging from POC diagnostics of human diseases to rapid assessment of biomanufacturing products will also be illustrated. Figure 1
Penerapan Metode Sariswara untuk Meningkatkan Hasil Belajar Matematika pada Siswa Kelas III SD

The purpose of this study is to describe the application of the sariswara method to enhance mathematics learning objectives for the third class students at public elementary school 3 Taskombang Klaten. Classroom action research is the term for this kind of study. The study’s subjects were class III pupils at public elementary school 3 Taskombang, consisting of 31 students. This research was used in II cycles, in each cycle two meetings were held. Methods of gathering data use observation, examination, documentation additionally giving questionnaires. The data interpretation technique utilized is both numerical and descriptive descriptive to analyze learning objectives. The outcomes of this research show that using the sariswara technique can get better mathematics learning objectives for class III pupils at SD Negeri 3 Taskombang. This can be seen based on the mean value of students' mathematics learning objectives for cycle I, cycle II and pre-cycle. The increase that occurred was the average pre-cycle score of 48 with a KKM achievement percentage of 9.6%. After applying the sariswara method, the average value for cycle I increased, namely 63.32 with a KKM achievement percentage of 48.38%, while the average value for cycle II was 84.48 with a KKM achievement percentage of 87.09%. This demonstrates a rise between cycle I and cycle II. The implications of education using the sariswara method make students more interested and their enthusiasm for learning increases and improves student learning objectives.
Text security by using a combination of the vigenere cipher and the rubik's cube method of size 4×4×4

Background: In the current era of technology, information security is increasingly important. The growth of technology leads to a higher level of threat to the security of data and information dissemination, and cryptography is a valuable protective tool.Aim: The primary objective of this research is to enhance text security through the fusion of the Vigenere cipher and the Rubik's cube algorithm. By leveraging this novel approach, we aim to fortify the confidentiality of textual data against potential eavesdroppers and adversaries. To demonstrate the practicality of this method, we perform a simulation using the Python programming language within the Google Colab environment. Method: This study employs a qualitative research methodology supplemented by empirical simulation. The combination of the Vigenere Cipher and the Rubik's Cube algorithm in a 4×4×4 configuration is implemented to encrypt and decrypt text. The simulation is executed using the Google Colab platform, enabling a practical illustration of the encryption process.Result: The results of our research indicate the feasibility of generating ciphertext through the amalgamation of the Vigenere Cipher and the Rubik's Cube algorithm in the specified 4×4×4 configuration. The simulation conducted in Google Colab serves as concrete evidence of the effectiveness and practicality of this combined encryption method.Conclusion: In conclusion, this research offers a compelling approach to bolstering text security in the modern era of information technology. By combining the Vigenere Cipher with the Rubik's Cube algorithm in a 4×4×4 configuration, we have demonstrated the potential to significantly enhance the confidentiality of sensitive textual data. The empirical simulation conducted in Google Colab reaffirms the practicality and viability of this innovative encryption technique, highlighting its potential as a valuable tool in the realm of information security.
The Impact of National Financing Initiatives on SMEs: An Applied Study

The relationship between financing programs and national initiatives and small projects has been studied, and it has been shown that there is a strong relationship between them, These programs and initiatives aim to enable the people, especially young people and women, to implement small projects that contribute to providing job opportunities, income, and vocational education, and to provide economic solutions and new ideas that contribute to the growth of the overall economy, as well as handicrafts and crafts. They contribute to enhancing financial freedom and the ability to control family economic decisions and change the income map in the neediest areas. The study emphasizes the importance of providing scientific, technical, and material support to project owners and workers, providing training and simulation opportunities, and transferring expertise. The study also indicates that investment incentives contribute to the stability of small projects and improve their ability to compete, and directly affect the ability of small projects to exist and survive in difficult economic conditions. In addition, the study found that the support provided by comprehensive and integrated support, consulting and training services is essential for the success of small projects, as most of these projects depend on skills that require training, simulation and transfer of expertise. The study also showed the importance of investment incentives in creating a strong impact on the stability of small projects and the surrounding community. Therefore, it can be said that integrated and comprehensive support is a key factor for the success of small projects and the achievement of the desired economic and social goals. Keywords: Funding initiatives – Small and medium enterprises – The Egyptian environment
Enhancing physical abilities in junior wrestlers through virtual reality training: An experimental study

This study aimed to investigate how virtual reality training (VRT) affects the physical skills of young wrestlers. It included 19 wrestlers, aged 15-17, who were part of the Egyptian Wrestling Federation and actively training during the 2022/2023 sports season. The participants were split into two groups: one experimental group with 12 athletes (further divided into two smaller groups of 7 and 5) and a control group with seven athletes. Before starting, measures were taken to ensure that the groups were similar and comparable. The experimental group participated in a VRT program for eight weeks, which consisted of 24 training sessions held three times a week. After the program ended, the researchers conducted tests to measure the outcomes, which were then analyzed statistically. The results showed a noticeable improvement in the physical abilities of the wrestlers in the experimental group, suggesting that the VRT program played a significant role. This research highlights the effectiveness of VRT as a tool for enhancing the physical capabilities of young wrestlers.
Analysis of Review of Literature on Pradhan Mantri Fasal Bima Yojana

