bluuebunny/crossref_metadata_2025 huggingface dataset:
A Data-Driven Snapshot Method for State of Health Modelling and Diagnostics of Maritime Battery Systems
Authors: Vanem Erik , Bruch Maximilian , Liang Qin , Gonzalez David Vicente Reyes , Åsheim Alnes Øystein
Published: October 2022

Battery systems are increasingly being used for powering ocean going ships, and the number of fully electric or hybrid ships relying on battery power for propulsion and manoeuvring is growing. In order to ensure the safety of such electric ships, it is of paramount importance to monitor the available energy that can be stored in the batteries, and classification societies typically require that the state of health of the batteries can be verified by independent tests - annual capacity tests. However, this paper discusses data-driven diagnostics for state of health modelling for maritime battery systems based on operational sensor data collected from the batteries as an alternative approach. There are different strategies for such data-driven diagnostics. Some approaches, referred to as cumulative damage models, require full operational history of the batteries in order to predict state of health, and this may be impractical due to several reason. Thus, snapshot methods that are able to give reliable estimation of state of health based on only snapshots of the data streams are attractive candidates for data-driven diagnostics of battery systems on board ships. In this paper, data-driven snapshot methods are explored and applied to a novel set of degradation data from battery cells cycled in laboratory tests. The paper presents the laboratory tests, the resulting battery data, shows how relevant features can be extracted from snapshots of the data and presents data-driven models for state of health prediction. It is discussed how such methods could be utilized in a data-driven classification regime for maritime battery systems. Results are encouraging, and yields reasonable degradation estimates for 40% of the tested cells. This is greatly improved if data from the actual cell is included in the training data, and indicates that better results can be achieved if more representative training data is available. Nevertheless, improved accuracy is required for such snapshot methods to be recommended for ships in actual operation.
Mixed Initiative Approach for Reliable Tagging of Maintenance Records with Machine Learning
Authors: Iyer Naresh , Virani Nurali , Yang Zhaoyuan , Saxena Abhinav
Published: October 2022

Free-form text-based maintenance and service records related to industrial assets capture the observations and actions of service engineers and are a crucial resource for assessing system-level asset health. To facilitate tracking of historical asset health issues, these records are categorized using tags from a predefined taxonomy, which is mostly a manual and time-consuming process. Given that these records can offer valuable information in troubleshooting maintenance issues, automating this process through deep learning (DL) based natural language processing (NLP) models can offer significant operational and maintenance (O&M) cost reductions. However, these data-based models are not expected to be fully accurate, requiring human experts to regularly review all predictions by DL models to verify or correct them, which is also an highly inefficient and costly process. On the other hand, new records that have novel or ambiguous context can be more appropriately resolved by a human expert. The objective of the work described in this paper is to create an interpretable mechanism that can assess reliability of individual predictions from DL-based maintenance record classifiers and help design a mixed initiative system. This system aims to identify scenarios where predictions are reliable enough for automated decision versus where human intervention is needed due to poor reliability. Additionally, this system aides decision support by providing exemplars from training set that can enhance the human tagger’s productivity and quality. Given a set of tagged records, it also has the capability to identify instances where the originally assigned tags are likely to be inaccurate/noisy. We illustrate these outcomes through tagging of maintenance records from the aviation domain, leading to improvements over only human-based or only DL-based tag assignments.
Wheel Bearing Fault Detection for Automobiles using Wheel Speed Sensor
Authors: Drame Samba , Garner Graeme , Sadjadi Hossein , Du Xinyu
Published: October 2022

Wheel bearing fault diagnosis and monitoring for automobiles are getting more attention as the market shifts towards electric vehicles (EV) and autonomous vehicles (AV). Electric drivetrains are expected to have longer lifespan than the reliable life of low-cost wheel bearing designs. The probability of having a failed wheel bearing in an EV thus increases. In an AV setting, most of the rides are taken by people who are unfamiliar to the vehicle, removing the human as a viable sensor to detect wheel bearing defects. Fleet managers will be required to pay a high price to inspect potential defects. The implementation of a wheel bearing fault detection system can help reduce these costs.

In our previous work, a method for injecting wheel bearing brinelling failure was developed. In this paper, we propose a wheel bearing brinelling fault detection algorithm using wheel speed sensor. The proposed algorithm detects wheel bearing faults by identifying peaks in the wheel speed spectrum at bearing critical frequencies. To implement this approach, we leverage phase domain transform technique to normalize against effect of varying speed. A wavelet filtering technique is employed to enhance the bearing fault signatures prior transforming the wheel speed signal into frequency domain. Post-processing techniques are developed to smooth the high-variance wheel speed spectra and improve the detectability of the wheel bearing faults. A regression model is then developed to calculate the wheel bearing health indicators. The results show that the proposed algorithm achieves high performance in detecting wheel bearing faults.
ML Detection and Isolation of Functional Failures using Syndrome Diagnostics
Authors: Li Yan , Chan Daniel , Zaman Navid , Apostolou Evan , Conroy Paddy
Published: October 2022

