Results in Engineering最新文献_第3页

AndroMD: An Android malware detection framework based on source code analysis and permission scanning AndroMD：基于源代码分析和权限扫描的Android恶意软件检测框架

IF 7.9

Results in Engineering Pub Date : 2025-09-10 DOI: 10.1016/j.rineng.2025.107050

Arvind Prasad , Shalini Chandra , Wael Mohammad Alenazy , Gauhar Ali , Sajid Shah , Mohammed ElAffendi

{"title":"AndroMD: An Android malware detection framework based on source code analysis and permission scanning","authors":"Arvind Prasad , Shalini Chandra , Wael Mohammad Alenazy , Gauhar Ali , Sajid Shah , Mohammed ElAffendi","doi":"10.1016/j.rineng.2025.107050","DOIUrl":"10.1016/j.rineng.2025.107050","url":null,"abstract":"<div><div>The rapid growth of Android-based mobile and IoT applications has significantly increased the attack surface for malicious actors. These adversaries often exploit apps and social engineering to deliver malware that compromises device security and user privacy. To address this ongoing threat, we present AndroMD, an intelligent and scalable Android malware detection framework that combines automated dataset construction, optimal feature selection, and ensemble-based classification. The proposed framework is built on three core components. First, an automated pipeline processes over 600,000 APKs to extract static features from more than 140 million Java files and 600,000 manifest files, resulting in three distinct datasets: KeyCount, ZeroOne, and MNF. These datasets are constructed using keys and patterns derived from a detailed analysis of real decompiled malware code, ensuring semantic relevance. Second, we introduce the AndroMD Optimal Feature Selection (AOFS) method, which selects compact, high-performing feature subsets using iterative evaluation based on ensemble feedback. Third, an ensemble detection model combines Random Forest, Decision Tree, and Bagging classifiers, with a threshold-based aggregation mechanism that allows fine-grained control over detection sensitivity. Extensive evaluation demonstrates AndroMD's strong performance, achieving up to 99.88% accuracy on internal datasets and 91.66% accuracy in live testing, including detection of custom and zero-day malware samples. AndroMD also identifies threats overlooked by VirusTotal, showcasing its real-world applicability. The framework, along with sample datasets and code, is made publicly available to support reproducibility and further research on Android security.</div></div>","PeriodicalId":36919,"journal":{"name":"Results in Engineering","volume":"28 ","pages":"Article 107050"},"PeriodicalIF":7.9,"publicationDate":"2025-09-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145047542","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Medical waste management in the modern healthcare era: A comprehensive review of technologies, environmental impact, and sustainable practices 现代医疗保健时代的医疗废物管理：对技术、环境影响和可持续做法的全面审查

IF 7.9

Results in Engineering Pub Date : 2025-09-10 DOI: 10.1016/j.rineng.2025.107210

Hossein Nematollahi , Maryam Tuysserkani , Ali Nematollahi

{"title":"Medical waste management in the modern healthcare era: A comprehensive review of technologies, environmental impact, and sustainable practices","authors":"Hossein Nematollahi , Maryam Tuysserkani , Ali Nematollahi","doi":"10.1016/j.rineng.2025.107210","DOIUrl":"10.1016/j.rineng.2025.107210","url":null,"abstract":"<div><div>This comprehensive review addresses critical challenges in modern medical waste management, a concern significantly heightened by the COVID-19 pandemic. Our work uniquely synthesizes and critically assesses emerging technologies, their economic feasibility, and sustainability frameworks within a post-COVID-19 context. The analysis reveals that while conventional incineration remains a dominant practice (60–75 % of global medical waste), it carries considerable environmental risks. In contrast, emerging solutions like plasma gasification and advanced pyrolysis are promising, but face significant implementation barriers. While plasma systems achieve a 90–97 % waste volume reduction and over 99.99 % pathogen elimination, and pyrolysis efficiently converts plastic waste into valuable fuels (35–50 wt% liquid oil), their high capital costs and operational complexities require careful consideration. The COVID-19 pandemic exacerbated waste pressures, increasing global medical waste production by an estimated 3.4 kg per bed per day, with surges up to 425 % in developing nations. We identify significant disparities in management, as many low-income countries face substantial infrastructure and resource challenges that hinder the adoption of these advanced technologies. This work concludes with a critical roadmap for future research and policy, emphasizing the need for robust technical innovations and harmonized international standards to foster more sustainable and pragmatic practices.</div></div>","PeriodicalId":36919,"journal":{"name":"Results in Engineering","volume":"28 ","pages":"Article 107210"},"PeriodicalIF":7.9,"publicationDate":"2025-09-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145057299","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Q-GRID SMART: A blockchain-enabled smart home energy management and analytics system Q-GRID SMART：一个基于区块链的智能家居能源管理和分析系统

