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International Conference on Contemporary Computing and Informatics (IC3I)

作者： Girish Singh Bisht Arpit Jain Vandna Bansla Khemraj Sharma Rudramani Bhutia Vikas Kumar Department of Computer Science & Engineering Tula’s Institute Dehradun India Department of Computer Science & Engineering Koneru Lakshamaiah Education Foundation Vadessahwaram A.P. India Shivalik Engineering College Dehradun India Department of Business Administration Doctoral Program in Management Sciences Nanhua University Dalin Chiayi Taiwan R.O.C. Department of Computer Science & Engineering Koneru Lakshmaiah Education Foundation A.P. India School Engineering and Computing Dev Bhoomi Uttrakhand University Dehradun Uttrakhand India

ISBN: (数字)9798350350067

ISBN: (纸本)9798350350074

Copy-move forgeries often exploit homogeneous regions in images with large-scale attacks to either highlight or conceal target objects. These manipulations are simple to execute but challenging to notice. Forgery detection techniques like Copy-Move Forgery Detection (CMFD) cannot detect these forged documents because they are unable to identify a sufficient number of effective keypoints in homogeneous areas, leading to inaccurate and inefficient results. SURF stands for Speeded-Up Robust Features and is used in this paper along with A-KAZE and Scale-Invariant Feature Transforms. According to our experiment, A-KAZE offers superior detection performance under diverse attacks, especially when it comes to large-scale attacks targeting homogeneous regions. A-KAZE is found to be more accurate than SIFT, SURF, and A-KAZE when applied to the NB-CASIA dataset, achieving detection accuracies of $\mathbf{8 9. 2 \%}, \mathbf{9 3. 9 \%}$ and $\mathbf{9 8. 9 8 \%}$.)

关键词： Accuracy Digital images Forensics Transforms Forgery Computational efficiency Reliability Informatics Software development management

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Enzymatic Synthesis, Characterization, and Application of Sucrose Ester Derived from Palm Kernel Oil Methyl Ester as Food Emulsifier

SSRN

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SSRN 2024年

作者： Rahmi, Rahmi Kurniasih, Eka Darusman, Darusman Supardan, Muhammad Dani Doctoral Program in Agricultural Science Universitas Syiah Kuala Banda Aceh23111 Indonesia Department of Chemistry Faculty of Mathematics and Natural Science Universitas Syiah Kuala Banda Aceh23111 Indonesia Department of Soil Science Faculty of Agriculture Universitas Syiah Kuala Banda Aceh23111 Indonesia Department of Chemical Engineering Faculty of Engineering Universitas Syiah Kuala Banda Aceh23111 Indonesia

Sucrose ester (SEs) is an emulsifier that is widely used in many kinds of food products. Its application improves flavor, color, and texture. SEs was synthesized from palm kernel oil methyl ester (PKOME) and sucrose using Candida antarctica lipase enzyme as a biocatalyst. The enzymatic synthesis occurred at 30°C, with a Candida antarctica load of 50 mg, and a stirring speed of 250 rpm. The crude SEs was purified by vacuum filtration and then dried at 35-40°C for 6-8 h. This study aimed to obtain the optimal substrate conversion depending on 2 affecting factors: reaction time and sucrose concentration. Determination of the reaction time was carried out at 2-20 h, and sucrose concentration at 100-1,000 ***-1. The substrate conversion was determined using the refractive index (oBrix value) and then validated with a spectrophotometer-UV. The study found that an optimal substrate conversion of 87.8% had been achieved at a sucrose concentration of 400 ***-1, lasted for 12 h. The characteristics of optimal SEs were as follows: SEs purity was 91.82%, free sucrose was 1.75%, acid value was 2.93%, and free methanol was 0.11%. SEs was an o/w emulsifier with an HLB value of 12.35. The functional groups of SEs were O-H, C-H2, C-H, C=O, and C-O, which differed from substrates. In addition, applying SEs of 0.6% (w/v) in a coconut milk emulsion enriched with cooking oil maintains emulsion stability with a creaming index of 54.30% and a pH of 5.75 for 7 days of storage. © 2024, The Authors. All rights reserved.

关键词： Sugar (sucrose)

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The Effect of Road Network and the Freight Transport Operation to the Development of the Region and Welfare of the Society in Langkat Regency 2

The Effect of Road Network and the Freight Transport Operati...

