Reviewerly/exHarmony huggingface dataset:
Design and Build of a Multifunctional Portable Fertilizer

Pangestu Farmer Group is a farming group in Pandanrejo Village, Batu Regency, that has high-quality sweet corn as a strategic asset with often fluctuating yields. Consequently, the market demand cannot be met. The main problem of fluctuations in corn yields is due to improper fertilization methods. Applying liquid fertilizer during the rainy season can result in nutrients being washed away by rainwater, but when granular fertilization is used, this results in increased costs and labour. A solution is needed to solve this problem so that the fertilization process is correct, and the timing of fertilization and labour costs can be reduced. Therefore, a portable fertilizing technology based on spring valves is needed. The goal is to develop and manufacture a valve spring-based portable fertilizer that can increase the effectiveness and efficiency of the fertilization process. The comparison of type 1 and type 2 fertilizers lies in the raw material used. Commercially available hand sprayer for comparison in design. Ergonomic analyses are also considered in the design of the fertilizer, both in terms of user safety and comfort. The method in this study is to design tools with power and ergonomic calculations, manufacture tools at Sahabat Teknik Workshop, and conduct tests at Brawijaya University's Agricultural Power and Machinery Laboratory. The test results for portable fertilizer types 1 and 2 show great advantages, namely, increase in working capacity 20 times to 1.2 ha/hour, reduce the number of workers from 7 people/ha to 5 people/ha, reduce operating time, reduce labour costs and increase farmers' income by up to 57, 72%/year.
Diagnosis of the competitiveness in the technological skills of high schools of macuspana, tabasco, for the generation of a proposal for improvement

Competitiveness is considered an important aspect that is determined in an individual, community or country. This refers to the ability to remain and adapt to local, national and international markets. In the case of the education system, the competences of those involved in the teaching-learning process (teachers, students, administrators, etc.) are taken into account to define and evaluate their performance. For education it is of major importance to be competitive in order to improve human development, so it is an essential factor that requires the planning of strategies that exceed expectations and allow to develop inclusion in all areas. In order to be competitive, it is necessary to constantly update and acquire skills in order to carry out any diligence in an appropriate manner, considering the emerging needs of today’s globalized society, given that this entails an evolution in technological innovations and thus a change in all social systems, including education. Therefore, this article seeks to reflect on the competitiveness of technological skills as part of the education sector where the necessary skills are required in any social, economic, political or technological field, which affects the quality of the academic community, for which the context in terms of technological competitiveness and education is briefly presented and subsequently the link between technological skills and study techniques is indicated, as is currently assumed. This diagnosis is part of a research project focused on determining the competitiveness of technological skills of high schools in Macuspana, Tabasco, Mexico.
Customer Preference Mining of Electric Vehicles for Design Decision-making Using Big Sales Data

Progressive Cavity Pump (PCP), also known as the Moineau pump, is an artificial lift method often used for pumping high viscosity and high solid content fluids from producing wells.It transfers slurry by means of progress, through a pump, of a sequence of small, fixed shape, discrete cavities, as its rotor is turned.Although PCP has been effectively adopted in the oil industry for decades, there is a lack of understanding of the effect of design parameters and operating conditions on the pump performance for a high viscosity paste.In this paper, the objectives of our study are to develop a PCP-based extruder model for paste extrusion additive manufacturing, predict an actual multi-lobe PCP performance and investigate the pump performance by simulating single-phase ceramic paste flow through it.The work primarily focuses on two aspects.In the initial stage, the ceramic paste of different industrial materials such as earthenware is simulated with given boundary conditions in PCP, and the results of ceramic paste simulation in PCP are then compared with the extrusion process.Output parameters such as exit velocity and pressure of the paste in the PCP clearly show that the flow of paste inside the PCP gives better results than compared to the extrusion process of the same material in the paste form.
The Impact of Human Capital on Organizational Performance through the Mediating Role of Social Capital: A Field Study at the Mobile Phone Companies in Yemen

The study aimed at identifying the impact of social capital on organizational performance, in mobile phone companies in Yemen. A descriptive analytical method was adopted, and a questionnaire was designed for data collection. The study sample consisted of 327 male and female employees from all administrative selected levels. A number of inferential statistical methods were followed using the SPSS. The study mainly revealed a significant impact of human capital on organizational performance through social capital.
Retracted: Karst Collapse Monitoring and Early Warning Evaluation Method Based on Multisensor Internet of Things

[This retracts the article DOI: 10.1155/2022/2099268.].
Retracted: Application of Ontology Matching Algorithm Based on Linguistic Features in English Pronunciation Quality Evaluation

