bluuebunny/crossref_metadata_2025 huggingface dataset:
PERBANDINGAN METODE CART DAN NAÏVE BAYES UNTUK KLASIFIKASI CUSTOMER CHURN
Authors: Adhitya Rahmat Ryan , Wina Witanti  , Rezki Yuniarti
Published: July 2023

Classification is the process of identifying and grouping an object into the same group or category Classification can be used to group a large-sized dataset, and some commonly used classification methods are CART (Classification And Regression Tree) and Naïve Bayes. This study discusses the comparison of CART and Naïve Bayes methods by measuring accuracy, precision, recall, and f1-score values with 3 scenarios of training and testing dataset distribution. Accuracy, precision, recall, and f1-score measurements are performed using a confusion matrix. The scenarios for training and testing dataset division are 70%, 80%, and 90% of the training dataset. From the results of the study, CART has the highest average accuracy and f1-score of 79.616% and 57.636% respectively, while the highest average accuracy and f1-score of Naïve Bayes are 75.104% and 62.004% respectively.
Pengaruh Media Pembelajaran KIT IPA Terhadap Motivasi dan Hasil Belajar Siswa Kelas IV
Authors: Anisah Aprilia Wahyuningtiyas  , Firmansyah Ihwan , Pratiwi Siska
Published: July 2023

Based on the results of observations, it can be seen that there are some students whose grades do not reach the KKM score. This happens because the method used by the teacher in learning is only the lecture method. Teachers who are creative in the learning process should immediately provide learning materials using tools in the form of learning media so that the scores of students who are below the KKM will decrease. The purpose of this writing is to determine the effect of KIT IPA learning media on motivation and student learning outcomes in learning. The writing method uses quantitative with the experimental method, namely trying to practice directly related to the material being taught by the teacher. The results that the writer got during the observation process were that there was an increase in the scores obtained by students after the teacher implemented the learning process using media aids. The next suggestion is that teachers can use learning media in schools to help the process of delivering material to students so that students can easily understand the material and are more enthusiastic about learning.
The Influence of Recruitment, Extrindic Rewards, and Training on Employee Performance in PT. Bakrie Metal Industries Bekasi
Authors: Nugroho Widi , Nurbaiti Beti
Published: July 2023

Specifically, this study aims to determine how much influence the recruitment  of extrinsic reward  and training  on employee performance  at PT. Bakrie Metal Industries simultaneously. The population is 344 employees and a sample of 125 employees is taken. The writer uses quantitative methods using Structural Equation Modeling (SEM) with the help of Lisrel 8.8 software (t value > 1.96) and primary data was obtained from questionnaires whose measurements used a Likert scale that was tested for validity and reliability. The results of the study based on the validity and reliability test showed that the data was valid and reliable. Based on the t test and F test shows that recruitment, extrinsic rewards and training have positive and significant effect on the performance of employees at PT Bakrie Metal Industries Bekasi.
Preparation of drug-loaded microspheres with a core-shell structure using silk fibroin and poly lactic-co-glycolic acid and their application
Authors: Zhang Yi , Wang Lu , Zhao Bin
Published: July 2023

BACKGROUND: Advances in bone tissue engineering offer novel options for the regeneration of bone tissue. In the current clinical treatment, the method of accelerating bone tissue regeneration rate by promoting early angiogenesis has been widely accepted. OBJECTIVE: This study aimed to develop a long-acting slow-release system using the pro-angiogenic drug tetramethylpyrazine (TMPZ) and pro-osteogenic drug icariin (ICA), which can be administered locally to achieve the sequential release of TMPZ and ICA for better clinically efficiency in the treatment of bone defects. METHODS: This study aimed to prepare microspheres with a core-shell structure using two polymers, poly lactic-co-glycolic acid and silk fibroin, by coaxial electrostatic spraying. Based on the therapeutic model for bone defects, the pro-angiogenic drug TMPZ and pro-osteogenic drug ICA were encapsulated in the shell and core layers of the microspheres, respectively. Subsequently, TMPZ and ICA were released sequentially to promote early angiogenesis and late osteogenesis, respectively, at the site of the bone defect. The optimal preparation parameters for preparing the drug-loaded microspheres were identified using the univariate controlled variable method. Additionally, microsphere morphology and core-shell structure, such as physical properties, drug-loading properties, in vitro degradation and drug release patterns, were characterised using scanning electron microscope and laser scanning confocal microscopy. RESULTS: The microspheres prepared in this study were well-defined and had a core-shell structure. The hydrophilicity of the drug-loaded microspheres changed compared to the no-load microspheres. Furthermore, in vitro results indicated that the drug-loaded microspheres with high encapsulation and loading efficiencies exhibited good biodegradability and cytocompatibility, slowly releasing the drug for up to three months. CONCLUSION: The development of the drug delivery system with a dual-step release mechanism has potential clinical applications and implications in the treatment of bone defects.
Study on deterioration identification method of rubber bearings for bridges based on YOLOv4 deep learning algorithm
Authors: Gao Xiaoni , Ren Hongwei , Liu Rufei , Chen Min , Lai Ruixin
Published: July 2023

