bluuebunny/crossref_metadata_2025 huggingface dataset:
Predicting Office Workers’ Productivity: A Machine Learning Approach Integrating Physiological, Behavioral, and Psychological Indicators
Authors: Awada Mohamad , Becerik-Gerber Burcin , Lucas Gale , Roll Shawn C.
Published: October 2023

This research pioneers the application of a machine learning framework to predict the perceived productivity of office workers using physiological, behavioral, and psychological features. Two approaches were compared: the baseline model, predicting productivity based on physiological and behavioral characteristics, and the extended model, incorporating predictions of psychological states such as stress, eustress, distress, and mood. Various machine learning models were utilized and compared to assess their predictive accuracy for psychological states and productivity, with XGBoost emerging as the top performer. The extended model outperformed the baseline model, achieving an R2 of 0.60 and a lower MAE of 10.52, compared to the baseline model’s R2 of 0.48 and MAE of 16.62. The extended model’s feature importance analysis revealed valuable insights into the key predictors of productivity, shedding light on the role of psychological states in the prediction process. Notably, mood and eustress emerged as significant predictors of productivity. Physiological and behavioral features, including skin temperature, electrodermal activity, facial movements, and wrist acceleration, were also identified. Lastly, a comparative analysis revealed that wearable devices (Empatica E4 and H10 Polar) outperformed workstation addons (Kinect camera and computer-usage monitoring application) in predicting productivity, emphasizing the potential utility of wearable devices as an independent tool for assessment of productivity. Implementing the model within smart workstations allows for adaptable environments that boost productivity and overall well-being among office workers.
A Novel Angle Segmentation Method for Magnetic Encoders Based on Filtering Window Adaptive Adjustment Using Improved Particle Swarm Optimization
Authors: Wang Lei , Wei Xin , Liang Pengbo , Zhang Yongde , Hao Shuanghui
Published: October 2023

In this paper we outline newly-developed control algorithms, designed to achieve high-precision feedback for a motor control system using a magnetic encoder. The magnetic encoder, combing single-pole and multi-pole magnetic steels, was adopted to extend the resolution of the magnetic encoder. First, with a view to settling the issue of the jump points of the multi-pole angle value at the convergence of two adjacent magnetic poles, the angle segmentation method, which uses the window filter discrimination method, is employed to determine the actual angle value. The appropriate filter window width is selected via the improved particle swarm optimization (IPSO) algorithm, and an expanded resolution is achieved. Second, a compensation table is completed via a linear compensation algorithm based on virtual cutting to enhance the accuracy of the combined magnetic encoder. On this basis, a linear difference algorithm is used to achieve deviation correction of the angle. Finally, the jump points can be restrained effectively via the angle segmentation method. The resolution reaches 0.05°, and the accuracy is 0.045°.
Age and Gender Impact on Heart Rate Variability towards Noninvasive Glucose Measurement
Authors: Stojmenski Aleksandar , Gusev Marjan , Chorbev Ivan , Tudjarski Stojancho , Poposka Lidija , Vavlukis Marija
Published: October 2023

Heart rate variability (HRV) parameters can reveal the performance of the autonomic nervous system and possibly estimate the type of its malfunction, such as that of detecting the blood glucose level. Therefore, we aim to find the impact of other factors on the proper calculation of HRV. In this paper, we research the relation between HRV and the age and gender of the patient to adjust the threshold correspondingly to the noninvasive glucose estimator that we are developing and improve its performance. While most of the literature research so far addresses healthy patients and only short- or long-term HRV, we apply a more holistic approach by including both healthy patients and patients with arrhythmia and different lengths of HRV measurements (short, middle, and long). The methods necessary to determine the correlation are (i) point biserial correlation, (ii) Pearson correlation, and (iii) Spearman rank correlation. We developed a mathematical model of a linear or monotonic dependence function and a machine learning and deep learning model, building a classification detector and level estimator. We used electrocardiogram (ECG) data from 4 different datasets consisting of 284 subjects. Age and gender influence HRV with a moderate correlation value of 0.58. This work elucidates the intricate interplay between individual input and output parameters compared with previous efforts, where correlations were found between HRV and blood glucose levels using deep learning techniques. It can successfully detect the influence of each input.
On-Device Execution of Deep Learning Models on HoloLens2 for Real-Time Augmented Reality Medical Applications
Authors: Zaccardi Silvia , Frantz Taylor , Beckwée David , Swinnen Eva , Jansen Bart
Published: October 2023

The integration of Deep Learning (DL) models with the HoloLens2 Augmented Reality (AR) headset has enormous potential for real-time AR medical applications. Currently, most applications execute the models on an external server that communicates with the headset via Wi-Fi. This client-server architecture introduces undesirable delays and lacks reliability for real-time applications. However, due to HoloLens2’s limited computation capabilities, running the DL model directly on the device and achieving real-time performances is not trivial. Therefore, this study has two primary objectives: (i) to systematically evaluate two popular frameworks to execute DL models on HoloLens2—Unity Barracuda and Windows Machine Learning (WinML)—using the inference time as the primary evaluation metric; (ii) to provide benchmark values for state-of-the-art DL models that can be integrated in different medical applications (e.g., Yolo and Unet models). In this study, we executed DL models with various complexities and analyzed inference times ranging from a few milliseconds to seconds. Our results show that Unity Barracuda is significantly faster than WinML (p-value < 0.005). With our findings, we sought to provide practical guidance and reference values for future studies aiming to develop single, portable AR systems for real-time medical assistance.
Structural Health Monitoring Design and Performance Evaluation of a Middle-Span Bridge
Authors: Xiang Wei , Wei Jiaoyuan , Zhang Fengliang
Published: October 2023