[This retracts the article DOI: 10.1155/2022/2734672.].
Retracted: Analysis of the Influence of Innovative Teaching Management Mode in Universities on Students’ One-to-One Training and Psychotherapy

[This retracts the article DOI: 10.1155/2022/8505257.].
Retracted: Sliding Mode Control of Flexible Articulated Manipulator Based on Robust Observer

[This retracts the article DOI: 10.1155/2022/2440770.].
Retracted: Research on Microseismic Source Location Method Based on Waveform Characteristics Monitored by Nanomaterial Sensor under the Background of Metal Oxide Polluted Environment

[This retracts the article DOI: 10.1155/2022/5479007.].
Penerapan Kriptografi Vigenere Cipher Pada Kekuatan Kata Sandi

One of the methods of securing information systems that is commonly known by many people is passwords. Without realizing it, passwords have an important role in securing information that is confidential. In some applications related to software, such as cellphones, ATM cards, and others. There is also a security system that functions similarly to a password. commonly known as a PIN Code. Although it only consists of numbers, its use is the same as a password, which is to secure information. The stored information is usually digital or database-based. Password security aims to secure a password stored in the database, the password needs to be secured because if the password is known by unauthorized parties or who are not entitled then important and other data will be stolen. The password that is secured is a password that is used daily, be it email passwords, social media, databases, operating systems on the device and others into the database. vigenere cipher algorithm to encode the password in a database. The result of this test is that password security is carried out based on the vigenere cipher method using a visual studio application and utilizing a Database with a MySQL application. The end result used is the result of the security process with the result key having no resemblance to the original record. Formation of keys based on user decisions. It is worth paying attention that the key should not be forgotten.
The Benefits of Gamification on User Experience: A Systematic Literature Review

influence the success of a product, and gamification is one purposed method which is expected to improve the user experience. But actually, whether gamification can provide benefits to increase user experience has not explicitly been explained before. This study purpose identifies the benefits implementation gamification for improving the user experience. To achieve the objectives, this study conducts the systematic literature review that summarized all the studies required in Gamification and User experience context. This study has discovered 539 papers and do three steps to select primary studies through kitchenham method with the results of the first stage is 314 research papers. Then, for the 2nd stage find 50 papers, and finally, the 3rd stage finds 16 best papers. During a systematic literature review, the study is a variety approach depends on two clustered such as intangible and tangible benefits. This study identified gamification have positive intangible and tangible benefits for improving the user experience.&#x0D;
Rancang Bangun Sistem Keamanan Lalu Lintas Menggunakan Smartphone Dan Esp32cam Berbasis Arduino Mega 2560

Lots of vehicle users who ignore this traffic light. Even though there are a lot of risks that are faced if you ignore traffic lights, for example accidents due to directly passing a red light while at another intersection there are vehicles that are speeding, congestion is getting worse due to the difficulty of vehicles from the opposite direction to move forward, and so on. At this time, penalties for traffic violators are still using civil and criminal penalties. The motorist community is currently still arbitrarily with civil and criminal penalties given if they violate traffic rules, one of which is if they pass a red light. Motorists who violate are given a penalty of paying a fine on the spot or given a ticket for further processing in court. However, this does not provide a deterrent effect for motorists, so they often violate the same thing. This tool consists of several main components, namely Android Smartphone, ESP32CAM, Infrared Sensor, RTC, LDR Sensor, 16x2 LCD, RGB LED, Buzzer, DFPlayer Mini, Speaker, Water Pump, Lamp, Arduino Mega 2560 and this tool is programmed using Arduino app.
PENDAMPINGAN LITERASI DAN NUMERASI PADA MASA PANDEMI COVID 19 DI KABUPATEN MADIUN

During the covid 19 pandemic, PGRI Madiun University has carried out community service programs through assistance in handling Covid-19 and online and offline Literacy &amp; Numeracy assistance in Jiwan and Pilangkenceng sub-districts, Madiun district. The service's flagship work programs are Reading Corner, Introduction to E-learning, Classroom learning assistance, Home visits, Making learning videos, Education on health protocols, Making hand sanitizers using local materials, and Making simple Faceshields.&#x0D; The results of the activities show the success of abdimas. The Home visit work program has been well received by the parents of the students. The home visit program is carried out to assist students and parents independently at home so that they can overcome the learning crisis of students. The reading corner fosters student interest in reading, namely: as a facilitator for reading, as the closest reading material, comfortable, and attracts attention. The introduction of e-learning (google meet, zoom meeting, making digital presences, making questions via google forms and so on) has not been fully accepted quickly by students and teachers because of device constraints that do not support, many senior teachers are lacking in technology adaptation. Assistance in this class is guided by the tutor teacher. The civil servant teacher provides positive inputs to students and is assisted in overcoming all conditions encountered in the field. Making Learning Videos makes it easier for teachers and providing a teaching database made by students with the guidance of the tutor teacher to be uploaded on YouTube so that it can be accessed easily by students. Education on the application of health protocols carried out by socializing and providing posters related to health protocols, hand washing procedures and so on has increased student and community awareness in taking care of themselves, their families and the environment during the pandemic. The manufacture of hand sanitizers from local materials focuses on education, socialization, and providing trainings to provide antiseptics independently by using the main ingredients that are around them and additional materials that are abundantly available. The manufacture of a simple faceshield is carried out for the provision or manufacture of a faceshield as a repair tool from used 1.5-2L drinking bottles which are clear in color so that it is easier and cheaper.
Scheduling Compact Error Correcting Codes in Entanglement Distribution Networks