How to quickly and accurately identify the bridge rubber bearing deterioration plays an important role in ensuring the bridge structure and road safety. This paper selects the common rubber bearings of domestic bridges as the research object, and proposes an improved YOLOv4-based bridge rubber bearing deterioration detection algorithm to address the reasons for the difficulty in detecting bridge rubber bearing deterioration due to large scale variations and small sample data sets. An image dataset (named HRBD) with annotations is constructed from real inspection scenarios, and the data is expanded by image processing means such as rotation, translation and brightness transformation, so that this dataset has sufficient data complexity and solves the problem of overfitting due to insufficient samples for network training. The anchor applicable to this dataset was regained by the K-means++ clustering algorithm, and then the CA module was inserted into the YOLOv4 backbone network for more accurate anchor localization. The improved YOLOv4 network was used for migration learning to train the dataset, and finally the trained network model was used for detection on the test set. The experimental results show that the improved YOLOv4 bridge rubber bearing deterioration detection and identification network can effectively identify and locate bridge rubber bearings and their deterioration types (crack damage, shear deformation, bearing void).
Sex-Related Differences in the Association Between Body Mass Index and Dementia Risk
Authors: Kostev Karel
Published: July 2023

In this issue, Zakharova et al. report on important findings concerning the association between body mass index and dementia risk as related to sex. Concretely, underweight was strongly associated with dementia risk in men but not in women. We compare the results of this study with a recent publication by Jacob et al. and consider the role of sex in the association between body mass index and dementia.
A local path planning algorithm based on improved dynamic window approach
Authors: Xu Wan , Zhang Yuhao , Yu Leitao , Zhang Tingting , Cheng Zhao
Published: July 2023

In order to solve the problem that the traditional DWA algorithm cannot have both safety and speed because of the fixed parameters in the complex environment with many obstacles, a parameter adaptive DWA algorithm (PA-DWA) is proposed to improve the robot running speed on the premise of ensuring safety. Firstly, the velocity sampling space is optimized by the current pose of the mobile robot, and a criterion of environment complexity is proposed. Secondly, a parameter-adaptive method is presented to optimize the trajectory evaluation function. When the environment complexity is greater than a certain threshold, the minimum distance between the mobile robot and the obstacle is taken as the input, and the weight of the velocity parameter is adjusted according to the real-time obstacle information dynamically. The current velocity of the mobile robot is used as input to dynamically adjust the weight of the direction angle parameter. In the Matlab simulation, the total time consumption of PA-DWA is reduced by 47.08% in the static obstacle environment and 39.09% in the dynamic obstacle environment. In Gazebo physical simulation experiment, the total time of PA-DWA was reduced by 26.63% in the case of dynamic obstacles. The experimental results show that PA-DWA can significantly reduce the total time of the robot under the premise of ensuring safety.
Neutrosophic ratio-type exponential estimators for estimation of population mean
Authors: Tahir Zaigham , Khan Hina , Alamri Faten S. , Aslam Muhammad
Published: July 2023

The current work is one step in filling a large void in the research left by the advent of neutrosophic Statistics (NS), a philosophized variant of classical statistics (CS). The philosophy of NS deals with techniques for investigating data that is ambiguous, hazy, or uncertain. The traditional techniques of estimation utilizing auxiliary information work under specific determinate data, which in the case of neutrosophic data may lead to mistakes (over/ under-estimation). This study presents a generalized neutrosophic ratio-type exponential estimator (NRTEE) for estimating location parameters and achieving the lowest mean square error (MSE) possible for interval neutrosophic data (IND). The offered NRTEE helps to deal with the uncertainty and ambiguity of data. Unlike typical estimators, its findings are not single-valued but rather in interval form, which reduces the possibility of over-or under-estimation caused by single crisp outcomes and also increases the likelihood of the parameter dwelling in the interval. It improves the efficiency of the estimator since we have an estimated interval that contains the unknown value of the population mean with a minimal MSE. The suggested NRTEE’s efficiency is further addressed by utilizing real-life IND of temperature and simulations. A comparison is also performed to establish the superiority of the proposed estimator over the traditional estimators. The limits are calculated and discussed in cases when our suggested estimator is always efficient. The suggested estimator is the most efficient of all estimators and outperformed all others on both IND and classical data.
Evaluation method of English online course teaching effect based on ResNet algorithm
Authors: Yang Juan
Published: July 2023

In order to improve the accuracy of English online course teaching effect evaluation results, a paper proposed an English online course teaching effect evaluation method based on ResNet algorithm. The effect of College English online teaching was evaluated from five aspects: pre-class preparation, teaching content, basic skills, ability training, and teaching methods. Each evaluation item was set with seven levels of scoring standards. An evaluation model of the classroom teaching effect was constructed based on convolutional neural network according to the internal relationship between facial expression recognition and classroom teaching effect evaluation. The problem of network depth deepening affecting the accuracy of evaluation in convolutional neural network models was innovatively solved by utilizing the ResNet algorithm. The evaluation of the effectiveness of English online course teaching was achieved. The experimental results showed that this method could effectively improve the effect of English online course teaching evaluation and improve the teaching quality of English online courses.
CODAS method for Pythagorean 2-tuple linguistic MAGDM and applications to quality evaluation of scientific research management in application-oriented universities
Authors: Li Hui
Published: July 2023