Failure identification in complex engineering systems often needs to be in form of multilevel analysis, the first of which involves detection and isolation of functional disruptions across the system down to a discrete item. Considering that there is a functional flow(s) of operation in the machine, the loss or deviation of that functional flow(s) will imply a Functional Failure of the system. Most often, the disruption may propagate from where it may be first found and thus, the root issue can be isolated via the causal relationship between components and their flows. This paper references the idea of Causation-based AI: intelligence that brings together the fast estimations of machine learning and the domain-based physics of failure via qualitative models in the form of Syndrome Diagnostics (SD). There are three main routines in SD. Firstly, the current operating mode of the system is determined. Secondly, functional failure detection techniques are used to detect the existence of an anomaly. Thirdly, a functional failure isolation routine is executed to isolate the failing component, which is composed of two steps: using classification methods to generate a predicted syndrome and matching this generated syndrome with the failure syndrome pattern extracted from the Digital Risk Twin of the system (where the causation aspect is taken advantage of). A series of experiments are conducted and 90% of the failures in validation data have been correctly identified, which verifies the effectiveness of SD in terms of functional failure detection and isolation.
Partially Supervised Classification for Industrial System using Deep Neural Network
Authors: Huang Hao , Shah Tapan
Published: October 2022

A general classification setting requires prior knowledge (i.e. labeled samples) to cover all classes. However, in many industrial problems, prior knowledge usually does not describe all the classes, and the generation of a complete training set that cover all classes often is a time-consuming, expensive and difficult (if not impossible) task. Our target of this work is, given labeled samples from only a subset of classes, how to assign label to any sample that potentially come from either known or unknown classes in real time data. We test our algorithm on industrial failure classification and experiments show that our method outperforms existing popular baselines.
Causal Approach to Integrate Component Health Data into System Reliability Models
Authors: Mandelli Diego , Wang Congjian
Published: October 2022

Two of the challenges of current plant reliability approaches are the ability to integrate plant health data, and to support decision making. Condition based data and diagnostic/prognostic information are in fact not considered into plant reliability models to inform system engineers on the most critical components. Currently, the propagation of quantitative health data from the component to the system level is a challenge given the diverse nature/structure of the data. On the other hand, plant reliability methods (which are typically based on fault-trees or reliability block diagrams) can effectively propagate data from the component to the system level, but values of failure rates or failure probabilities are an approximated integral representation of the past industry-wide operational experience, and it neglects the present component health status (e.g., diagnostic and condition-based data) and health projection (when available from prognostic data). Our first claim is that system reliability models should propagate health information from the component to the system/plant level in order to provide a quantitative snapshot of system/plant health and identify the most critical components. Our second claim is that component health should be informed solely by that specific component current and historical performance data and should not be an approximated integral representation of the past industry-wide operational experience. This paper is directly supporting these two claims by proposing a different approach to perform reliability modeling which relies on available component diagnostic, prognostic and condition-based data to measure component health, and it propagates this information through fault tree models. The propagation of health data from the component to the system level is performed not in terms of probability, but in terms of margins where margin is defined as the “distance” between the present actual status and an undesired event (e.g., failure or unacceptable performance). Through a cause-effect lens, while classical reliability models target the effect associated to a component performance, a margin-based approach focuses on the cause of an undesired component performance (i.e., component health). Hence, thinking of reliability in terms of margins implies decision making based on causal reasoning. We will show how fault tree models can be solved using a margin language and how this process can effectively assist system engineers to identify the most critical components.
A Transfer Learning-Based Rolling Bearing Fault Diagnosis Across Machines
Authors: Peng Dandan , Liu Chenyu , Gryllias Konstantinos
Published: October 2022

Currently, most studies focus on training an excellent deep learning model based on sufficient labeled data collected from machines. However, in real applications, it is costly or impractical to obtain massive labeled data for model training. Therefore, in this paper, a Transfer Learning (TL)-based fault diagnosis method is proposed to transfer the model learnt from one machine (source domain) to another one (target domain). In the training process, labeled source data and unlabeled target data are used, which is very promising for real industrial applications. In this frame of transfer learningbased fault diagnosis, a cyclic spectrum correlation analysis method is firstly introduced to obtain order frequency maps for removing the influence of speed variation and revealing the hidden cyclic frequency of signals. Then, the Dynamic Adversarial Adaptation Network (DAAN) is introduced to transfer label information across machines. The proposed fault diagnosis method across machines is applied on two rolling element bearing datasets collected from two different test rigs. Experimental results demonstrate the effectiveness and superiority of the proposed method compared with stateof-the-art approaches.
Unsupervised Anomaly Detection using Batteries in eVTOL Vehicle Propulsion Test Bed
Authors: Prasad Rao Jubilee , Williams Jesse , Pace John , He Liang
Published: October 2022