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2nd International Conference on Sciences and Technology Applications, ICOSTA 2020

作者： Tarigan, Harimin Rahim Matondang, A. Lubis, Suwardi Sirojuzilam Doctoral Program in Regional Planning Universitas Sumatera Utara Medan Indonesia Department of Industrial Engineering Universitas Sumatera Utara Medan Indonesia Department of Communication Science Universitas Sumatera Utara Medan Indonesia Department of Development Economics Universitas Sumatera Utara Medan Indonesia

This study aims to determine the effect of the road network and the implementation of freight transportation on regional development and the community welfare in Langkat Regency. This type of research is associative and explanatory research whose data are obtained through surveys. The study population was drivers of motor vehicles transporting goods in Langkat Regency. The number of samples is 305 respondents by means of probability sampling and data analysis techniques using Structural Equation Modelling (SEM). The results showed that the road network variables did not significantly influence the community welfare, but the road network had a significant and positive effect on the community welfare through the development of the Langkat Regency. The implementation of freight transportation has a significant and positive effect on the community welfare partially, directly and through the development of the Langkat Regency. Regional development has a significant and positive effect on the community welfare of Langkat Regency. © Published under licence by IOP Publishing Ltd.

关键词： Freight transportation

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Scoliocorrector Fatma-UI for correction of adolescent idiopathic scoliosis: Development, effectivity, safety and functional outcome

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World Journal of Orthopedics 2024年第1期15卷 61-72页

作者： Phedy Phedy Ismail Hadisoebroto Dilogo Wresti Indriatmi Sugeng Supriadi Marcel Prasetyo Fitri Octaviana Zairin Noor Doctoral Program in Medical Sciences Faculty of Medicine University of IndonesiaJakarta Pusat 10430DKI JakartaIndonesia Department of Orthopaedic and Traumatology Universitas IndonesiaJakarta 10430DKI JakartaIndonesia Department of Dermatology and Venereology Faculty of MedicineUniversity of IndonesiaJakarta Pusat 10430DKI JakartaIndonesia Faculty of Mechanical Engineering University of IndonesiaDepok 16424Jawa BaratIndonesia Department of Radiology University of IndonesiaJakarta Pusat 10430DKI JakartaIndonesia Department of Neurology Faculty of MedicineUniversity of IndonesiaJakarta Pusat 10430DKI JakartaIndonesia Research Center for Osteoporosis Department of Orthopaedic and TraumatologyLambung Mangkurat UniversityBanjarmasin 70123Kalimantan SelatanIndonesia

BACKGROUND Adolescent idiopathic scoliosis remains a major problem due to its high incidence,high risk,and high *** of the aims of the management in scoliosis is to correct the *** techniques are available to correct scoliosis deformity;however,they are all far from ideal to achieve three-dimensional correction in *** To develop a set of tools named Scoliocorrector Fatma-UI(SCFUI)to aid threedimensional correction and to evaluate the efficacy,safety,and functional *** This study consists of two *** the first stage,we developed the SCFUI and tested it in finite element and biomechanical *** second stage was a single-blinded randomized clinical trial to evaluate the SCFUI compared to direct vertebral rotation(DVR).Forty-four subjects with adolescent idiopathic scoliosis were randomly allocated into the DVR group(n=23)and SCFUI group(n=21).Radiological,neurological,and functional outcome was compared between the *** Finite element revealed the maximum stress of the SCFUI components to be between 31.2-252 *** analysis revealed the modulus elasticity of SCFUI was 9561324±633277 *** groups showed improvement in Cobb angle and sagittal profile,however the rotation angle was lower in the SCFUI group(11.59±7.46 vs 18.23±6.39,P=0.001).Neurological and functional outcome were comparable in both *** We concluded that SCFUI developed in this study resulted in similar coronal and sagittal but better rotational correction compared to *** safety and functional outcomes were also similar to DVR.