Structural health monitoring (SHM) has attracted significant attention over the past two decades due to its ability to provide real-time insight into the condition of structures. Despite the development of several SHM systems for long-span bridges, which play a crucial role in the assessment of these structures, studies focusing on short- or middle-span bridges remain scarce. This research paper presents an efficient and practical bridge monitoring and warning system established on a middle-span bridge, a key crossroad bridge located in Shenzhen. The monitoring system consists of sensors and measuring points that collect a substantial amount of data, enabling the close monitoring of various operational indicators to facilitate the early detection of threshold exceedances. Based on this system, the subtle condition of the bridge can be evaluated, and the operational condition of the bridge can be studied through the comparative analysis of the collected data. Over four months of monitoring, data including the strain and creep of the main beam, the strain and settlement of piers and the crack width of the bridge body are observed. Furthermore, the real-time operational status of the bridge is analyzed and evaluated through the combination of the collected data and the structural finite element model.
Comparison of Interdependent and Subjective Happiness between Japanese and Thai College Students: A Research Note
Authors: Aoyama Hitomi , Horiuchi Satoshi
Published: October 2023

Cross-cultural studies have suggested that happiness in Eastern countries is characterized by a greater extent of relationships and harmony with others than in Western countries; however, happiness levels may differ across Asian countries. A comparison of happiness levels between Japan and Thailand provides a unique opportunity to identify this difference. Thailand has experienced rapid economic growth, going from a low-income to an upper-middle-income country in the span of a single generation. Japan is a high-income country. This study compared levels of interdependent and subjective happiness between Japanese and Thai college students. Participants were 101 Japanese and 157 Thai college students who completed well-established multiple-item scales for interdependent and subjective happiness. The data were collected through online surveys. The level of subjective happiness was significantly higher among Thai college students than their Japanese counterparts, while that of interdependent happiness did not differ. The differences were small based on the effect sizes. These results extend previous findings by using established, multiple-item scales of interdependent and subjective happiness to demonstrate that Thai individuals show higher levels of happiness compared with their Japanese counterparts.
Designing an In Vivo Preclinical Research Study
Authors: Moctezuma-Ramirez Angel , Dworaczyk David , Whitehorn Julia , Li Ke , Cardoso Cristiano de Oliveira , Elgalad Abdelmotagaly
Published: October 2023

During the preclinical research process, multiple factors can be difficult to implement without the careful consideration and planning of each step. As research has become more advanced with the use of increasingly complex technology, animal models have also become essential for understanding the potential impact of devices, drug therapies, and surgical techniques on humans before clinical trials are conducted. The use of an in vivo animal model is a key and necessary step in the progression of preclinical research studies that will lead to future medical inventions and innovation. Here, we describe the three phases of effectively designing a preclinical research protocol: the research, preprocedural planning, and experimental phases. Furthermore, we provide researchers with guidance through these phases and discuss important considerations.
Modelling Acid-Induced Lung Damage in Precision-Cut Lung Slices: An Ex Vivo Animal Model
Authors: Moes Carmen A. , Gan C. Tji , Venema Leonie H. , Hoffmann Roland F. , Melgert Barbro N. , Kerstjens Huib A. M. , Olinga Peter , Ruigrok Mitchel J. R.
Published: October 2023

Background: Donor lungs are often discarded, with gastric aspiration accounting for ~9% of lungs unsuitable for transplantation. To increase the donor pool, it is important to understand the pathophysiology of aspiration-induced lung damage (AILD) and to assess its treatment. Methods: Precision-cut lung slices (PCLS) were prepared from murine lungs and exposed to acid—pH 1.5 to 5.5—for 15 min. We also investigated whether acid-exposed slices (pH 3.5) could affect unexposed slices. In addition, we investigated whether dexamethasone (0.5 or 1 μM) could mitigate and treat the damage in each group. In each experiment (n = 3), we analyzed cell viability (ATP/protein content) and markers of inflammation (IL-1β, IL-6, TNF-𝛼, TRAIL). Results: PCLS subjected to pH 1.5–3.5 had a significantly reduced amount of ATP, albeit no increase in inflammation markers. There was no interaction of secretions from acid-exposed slices on unexposed slices. Dexamethasone had no beneficial effects in either group. Conclusion: Direct exposure to acid in the PCLS leads to a decrease in cell viability. Acid-exposed slices had no effect on the cell viability of unexposed slices. Treatment with dexamethasone offered no mitigation. More studies have to be performed to elucidate the pathophysiology of AILD and the possible treatment of aspiration-induced injury.
User Preference Analysis for an Integrated System of Bus Rapid Transit and On-Demand Shared Mobility Services in Amman, Jordan
Authors: Altarifi Farah , Louzi Nawal , Abudayyeh Dana , Alkhrissat Tariq
Published: October 2023