There is a growing variety of manned and unmanned aerial vehicles that utilize batteries as their primary power source. These vehicles are composed of a large variety of interacting components and sensors that are needed for safe operation and to carry out their respective missions. As their interactions, complexity, and numbers increase, the risk for anomalies such as degradation of components, sensor faults, and erroneous controls also increase. These anomalies pose significant risks for vehicles flying over densely populated areas or conducting critical missions. It is, therefore, crucial to detect and mitigate these anomalies. There exist several approaches for anomaly detection such as traditional rule or threshold-based methods, model-based approaches, supervised machine learning-based methods, and even unsupervised methods to detect different types of abnormal behaviors. These methods have inherent drawbacks such as lack of sensitivity, inability to detect previously unknown faults, not being robust to compromised innetwork information, or requiring sophisticated system models. To this end, we propose BDAV, a Battery-based Diagnosis for Aerial Vehicles. Assuming a vehicle’s battery is nominal, BDAV utilizes a system’s battery as root of trust to diagnose other vehicle subsystems. Simple machine learning models learn physical dependencies between battery measurements and other vehicle operational variables and an unsupervised algorithm to detect and identify anomalies.
Probabilistic Safety Assessment in Composite Materials using BNN by ABC-SS
Authors: Fernández Juan , Chiachío Juan , Chiachío Manuel , Saleh Ali
Published: October 2022

Carbon fiber reinforced polymer composites present excellent mechanical properties, however, their behaviour under fatigue and the interaction between the different failure modes is not yet well understood. This uncertainty, or lack of knowledge, is the reason why they are still not extensively used in the aerospace industry, where safety is critical. In this paper, Bayesian neural networks trained with approximate Bayesian computation (BNN by ABC-SS) are used to quantify such uncertainty and undertake a probabilistic safety assessment. An experiment is carried out using data from composite fatigue testing, where the proposed algorithm is compared against the state-of-the-art Bayesian neural networks. The results show that, the flexibility of BNN by ABC-SS to quantify the uncertainty significantly contributes towards a reliable safety assessment. Measuring the unknowns with confidence can be crucial when safety is at stake.
Developing Deep Learning Models for System Remaining Useful Life Predictions: Application to Aircraft Engines
Authors: Darrah Timothy , Lovberg Andreas , Frank Jeremy , Biswas Gautam , Quinones-Gruiero Marcos
Published: October 2022

Prognostics and health management (PHM) is an important part of ensuring reliable operations of complex safety- critical systems. System-level remaining useful life (RUL) estimation is a much more complex problem than making estimations at the component level, and system-level RUL methodologies remain sparse in the literature. Model-based approaches have traditionally worked in the past for components such as capacitors, MOSFETs, batteries, or hard-drives (to name a few examples), but developing high fidelity dynamics models of cyber physical systems that can be used to study the effects of multiple degrading components in the system remains a challenging task. Some initial work on model-based System RUL predictions was demonstrated in Khorasgani, et al [1], but, to generalize the system-level prognostics problem, we have to resort to pure data driven and hybrid approaches. In this work, we propose an end-to-end data- driven framework for developing deep learning models to predict remaining useful life of cyber physical systems operating under unknown faulty conditions. The raw data is organized with a data schema that improves the model development process anddown stream data analysis tasks. Due to the unknown faulty conditions, the raw sensor data is transformed into signals that expose the underlying degradation processes, which are then used for model development. Bayesian Optimization is used to tune the model parameters prior to training and validation. We show that this approach results in accurate predictions within 3 cycles to end of life (EOL). We demonstrate the effectiveness of our approach by applying it to the N-CMAPSS turbofan engine dataset recently released by NASA, which includes high fidelity degradation modeling, real world operating conditions, and a large set of fault operating modes.
Pengaruh Metode Praktikum terhadap Hasil Belajar IPA Materi Pertumbuhan dan Perkembangbiakan pada Tumbuhan Siswa Kelas 3 SDN Cikupa III Kabupaten Tangerang
Authors: Muplihah Zahrotul , Magdalena Ina , Huliatunisa Yayah
Published: October 2022

The concept of science in elementary schools is an integrated concept because it has not been separated separately, such as biology, chemistry, and physics. The low quality of education can be seen from the low quality of student learning. One of the causes of the low quality of education is due to the learning difficulties experienced by most students. This study aims to determine the differences in student learning outcomes between students who use practicum methods and students who do not use conventional practicum or learning methods. The population in this study were all class III students at SDN Cikupa III, totaling 57 students, consisting of 27 students in class III A as the control class and class III B with 30 students as the experimental class. The research used is Quasi Experimental Design. The results of the pretest calculation between the control class and the experimental class obtained a tcount value of  0.167 > 0.05, while the post-test calculation between the control class and the experimental class obtained a tcount value of 0.139 > 0.05, which causes H0 to be accepted and HI rejected. The results of this test prove that there is no influence on the learning outcomes of science learning material on growth and reproduction in the third grade students of SDN Cikupa III, Tangerang Regency.
Analisis Kesulitan Belajar Peserta Didik pada Mata Pelajaran Pendidikan Agama Islam di SMA N 1 Pantai Cermin Kabupaten Solok
Authors: Maber Rezha Hermawati , Wiza Rahmi
Published: October 2022