The scientific research work of colleges and universities has attracted more and more social attention because of its large number of multidisciplinary scientific and technological talents, hardware facilities and good scientific research environment, and the quality of scientific and technological management work of colleges and universities directly affects the level of scientific and technological work of colleges and universities. Starting from the common problems of scientific research management in colleges and universities, this paper explores the ideas and methods to further promote scientific research work by improving the quality of scientific research management. The quality evaluation of scientific research management in application-oriented universities is classical multiple attribute group decision making (MAGDM). Based on this, we extend the traditional CODAS method to the Pythagorean 2-tuple linguistic sets (P2TLSs) and propose the Pythagorean 2-tuple linguistic CODAS (P2TL-CODAS) method for quality evaluation of scientific research management in application-oriented universities. The P2TL-CODAS method is established and all computing steps are simply presented. Furthermore, we apply the P2TL-CODAS method to evaluate the quality evaluation of scientific research management in application-oriented universities.
A movie recommendation method based on knowledge graph and time series
Authors: Zhang Yiwen , Zhang Li , Dong Yunchun , Chu Jun , Wang Xing , Ying Zuobin
Published: July 2023

Traditional collaborative filtering algorithms use user history rating information to predict movie ratings Other information, such as plot and director, which could provide potential connections are not fully mined. To address this issue, a collaborative filtering recommendation algorithm named a movie recommendation method based on knowledge graph and time series is proposed, in which the knowledge graph and time series features are effectively integrated. Firstly, the knowledge graph gains a deep relationship between users and movies. Secondly, the time series could extract user features and then calculates user similarity. Finally, collaborative filtering of ratings can calculate the user similarity and predicts ratings more precisely by utilizing the first two phases’ outcomes. The experiment results show that the A Movie Recommendation Method Fusing Knowledge Graph and Time Series can reduce the MAE and RMSE of user-based collaborative filtering and Item-based collaborative filtering by 0.06,0.1 and 0.07,0.09 respectively, and also enhance the interpretability of the model.
Optimal adaptive neuro-fuzzy inference system with biogeography-based optimization for numbers of COVID-19 vaccination prediction
Authors: Hsu Pi-Shan , Huang Chien-Chung , Sung Wei-Ying , Tsai Han-Ying , Wu Zih-Xin , Lin Ting-Yu , Lin Kuo-Ping , Liu Gia-Shie
Published: July 2023

This study attempts to develop the adaptive neuro-fuzzy inference system (ANFIS) with biogeography-based optimization (BBO) (ANFIS-BBO) for a case study of the actual number of COVID-19 vaccinations in a medical center, considering the variables of the date and time of vaccination, the brand of vaccine, and the number of open appointments on the government network platform in Taiwan. The COVID-19 has brought about a great burden on the health and economy of the world since the end of 2019. Many scholars have proposed a prediction model for the number of confirmed cases and deaths. However, there is still a lack of research in the prediction model for mass vaccination. In this study, ANFIS-BBO is developed to predict the number of COVID-19 vaccination, and three other forecasting models, support vector machines (SVM), least-square support vector machines (LSSVM) and general regression neural network (GRNN) are employed for forecasting the same data sets. Empirical results show that the ANFIS-BBO with trapezoidal membership function model can achieve better performance than other methods and provide robust predictions for the actual number of COVID-19 mass vaccination.
Using knowledge graphs and contrastive learning for detecting APT Malware on Endpoint systems
Authors: Xuan Cho Do , Nguyen Hoa Dinh
Published: July 2023

Advanced persistent threat (APT) attacking campaigns have been a common method for cyber-attackers to attack and exploit end-user computers (workstations) in recent years. In this study, to enhance the effectiveness of the APT malware detection, a combination of deep graph networks and contrastive learning is proposed. The idea is that several deep graph networks such as Graph Convolution Networks (GCN), Graph Isomorphism Networks (GIN), are combined with some popular contrastive learning models like N-pair Loss, Contrastive Loss, and Triplet Loss, in order to optimize the process of APT malware detection and classification in endpoint workstations. The proposed approach consists of three main phases as follows. First, the behaviors of APT malware are collected and represented as graphs. Second, GIN and GCN networks are used to extract feature vectors from the graphs of APT malware. Finally, different contrastive learning models, i.e. N-pair Loss, Contrastive Loss, and Triplet Loss are applied to determine which feature vectors belong to APT malware, and which ones belong to normal files. This combination of deep graph networks and contrastive learning algorithm is a novel approach, that not only enhances the ability to accurately detect APT malware but also reduces false alarms for normal behaviors. The experimental results demonstrate that the proposed model, whose effectiveness ranges from 88% to 94% across all performance metrics, is not only scientifically effective but also practically significant. Additionally, the results show that the combination of GIN and N-pair Loss performs better than other combined models. This provides a base malware detection system with flexible parameter selection and mathematical model choices for optimal real-world applications.
An integrated cross entropy methodology for planning scheme evaluation of highway transportation hub with interval-valued intuitionistic fuzzy information
Authors: Wang Lu
Published: July 2023