Amman, the capital of Jordan, has experienced significant traffic congestion due to the rise in private vehicle ownership and limited public transportation services. A Stated Preference (SP) survey was conducted to determine public transportation users’ willingness to use the Bus Rapid Transit (BRT) service. Another survey assessed the demand for an on-demand transit bus service with flexible and moderate costs, particularly for individuals far from the main BRT stations who need to reach them. Two models, Multinomial Logit (MNL) and Mixed Logit (ML), were utilized to understand user preferences for work-related trips. The study findings indicate that the cost of the trip and the waiting time are the two primary factors influencing public transport users’ choices. Furthermore, sociodemographic factors, such as age, income, household size, and current status, were found to have a significant impact. The results reveal that approximately 71% of participants would utilize an integrated public transportation system comprising BRT and on-demand services. The findings underscore the potential benefits of an integrated public transport system in addressing Amman’s traffic congestion. By combining BRT and on-demand services, the city can offer residents comfortable, affordable, and efficient transportation options, thus effectively mitigating congestion.
The author’s view on the definition of the category “valuation” in accounting and reporting
Authors:   Federal State Autonomous Educational Institution of Higher Education “Lobachevsky State University of Nizhni Novgorod”, Nizhny Novgorod, Russia, Druzhilovskaya E.S.
Published: October 2023

Valuation is certainly the main content of modern accounting and reporting. At the same time, there is still no definition of this category in accounting standards. At the same time, various definitions of valuation are given in the scientific and educational literature. These definitions were critically analyzed by us in the previous article. In this article, we present our own view on the definition of the category “valuation” in accounting and reporting. During the research, such methods as analysis and synthesis, logical approach, systematic approach, comparison, grouping method, analogy method were used. As a result of the research, this paper presents a new view on the category of “valuation” in accounting and reporting, which meets the requirements of modern times. In addition, proposals are also made for amending accounting regulations. The results obtained in this article will be useful to a wide range of readers interested in various problems of Russian and foreign accounting and reporting, including the valuation of accounting objects and reporting elements. In addition, the results reflected in this paper can be used in the educational process of higher educational institutions and in the practical work of accounting departments. In addition, the results of our study can be used in the development and improvement of relevant domestic and foreign regulatory documents on accounting and reporting.
Workload and GP burnout: a survey and register-based study in Danish general practice
Authors: Ibsen Bruun Astrid , Vedsted Peter , Pedersen Henrik Schou , Pedersen Anette Fischer
Published: October 2023

Background

Burnout is common among GPs. Previous studies have indicated an association between high workload and burnout among doctors.

Aim

To assess the risk of burnout among single-handed GPs in Denmark in relation to self-reported and register-based workload.

Design & setting

Questionnaire data from 312 Danish single-handed GPs and register data on their patients and provided services.

Method

Burnout was measured using the Maslach Burnout Inventory-Human Services Survey (MBI-HSS). A composite burnout score of quartile points was calculated. The questionnaire provided information on working hours. Register data included number of services and patient list size. Association between composite burnout score and workload was estimated with binomial regression analyses adjusting for the GP’s age and sex, and social deprivation score of their patient lists.

Results

Working >5 days a week in practice increased the risk of a high burnout score (adjusted risk ratio [RR] = 2.34, 95% confidence interval [CI] = 1.62 to 3.37). Spending >7.5 hours a day on patient-related tasks increased the risk of a high burnout score. The highest score was among GPs spending 8.5–9.5 hours a day on patient-related tasks (adjusted RR = 2.01, 95% CI = 0.90 to 4.51), although not statistically significant. There was no association between number of services and risk of burnout.

Conclusion

Working 5 days a week in practice significantly increased the risk of burnout in Danish single-handed GPs. Spending >7.5 hours a day on patient-related tasks tended to increase the risk. We found no association between a high number of services and increased risk of burnout.
Achados neurológicos em estudos de imagem e achados clínicos: revisão de literatura
Authors: Almeida Santos de Santana Gabriella , Garcia de Carvalho Laguna Gabriela , Da Mota Carneiro Caroline , Alves Fernandes Larissa , Alves de Souza Assis Gabriela , Da Silva Oliveira Patrícia
Published: October 2023