IF 7.9

Results in Engineering Pub Date : 2025-09-10 DOI: 10.1016/j.rineng.2025.107093

Ameni Boumaiza

引用次数: 0

Advanced biomolecule sensing: Simulation and sensitivity analysis of a dielectric-modulated bilayer electrode in DGOTFT 先进生物分子传感：DGOTFT中介电调制双层电极的模拟与灵敏度分析

IF 7.9

Results in Engineering Pub Date : 2025-09-09 DOI: 10.1016/j.rineng.2025.107039

Chandaboina Pavan Kumar, Manish Kumar Singh

{"title":"Advanced biomolecule sensing: Simulation and sensitivity analysis of a dielectric-modulated bilayer electrode in DGOTFT","authors":"Chandaboina Pavan Kumar, Manish Kumar Singh","doi":"10.1016/j.rineng.2025.107039","DOIUrl":"10.1016/j.rineng.2025.107039","url":null,"abstract":"<div><div>A dielectric-modulated bilayer electrode double-gate organic thin-film transistor (DMBE-DGOTFT), employing Dinaphtho[2,3-b:2',3'-f]thieno[3,2-b]thiophene (DNTT) as the active layer, is designed for selective and label-free biomolecule detection. The DMBE-DGOTFT biosensor leverages a biocavity integrated within the gate dielectric region, where the variations in dielectric constant and biomolecular charge density significantly influence the device electrical response. The key parameters, including Drain current variation, DNTT thickness, electric field distribution, charge polarity, and electrostatic potential—are systematically analyzed under diverse biosensing conditions using SILVACO ATLAS TCAD simulations. The DMBE-DGOTFT biosensor exhibits a maximum sensitivity of <span><math><mn>4.5</mn><mo>×</mo><msup><mrow><mn>10</mn></mrow><mrow><mn>2</mn></mrow></msup></math></span> for a charged biomolecule (<span><math><msub><mrow><mi>Q</mi></mrow><mrow><mi>f</mi></mrow></msub><mo>=</mo><mn>1</mn><mo>×</mo><msup><mrow><mn>10</mn></mrow><mrow><mn>12</mn></mrow></msup><mspace></mspace><msup><mrow><mtext>cm</mtext></mrow><mrow><mo>−</mo><mn>2</mn></mrow></msup></math></span>) at a dielectric constant of 12, it demonstrates superior performance compared to conventional dielectric-modulated double-gate biosensors, with a sensitivity of 38.1. The dual-gate control and bilayer electrode configuration enhance charge transport and gate coupling, resulting in improved drain current modulation and detection accuracy. With its high sensitivity, real-time detection capability, biocompatibility, and suitability for scalable, low-cost fabrication, the DMBE-DGOTFT platform offers significant promise for next-generation applications in medical diagnostics, environmental monitoring, and point-of-care healthcare systems.</div></div>","PeriodicalId":36919,"journal":{"name":"Results in Engineering","volume":"28 ","pages":"Article 107039"},"PeriodicalIF":7.9,"publicationDate":"2025-09-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145047246","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Phytoplankton identification with prototypical networks: A few-shot learning approach 浮游植物识别的原型网络：几次学习方法

IF 7.9

Results in Engineering Pub Date : 2025-09-09 DOI: 10.1016/j.rineng.2025.106984

Gloria Bueno , Lucia Sanchez , Gabriel Cristobal , Michael Kloster , Bánk Beszteri , Jesus Salido

{"title":"Phytoplankton identification with prototypical networks: A few-shot learning approach","authors":"Gloria Bueno , Lucia Sanchez , Gabriel Cristobal , Michael Kloster , Bánk Beszteri , Jesus Salido","doi":"10.1016/j.rineng.2025.106984","DOIUrl":"10.1016/j.rineng.2025.106984","url":null,"abstract":"<div><div>The recognition of phytoplankton in microscopy images remains a challenging task due, among other factors, to the vast diversity of known species and the limited availability of labeled training data. Recent advances in pattern recognition have facilitated the automation of this process, offering experts tools to reduce annotation time and increase classification reliability. However, the core difficulty persists, traditional models struggle with unseen species and data scarcity. This study presents a novel application of <em>Prototypical Networks</em> for the automatic recognition of cyanobacteria and diatoms, a method not previously applied to this domain, to the best of our knowledge. Our approach addresses a critical limitation of conventional classifiers by enabling the integration of new, previously unseen species into the recognition framework. To this end, data balancing and augmentation techniques based on <em>deep learning</em> were applied, followed by the training of detection and classification models using <em>Few-Shot Learning</em>, with a focus on <em>Prototypical Networks</em>. The results demonstrate the model's ability to incorporate novel cyanobacteria and diatom genera with minimal annotated data, offering a promising solution for biodiversity monitoring and environmental assessment.</div></div>","PeriodicalId":36919,"journal":{"name":"Results in Engineering","volume":"28 ","pages":"Article 106984"},"PeriodicalIF":7.9,"publicationDate":"2025-09-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145027627","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Robust hybrid optimization design for axial flux-switching transverse-flux permanent magnet wind generator 轴向磁通开关横磁通永磁风力发电机鲁棒混合优化设计