关键词： Adolescent idiopathic scoliosis Scoliocorrector Fatma-UI Scoliosis surgery Posteromedial translation Direct vertebral rotation

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Stroke Prognostication in Patients Treated with Thrombolysis Using Random Forest

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Open Neuroimaging Journal 2024年 17卷

作者： Yunus, Reyhan Eddy Harris, Salim Sidipratomo, Prijo Kekalih, Aria Jatmiko, Wisnu Pandelaki, Jacub Rachman, Andhika Syahrul, Syahrul Valindria, Vanya Vabrina Rachmadi, Muhammad Febrian Muzakki, Muhammad Faris Tjuatja, Andrew Wijaya, Anthony Eka Teresa, Devina Faculty of Medicine Universitas Indonesia Rumah Sakit Umum Pusat Nasional Cipto Mangunkusumo Doctoral Program in Medical Sciences Faculty of Medicine Universitas Indonesia Faculty of Computer Science Universitas Indonesia Faculty of Medicine Universitas Syiah Kuala School of Electrical Engineering and Informatics Institut Teknologi Bandung

Background: Early identification and accurate prognostication of acute ischemic stroke are crucial due to the narrow time frame for treatment and potential complications associated with thrombolysis intervention. Objectives: This pilot study in the Southeast Asian region using Indonesian data, aims to develop a novel machine learning model for predicting the clinical outcome of acute ischemic stroke patients following thrombolysis. The model seeks to aid clinicians in identifying eligible candidates for thrombolysis therapy. Methods: This retrospective study at Cipto Mangunkusumo Hospital’s medical records from 2014 to 2023 used non-contrast brain CT, clinical, and lab data to develop a Random Forest (RF) algorithm predicting Δ NIHSS (National Institutes of Health Stroke Scale) score, indicating functional outcome. The developed RF model was applied to a validation dataset, with performance evaluated. The study also compared RF with a previous Convolutional Neural Networks (CNN) algorithm. Results: This study included 145 acute ischemic stroke patients treated with thrombolysis. It demonstrated the promising feasibility of using machine learning algorithms to predict clinical outcomes in this population. Integration of CT, clinical, and laboratory data as inputs to the RF models shows the best prediction performance (Accuracy = 0.75, AUC = 0.72, F1=0.50, Precision=0.60, Sensitivity=0.43, Specificity=0.88) Conclusions: The application of machine learning shows the potential to enhance the selection process for thrombolysis intervention in treating acute ischemic stroke. Further research with larger multicenter datasets and additional imaging modalities is required to improve predictive ability. © 2024 The Author(s).

关键词： Artificial intelligence International license Machine learning Prognostication Stroke Thrombolysis

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Borneo Smart Forest Information System for Management of Dipterocarp Plants in Kalimantan Rainforest

Borneo Smart Forest Information System for Management of Dip...

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Information Technology International Seminar (ITIS)

作者： Masna Wati Novianti Puspitasari Ummul Hairah Joan Angelina Widians Anindita Septiarini Ade Fiqri Tjikoa Dept. of Informatics Faculty of Engineering Universitas Mulawarman Samarinda Indonesia Dept. of Informatics Universitas Mulawarman Doctoral Program Dept. of Computer Science and Electronics Universitas Gadjah Mada Yogyakarta Indonesia

ISBN: (纸本)9798350398205

Kalimantan’s tropical rainforest is home to indigenous plants of the Dipterocarpaceae family (tribe), which is renowned for having the most endemic species. Dipterocarp is a family of pantropical plants, many of which are used in the wood industry. This study aims to provide information on the potential of Dipterocarp in Kalimantan forests. Education and conservation efforts for Dipterocarp trees, a prominent component of the forest ecosystem, are crucial in light of the significant harm done to Kalimantan’s rainforests. The authors develop the Borneo Smart Forest information system. This system digitally organizes data on the diversity of Dipterocarp in the Kalimantan rainforest based on Web and QR-Code technology. Borneo Smart Forest (BSF) system for monitoring plant inventory and plant markers can be read by smartphones using QR codes. It gives visitors a comprehensive overview of the plants. A QR code is a printed, two-dimensional barcode with limited space for data storage. This technology allows the plant to show earlier administrator-made additions to the inventory information system. The QR code will direct the user to the BSF website, which has data about the plants. The development of this system is one of the efforts to support the achievement of Dipterocarp conservation.