Introdução. A Síndrome de Rett é um distúrbio raro de neurodesenvolvimento, que se caracteriza      por perda de habilidades, manifestando-se entre os 6 e 18 meses de idade. O diagnóstico é clínico, mas exames de imagem facilitam diagnósticos diferenciais, determinação prognóstica e direcionamento do tratamento. Objetivo. Avaliar a relação entre os principais achados neurológicos em exames de imagem de pacientes com síndrome de Rett e os achados clínicos. Método. Revisão da literatura com dados foram obtidos a partir das bases de dados PubMed, SciELO, Cochrane e Web of Science, por artigos em português ou inglês, publicados entre 2011-2020, a partir dos descritores "Rett, ressonância" e "Rett, tomografia," combinados com "Rett Syndrome". Os 100 artigos localizados foram triados de acordo com critérios de exclusão: idioma, período, artigo de revisão, em modelos experimentais, que não abordassem dados do sistema nervoso, sem confirmação de Síndrome de Rett com mutação em MECP2 e/ou que não respondessem aos objetivos da pesquisa; e 6 artigos foram selecionados. Resultados. Os principais achados neurológicos nos exames de imagem foram hipotrofia cerebral e anisotropia fracionada. Os sinais e sintomas mais recorrentes foram deterioração da função motora, perda da função verbal e tônus muscular anormal. A análise      demonstrou que os sintomas mais recorrentes podem ser atribuídos, pelo menos em parte, a alterações neurobiológicas. Conclusão. Esta revisão contribui para a compreensão da relação entre sintomas clínicos e achados em exames de imagem de pacientes com Síndrome de Rett, entretanto, considerando a pequena amostra localizada, são importantes novas pesquisas relacionadas ao tema.
DESKRIPSI PERWUJUDAN HIDUP PERSAUDARAAN MUDA-MUDI FRANSISKAN (MUDIFRA) SAN PIO MELA BERDASARKAN SPIRITUALITAS SANTO FRANSISKUS DARI ASISI
Authors: Tamba Henny Yuni Ceta Pebronia , Wulung FX Heryatno Wono
Published: October 2023

Mudifra is a community of the Catholic youth living the Gospel according to spirituality of universal brotherhood Francis of Assisi. He respects God's creatures as brothers. Francis taught that brotherhood isn't only with humans, but also with animals, plants, and other creatures. As followers of Francis, youth are expected to emulate the universal fraternity of Francis. Therefore, the writer is interested in knowing the manifestation of the fraternity of the Franciscan youth group of San Pio Mela which imitates the spirit of the fraternity of Francis. The main problem of this paper is how to strive for the realization of youth fraternity life based on the spirituality of Francis, which includes brothers in the faith, brothers and sisters of different faiths, the poor, and the natural environment. To examine the subject matter, the authors conducted interviews to obtain data and validate its truth. The results of the study show the youth group has been able to establish brotherhood in all of creation fairly well. However, the brotherhood of youth groups with brothers of different faiths and poor relatives who're excluded isn't very visible because there're very few activities related to this. But they realize the brotherhood through their respective experiences.
Number of ventricular premature beats and other causes of cardiomyopathy associated with arrhythmia: case reports
Authors: Shubik Yu. V. , Korneev A. B. , Morozov A. N.
Published: October 2023

We report a case of two patients with frequent idiopathic premature ventricular contractions. One of them had more than 25% of ventricular contractions per day leading to fast development of cardiomyopathy and its complete regression upon ventricular arrhythmia elimination. The second one had from 40% to 73% of ventricular contractions per day including non-sustained and sustained ventricular tachycardia without any structural changes of the heart during 28 years of follow-up.
Educación científica en educación infantil mediada por las tecnologías: una revisión sistemática
Authors: Pino-Perdomo Felipe
Published: October 2023

ABSTRACT: Introduction: The development of scientific competencies in early childhood education allows the understanding of the world that surrounds the infant, historically it has been done from the exploration of the environment, however, the use of technologies is a current need in the learning processes, continuous improvement and contextualization of pedagogical practice in early childhood education. Objective: to identify training trends in scientific competencies in early childhood education focusing on teaching strategies and didactic resources mediated by educational technology. Methodology: the review was based on a qualitative approach, a search was carried out in the SCOPUS database characterizing the title of the article, abstract and keywords with the following search criteria: early AND childhood AND science AND education AND educational AND technology, applying the filter Source type: Journal in the period between 2007 and 2022 for a subsequent hermeneutic analysis taking into account the categories of teaching strategies and didactic resources. Results: it was found that there is a strong tendency to use the Science, Technology, Engineering and Mathematics -STEM- models; in the case of didactic resources, the use of robots, online and interactive educational applications, websites, use of mobile devices and software for tactile use and computer equipment stand out in the literature reviewed. Conclusions: the present study allows highlighting that it is important to take into account technological, pedagogical and content limitations when implementing teaching strategies in early childhood education, since these limitations can affect the success of educational practices and the ability of teachers to teach scientific competencies effectively.
Prototype of Automatic Control System for Water Temperature and Acidity in Ornamental Fish Aquarium Based on Internet of Things (IOT)
Authors: Hermansyah Adi , Septian Tri Wanda , Perdana P Aditya Putra , Faris Mgs Muhammad
Published: October 2023

The prototype application of an automatic control system in an Internet Of Things-based aquarium using DS18B20 and PH-4502C temperature sensors using the NodeMCU ESP 8266 microcontroller is a system that can regulate the temperature and pH of water automatically which is applied to a small aquarium. This technological advancement is very helpful for people who have busy daily lives who do not have time or cannot check the condition of the fish in their aquarium. To see the condition of ornamental fish aquarium can be checked from mobile phone through blynk application. Monitoring using the blynk application can be done anywhere as long as the device is always connected to the internet.
Analysis of Histogram and Grayscale on Chest X-Ray in Lung Cancer Using Image-J
Authors: Susanto Fani , Utami Hernastiti Sedya
Published: October 2023