After entering the 21st century, China’s national economy has shown a rapid growth momentum, the comprehensive transportation system has been continuously improved, the road traffic infrastructure has made remarkable achievements, and the modern logistics industry has also risen rapidly and grown rapidly, which has greatly changed the market demand for road transport hubs. The road transport hub is the main node of the road transport network, the hub of passenger and freight distribution of road transport, and the organizational center for the interconnection of road transport and other transport modes and the development of comprehensive transport. Highway transportation hub is an important part of highway transportation infrastructure and plays an important role in highway transportation. The planning scheme evaluation of highway transportation hub is a multi-attribute decision making (MADM). This paper intends to propose a MADM methodology based on cross-entropy (CE) method under interval-valued intuitionistic fuzzy sets (IVIFSs) for planning scheme evaluation of highway transportation hub. First of all, this paper extends the cross entropy method under the IVIFSs to propose the interval-valued intuitionistic fuzzy number CE(IVIFN-CE) method, it enlarges the application range of the CE method. Secondly, a new MADM model for planning scheme evaluation of highway transportation hub based on IVIFN-CE algorithm is proposed.
Visual rehabilitation indicating neuroplasticity in an esotropic adult patient with diplopia after sudden visual acuity loss in the non-amblyopic eye: A case report
Authors: Michalski Andrzej , Dubas Katarzyna , Nogaj Sławomir , Stopa Marcin
Published: July 2023

BACKGROUND: The aim of this case report is to present the successful management of both diplopia and amblyopia in a specific clinical situation, demonstrating neuroplasticity of the visual system in an adult patient. Causes of diplopia include eye pathologies in monocular diplopia and ischemic ocular motor nerve palsies, sudden life-threatening and chronic conditions in central nervous system in binocular diplopia. Strabismic amblyopia and nonarteritic anterior ischemic optic neuropathy are quite often ophthalmic conditions, first one is caused by suppression during developmental period and the latter one by ischemia of the optic nerve in adults. Coexistence of aforementioned conditions may cause unusual clinical situation in which ability of nervous system to functional reorganization could be demonstrated. CASE PRESENTATION: In our adult patient, diplopia was incited by the loss of suppression of the strabismic amblyopic eye, which was the consequence of a sudden decrease of the visual acuity in the previously better eye in the course of nonarteritic anterior ischemic optic neuropathy. This led to impairment in daily activities. RESULTS: Visual training rehabilitation improved distance and near visual acuity in the amblyopic eye over three months, and prescribing two pairs of glasses with prisms enabled the patient to return to daily activities. CONCLUSION: The discussed patient lost the suppression of the strabismic amblyopic eye. Management of amblyopia is usually undertaken in children, however considering neuroplasticity we successfully attempted to improve visual functioning of our patient, despite lower intensity of neuroplasticity functions in an adult brain.
The effects of dynamic motion instability system training on motor function and balance after stroke: A randomized trial
Authors: Shen Jie , Ma Lianjie , Gu Xudong , Fu Jianming , Yao Yunhai , Liu Jia , Li Yan
Published: July 2023

BACKGROUND: The balance and postural control of humans is related to the coordination of dynamic perception and movement. Multiple senses, such as vision, vestibular sense, proprioception, and/or a single sensory disorder, would lead to its integration disorder and induce imbalance and abnormal gait. OBJECTIVE: The present study aimed to determine the effects of dynamic motion instability system training (DMIST) on the balance and motor function of hemiplegic patients after stroke. METHODS: In this assessor-blinded, randomized controlled trial, the participants allocated to the intervention group (n = 20) received 30 minutes of conventional treatment and 20 minutes of DMIST training. Participants randomized to the control group (n = 20) received the same dose of conventional therapy and 20 minutes of general balance training. Rehabilitation was performed 5 times per week for 8 weeks. The primary outcome was the Fugl-Meyer assessment for the lower extremity (FMA-LE), and the secondary outcomes were the Berg balance scale (BBS) and gait function. Data were collected at baseline and immediately after the intervention. RESULTS: After 8 weeks (t1), both groups showed significant post-intervention improvements in BBS, FMA-LE, gait speed and stride length (P < 0.05); there were significant positive correlations between the increase in FMA-LE and gait speed and stride length. Compared with the control group, the DMIST group showed significant post-intervention improvements in FMA-LE, gait speed and stride length (P < 0.05). However, no significant differences between the groups were found over time with respect to BBS (P > 0.05). The experiences of patients with DMIST were positive, and no serious adverse events were related to the interventions. CONCLUSION: Supervised DMIST could be highly effective in treating lower-limb motor function in patients with stroke. Frequent (weekly) and medium-term (8 weeks) dynamic motion instability-guided interventions might be highly effective in enhancing motor function, and subsequently improving gait in stroke patients.
Group-based circuit training to improve mobility after stroke: a cross-sectional survey of German and Austrian physical therapists in outpatient settings
Authors: Diermayr Gudrun , Greisberger Andrea , Stadel Maria , Garbade Sven , Salbach Nancy M.
Published: July 2023

BACKGROUND: A contextual transferability analysis identified group-based circuit training (GCT) as an optimal intervention in German and Austrian outpatient physical therapy to improve mobility post-stroke. GCT incorporates task-oriented, high-repetitive, balance, aerobic and strength training and allows for increased therapy time without increasing personnel. OBJECTIVE: To determine the extent to which German and Austrian physical therapists (PTs) use GCT and its components in the outpatient treatment of stroke-related mobility deficits and to identify factors associated with using GCT components. METHODS: A cross-sectional online survey was conducted. Data were analyzed descriptively and using ordinal regression. RESULTS: Ninety-three PTs participated. None reported using GCT moderately to frequently (4–10/10 patients). The percentage of PTs reporting frequent use (7–10/10 patients) of task-oriented, balance, strength, aerobic, and high-repetitive training was 45.2%, 43.0%, 26.9%, 19.4%, and 8.6%, respectively. Teaching or supervising students, time for evidence-based practice activities at work, and working in Austria was associated with using GCT components frequently. CONCLUSION: German and Austrian PTs do not yet use GCT in outpatient physical therapy for stroke. Almost half of PTs, however, employ task-oriented training as recommended across guidelines. A detailed, theory-driven and country-specific evaluation of barriers to GCT uptake is necessary to inform implementation.
Venous thromboembolism and anticoagulation in spinal cord lesion rehabilitation inpatients: A 10-year retrospective study
Authors: Bluvshtein Vadim , Catz Amiram , Mahamid Ala , Elkayam Keren , Michaeli Dianne , Front Lilach , Kfir Adi , Gelernter Ilana , Aidinoff Elena
Published: July 2023