This study aims to find out what types of learning difficulties are experienced by students in this material and what factors cause learning difficulties. This research uses qualitative research method with descriptive research type. The research subjects consisted of student representatives, PAI teachers, Bk teachers, students and parents. Data collection instruments used in the form of observation, interviews and documentation. The results show that the types of learning difficulties faced by students are (1) students have difficulty reading the Qur'an, (2) students are slow in understanding learning and (3) students have difficulty controlling their emotions. While the factors that cause learning difficulties in students are two factors, first internal factors, namely low intelligence and interest in learning, second external factors, namely lack of motivation to learn from the family, less varied learning methods, and technology that makes students lazy to learn. As for how the teacher overcomes the learning difficulties of students by the teacher, namely (1) using varied learning methods, (2) remedial lessons, (3) providing motivation to learn and (4) providing additional assignments.
Dampak Negatif Game Online terhadap Pelaksanaan Ibadah Shalat Remaja di Nagari Alahan Panjang Kecamatan Lembah Gumanti Kabupaten Solok
Authors: Fitri Rahmida , Muliati Indah
Published: October 2022

Online games is a game that is played with the supported of an internet network. Along with the development of increasingly sophisticated technology, this online game will have a bad impact for an individual if he cant’t manage the time while playing the game. At this time, online Indonesian people, including teenagers. Online games at this time have become a necessity that cannot be abandoned by many people starting from children, teenagers and even adults but at this time the most enthusiasts of online game are among teenagers. This study aims to determine the impact of online games on the implementation of prayer worship, to determine the factors that cause the negative impact of online games and to determine the efforts to overcome the impact of online games on the implementation of youth prayers in Nagari Alahan Panjang. This study uses a qualitative method with the type of research that is descriptive. Sources of data were taken from fifteen informants through in-depth interviews who had been selected using the purposive sampling technique, the informants consisted of ten teenagers ranging in age from 12-18 years and five parents of teenagers playing online games. The result of this study indicate that negative impacts. In addition to the positive impact, it turns out that is online game also his negative impact namely: 1) Causing addition, 2) Procrastinating prayers times, neglecting and even leaving the implementation of prayer, 3) Laziness to pray, 4) Waste of time and material, 5) Words that are not polite, 6) Rebbuting parents, 7) Irritability, 8) Can interfere with health. The result of this study can be used as information for researchers in examining this problem in a more in-depth context.
Students’ Perception of Learning English Through Hybrid Learning (Online and Offline)
Authors: Wahyuni Dewi , Arifuddin Arifuddin , Putera Lalu Jaswadi
Published: October 2022

This research aims to: find out students’ perceptions of learning English through hybrid learning (online and offline), find out the difficulties of learning English through hybrid learning, and find out the positive impacts of learning English through hybrid learning according to high school students in Mataram. This research is a survey research that used quantitative descriptive method. 43 students of SMA Negeri 3 Mataram participated in this research. To collect data, questionnaires that consisted of close-ended questionnaire and open-ended questionnaire and interviews were used. The results of the study show that the positive impacts of learning English through hybrid learning are: (1) having a conducive classroom environment when learning English through hybrid learning, and (2) feeling comfortable since they can access the material anytime and anywhere. However, the students opined some difficulties in learning English through hybrid learning that included: (1) having difficulty in understanding the materials due to the unstable internet connection/signal, (2) having difficulty to express the ideas, and (3) having difficulty to participate in a more active, collaborative and communicative class discussion. The students’ perceptions toward the implemention of hybrid learning in learning English split into 3 categories: supportive, not supportive, and neutral perceptions. The total weight of each category in the questionnaires are “strongly agree” 8.7%, “agree” 25.1%, “neutral” 37.5%, “disagree” 20.1%, and “strongly disagree” 8.7%. The group of students that chose “neutral’ answers scores the biggest with 37.5% of the total students, followed by the groups of students that oppose or do not support the implementation of hybrid learning that comprises 33.8% or one third of the total students. The bottom position is seated by the group of students that propose or support the implementation of hybrid learning in learning English with 28.8% or less than one third of the total students. Thus, it can be concluded that the more students have neutral position towards the use of HL in learning English.
Implementasi Model Pembelajaran Cooperative Learning Tipe STAD untuk Meningkatkan Hasil Belajar Siswa dalam Pembelajaran PAI dan Budi Pekerti di SMP Namira Kota Probolinggo
Authors: Hamid Abdul , Pangestu Dimas Adji , Muhammad Devy Habibi
Published: October 2022

Efforts to improve the Learning Outcomes of Class VIII Junior High School Students in Islamic Religious Education Subjects with the STAD Type Cooperative Learning Model at Namira Middle School, Probolinggo City, for the 2022/2023 Academic Year. This research is a classroom action research that aims to improve student learning outcomes of SMP Namira City Probolinggo class VIII-B with the STAD Type Cooperative Learning learning model. The subjects of this study were students of class VIII-B SMP Namira Probolinggo City as many as 20 students. The information collection tool used is in the form of observation sheets and ordinary multiple preference objective tests, based on the results of observations in cycle I and cycle II activities, there is an increase in student learning outcomes. Universally obtained 75% of students in the first cycle and 100% in the second cycle. This increase in learning outcomes took place because each student discussed the division of his group members into expert groups based on the teacher's direction, as well as in the group from which students were eager to present the results of the discussion. Next, it was found that the increase in learning outcomes that appeared in the gain index criteria for each student were 5 incomplete, 12 medium students and 3 high students above 90 in the first cycle, 20 students completed and most of them increased in the second cycle.
Upaya Guru PAI dalam Mengatasi Efek Negatif Media Sosial terhadap Perilaku Peserta Didik di Tingkat Sekolah Menengah Pertama
Authors: Rahim Rahim , Sulaiman Sulaiman
Published: October 2022