Posteranterior (PA) chest radiographic examination is a support in screening for the diagnosis of lung cancer. Computed radiography (CR) modality can produce chest images quickly, optimally and can be processed as needed. However, so far radiologists interpret images only by visual assessment, so the results are very subjective. Therefore digital medical image processing can be done by looking at the histogram and gray scale values to increase the accuracy of enforcing patient diagnoses. This study aims to analyze the comparison of histograms and gray degree values on CR chest images between normal patients and lung cancer patients. The study was conducted using 30 chest images consisting of normal and lung cancer patient groups with 15 images each. All images are calculated grayscale and display histogram graphics with the Image-J application and statistically analyzed using the Independent T-Test. The results show that there is a difference in grayscale values between normal chest images and lung cancer (p<0.001). The grayscale and histogram values on lung cancer chest images ( 103.2908 + 6.119 ) are higher and tend to the right compared to the grayscale and histogram values on normal chest images ( 64.5848 + 3.28) . Histogram and grayscale values add objective image interpretation in diagnosing lung cancer.
Accuracy of Infrared Photodiode Sensors at The Flowrate Measurement in Infusion Device Analyzer with 2 Channel TFT Display
Authors: Azizah Wafiq Nur , Rahmawati Triana , Syaifudin Syaifudin
Published: October 2023

The use of infusion is crucial for patient healing. Infusion refers to a fluid that consists of drugs, nutrients, and hydration delivered continuously into the patient's bloodstream over a specific period. One of the types of infusion devices is the infusion pump and syringe pump. These devices play a vital role in accurately and precisely controlling the volume or flow rate of fluids. However, continuous usage of these devices can sometimes result in inaccurate measurements, which can affect their overall accuracy. The accuracy of these devices is crucial for proper dosage administration to patients, particularly in critical situations. Therefore, it is necessary to periodically calibrate healthcare devices, at least once a year, as specified in Ministry of Health Regulation No. 54 of 2015. Calibration is an activity performed to determine the true value of a device. The objective of this study is to develop an Infusion Device Analyzer (IDA) with a TFT LCD display that showcases graphical representations of flow rate parameters. By analyzing the calculation of flow rate values using Infrared Photodiode sensors, the stability of the flow rate graph can be observed on a 7-inch TFT LCD display. The measurement involved the use of two different brands of syringe pumps and two different brands of infusion pumps. The results were presented in real-time on the 7-inch TFT LCD display, both in graphical and numerical formats. Additionally, the data was transmitted via Bluetooth to a PC, allowing the graph to be simultaneously displayed in a Delphi program.The measurement results revealed performance errors when using the Terumo Syringe Pump with Terumo syringes in Channel 1, with values of 0.45% (10 ml/h), 0.72% (50 ml/h), and 0.40% (100 ml/h). In Channel 2, the errors were 0.32% (10 ml/h), 0.40% (50 ml/h), and 0.32% (100 ml/h). When using the B-Braun Syringe Pump with B-Braun syringes, Channel 1 exhibited errors of 0.45% (10 ml/h), 0.7% (50 ml/h), and 0.85% (100 ml/h), while Channel 2 had errors of 0.8% (10 ml/h), 0.3% (50 ml/h), and 1% (100 ml/h). In the case of the Terumo Infusion Pump with Terumo Infusion Sets, Channel 1 showed errors of 0.4% (10 ml/h), 0.5% (50 ml/h), and 0.45% (100 ml/h), and Channel 2 exhibited errors of 0.32% (10 ml/h), 0.4% (50 ml/h), and 0.72% (100 ml/h). Lastly, when using the B-Braun Infusion Pump with B-Braun Infusion Sets, Channel 1 had errors of 0.72% (10 ml/h), 1% (50 ml/h), and 1,2% (100 ml/h), while Channel 2 displayed errors of 0.8% (10 ml/h), 0.72% (50 ml/h), and 0,4% (100 ml/h).INDEX TERMS Infrared Photodiode Sensor, Calibration, Real Time, Flow Rate.
Self-Efficacy dan Quarter Life Crisis pada Mahasiswa Rantau dari Luar Pulau Jawa
Authors: Gendolang Nola Marsela , Ambarwati Krismi Diah
Published: October 2023

Self-efficacy memengaruhi quarter life crisis. Individu dengan self-efficacy yang tinggi akan cenderung memiliki rasa yakin dan percaya akan kemampuan yang dimiliki dalam melewati suatu persoalan. Maka, peneliti tertarik untuk mengetahui hubungan self-efficacy dengan quarter life crisis pada mahasiswa rantau dari luar pulau Jawa di Kota Salatiga. Tujuan dari penelitian ini adalah untuk mengetahui hubungan self-efficacy dengan quarter life crisis pada mahasiswa rantau dari luar pulau Jawa di Kota Salatiga. Penelitian ini merupakan penelitian kuantitatif korelasional. Partisipan dalam penelitian ini adalah 335 mahasiswa rantau dari luar pulau Jawa di kota Salatiga yang berusia 18-29 Tahun. Teknik sampling yang digunakan yaitu probability sampling. Alat ukur yang digunakan adalah skala quarter life crisis dengan nilai α = .886 dan skala self-efficacy dengan nilai α = .881. Data penelitian diproses dengan menggunakan uji korelasi product moment dari Karl Pearson dengan bantuan program SPSS versi 21.0. Hasil penelitian menunjukkan terdapat hubungan negatif yang signifikan antara self-efficacy dengan quarter life crisis, yang dapat diartikan semakin rendah self-efficacy maka semakin tinggi quarter life crisis, begitu pun sebaliknya. Sehingga hipotesis penelitian ini diterima.
Toxic Relationships ditinjau dari Self Esteem pada Mahasiswa
Authors: Setianingrum Margaretta Erna , Kelly Estalita
Published: October 2023