BACKGROUND: Venous thromboembolism (VTE) is a concern following the onset of spinal cord lesions (SCL). OBJECTIVES: To assess the current efficacy and risks of anticoagulation after SCL and consider changes in thromboprophylaxis. METHODS: This retrospective cohort study included individuals admitted to inpatient rehabilitation within 3 months of SCL onset. Main outcome measures were the incidence of deep vein thrombosis (DVT), pulmonary embolism (PE), bleeding, thrombocytopenia, or death, which occurred within 1 year of the SCL onset. RESULTS: VTE occurred in 37 of the 685 patients included in the study (5.4%, 95% CI 3.7–7.1%, 2.8% PE), and in 16 of 526 patients who received prophylactic anticoagulation at rehabilitation (3%, 95% CI 1.6–4.5%, 1.1% PE, with at least 1 fatality). Of these 526, 1.3% developed clinically significant bleeding and 0.8% thrombocytopenia. Prophylactic anticoagulation, most commonly 40 mg/day, continued until a median period of 6.4 weeks after SCL onset (25% –75% percentiles 5.8–9.7), but in 29.7%, VTE occurred more than 3 months after SCL onset. CONCLUSION: The VTE prophylaxis used for the present cohort contributed to a considerable but limited reduction of VTE incidence. The authors recommend conducting a prospective study to assess the efficacy and safety of an updated preventive anticoagulation regimen.
Does occupational therapy improve activities of daily living and/or cognitive abilities in stroke patients with cognitive impairment? A Cochrane Review summary with commentary1
Authors: Cecchi Francesca
Published: July 2023

BACKGROUND: Cognitive Impairment (CI) after stroke is frequent and often persistent, and is associated with poor functional outcome. Occupational therapy (OT) is aimed at restoring functioning also by addressing CI. OBJECTIVE: Commentary on the review by Gibson et al. (2022) updating a previous Cochrane Review (Hoffmann et al., 2010) to investigate the effectiveness of OT on CI after stroke. METHODS: This review included randomised and quasi-randomised controlled trials evaluating OT for adults with clinically defined stroke and confirmed CI. Outcomes included basic activities of daily living (BADL) (primary), instrumental ADL (IADL), community integration and participation, global cognitive function and specific cognitive abilities. RESULTS: Overall, 24 trials from 11 countries including 1142 participants. For BADL, a small effect below the minimal clinically important difference (MCID) was found immediately after intervention and at six months’ follow-up (low certainty evidence), but not at three months follow-up (insufficient evidence). For IADL, the evidence was very uncertain about an effect, while for community integration, there was insufficient evidence of an effect. For global cognitive performance, there was an improvement of clinical importance after the intervention (low-certainty). There was some effect for attention overall, and for executive functional performance overall (very low-certainty). Of the cognitive subdomains, there was evidence of effect of possible clinical importance, immediately after intervention, only for sustained visual attention (moderate certainty), for working memory (low certainty), and thinking flexibly (low certainty), while there was only low or very low certainty or insufficient evidence of an effect for other cognitive domains/subdomains; CONCLUSION: The authors concluded that the body of evidence for the effectiveness of OT interventions has improved since their first review. However, although their findings provide some support for the potential benefits of OT (mostly based on low certainty evidence), OT effectiveness for stroke patients remains unclear.
Resilient edge machine learning in smart city environments
Authors: Vrachimis Andreas , Gkegka Stella , Kolomvatsos Kostas
Published: July 2023

Distributed Machine Learning (DML) has emerged as a disruptive technology that enables the execution of Machine Learning (ML) and Deep Learning (DL) algorithms in proximity to data generation, facilitating predictive analytics services in Smart City environments. However, the real-time analysis of data generated by Smart City Edge Devices (EDs) poses significant challenges. Concept drift, where the statistical properties of data streams change over time, leads to degraded prediction performance. Moreover, the reliability of each computing node directly impacts the availability of DML systems, making them vulnerable to node failures. To address these challenges, we propose a resilience framework comprising computationally lightweight maintenance strategies that ensure continuous quality of service and availability in DML applications. We conducted a comprehensive experimental evaluation using real datasets, assessing the effectiveness and efficiency of our resilience maintenance strategies across three different scenarios. Our findings demonstrate the significance and practicality of our framework in sustaining predictive performance in smart city edge learning environments. Specifically, our enhanced model exhibited increased generalizability when confronted with concept drift. Furthermore, we achieved a substantial reduction in the amount of data transmitted over the network during the maintenance of the enhanced models, while balancing the trade-off between the quality of analytics and inter-node data communication cost.
Automated lung tumor segmentation robust to various tumor sizes using a consistency learning-based multi-scale dual-attention network
Authors: Lee Jumin , Lee Min-Jin , Kim Bong-Seog , Hong Helen
Published: July 2023