Agriculture, being first order economic activity, is highly susceptible to vagaries of climate. With small land holdings and low coping capacity, vulnerability of Indian farmer is high to deviations in monsoons. This vulnerability level becomes a serious concern during drought years. To provide some relief to farmers, States have evolved a few instruments, such as Input Subsidy, Minimum Support Price (MSP), Crop Insurance etc. Input Subsidy provides minimum support to farmers to continue with farming in subsequent post damage season and thus becomes operational only when there is a significant damage due to drought or excessive rainfall. Present study analyzes literature review on Pradhan Mantri Fasal Bima Yojana. This paper aims to provide a selective literature review of articles published in the last decade on Pradhan Mantri Fasal Bima Yojana. The review also found that this research lacked a theoretical underpinning and that more research studies are needed to empirically validate some of the key variables emerging in this area of research. The study concludes with a literature synthesis and recommendations for future research.
Factor Analysis of Increasing Customer Loyalty in The Automotive Industry

This study aims to analyze the factors that influence loyalty in the automotive industry. The population of this study are car owners who live in Jabotabek . Using two types of questionnaires, namely the screening questionnaire and the main questionnaire consisting of 27 indicators. Probability sampling was used in determining the sample so that 135 samples were obtained which were dominated by Toyota and Honda brand users with the MVP segment. Factor analysis was carried out using the SEM (structural equation model) method with Smart PLS software and tested the validity, Cronbach's Alpha reliability test and goodness of fit to test the structural model. The results showed that among the 3 variables, namely brand image, product and staff, only brand image proved to have a positive and significant effect on loyalty (50.1%), while the product and staff variables had no significant effect. With the results of this study, it is hoped that ATPM can maintain the loyalty of their customers by continuing to improve their brand image by paying attention to 7 indicators, namely reliable, advanced, challenging, creative, sophisticated, luxury and sustainable.
Application of Convolution Neural Network Algorithm in English Translation

In order to further strengthen the application effect of deep learning neural network algorithm in English translation and solve the problems of unknown words, transitional translation and missing translation that are common in neural network machine translation technology, this paper proposes an English Chinese machine translation model based on convolution neural network semantic segmentation algorithm on the basis of traditional deep learning machine translation technology. The generalized corpus is used to train the model and predict the translation. At the same time, the unlisted words are translated with the help of dictionaries and translation rules. Model experiments show that based on RNN and transformer models, Bleu values are increased by 4.72% and 4.21% respectively, and the translation accuracy of unlisted words on the latter model is increased by 35.16%, which verifies the application effect of convolution neural network algorithm in Chinese-English machine translation.
Waterwheel Plant Algorithm Optimization Based Resource Allocation in the Cloud Computing

In recent years, the Cloud Computing (CC) is one of the most fast developing distributed computing technologies and the cloud-based applications have extended crucially. The CC environment provides the computing resources according to the need of cloud user’s demand. The CC develops resource allocation system by the distributed computing as well as virtualization to highlights the cloud services scalability. One of the most important problems faced by the cloud customers are choosing the resources for the application deployment without compromising the Quality of Service (QoS) requirements. However, to control the user demand creates critical problems in the on-demand resource allocation framework. To address this problem, this research proposed the Waterwheel Plant Algorithm (WWPA) based resource allocation in the cloud. The virtualization conception supports to implements the task based on the resource accessibility as well as minimizes response time. The WWPA utilizes the hunting strategy to attains the efficient and effective resource allocation. The proposed WWPA method attains better results and it achieves the execution time of 80.5667, energy consumption of 7453.201 and resource utilization of 0.876 respectively when compared to the existing methods like Whale Optimization Algorithm (WOA) and Emperor Penguin Optimization (EPO).
Enhancing Cybersecurity Through Machine Learning-Based Classification of IoT Network Traffic

An exponential increase in smart devices connected to the internet leads to progress in the growth of Internet of Things (IoT) technology that has become integral to part of our daily lives. IoT plays a pivotal role in manufacturing, enabling companies to monitor machine statuses in real-time, assess product quality, and track environmental variables within factories. This not only empowers managers to mitigate risks and minimize losses but also facilitates decision-making from a broader operational perspective. However, the proliferation of IoT also introduces security and safety concerns, making anomaly detection crucial for IoT networks. Detecting anomalies promptly and alerting users is essential to prevent potential damage or losses. In this work, utilizing the Machine Learning and Deep Learning techniques for detecting anomalies in the IoT network and the dataset used to conduct the experimentation on IoT-23 dataset. Finally, identifying the best model for detecting the anomalies in the IoT network by considering the performance of the model and its training time of different models. In the proposed machine and deep learning models, decision tree outperformed with other models in detecting the anomalies with an accuracy of 73% and model time of 7 seconds.