Kebutuhan mahasiswa adalah menjalin hubungan yang hangat dan bahagia dengan siapapun namun kenyataannya justru terjebak dalam toxic relationship. Ciri toxic relationship berupa kemarahan, ketidakbahagiaan, stres, frustrasi, serta beragam gangguan yang dilakukan pada sebuah hubungan. Toxic relationship yang berkelanjutan menyebabkan munculnya konflik, kemarahan, frustrasi dan ketidakbahagiaan. Salah satu faktor yang memengaruhi toxic relationship adalah self esteem, yaitu kepuasan mahasiswa terhadap dirinya yang memengaruhi kepercayaannya dalam segala hal, baik dalam hubungan romantis maupun hubungan yang lain.  Tujuan penelitian ini mengetahui pengaruh self esteem terhadap toxic relationship, dengan memakai metode kuantitatif korelasional. Data dikumpulkan dengan skala self esteem dan skala toxic relationship. Subjek penelitian sebesar 200 orang mahasiswa Fakultas Psikologi. Hasil analisis regresi menunjukkan F sebesar 16,688 dengan nilai signifikan 0,000 artinya adanya pengaruh self esteem terhadap toxic relationship mahasiswa. Nilai Beta sebesar -0,279 menerangkan bahwa makin tinggi self esteem maka makin rendah toxic relationship dan sebaliknya. Hasil penelitian ini menyarankan perlunya meningkatkan self esteem mahasiswa. Ketika self esteem mahasiswa tinggi akan lebih mampu menjauhi relasi yang buruk dan tidak sehat.
Fast Sparse PCA via Positive Semidefinite Projection for Unsupervised Feature Selection
Authors: Zheng Junjing , Zhang Xinyu , Jiang Weidong , Huo Kai , Liu Yongxiang , Liu Li
Published: October 2023

In the field of unsupervised feature selection, sparse principal component analysis (SPCA) methods have attracted more and more attention recently. Compared to spectral-based methods, SPCA methods don’t rely on the construction of a similarity matrix and show better feature selection ability on real-world data. Existing convex SPCA methods reformulate SPCA as a convex model by regarding the reconstruction matrix as an optimization variable. However, they are lack of constraints equivalent to the orthogonality restriction in SPCA, leading to larger solution space. In this paper, a standard convex SPCA-based model for unsupervised feature selection is proposed and proven to have its optimal solution falling onto the Positive Semidefinite (PSD) Cone. Further, a two-step fast optimization algorithm via PSD projection is presented to solve the proposed model (SPCA-PSD), whose computational complexity is linear to the number of samples. Two other existing convex SPCA-based models’ optimal solution space is also proven to be the PSD cone. Therefore, the PSD versions of these two models are proposed to accelerate their convergence. Experiments on synthetic and real-world datasets demonstrate the effectiveness and efficiency of the proposed methods. 
Mitigating Road Traffic Crashes in Urban Environments: A Case Study and Literature Review-based Approach
Authors: Musingura Crispus , Lee Gunwoo , Ahn YongHan , Kim Kibum
Published: October 2023

Road traffic crashes in urban areas pose significant safety and efficiency challenges. This paper presents an approach, merging case studies and literature reviews, to mitigate urban road traffic crashes and enhance safety. The study commences with an extensive literature review, delving into existing research on road traffic crashes. This review establishes the groundwork for comprehending urban road safety solutions, insights into ongoing research trends, and guiding case study selection. Three case studies parallel analogous cities where Intelligent Transportation Systems and other smart city initiatives targeting road safety succeeded. Each case dissects safety interventions, accomplishments, and lessons learned. Scrutinizing these studies aims to unveil trends underpinning a holistic road safety strategy. From literature and case studies, a comprehensive road safety strategy emerges. It leverages advanced technology, data insights, and proactive measures to enhance road safety, curtail accidents, and optimize urban traffic. This research yields an all-encompassing road safety strategy for policymakers, planners, and safety practitioners to elevate urban road safety. It promotes secure, efficient, technologically advanced urban areas, endorsing sustainable transportation, elevating residents’ lives, and positioning cities as urban mobility leaders. Furthermore, this study contributes to the academic literature on road safety and urban transportation. Through case studies and literature reviews, it supplements knowledge about effective road traffic crash mitigation strategies. These insights have the potential to guide future research, advancing road safety and urban transportation domains.
An Explicit Improvement on Generative Adversarial Network-Based Time Series Generation: Applying Synthetic Data to N2O Emission Prediction in Farming
Authors: Lin Ci , Killeen Patrick , Li Futong , Yeap Tet , Kiringa Iluju
Published: October 2023

Traditionally, time series data augmentation has primarily focused on improving the architecture of Generative Adversarial Network (GAN), with the aim of closely matching the original data distribution while also preserving the dynamic behavior of the original data. However, even state-of-the-art GAN models like TimeGAN fall short in preserving the temporal dynamics present in the original time series due to the absence of first-order difference information. To address this limitation, this study proposes a novel process for generating multivariate time series data. The proposed process comprises four essential modules: a) the GAN module for generating multivariate time series data, b) the sampling module for preserving the first-order difference distribution, c) the smoothing module for refining the generated data, and d) an evaluation module using the Kolmogorov-Smirnov Test (KS-test) and Hilbert-Schmidt Independence Criterion (HSIC), along with other metrics to test the synthetic time series data. This comprehensive approach ensures that the synthetic time series data maintains both the distribution and the dynamic behavior of the original data.