This study aims to identify and describe the efforts made by Islamic Religious Education Teachers at the SMP Pembangunan Laboratorium Universitas Negeri Padang (UNP) to overcome the negative effects of social media on the behavior of class VII students. This study uses a qualitative research methodology with a case study approach. Principals, Islamic Religious Education Teachers, Guidance and Counseling Teachers, and students of SMP Pembangunan Laboratorium Universitas Negeri Padang were the subjects of observation and interviews in this study. According to research, social media is generally used by seventh grade students at SMP Pembangunan Laboratorium Universitas Negeri Padang such as WhatsApp, Instagram, TikTok and YouTube. The widespread use of social media has a negative impact on student behavior, including disrespectful language, bullying, forgetting time, and a decreased social sense. With Dhuha prayer activities, one day one verse, and tadarus Al-qur'an, Islamic Religious Education Teachers at the SMP Pembangunan Laboratorium UNP are trying to overcome the negative effects of social media on students.
Pengaruh Penggunaan Media Animasi Berbasis Multimedia terhadap Minat Belajar Siswa pada Mata Pelajaran Pendidikan Agama dan Budi Pekerti
Authors: Miranda Voni , Sulaiman Sulaiman
Published: October 2022

In PAI learning the learning process is still often done conventionally and the learning media used are less varied which results in student interest in PAI learning is still low. The purposes of this study are: 1. To find out how the use of multimedia-based animation media in PAI subjects at SMK Negeri 2 Padang. 2. To find out students' interest in learning by using multimedia-based animation media in PAI learning. 3. To determine the effect of multimedia-based animation media on PAI subjects. This study uses a pre-experimental method with a one-shot case study design. The sample in this study was class XI TKJ 1 and 2 at SMK N 2 Padang. Data was collected through a questionnaire and the analysis used was simple linear regression. From the analysis proves that animation media has an effect on students' interest in learning, as evidenced by the data generated in class XI TKJ 1 on average all students pay attention and focus during learning only a few people do not focus or follow the lesson well. Likewise with class XI TKJ 2 the number of students who did not take part in learning was 4 people. Based on the results of the f test, the results of the f table > f count are 9.543 > 4.00 with a sign value of 0.003 <0.05, which means that the X variable has an influence on the Y variable and H1 is accepted. And the results of the t test are found that the results of t count> t table 3.089> 2.00100, which means that H1 is accepted and H0 is rejected. It is hoped that teachers will be more active in teaching and learning activities and teachers are expected to be able to make other learning media to make it easier for students to understand learning with the help of media including animation media.
Strategi Komunikasi dalam Merekrut Peserta Didik Baru di SMP Islam Al Abidin Surakarta
Authors: Khalik Idhan , Daulay Hamdan
Published: October 2022

This research is motivated by the number of private educational institutions, especially those who are members of the Integrated Islamic School Network or JSIT and these institutions will carry out a communication strategy in introducing schools to the community and compete with each other to increase the number of students through the quality and quality of the school. In the midst of increasingly fierce competition, this will be taken into consideration in how to develop the most effective communication strategy to introduce the school to the wider community. This study aims to find out how the communication strategy used by Al Abidin Islamic Junior High School Surakarta in recruiting new students. The research approach used in this study is a qualitative descriptive research approach. The setting of the research was conducted at Al Abidin Islamic Junior High School. The subjects were the head of SMP Al Abidin and the deputy head of SMP Al Abidin in the field of curriculum. The informants of this research were the PPDB team, school principals and vice principals in the field of education. Methods of data collection using the method of documentation, interviews and observations. The results showed that the Communication Strategy carried out by Al Abidin Islamic Junior High School Surakarta was realized in three stages of strategy, namely strategy formulation, the second was strategy implementation and the final stage of strategy was strategy evaluation.
Analisis Dampak Penggunaan Media Sosial Facebook terhadap Akhlak Ibu-Ibu Rumah Tangga di Kampung Durian Kandang
Authors: Susanti Novella , AlFurqan AlFurqan
Published: October 2022