IF 7.9

Results in Engineering Pub Date : 2025-09-09 DOI: 10.1016/j.rineng.2025.107124

Fariba Farrokh, Aghil Ghaheri, Ebrahim Afjei

{"title":"Robust hybrid optimization design for axial flux-switching transverse-flux permanent magnet wind generator","authors":"Fariba Farrokh, Aghil Ghaheri, Ebrahim Afjei","doi":"10.1016/j.rineng.2025.107124","DOIUrl":"10.1016/j.rineng.2025.107124","url":null,"abstract":"<div><div>This paper presents a robust hybrid optimization approach for a novel axial transverse-flux permanent magnet (TFPM) wind generator designed for direct-drive wind turbines. The generator features permanent magnets embedded in the middle arm of a ƎE-shaped stator core, enabling high torque density and modular manufacturability. To address the challenges of its complex 3D magnetic flux and interdependent parameters, a three-layer multi-objective optimization framework is employed. Taguchi analysis identifies critical design variables, response surface methodology develops accurate regression models, and constrained sensitivity analysis refines the design through targeted 3D finite element evaluations. Experimental validation confirms that the proposed optimization strategy significantly enhances generator performance, including a 64.7 % reduction in total harmonic distortion, a 10.1 % improvement in power factor, and a 66 % decrease in cogging torque. Thermal and structural analyses further demonstrate safe operation and mechanical stability. These results highlight the effectiveness of the proposed method in delivering a reliable, efficient, and compact generator solution for next-generation direct-drive wind energy systems.</div></div>","PeriodicalId":36919,"journal":{"name":"Results in Engineering","volume":"28 ","pages":"Article 107124"},"PeriodicalIF":7.9,"publicationDate":"2025-09-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145047511","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

ERAnet: Emotion Recognition based Assistive learning network for autistic children 基于情绪识别的自闭症儿童辅助学习网络

IF 7.9

Results in Engineering Pub Date : 2025-09-09 DOI: 10.1016/j.rineng.2025.106989

Nirudeeswar R , Thrishal S , Shruthi V , S. Angalaeswari , Aravindkumar Sekar

{"title":"ERAnet: Emotion Recognition based Assistive learning network for autistic children","authors":"Nirudeeswar R , Thrishal S , Shruthi V , S. Angalaeswari , Aravindkumar Sekar","doi":"10.1016/j.rineng.2025.106989","DOIUrl":"10.1016/j.rineng.2025.106989","url":null,"abstract":"<div><div>Children with Autism Spectrum Disorder (ASD) often face difficulties with traditional learning methods, particularly in understanding emotions, interpreting social cues, and maintaining attention due to hyperactivity. To address these challenges, we propose the Emotion Recognition-based Assistive Learning Network (ERAnet), which consists of three main phases: the ASD Learning Phase, the Emotion Recognition Phase, and the Audio Analysis Phase. In the ASD Learning Phase, facial emotions are detected and translated into emojis that serve as learning cues for the child. During the Emotion Recognition Phase, the child attempts to identify the displayed emotion by matching it to the correct emoji, with up to three attempts allowed. In the Audio Analysis Phase, the child's facial reactions while listening to audio are monitored to compute an emotion score. We thoroughly evaluated the model's performance using standard metrics such as precision, recall, F1-score, and accuracy. The model was also validated on benchmark datasets, achieving an accuracy of 91.45%. Additionally, we tested the model's real-time effectiveness through interactive sessions with autistic children. The results indicate that ERAnet outperforms current state-of-the-art methods.</div></div>","PeriodicalId":36919,"journal":{"name":"Results in Engineering","volume":"28 ","pages":"Article 106989"},"PeriodicalIF":7.9,"publicationDate":"2025-09-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145027158","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Optimal operation of the non-drinking water distribution network considering future conditions (Case study: Isfahan University non-drinking water distribution network) 考虑未来条件的非饮用水配网优化运行（以伊斯法罕大学非饮用水配网为例）