BACKGROUND: It is often difficult to automatically segment lung tumors due to the large tumor size variation ranging from less than 1 cm to greater than 7 cm depending on the T-stage. OBJECTIVE: This study aims to accurately segment lung tumors of various sizes using a consistency learning-based multi-scale dual-attention network (CL-MSDA-Net). METHODS: To avoid under- and over-segmentation caused by different ratios of lung tumors and surrounding structures in the input patch according to the size of the lung tumor, a size-invariant patch is generated by normalizing the ratio to the average size of the lung tumors used for the training. Two input patches, a size-invariant patch and size-variant patch are trained on a consistency learning-based network consisting of dual branches that share weights to generate a similar output for each branch with consistency loss. The network of each branch has a multi-scale dual-attention module that learns image features of different scales and uses channel and spatial attention to enhance the scale-attention ability to segment lung tumors of different sizes. RESULTS: In experiments with hospital datasets, CL-MSDA-Net showed an F1-score of 80.49%, recall of 79.06%, and precision of 86.78%. This resulted in 3.91%, 3.38%, and 2.95% higher F1-scores than the results of U-Net, U-Net with a multi-scale module, and U-Net with a multi-scale dual-attention module, respectively. In experiments with the NSCLC-Radiomics datasets, CL-MSDA-Net showed an F1-score of 71.7%, recall of 68.24%, and precision of 79.33%. This resulted in 3.66%, 3.38%, and 3.13% higher F1-scores than the results of U-Net, U-Net with a multi-scale module, and U-Net with a multi-scale dual-attention module, respectively. CONCLUSIONS: CL-MSDA-Net improves the segmentation performance on average for tumors of all sizes with significant improvements especially for small sized tumors.
Learning technology for detection and grading of cancer tissue using tumour ultrasound images
Authors: Zhang Liyan , Xu Ruiyan , Zhao Jingde
Published: July 2023

BACKGROUND:

Early diagnosis of breast cancer is crucial to perform effective therapy. Many medical imaging modalities including MRI, CT, and ultrasound are used to diagnose cancer.

OBJECTIVE:

This study aims to investigate feasibility of applying transfer learning techniques to train convoluted neural networks (CNNs) to automatically diagnose breast cancer via ultrasound images.

METHODS:

Transfer learning techniques helped CNNs recognise breast cancer in ultrasound images. Each model’s training and validation accuracies were assessed using the ultrasound image dataset. Ultrasound images educated and tested the models.

RESULTS:

MobileNet had the greatest accuracy during training and DenseNet121 during validation. Transfer learning algorithms can detect breast cancer in ultrasound images.

CONCLUSIONS:

Based on the results, transfer learning models may be useful for automated breast cancer diagnosis in ultrasound images. However, only a trained medical professional should diagnose cancer, and computational approaches should only be used to help make quick decisions.
Development of T-ARMS-PCR to Detect MYBPC3 Gene Variation in Hypertrophic Cardiomyopathy (HCM) Patients
Authors: Sadia Haleema , Ahmed Khan Waqas , Hussain Misbah , Murtza Iqra
Published: July 2023

Hypertrophic cardiomyopathy (HCM) is a common and complex, genetically inherited, cardiovascular disorder. It is typically inherited in an autosomal dominant manner with variable penetrance and mutable expression. Mutations in MYBPC3 gene is one of the genetic causes of HCM. Only 0.2% of general population suffers from HCM. The MYBPC3 gene provides instructions for making cardiac myosin binding protein C, which is imperative for the maintenance and regulation of normal cardiac functions. This study aims to explore the reported SNP rs1052373 from exon 30 of MYBPC3 gene in the population of Punjab, Pakistan. The reported SNP rs1052373 was analysed using Tetra Amplification Refractory Mutation System Polymerase Chain Reaction (T-ARMS-PCR) to find the allelic frequency in the selected population. T-ARMS-PCR is a cost effective, flexible, rapid, and accurate tool for genotyping.  The specific sequences of MYBPC3 gene from exons 30 and 31 and introns 29, 30, and 31 were retrieved from NCBI (https://www.ncbi.nlm.nih.gov/). A tetra primer designing tool known as Primer 1 (http://primer1.soton.ac.uk/primer1.html) was used to design the primers for the targeted region of MYBPC3 gene. In this study, the genotyping of previously reported SNP rs1052373 showed variation in the disease group, giving CC, CT, and TT genotypes with the frequency of 0.04. The genotyping analysis of rs1052373 showed that the allelic frequency of homozygous condition T/T was 0.02 and the allelic frequency of heterozygous condition C/T was 0.02 in disease group as compared to the control group. In the latter, the homozygous T/T and heterozygous C/T genotypes were not observed in any individuals. All the individuals in control group carried homozygous C/C genotype. While, the frequency of homozygous C/C genotype was 0.96 in disease group. The findings of this study would help to find novel molecular markers for HCM diagnosis.
Phenotypic and Genotypic Detection of Virulence Factors Affecting Proteus mirabilis Clinical Isolates
Authors: Hayat Fawad , Khan Muddasir , Umair Muhammad , Akbar Sajeela , Javed Rida , Shah Syed Hussain
Published: July 2023