This study aims to find out what are the forms of facebook social media abuse against housewives, how the impact of facebook social media has on the morals of housewives and find out what efforts can be made to avoid facebook social media abuse in Durian Kandang Jorong Sigunanti Village, Kinali District, West Pasaman Regency. This type of research is qualitative research with a case study approach. The main instrument in this study is the researcher himself. Data collection techniques are carried out by means of observation, interviews and documentation. The steps of analyzing data are data reduction, data presentation and drawing conclusions. The results of this study are 1) the form of facebook social media abuse that occurs in Kampung Durian Kandang, namely the first, facebook social media is used as a place to vent, facebook social media is used as a place to satirize each other, and facebook social media is used as a place to show off riya'(show off), 2) the impact of facebook social media on the morals of housewives in Kampung Durian Kandang is,  morals in speaking impolite words, indulge in personal things or disgrace through facebook social media, both in terms of household and family privacy, as well as neglect in terms of worshipping Allah SWT, namely the obligation in praying five times, 3) efforts that can be made to avoid misuse of facebook social media in Kampung Durian Kandang is to carry out sports activities,  housewives' food and wirid yasin activities are carried out once a week.
Penggunaan Media Seven in One dalam Pembelajaran Matematika Madrasah Ibtidaiyah
Authors: Marvida Tria , Abidin Zainal , Jarmita Nida
Published: October 2022

The problem in this study is the use of media in the process of learning mathematics with flat building materials. Of the many media that can be used, Seven In One is one of the most suitable media used to teach flat material. The purpose of this study was to find out the difference in learning outcomes between students taught and Seven In One media and learning without Seven In One media. The method used in this study is the experiment method using data collection techniques. That is, ask Pre-Test and Post-Test questions. The research was conducted at MIN 46 Aceh Besar school with a research sample of 38 grade IV students. The approach used is a quantitative approach that uses data analysis techniques to test normality, homogeneity, and hypothesis testing. Based on the results of the data analysis can be concluded that there are differences in student learning outcomes that are studied with Media Seven In One.
Urgensi Ekstrakurikuler Pramuka dalam Membentuk Akhlakul Karimah Siswa SMAN 1 VII Koto Sungai Sariak Kabupaten Padang Pariaman
Authors: Nelfadina Silvi , Rahman Rini
Published: October 2022

The purpose of this research is to find out more deeply and also to describe the urgency of Scout extracurriculars in shaping the morality of the students of SMAN 1 VII Koto Sungai Sariak. This research is a qualitative research with descriptive research type. The data of this research were obtained and collected through interview, observation, and documentation techniques. Furthermore, the data were analyzed using techniques data reduction, data display, and conclusion drawing/verificaton. Based on the research that has been done, the moral violations that occured at SMAN 1 VII Koto Sungai Sariak were speaking and being unkind and impolite, making fun of excessively, and lacking respect. In addition, there are students who are not disciplined, and are lazy at school. This is done by student who have not been active in Scout extracurriculars. Scout  extracurricular implementation is very important in this school. This is because through its interesting and fun activities, as well as always conducting coaching related to Scouting’s dasa dharma and evaluating every meeting, this Scout extracurricular is very effective in shaping students morality.
Pengembangan Aplikasi Augmented Reality sebagai Media Pembelajaran Materi Bangun Ruang Sisi Datar Kelas VIII SMP Negeri 13 Mataram
Authors: Sukma Lalu Riki Gita , Prayitno Sudi , Baidowi Baidowi , Amrullah Amrullah
Published: October 2022

This development research aims to develop applications based on augmented reality as a medium of learning material build flat side space and meet the criteria of valid, practical, and effective to use. This type of research is research and development (R&D) by adopting the 4D model, namely define, design, develop, and disseminate. At the stage of development conducted a trial by using one group Pretest-Posttest Design with research subjects as many as 25 students of Class VIII SMP Negeri 13 Mataram were selected using a simple random sampling technique. Data collection is done using test instruments’ validity, practicality, and effectiveness. The data obtained from this study are: (1) validity test based on the assessment of 3 expert validators get an average result of 4.5933 with a very valid Category; (2) practicality test based on the assessment of students get an average percentage of 92.27% of all aspects assessed; (3) the effectiveness test was conducted by analyzing the results of pretest and posttest with paired t-test Test and there was an increase in student learning outcomes, but the results of the N-gain Test obtained a percentage of 48.9429 with less effective categories.  The level of effectiveness obtained by the media is due to some shortcomings of the developed media. Based on these results, it can be concluded that the media developed is very valid and very practical to be used in learning, but still less effective in improving the learning outcomes of learners, so the media needs to be developed further.
Branding Image melalui Penerapan Pendidikan Inklusif dalam Meningkatkan Daya Saing Madrasah
Authors: Fachri Moh. , Rozi Fathor , Tamimullah Tamimullah
Published: October 2022

This study aims to analyze and understand the brand image applied through inclusive education to improve the competitiveness of madrasas. Brand image assistance is carried out to improve the quality of institutions and institutions from a negative image. This research was conducted through a case study-type approach. This research was conducted at the MI Nurul Yaqin Kertosono Gading Probolinggo institution. Results Based on the study shows that; First, the institution has implemented a brand image through the implementation of inclusive education in increasing the competitiveness of madrasas. Second, the performance of an inclusive branding image is carried out in several stages, including; Branding Analysis, Establishing Partnerships, Implementation of Inclusive Education, and Evaluation. The implications obtained from institutions with brand image through the implementation of inclusive education are; The institution has a new idea in the quality and quality assurance of the institution, the revolutionary madrasa is dignified and embraces all circles so that it is of high quality and ready to compete.
Analisis Kesulitan Membaca Permulaan pada Peserta Didik Kelas II Sekolah Dasar Negeri 30 Pontianak Selatan
Authors: Tarigas Melin , Kartono Kartono , Suparjan Suparjan , Kresnadi Hery , Salimi Asmayani
Published: October 2022