IF 7.9

Results in Engineering Pub Date : 2025-09-09 DOI: 10.1016/j.rineng.2025.107190

Mohamad Reza Najarzadegan, Ramtin Moeini

{"title":"Optimal operation of the non-drinking water distribution network considering future conditions (Case study: Isfahan University non-drinking water distribution network)","authors":"Mohamad Reza Najarzadegan, Ramtin Moeini","doi":"10.1016/j.rineng.2025.107190","DOIUrl":"10.1016/j.rineng.2025.107190","url":null,"abstract":"<div><div>Population growth and climate change have increased the demand for freshwater resources. In Iran, the average per capita freshwater consumption is approximately 5 % to 85 % higher than the global average. In addition, high levels of water loss and inefficient use of drinking water emphasize the need to reduce reliance on these resources. One solution is the use of non-drinking water distribution networks (WDNs), which are often designed based on current conditions but should also be optimized for future scenarios. This study investigates the existing non-drinking WDN at the University of Isfahan and determines an optimal operation strategy considering future water demand. In other words, a new approach is proposed to overcome the limitation of climate-influenced and population increasing water demand value by prediction them. For this purpose, an optimization model is equipped with data-driven based water demand prediction model for proper pump schedules considering the limitation of full life-cycle-cost formulation. Here, the operation of the network’s pumps is optimized using a Binary Genetic Algorithm (BGA), which determines their on/off schedules based on electricity costs and pump depreciation. In addition, water demand is predicted for the next five years using an Artificial Neural Network (ANN), based on historical consumption data (2013–2017). Results show that energy consumption can be reduced by 19.77 % in summer and 37.5 % in winter using the proposed method. Furthermore, the best ANN model leads to an R² value of 0.89 (training) and 0.85 (testing/validation), indicating strong predictive performance.</div></div>","PeriodicalId":36919,"journal":{"name":"Results in Engineering","volume":"28 ","pages":"Article 107190"},"PeriodicalIF":7.9,"publicationDate":"2025-09-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145047553","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Synchronous transfer control of medium voltage pump in water treatment: A multilevel cascaded H-bridge inverter-based solution 水处理中压泵的同步传输控制：基于多级级联h桥逆变器的解决方案

IF 7.9

Results in Engineering Pub Date : 2025-09-09 DOI: 10.1016/j.rineng.2025.107006

M.L. Nguyen, Duy Anh Ta

引用次数: 0

Integrating optimal production size and selling price of a production-inventory system with power-time and exponential-price demand 考虑电力时间和指数价格需求的生产库存系统的最优生产规模和最优销售价格

IF 7.9

Results in Engineering Pub Date : 2025-09-08 DOI: 10.1016/j.rineng.2025.106922

Luis A. San-José , Joaquín Sicilia , Valentín Pando , David Alcaide-López-de-Pablo

{"title":"Integrating optimal production size and selling price of a production-inventory system with power-time and exponential-price demand","authors":"Luis A. San-José , Joaquín Sicilia , Valentín Pando , David Alcaide-López-de-Pablo","doi":"10.1016/j.rineng.2025.106922","DOIUrl":"10.1016/j.rineng.2025.106922","url":null,"abstract":"<div><div>This paper presents and studies a new production-inventory model with constant production rate in which demand depends simultaneously on price and time. Thus, it is assumed that the demand rate is the multiplication of an exponential function of the selling price and a power function of time. This price- and time-dependent demand can be useful for describing the behavior of demand for some products, because it can be better and more easily adjusted to empirical data. To the best of our knowledge, this is the first time that this demand rate has been used in an EPQ system. The aim is to find the optimal production lot size and the optimal selling price that maximize the profit per unit of time. An efficient algorithm to establish the best solution of the problem based on the parameters of the model is developed. This procedure determines whether the production-inventory system is profitable and, in this case, finds the optimal selling price, the optimal inventory cycle, the optimal production lot size and the maximum profit. Some numerical examples are presented to illustrate how the algorithm works. Finally, a sensitivity analysis on the input parameters of the optimal production-inventory policy is presented and managerial insights from these results are discussed.</div></div>","PeriodicalId":36919,"journal":{"name":"Results in Engineering","volume":"28 ","pages":"Article 106922"},"PeriodicalIF":7.9,"publicationDate":"2025-09-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145047554","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0