We extensively discuss the role of the β factor in the modified Metropolis-Hastings algorithm (in the sampling module), which controls the level of information preservation from the original time series. Our experiments reveal that with small β values, periodic information can be retained effectively. The joint distribution of the first-order difference of the synthetic time series data remains consistent when the same β value is applied in the modified Metropolis-Hastings algorithm. However, we observe that β has no impact on the partial autocorrelation functions. Nevertheless, the generated data from the sampling module maintains the memoryless property of the Markov Chain. Therefore, in the smoothing module, we apply the exponential moving average (EMA) method to simulate the long-term relationships within the original time series, and find that an optimal α value is approximately 0.4 or 0.5. Lastly, we employ the synthetic time series data to train a neural network model developed in another work. Our findings indicate that the neural network model trained on synthetic time series data exhibits performance comparable to that of a model trained on the original data.
AI-Based Mutation Prediction in SARS-CoV-2
Authors: Miar Yasin
Published: October 2023

This study focuses on the development of an AI model to predict the next variants of the SARS-CoV-2 virus based on genomic data. Leveraging a dataset comprising a wide range of SARS-CoV-2 variants, including the Alpha, Beta, Gamma, Delta, Epsilon, and Omicron variants, we employ Artificial Intelligence (AI) algorithms to train a model capable of identifying patterns and mutations within the viral genome. Furthermore, we emphasize the significance of the Spike protein region, given its relevance to vaccine development. By treating the Spike protein sequences as 2-dimensional images, we apply image recognition techniques commonly used in AI research to analyze and extract meaningful insights from these protein sequences.We also highlight the status of AI applications in genomics, noting previous studies focused on binding affinity prediction and clustering analysis of Spike proteins. However, no existing AI models have addressed the prediction of future variant sequences. Consequently, our study aims to bridge this gap by developing an AI model with the potential to forecast the sequence of forthcoming SARS-CoV-2 variants. This research contributes to our understanding of viral evolution and assists in the proactive development of strategies to combat the evolving COVID-19 landscape.
Leveraging Transfer Learning for Radio Map Estimation via Mixture of Experts
Authors: Jaiswal Rahul Kumar , Elnourani Mohamed , Deshmukh Siddharth , Beferull-Lozano Baltasar
Published: October 2023

This paper leverages transfer learning~(TL) on a mixture of experts~(MoE) model for radio map estimation. The proposed MoE combines location-based and location-free experts through a gating network exploiting their complementary benefits. To estimate the radio map in a new wireless environment, the learned model of another sufficiently similar environment is transferred and fine-tuned with additional data from the new environment. The proposed data-driven similarity measure predicts the amount of data needed for TL. Results demonstrate that the proposed method only requires 20-40\% of measurements to adapt to several varying environments, and as expected, the proposed MoE method outperforms both experts.
Using Machine Learning Method for Probing Congestion in High-Performance Datacenter Network
Authors: Rupani Sidharth
Published: October 2023

Even if, as we all known, High Performance Computing (HPC) systems can greatly reduce application performance, there is little quantification of congestion on credit-based in- terconnected networks. This paper proposed a method for de- tecting, extracting and characterizing congested regions in the network. The authors have implemented this methodology in a deployable tool, Monet, which can provide such analysis and feedback at runtime. Using Monet, we can character- ize and diagnose the congestion in Blue Waters, the world’s largest 3D torus network. Blue Waters is a 13.3- petaflop su- percomputer at the National Center for Supercomputing Applications.
Scenario-based trajectory generation and density estimation towards risk analysis of autonomous vehicles
Authors: Johansson Edvin , Sönnergaard Matilda , selpi selpi , Rahrovani Sadegh , Basimfar Parsia
Published: October 2023

Machine learning approach to estimate a probability distribution of trajectories in a dataset.
Hybrid Physics-Informed Neural Network for the Wave Equation with Unconditionally Stable Time-Stepping
Authors: Qi Shutong , Sarris Costas
Published: October 2023

This letter introduces a novel physics-informed approach for neural network-based three-dimensional electromagnetic modeling. The proposed method combines standard leap-frog time-stepping with neural network-driven automatic differentiation for spatial derivative calculations in the wave equation. This methodology effectively addresses the challenge of accurately modeling high-frequency electromagnetic fields with physics-informed neural networks, often characterized as ``spectral bias", in the time domain. We demonstrate that the resultant numerical scheme enables unconstrained time-stepping with respect to stability, in contrast to the Finite-Difference Time-Domain method, which is subject to the Courant stability limit. Furthermore, the use of neural networks allows for seamless GPU acceleration. We rigorously evaluate the accuracy and efficiency of this finite-difference automatic differentiation approach, by comprehensive numerical experiments.
Attenuation Correction of Airborne Gamma Ray Spectrometric Data Using Digital Terrain Models
Authors: Wendorff Lutz
Published: October 2023