The current study attempts the phenotypic and molecular detection of the virulence factors of Proteus mirabilis clinical isolates. A total of 600 urine samples were collected from urinary tract-infected patients at Khyber Teaching Hospital, Peshawar, Pakistan. P. mirabilis isolates were identified through different biochemical tests. Virulence factors including urease production, biofilm formation, and swarming phenomenon were determined by using different markers (ureC1, rsbA, and luxS genes), identified via the polymerase chain reaction (PCR) technique. Out of the selected samples, 95 samples (15.83%) were identified as P. mirabilis. The molecular study showed that all isolates (100%) possessed the ureC gene. Whereas, 90.52% and 92.63% of the isolates gave positive results for biofilm formation (rsbA gene) and swarming phenomenon (luxS gene), respectively. The phenotypic and molecular study of P. mirabilis virulence factors provides a better understanding of how P. mirabilis infection spreads. The results could be used for prevention and improvements in its clinical treatment.
Shape-Preserving Curve and Surface Data Embedding Algorithm
Authors: Ibraheem Farheen , Samreen Shamaila , Bilal Riaz Muhammad , Arooj Tayba
Published: July 2023

In this study, shape preserving data driven rational cubic schemes are developed. A rational cubic piecewise function (quadratic denominator and cubic numerator) with two parameters was transformed to C1 rational cubic piecewise function. Constraints were derived on free parameters by means of some mathematical derivations to train and demonstrate convex curve. The scheme, then, was advanced to partially blended rational bi-cubic function with eight free parameters which were controlled to ascertain convex surface. A numerical comparison with certain existing schemes manifested that the proposed method was economical. The proposed scheme was put into visualization of convex 2D and 3D data using MATLAB software packet. Additionally, the suggested approach produced a more visually appealing interpolating curve for scientific visualization for specific data sets.
PENGARUH PEMAKAIAN BAHAN TAMBAH TAWAS PADA AIR RAWA TERHADAP COMPRESSIVE STENGTH BETON
Authors: Oemiati Nurnilam Oemiati , Royan Noto
Published: July 2023

Kenten Laut is a rural locality in the Talang Kelapa District that consists largely of a swamp. Residentsrely heavily on the swamp's corrosive water for mundane concrete mixing. Researchers in this study usedswamp water and alum in the concrete recipe. Swamp water and alum were utilized as the supplementarycomponents, with the alum content of the solution varying between 2% and 4% by weight of cement. Thetest object is a cube with the dimensions (15, 15, and 15) cm and there are fifty of them.Compressive strength testing in swamp water revealed findings of 152.69 kg/cm2 for 14-day-old concreteand 251.93 kg/cm2 for 28-day-old concrete. The compressive strength of 14-day-old swamp water concretevaried between 156.16 kg/cm2 and 149.78 kg/cm2 depending on the percentage of alum added to the mix.Compressive strength values for 28-day-old concrete made with swamp water with 2%, 4%, or 6% alumare 256.19 kg/cm2, 253.97 kg/cm2, and 245.61 kg/cm2, respectively. These numbers are lower than whatwas anticipated for the K-300. Compressive strength in typical concrete drops by 20.6% after 28 days ofage, but only 14.7% after 14 days.
KAJIAN FINANSIAL PENGADAAN PERALATAN PENGUKUR KETIDAKRATAAN JALAN LASER PROFILEMETER KELAS I HAWKEYE 2000 DI LINGKUNGAN BALAI PELAKSANAAN JALAN NASIONAL BENGKULU
Authors: Budiharto Punto , Amanah Tody
Published: July 2023

Balai Pelaksanaan Jalan Nasional (BPJN) Bengkulu was born based on PUPR Regulation Number. 26 of2020. The Function is the implementation of feasibility studies, surveys, investigation, and evaluation ofplanning for the technical field of road and bridge including road safety. The Important type of survey arelongitudinal profile survey International Roughness Index (IRI), and Pavement Condition Index (PCI). TheMethod is to examined secondary data obtained from literature review and analyzed financial data (NetPresent Value, Benefit Cost Ratio, and Payback Period. The author builds four scenarios (pessimistic,medium, optimistic, and do nothing). The Benefit Cost Ratio for the scenario 1 (pessimist) is 0.33, thescenario 2 (medium) is 1.54, the scenario 3 (optimistic) is 2.82, and the scenario 4 (do-nothing) is N/A.Value of Payback Period for the scenario 2 (medium) is 5.62 years, and the scenario 3 (optimistic) is 2.79years. Based on the analysis, the decision to purchase a Hawkeye 2000 digital laser profilemeter withinBPJN Bengkulu is financially feasible as long as the hawkeye used not only for Internal, but as a source ofPNBP from client like private sector or provincial government, and distric or city governments in BengkuluProvince.
ANALISA WAKTU DAN BIAYA DENGAN METODE EARNED VALUE ANALYSIS PADA PEKERJAAN PROYEK PEMBANGUNAN JEMBATAN
Authors: Revisdah Revisdah , Arfan Muhammad , Jonizar Jonizar , Arravi Rajulian Nurkholis
Published: July 2023