A fundamental challenge in generating and distributing high-fidelity entanglement in quantum repeater networks is the management and suppression of quantum errors. In this work, we develop an approach for extending the effective coherence time of shared entanglement between nodes by utilizing compact quantum error correcting (QEC) codes, which are scheduled and run locally on resource-constrained repeaters, to maximize the fidelity of the shared state, while also accounting for the incurred gate noise from QEC circuit operations. This local QEC approach stabilizes the distributed state via local operations, so independent execution on the nodes requires no additional synchronization or protocol overhead. Simulation results show significant improvements in the effective coherence time relative to idle decay, suggesting this approach could be useful in several quantum networking protocols such as entanglement generation, swapping, purification, and teleportation.
Pedagogical dimension of the evaluative culture of learning and student satisfaction

The objective of this research was to determine the relationship between the perception of the pedagogical dimension of the evaluative culture of learning and student satisfaction in virtual courses. A quantitative approach was used and the research design was non-experimental with a cross-sectional cut, since data collection was carried out at a single point in time. The study was conducted with a population of 188 students from a private university in Lima. The results obtained showed that there is a direct correlation between students' perception of the evaluation culture and the satisfaction they express regarding their evaluation. This perception is determined by different aspects, among which the pedagogical dimension is included.
Quantum Learning Transfer Model for the classification of people with safety helmets

The problem of personal accidents in a work environment in many cases is due to the lack of use of helmets, among other safety elements. The objective of this work was to classify images of people who use or not use safety helmets, in the classes identified as correct use of the helmet, incorrect use and without a safety helmet, with a Quantum Transfer Learning model. For this, the method used has allowed the collection of a data set of 750 images of people in different work activities. The classical learning transfer model chosen was ResNet-18; the variational layers of the proposed model were built with the Basic Entangler Layers template for four qubits with the Pennylane quantum simulator. The results were 95.47% accurate in classifying the correct Safety Helmets. The conclusion reached is that the proposed model is a good option to detect and classify people with the use of safety helmets in a work environment.
Link prediction on bipartite networks using matrix factorization with negative sample selection

We propose a new method for bipartite link prediction using matrix factorization with negative sample selection. Bipartite link prediction is a problem that aims to predict the missing links or relations in a bipartite network. One of the most popular solutions to the problem is via matrix factorization (MF), which performs well but requires reliable information on both absent and present network links as training samples. This, however, is sometimes unavailable since there is no ground truth for absent links. To solve the problem, we propose a technique called negative sample selection, which selects reliable negative training samples using formal concept analysis (FCA) of a given bipartite network in advance of the preceding MF process. We conduct experiments on two hypothetical application scenarios to prove that our joint method outperforms the raw MF-based link prediction method as well as all other previously-proposed unsupervised link prediction methods.
Deep learning algorithms to forecast the magnitude of earthquakes in Peru

The research proposes the application of the algorithm. LSTM with the aim of forecasting the magnitude of earthquakes in Peru adding pink noise in its dynamics to replicate and capture the complex dynamics of magnitude, confirms a anti persistence in the increments by means of the coefficient of hurst. less than 0.5 and stable. Then a model is implemented of higher precision LSTM network in the generation of forecasts than the one-way multilayer perceptron network. By Therefore, evidence of better network performance is presented LSTM in relation to the magnitude variables of the earthquake due to the pink noise thatoccurs in its dynamics.The study period consists from January 1, 2020 to October 23, 2021.
Staff Turnover and Job Performance of Janitors and Cleaning Workers: A correlational study in SMEs