This study aims to describe the types of early reading difficulties, the causes of early reading difficulties, and explain how teachers overcome early reading difficulties in second grade students. This research use desciptive qualitative approach. The data analysis technique used is the Creswell model which includes four stages, namely preparing data, coding, using code to build descriptions and themes, and showing how these descriptions and themes will be written in a qualitative narrative or report. The results of this study indicate that the types of early reading difficulties in students are not able to recognize and pronounce the letters of the alphabet, difficulty distinguishing the same letters, difficulty reading one consonant letter and one vowel letter, difficulty reading open syllables, difficulty reading syllables into words, and reading is still stuttering. The causes of early reading difficulties are interest factors, motivational factors, parental factors, and teacher factors. The teacher's way of overcoming the difficulty of early reading is by training and familiarizing students to read in their spare time or at school hours in approximately 10 minutes.
Evaluation of Biochemical Parameters among Diabetes Patients and Healthy Participants in a Nigerian Tertiary Hospital
Authors: N Yashim , Y. Obazee D. , P Ogbe O. , F. Ajobiewe H. , O. Ajobiewe J. , Y. Dah T. , A. Oyetunde B. , T. Vamparious M. , A. Dangana , F. Ogunkoya O.
Published: October 2022

Background: Diabetes mellitus (DM) burden is one of the key concerns in developing countries like Nigeria. This study aimed to evaluate the biochemical parameters among diabetes patients and healthy persons in Abuja, Nigeria. Methodology: The study was a cross-sectional prospective study that included 60 DM patients (case) and 48 healthy individuals (control) aged 19 to 80 years from April 1 and June 30, 2018. Five ml of venous fasting blood samples were obtained under aseptic precautions and biochemical parameters were evaluated: fasting blood glucose (FBS) and liver enzymes were determined using Bio systems; A 25 fully automated biochemistry analyzer while hemoglobin A lc (HbAlc) was estimated by High-performance liquid chromatography (HPLC) method. Data analysis was performed using IBM SPSS version 25 and a value of P <0.05 was taken as statistically significant. Results: Mean FBS, HBA1c, AST, ALT, and LDH were significantly higher in DM than control (P<0.05). Mean values of FBS and HBA1c in DM were 9.00mg/d1 and 5.99% respectively while liver enzymes; ALT and AST and ALP were 25.77U/L, 28.87U/L, and 214.35U/L respectively. The mean values of cardiac enzymes; LDH and CK-MB normal were 438.87U/L and 75.47U/L respectively. The mean values of HBAlc, AST, ALT, ALP, LDH and CK-MB were higher than normal range in 48.3%, 16.0%, 15.0%, 23.3%, 26.6%, and 36.6% DM respectively. Conclusion: Thus these liver enzymes can be used as a biomarker for the assessment of diabetes. With a thorough study about the level of liver enzymes, it is possible to monitor complications of diabetes.
Os grandes debates dos anos 1920: notas sobre o feminino, em psicanálise
Authors: Rosa Camila Terra da , Weinmann Amadeu de Oliveira
Published: October 2022

Este trabalho tem como foco a emergência de uma geração de psicanalistas mulhe-res, nos anos 1920, cuja autoria foi reconhecida e que encontrou um lugar na his-tória do movimento psicanalítico. A partir de um breve contraste com a geração de psicanalistas mulheres dos anos 1910, o artigo interroga: o que tornou possível às analistas dos anos 1920 ocuparem um novo lugar? Nesse sentido, realçamos dois processos: o avanço das lutas feministas, encarnadas no movimento sufragista, e a abertura de um tempo em que as controvérsias, no movimento psicanalítico, não implicam, necessariamente, rupturas. A partir do Congresso de Berlim, em 1922, três temas dominaram os debates: a formalização da prática clínica, a análise de crianças e a sexualidade feminina. Nossa hipótese é de que o problema do feminino perpassa esses três temas como efeito de uma marca instaurada pela geração de 1910, que a de 1920 ativa, retrospectivamente.
Monitoramento da temperatura de distribuição de preparações quentes e frias em restaurante na cidade de Tangará da Serra- MT
Authors: Ferreira Érika Luana , De Brito Sodré Lainy Waleska , Decol Celina Martins , Oliveira Aline Pedrosa de , Covre Lara
Published: October 2022