Due to the intricacy of the challenges that arise during the execution of work, a significant amount of thework that is done does not conform to the one that was intended. Neither on time, quality, nor the price,which is something that sometimes happens overbugdet. To be successful in overcoming this obstacle, youwill need to have excellent cost, quality, and time management.Using the Value of Results Method is oneof the many ways that construction work may be handled in an efficient and straightforward manner. Thisstudy's objective is to arrive at an estimate of the time and money required to complete the project interms of how much it will effect the cost if it happens. Using the Earned Value Analysis approach is theresearch method that will be used to determine how to assess the value of the outcomes on projectperformance in terms of time and cost as well as the expected amount of time needed to finish the project.Based on the application of the results value that was studied during a period of 54 weeks, it wasdiscovered that the completion of the project would experience an acceleration of work, specifically for74.4 weeks, when the anticipated duration was 76 weeks. This was discovered after the results value wasexamined within a period of 54 weeks. In the meanwhile, when it came to the expenses of the job, it didnot come out as expected, which was Rp. 71.424.373.019. The ultimate sum of all costs associated withthe project was Rp 66.081.465.169. The fact that there is a gap of -Rp.5.342.907.850 between the overallcost of the work and the cost of the plan indicates that the project will be profitable.
PENGARUH PEMANFAATAN AIR EKSTRAKSI ECENG GONDOK TERHADAP KUAT TEKAN BETON K-175
Authors: Setiobudi Agus , Purwanto Herry
Published: July 2023

This study aims to determine the compressive strength value of K-175 concrete with variations in theaddition of water hyacinth extraction water. The research method used was a laboratory experiment, bydetermining the cement water factor and the composition of the new mixture. In this study, 24 cube testobjects were made using variation of water hyacinth extrac mixtures of 1%, 3% and 5%. The results of thisstudy were the compressive strength value of the average normal K-175 concrete at the age of 14 and28days the compressive strength results were 144.3 kg/cm2 and 184.3 kg/cm2, while the compressive strengthwith variations in the addition of 1% water hyacinth extraction water was of 154.8 kg/cm2 and196.4 kg/cm2, variations in the addition of 3% water hyacinth extraction water was 164.7 kg/cm2 and212.3 kg/cm2, while for variations in the addition of 5% was 149.6 kg/cm2 and 193.4 kg/cm2. The optimumcompressive strength obtained in this study was the variation of 3% water hyacinth extracti mixture for theage for 28 days of age, which was 212.3 kg/cm2.
Pemidanaan Terhadap Pelaku Zina (Suami/Istri Selingkuh)
Authors: Ardha Dea Justicia , Emilson Nur Husni , Kasra Helwan Kasra , Rusydi Yudistira Rusydi , Okpirianty Reny Okpirianty , Rani Febrina Hertika , Mulkan Hasanal Mulkan , Sarah Sarah Sarah
Published: July 2023

Fenomena mengenai perselingkuhan semakin marak akhir-akhir ini. Hampir setiap hari media cetak maupun elektronik sering menampilkan berita hangat mengenai kasus perselingkuhan. Perselingkuhan dalam pernikahan bersifat merusak dan dapat menimbulkan akibat negatif. Akibat negatif yang ditimbulkan dapat terjadi pada pelaku perselingkuhan maupun pasangan pelaku perselingkuhan. Selingkuh adalah perbuatan zina karena intinya adalah hubungan seksual secara illegal antara dua insan yang berbeda jenis tanpa ikatan perkawinan. Karena itu tidak ada hukum yang mentolerir perbuatan tersebut, masyarakat pun mencelanya, apalagi norma agama (Islam) tidak membenarkannya. Dalam KUHP Indonesia dijelaskan bahwa yang dinamakan zina adalah sebagaimana disebutkan di dalam pasal 284 KUHP sebagai sebuah tindak pidana dengan hukuman penjara selama-lamanya sembilan bulan, dengan ketentuan sebagai berikut: a. Laki-laki yang beristeri yang berzina sedang diketahuinya bahwa pasal 27 KUHP berlaku baginya. b. Perempuan yang bersuami yang berzina.
PENDAMPINGAN GURU DALAM PENGISIAN KONTEN MATERI AJAR TATA BAHASA INGGRIS DASAR PADA WEBSITE GRAMMAR
Authors: Sari Fatimah Mulya
Published: July 2023

Proses pengajaran Bahasa Inggris melalui website pembelajaran sudah banyak disediakan oleh guru-guru milenial di Indonesia. Keterampilan dan kreatifitas dalam menyajikan materi-materi ajar pun harus dimiliki oleh guru agar website online yang dikelola dapat dimanfaatkan untuk belajar secara optimal oleh para pengguna, terutama untuk kalangan pelajar. Tujuan dari kegiatan pengabdian kepada masyarakat ini adalah untuk melakukan pendampingan kepada guru-guru dalam proses pengisian konten pembelajaran tata Bahasa Inggris dasar melalui website grammar. Salah satu kendala yang terjadi kepada guru adalah belum terbiasanya mengoperasikan teknologi, terutama dalam mengelola dan mengisi konten dari sebuah website pembelajaran. Tahapan kegiatan pengabdian ini dilakukan dari tahapan persiapan, tahapan pelaksanaan kegiatan pendampingan, dan tahapan evaluasi pelaksanaan kegiatan pendampingan. Dari kegiatan pengabdian ini, hasil menunjukkan bahwa kegiatan pendampingan dapat memberikan solusi yang baik dan optimal untuk membiasakan guru-guru belajar untuk mengelola website secara efektif sehingga isi pembahasan dalam website tersebut dapat membantu siswa untuk belajar secara efektif dan efisien.