关键词： Seminars Memory Forestry QR codes Vegetation Wood industry Information technology

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Targeting chondroitin sulfate suppresses macropinocytosis of breast cancer cells by modulating syndecan-1 expression

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Molecular Oncology 2024年第10期18卷 2569-2585页

作者： Yen, Hung-Rong Liao, Wen-Chieh Chen, Chia-Hua Su, Ying-Ai Huang, Ying-Wei Hsiao, Chi Chou, Yu-Lun Chu, Yin-Hung Shih, Pin-Keng Liu, Chiung-Hui Department of Chinese Medicine China Medical University Hospital Taichung Taiwan Chinese Medicine Research Center and School of Chinese Medicine College of Chinese Medicine China Medical University Taichung Taiwan Doctoral Program in Tissue Engineering and Regenerative Medicine College of Medicine National Chung Hsing University Taichung Taiwan Department of Post-Baccalaureate Medicine College of Medicine National Chung Hsing University Taichung Taiwan Molecular Medicine Research Center Chang Gung University Taoyuan Taiwan College of Medicine Chung Shan Medical University Taichung Taiwan Department of Surgery China Medical University Hospital Taichung Taiwan School of Medicine China Medical University Taichung Taiwan

Accumulation of abnormal chondroitin sulfate (CS) chains in breast cancer tissue is correlated with poor prognosis. However, the biological functions of these CS chains in cancer progression remain largely unknown, impeding the development of targeted treatment focused on CS. Previous studies identified chondroitin polymerizing factor (CHPF;also known as chondroitin sulfate synthase 2) is the critical enzyme regulating CS accumulation in breast cancer tissue. We then assessed the association between CHPF-associated proteoglycans (PGs) and signaling pathways in breast cancer datasets. The regulation between CHPF and syndecan 1 (SDC1) was examined at both the protein and RNA levels. Confocal microscopy and image flow cytometry were employed to quantify macropinocytosis. The effects of the 6-O-sulfated CS-binding peptide (C6S-p) on blocking CS functions were tested in vitro and in vivo. Results indicated that the expression of CHPF and SDC1 was tightly associated within primary breast cancer tissue, and high expression of both genes exacerbated patient prognosis. Transforming growth factor beta (TGF-β) signaling was implicated in the regulation of CHPF and SDC1 in breast cancer cells. CHPF supported CS–SDC1 stabilization on the cell surface, modulating macropinocytotic activity in breast cancer cells under nutrient-deprived conditions. Furthermore, C6S-p demonstrated the ability to bind CS-SDC1, increase SDC1 degradation, suppress macropinocytosis of breast cancer cells, and inhibit tumor growth in vivo. Although other PGs may also be involved in CHPF-regulated breast cancer malignancy, this study provides the first evidence that a CS synthase participates in the regulation of macropinocytosis in cancer cells by supporting SDC1 expression on cancer cells. © 2024 The Authors. Molecular Oncology published by John Wiley & Sons Ltd on behalf of Federation of European Biochemical Societies.

关键词： breast cancer chondroitin sulfate CHPF macropinocytosis syndecan 1

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Photovoltaic Microinverter with Hybrid Energy Storage System (HESS) and Virtual Impedance Control for Injection into a Microgrid

Photovoltaic Microinverter with Hybrid Energy Storage System...

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IEEE Annual Southern Power Electronics Conference (SPEC)

作者： Patricio Gaisse Javier Muñoz Marco Rivera Carlos Restrepo Galina Mirzaeva Engineering Systems Doctoral Program Faculty of Engineering University of Talca Curicó Chile Department of Electrical Engineering Faculty of Engineering Universidad de Talca Curicó Chile Doctorate in Engineering Systems Faculty of Engineering Universidad de Talca Curicó Chile School of Electrical Engineering and Computer Science The University of Newcastle Callaghan NSW Australia

In this work, a photovoltaic (PV) microinverter is developed, which includes an hybrid energy storage system based on a battery and an ultracapacitor that are connected in parallel to the dc-link through two buck-boost bidirectional converters. The PV panel is connected in parallel to dc-link through an unidirectional boost converter. For the dc-ac stage, a two-stage Flyback / H-bridge inverter will be considered, which will be used to inject the available power into a microgrid. The study proposes the necessary control strategies to manage the power flow according to generation and injection conditions, where a virtual impedance loop is incorporated in the control of the energy storage elements. The presented results confirm the suitability of the proposed strategy.