Workers are a fundamental part in the development and growth of organizations since their operation and productivity depend on them. Therefore, one of the factors to consider is the job performance and staff turnover of a company for better growth. The objective of the research was to determine the relationship between staff turnover and job performance of janitors and cleaning workers in a SME (Small and Medium-Sized Enterprise). The methodology had a quantitative approach, with a nonexperimental design, cross-sectional and correlational level. The sample consisted of 120 workers, including janitors and cleaning workers; to whom a survey was applied to collect information. The results obtained showed a value p<0.05; therefore, the null hypothesis is rejected; in addition, a moderate positive correlation (r = 0.359) was determined between staff turnover and job performance; likewise, a moderate positive correlation (r = 0.380) between voluntary turnover and job performance; finally, a moderate positive correlation (r = 0.352) between involuntary turnover and job performance. It was concluded that there is a relationship between staff turnover and job performance of janitors and cleaning workers in the SME company.
Machine Learning for Sentiment Analysis Utilizing Social Media

Sentimental analysis is a crucial step in natural language processing that aids in figuring out whether a text has a positive, negative, or neutral sentiment. In this experiment, we analyzed the sentiments expressed in tweets that included text, emojis, and emoticons. To categorize the tweets into different sentiments, we utilized four different algorithms: Multinomial Naive Bayes (MNB),Random Forest, Support Vector Machine (SVM) and Decision Tree. In order to increase the model's accuracy, we also combined the predictions from the four algorithms using the Voting Classifier, an ensemble learning technique. To preprocess the data, we used various techniques, such as removing stop words, stemming, and converting emojis and emoticons to their corresponding text representations. The performance of each algorithm was then trained on the preprocessed data using various assessment measures, including accuracy, precision, F1-score and recall. The SVM method fared better than the other algorithms, obtaining an accuracy of 96.27%, according to the data. Furthermore, we applied ensemble learning techniques, such as bagging to improve the performance of all the four algorithms. We also used the Voting Classifier to combine the predictions of the bagging models to further improve the accuracy of the model. The results revealed that the accuracy was increased to 97.21% by combining the bagging and voting classifiers. Overall, the project demonstrates the effectiveness of various algorithms and ensemble learning methods in performing sentimental analysis on tweets containing text, emojis, and emoticons.
A Multi-Stage Partial Homomorphic Encryption Scheme for Secure Data Processing in Cloud Computing

Cloud computing has emerged as a prominent paradigm for the efficient storage and processing of large volumes of data. However, the security of sensitive information remains a primary concern for both users and service providers in cloud environments. Homomorphic encryption has proven to be a viable solution to secure data processing in cloud computing while maintaining the confidentiality of the data. In this research article, we propose a novel homomorphic encryption scheme based on multistage partial homomorphic encryption, specifically designed for secure and efficient computations in cloud computing environments. The proposed scheme combines the strengths of partial homomorphic encryption and multistage encryption techniques to enable secure and privacy-preserving data processing in the cloud.
Hand Gesture Recognition based on Convolution Neural Network (CNN) and Support Vector Machine (SVM)

Gestural communication is a type of nonverbal communication in which visible body gestures are utilised to communicate vital messages, either in place of speech or in conjunction with it. The problem of gesture division is presented as a first step toward visual hand gesture recognition, i.e., the detection, analysis, and recognition of gestures through real-time hand sequences. Visual hand recognition and motion tracking are quite challenging to solve due to their inconvenient nature. This research seeks to address the issue by determining which classification technique, Convolutional Neural Network (CNN) or Support Vector Machine (SVM), is superior in recognising hand motions. The hand-skeletal was used as the features to represent the hand gestures. Both classification methods utilised the same sample dataset and camera input to achieve a fair comparison. Then, the performance in terms of accuracy and processing time being analysed. The results indicate that the CNN excels in recognising hand gestures with an accuracy of 97.78% compared to the SVM with 96.30%. In terms of processing time to train/process the datasets, SVM has the upper hand by taking 5 minutes and 16 seconds. Meanwhile the CNN used 8 minutes and 24 seconds.
Cinematic Design and Force Analysis of a SCARA Robot with Pneumatic Actuators

The use of pneumatics applied to industry is greatly favored by its great availability and for being a non-polluting fluid, thus having a potential to replace other systems in the industry. In the field of industrial robotics, a robotic arm with pneumatic servomotors is rarely designed, as there are few studies about it. This technology being a closed loop repetitive control system with feedback makes feasible its implementation for processes in the industry. Since there are few pneumatic industrial robots, this study seeks to design a prototype with an analysis for the precise control of the positions and reduce the nonlinear randomness of the pneumatic system, through the resolution of the kinematics, which will provide necessary information on the mechanical adjustments in the pneumatic servomotors for a required application as well as the interpretation of transmission simulations. This study provides a manufacturing model of a fully pneumatic and functional robotic prototype, opening the field for future research on pneumatic control applied to industrial robotics.