Attenuation correction of airborne gamma-ray spectrometric data using digital terrrain models. Gamma-rays are partially absorbed in air on there way from Earth's surface to the sensor package in the aircraft, thus attenuated following an exponential law, coming from a footprint area with a few hundred metres diameter. This effect shall be removed as far as flying height deviates from some nominal flying height. Instead of assuming a flat surface, this is done for the true travel distance of the gamma-rays using digital terrain models and an arbitrarily fine sector system around the sensor package.
Speech signal likability estimation through harmony between pitch and formant
Authors: Choi Yuha
Published: October 2023

Voice likability is a critical factor in machine-human interaction. However, studies on speech likability typically does not apply the harmony theory in music, which suggests general rules for pleasant sounds. In this paper, I propose a new method that estimates the likability of vocal signals using the harmonic relation of pitch and the first formant (F1). I extract the pitch and F1 from the vowel signal and compute the average cent value between notes in the musical scale from each pitch and F1. A small cent value indicates a consonant relation between pitch and F1. I compared the calculated cent values with the MOS test results from ten speech samples. The results showed a clear correlation between the subjective MOS scores and the consonance of pitch and F1 in vowels.
HaptiYarn Development of an actuator yarn that can transform everyday textiles into haptic devices
Authors: Lugoda Pasindu , Arm Richard , wooler Angus , Barnes Lincoln , Butt Ahmed Tamkin , Oliveira Carlos , Shahidi Arash , navaraj william
Published: October 2023

A method of providing discreet localised haptic feedback at precise locations on the body, utilising a lightweight textile garment is presented in this short paper. The textile comprises of subtly integrated actuator yarns (HaptiYarns) which are controlled by electropneumatic circuitry. Each yarn has two functional layers, an inner porous textile layer with limited extensibility and a second, durable outer layer made from an extensible elastomer. The HaptiYarns can provide radial forces and a maximum radial displacement of 28.09 ± 0.14 mm. It was found that the intrinsic addition of graphite powder (5% by weight), during elastomer preparation, offered better resistance to layer delamination and increased the ability of the yarn to withstand higher internal air pressures by 48%. Both the graphite-filled composite and the graphite free yarns demonstrated high durability, withstanding cyclic testing of >7500 cycles while having no significant impact on the force feedback. Finally, a wearable prototype knitted textile garment is presented with eight HaptiYarns subtly integrated within it and connected to a virtual reality (VR) program providing an immersive haptic experience. These yarns offer the potential to transform everyday clothing into wearable haptic devices with potential to revolutionise healthcare, VR-based training, gaming, and entertainment sectors
MUSCLE ENERGY TECHNIQUE VERSUS PASSIVE MANUAL SOFT TISSUE THERAPIES ON PLANTER FASCIITIS: A SYSTEMIC REVIEW
Authors: Sandhu Taliah Bashir , Jamil Ayesha
Published: October 2023

Aims of Study: Planter fasciitis (PF) is a common cause of heel pain. Muscle energy technique (METs) and passive soft tissue therapies are widely used for its management. The objective of this review was to evaluate the comparative effectiveness of METs and passive soft tissue therapies on PF.

Methodology: An extensive electronic literature search was made using different databases and search engines. Studies regarding METs and soft tissues therapies were investigated according to the eligibility criteria, using extracted data form and assessed for risk of bias. Outcome measures were pain and functional status. Quality assessment was done with Downs and Black, Cochrane risk of bias tool, PEDro scale and Critical Appraisal Skill Program (CASP) tool.

Results: Five articles met the selection criteria, were systematically reviewed for quantitative synthesis on comparative effects of METs and passive soft tissue therapies on PF. The quality of studies was moderate to high.

Limitations and Future Implications: Less evidence on desired interventions and outcome measures was the limitation. Relative efficacy helps in clinical decision making and improves patient’s related outcomes.

Originality: This review is the independent creation of authors.

Conclusion: Manual soft tissue techniques are more effective than METs on improving pain and function in planter fasciitis.
Pola Perilaku Konsumen terhadap Keputusan Mengikuti Event K-Pop
Authors: Ramadhania Almira Fidia , Setyaningrum Idfi , Kartikasari Cynthia Yohanna
Published: October 2023

The present Korean wave has become a worldwide phenomenon, even in Indonesia. Consumer behaviour changes toward numerous activities, including K-Pop events, have been noticed. Participation of fans in various K-Pop events and the purchase of things as a form of social identity associated with K-Pop provide not only economic value but also satisfaction and greater self-confidence for K-Pop lovers. As a result, the purpose of this research is to better understand the consumer behaviour patterns around the decision to attend BTS K-Pop events in Surabaya. Through interviews and observations, the research uses a qualitative descriptive method. According to the survey, K-Pop events are more than just a form of entertainment; they also represent huge commercial potential. The passion of K-Pop fanbases is critical not only in changing behavioural patterns in attending various K-Pop events but also in driving social changes and fostering enhanced self-confidence in network development.