关键词： Photovoltaic systems Microgrids Hybrid power systems Batteries Circuit stability Topology Impedance

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A computational framework for longitudinal medication adherence prediction in breast cancer survivors: A social cognitive theory based approach

arXiv

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arXiv 2025年

作者： Kaur, Navreet Gonzales, Manuel Alcaraz, Cristian Garcia Gong, Jiaqi Wells, Kristen J. Barnes, Laura E. Department of Systems and Information Engineering University of Virginia CharlottesvilleVA United States SDSU/UC San Diego Joint Doctoral Program in Clinical Psychology San DiegoCA United States Department of Computer Science The University of Alabama TuscaloosaAL United States Department of Psychology San Diego State University San DiegoCA United States

Non-adherence to medications is a critical concern since nearly half of patients with chronic illnesses do not follow their prescribed medication regimens, leading to increased mortality, costs, and preventable human distress. Amongst stage 0-3 breast cancer survivors, adherence to long-term adjuvant endocrine therapy (i.e., Tamoxifen and aromatase inhibitors) is associated with a significant increase in recurrence-free survival. This work aims to develop multi-scale models of medication adherence to understand the significance of different factors influencing adherence across varying time frames. We introduce a computational framework guided by Social Cognitive Theory for multi-scale (daily and weekly) modeling of longitudinal medication adherence. Our models employ both dynamic medication-taking patterns in the recent past (dynamic factors) as well as less frequently changing factors (static factors) for adherence prediction. Additionally, we assess the significance of various factors in influencing adherence behavior across different time scales. Our models outperform traditional machine learning counterparts in both daily and weekly tasks in terms of both accuracy and specificity. Daily models achieved an accuracy of 87.25% (Precision – 92.04%, Recall – 93.15%, Specificity – 77.50%), and weekly models, an accuracy of 76.04% (Precision – 75.83%, Recall – 85.80%, Specificity – 72.30%). Notably, dynamic past medication-taking patterns prove most valuable for predicting daily adherence, while a combination of dynamic and static factors is significant for macro-level weekly adherence patterns. While our models exhibit strong predictive performance, they are constrained by potential cohort-specific biases, reliance on self-reported adherence data, and a limited understanding of the context around non-adherence. Future research will focus on external validation across diverse populations and explore the real-world implementation of sensor-rich systems for a more compre

关键词： Endocrinology

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Hand-Woven Fabric Motif Recognition Methods: A Systematic Literature Review

Hand-Woven Fabric Motif Recognition Methods: A Systematic Li...

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International Conference on Informatics, Multimedia, Cyber and Information System (ICIMCIS)

作者： Handrie Noprisson Ermatita Ermatita Abdiansah Abdiansah Vina Ayumi Mariana Purba Marissa Utami Doctoral Program in Engineering Universitas Sriwijaya Palembang Indonesia Faculty of Computer Science Universitas Sriwijaya Palembang Indonesia Program of Informatics Management Politeknik Anika Palembang Indonesia Faculty of Engineering Muhammadiyah University of Bengkulu Bengkulu Indonesia

ISBN: (纸本)9781665427340

Knowledge of hand-woven motif recognition is only owned by the older generation, which has not been passed down to the younger generation. Moreover, computer technology can be used to support the recognition of traditional woven fabric motifs. The aim of this research is to conduct a literature review on hand-woven fabric motif recognition, with an emphasis on performance accuracy, techniques, and datasets utilized. This research included three distinct stages of systematic literature review (SLR): planning, execution, and reporting of findings. We found several datasets between 924,845 data and the number of classes between 3–25 class. Based on research result, we obtained several methods for hand-woven fabric motif recognition focused on performance examination. We recommended image pre-processing method, including Adaptive Filtering Denoising, Adaptive Wiener Filtering, Histogram Equalization, Gradient Pyramid (GP) Decomposition. Moreover, we suggested five feature extraction methods, including Radon Transform, Wavelet Transform, Locally Rotation Invariance Measure (LBP-ROR), Transform Invariant Low-Rank Textures (TILT) and Histogram of Oriented Gradients (HOG). For learning method, we recommend Fuzzy C-Mean (FCM), Convolutional neural network (CNN), Deep Neural Network (DNN), MobileNets, Inception-v3 and ResNet-50.

关键词： Wavelet transforms Histograms Wiener filters Systematics Bibliographies Neural networks Fabrics

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