Os serviços de alimentação envolvem toda uma cadeia de produção e distribuição de alimentos, sendo que no Brasil, a cada cinco refeições, uma seja é feita fora do domicílio e os locais mais procurados são os restaurantes. Com base nisso, esse estudo objetivou monitorar as temperaturas de preparações quentes e frias em balcões de exposição em um restaurante comercial na cidade de Tangará da Serra – MT. Os monitoramentos ocorreram durante quatro semanas em dois dias alternados na mesma semana, com realizaçãom de quatro monitoramentos por dia para todos os alimentos selecionados. As preparações quentes monitoradas foram arroz branco, feijão carioca e arroz integral e as preparações frias foram tomate fatiado, pepino em conserva, maionese e salpicão. Utilizou-se para a aferição das temperaturas um termômetro digital do tipo espeto com variação de temperatura de -50ºC a +300ºC sendo este inserido no centro geométrico de cada cuba de alimento, com correta higienização entre as aferições. Os resultados obtidos durante os monitoramentos foram confrontados com as resoluções vigentes da Agência Nacional de Vigilância Sanitária para alimentos quentes e frios. Os resultados encontrados para as preparações quentes tiveram um grau de adequação de 60,6% apresentando falhas com possibilidade de correção. Para as preparações frias, as inadequações nas temperaturas de exposição foram encontradas em 100% dos monitoramentos, sendo necessária adequação imediata no equipamento utilizado para a manutenção da temperatura dos alimentos durante a sua exposição, bem como a diminuição da mesma no momento anterior a exposição, em que as cubas contendo os alimentos após sua montagem, ficam em temperatura ambiente, sem qualquer refrigeração.
Profile of nasal and oropharyngeal colonization by Staphylococcus aureus in pharmacy students
Authors: Vicenti Camila Medeiros , Tomazeli Emilia Chuina , Muraoka Júlia Yumi , Donofrio Fabiana Cristina , Bonacorsi Cibele
Published: October 2022

É comum indivíduos saudáveis serem colonizados pelo Staphylococcus aureus, sendo o mesmo encontrado em diversas áreas do corpo, com maior frequência na cavidade nasal. Apesar de ser membro de microbiota, esse micro-organismo pode estar relacionado com uma variedade de doenças infecciosas. Em décadas anteriores as infecções por S. aureus eram tratadas com facilidade através do uso da penicilina e moléculas semissintéticas de β-lactâmicos, como a meticilina e seu análogo oxacilina. Entretanto, dentro de um curto período, à resistência à meticilina, foi detectada em cepas de S. aureus (MRSA – metthicillin-resistante Staphylococcus aureus), passando de um organismo presente predominantemente em hospitais para uma causa comum de infecções também dentro da comunidade. Considerando a importância das infecções nosocomiais e na comunidade, o presente trabalho teve como objetivo a avaliação do perfil de colonização nasal e oral pelo S. aureus, bem como a determinação da resistência à meticilina/oxacilina, entre os estudantes do curso de Farmácia. Também foi avaliado o perfil geral de contaminação dos aparelhos celulares (tipo smartphones), verificando a presença de S. aureus. Amostras da cavidade nasal, orofaringe e da superfície (tela frontal) do aparelho celular dos acadêmicos, foram coletadas utilizando-se swabs estéreis e semeadas em Agar Sal Manitol e Agar Mueller Hinton. A avaliação do perfil de sensibilidade das cepas de S. aureus isoladas dos estudantes foi realizada por técnica de difusão em agar. Dos 50 voluntários empregados na pesquisa, 29 (58%) apresentaram amostras positivas para o S. aureus na cavidade nasal e/ou oral. Sendo que, 14 voluntários (28%) possuíam o S. aureus somente na cavidade nasal, 5 (10%) somente na cavidade oral e 10 voluntários (20%) apresentaram a bactéria em ambos os locais (cavidade nasal e orofaringe). Dos portadores da bactéria, um voluntário (3,4%) apresentou cepa MRSA. Na contagem de micro-organismos mesófilos aeróbios totais (nos aparelhos celulares), 100% das amostras obtiveram crescimento, sendo que 80% apresentaram contagens menores ou iguais a 5 UFC/cm2 da superfície frontal do smartphone. Na pesquisa de bactérias específicas, 9 (18%) celulares revelaram a presença de S. aureus. Através dos resultados foi possível observar que a maioria dos estudantes apresentam S. aureus colonizando a cavidade nasal e/ou oral, entretanto, não sendo verificada uma alta porcentagem de cepas resistentes a oxacilina/meticilina. Todos os acadêmicos apresentaram aparelhos com algum nível de contaminação microbiológica, sendo detectado o S. aureus apenas nos aparelhos dos estudantes que eram portadores nasais e/ou orais dessa bactéria.
A Study on Identifying and Categorising Students based on Personal Learning Traits for Adaptive Learning Systems
Authors: M Aryaman , T. Anoop Sai , N Dr. Sandhya
Published: October 2022

Sending messages automatically without the involvement of human input is known as Message Automation or Text Automation. This study aims to identify and Categorise students based on Personal Learning Traits for Adaptive Learning Systems.Despite the growing academic research in the field of adaptive learning, its various applications and implementations, the field lacks a comprehensive literary analysis that categorises users of adaptive learning apparatuses depending on independent understanding abilities in these settings. This study provides an overview of various student personality attributes and methods for grouping them together to provide better and improve adaptive learning environments and systems to cater to a larger user base.