检索结果-内蒙古大学图书馆

Conversion of palm oil mill wastes into high-value biochar and syngas using wet torrefaction and gasification with palm oil mill effluent as a liquid stream

引用

Clean Technologies and Environmental Policy 2025年 1-13页

作者： Aziz, Nur Atiqah Mohamad Yu, Kai Ling Mohamed, Hassan Zainal, Bidattul Syirat Mahlia, Teuku Meurah Indra Ong, Hwai Chyuan Hamid, Hamidah Abd Kania, Dina Salehmin, Mohd Nur Ikhmal Yap, Taufiq Yun Hin Institute of Sustainable Energy (ISE) Universiti Tenaga Nasional (UNITEN) Kajang Malaysia Department of Engineering School of Engineering and Technology Sunway University Bandar SunwayPetaling Jaya Malaysia Tan Sri Leo Moggie Distinguished Chair in Energy Informatics Institute of Informatics and Computing in Energy (IICE) Universiti Tenaga Nasional (UNITEN) Kajang Malaysia Mechanical Engineering Department College of Engineering (COE) Universiti Tenaga Nasional (UNITEN) Kajang Malaysia Centre for Technology in Water and Wastewater School of Civil and Environmental Engineering Faculty of Engineering and Information Technology University of Technology Sydney Ultimo Australia Department of Petroleum Engineering Faculty of Engineering Universitas Islam Riau Pekanbaru Indonesia Department of Chemistry Faculty of Science Universiti Putra Malaysia (UPM) Serdang Malaysia

The palm oil industry generates significant waste, particularly oil palm empty fruit bunch (EFB) and palm oil mill effluent (POME). This study successfully converted these wastes into high-heating-value (HHV) biochar, bio-oil, and syngas through a combination of wet torrefaction and gasification processes, addressing a research gap in bioenergy co-production. EFB and POME underwent wet torrefaction at 200 °C for 30 min, producing biochar with an HHV of 22.6 MJ/kg, a 31% increase from that of raw EFB. Subsequent gasification of the biochar at 700–900 °C further enhanced the HHV to 23.8 MJ/kg, a 38% increase from raw EFB. Gasification yielded biochar, bio-oil, and syngas in proportions of 39–55%, 12–20%, and 27–44%, respectively. Gas chromatography analysis of the syngas identified CO2 (0.003 mmol/mL), H2 (0.002 mmol/mL), CH4 (0.002 mmol/mL), and CO (0.005 mmol/mL). The novelty of this paper lies in integrating wet torrefaction and gasification processes for the co-production of high-quality biochar and syngas from palm oil mill waste, particularly EFB and POME, offering a sustainable energy solution and addressing gaps in biomass conversion technologies.

关键词：

来源：评论

学校读者我要写书评

暂无评论

A Review of Android and iOS Operating System Security

A Review of Android and iOS Operating System Security

引用

2022 ASU International Conference in Emerging Technologies for Sustainability and Intelligent Systems, ICETSIS 2022

作者： Khan, Shahnawaz Yusuf, Ammar Haider, Mohammad Thirunavukkarasu, K. Nand, Parma Imam Rahmani, Mohammad Khalid Faculty of Engineering Design and Information and Communications Technology Bahrain Polytechnic Isa Town Bahrain Applied Science University College of Arts and Science Bahrain Saudi Electronic University College of Computing and Informatics Dammam Saudi Arabia Galgotias University Department of Computer Science and Engineering Greater Noida India Sharda University School of Engineering and Technology Greater Noida India Saudi Electronic University College of Computing and Informatics Riyadh11673 Saudi Arabia

ISBN: (数字)9781665469197

ISBN: (纸本)9781665469197

Mobile devices are an inseparable part of our lives. They have made it possible to access all the information and services anywhere at any time. Almost all of the organizations try to provide a mobile device-based solution to its users. However, this convenience has arisen the risk of losing personal information and has increased the threat to security. It has been observed recently that some of the mobile device manufacturers and mobile apps developers have lost the private information of their users to hackers. It has risen a great concern among mobile device users about their personal information. Android and iOS are the major operating systems for mobile devices and share over 99% of the mobile device market. This research aims to conduct a comparative analysis of the security of the components in the Android and iOS operating systems. It analyses the security from several perspectives such as memory randomization, application sandboxing, isolation, encryption, built-in antivirus, and data storage. From the analysis, it is evident that iOS is more secure than Android operating system. However, this security comes with a cost of losing the freedom. © 2022 IEEE.

关键词： Android (operating system)

来源：评论

学校读者我要写书评

暂无评论

Citrus Limon L. Ripeness Identification Using Feature Extraction of Mean RGB, HSV, LBP and K-Nearest Neighbor

Citrus Limon L. Ripeness Identification Using Feature Extrac...

引用

2023 International Seminar on Application for technology of Information and Communication, iSemantic 2023

作者： Priyo Utomo, Ade Cahyo Sari, Christy Atika Rachmawanto, Eko Hari Hadi, Heru Pramono Mostafa, Salama A. Al-Dayyeni, Wisam Subhi Talib University of Dian Nuswantoro Study Program in Informatics Engineering Semarang Indonesia University of Dian Nuswantoro Study Program in Information Systems Semarang Indonesia Universiti Tun Hussein Onn Malaysia Faculty of Computer Science and Information Technology Johor Malaysia Ada University School of Information Technologies and Engineering Baku Azerbaijan

ISBN: (纸本)9798350339215

Citrus Limon L. (Lemon) is a type of fruit that is currently widely consumed, because it contains abundant vitamin C, fiber, and antioxidants. This fruit have high potential in the agribusiness sector and is widely cultivated by traditional farmers. However, during harvest time, traditional farmers generally still use manual methods using the human eye in distinguishing the maturity level of lemons which is less efficient because it has a low accuracy. Digital image processing is one solution to this problem. In the research on the classification of lemon maturity levels using digital image processing with the feature extraction method of the Mean RGB, HSV, and LBP methods and the K-Nearest Neighbor classification algorithm in this study, a total of 120 lemon images were used which were divided into 80 training image data and 40 image data. testing. The results of model performance measurements in the form of the highest accuracy level in the Mean RGB method of 100%, the highest accuracy in the HSV method of 98%, and the highest accuracy in the LBP method of 82.5%. © 2023 IEEE.

关键词： Citrus fruits

来源：评论

学校读者我要写书评

暂无评论

Sensors and healthcare 5.0:transformative shift in virtual care through emerging digital health technologies

引用

Global Health Journal 2021年第4期5卷 169-177页

作者： Elliot Mbunge Benhildah Muchemwa Sipho'esihle Jiyane John Batani Department of Computer Science Faculty of Science and EngineeringUniversity of EswatiniKwaluseniManziniEswatini Department of Information Technology Faculty of Accounting and InformaticsDurban University of TechnologyP.O.Box 1334Durban 4000South Africa Faculty of Engineering and Technology Botho UniversityMaseru 100Lesotho

Emerging digital technologies continues to evolve posing unprecedented opportunities in health systems globally to improve healthcare services *** has been significant progress in ***,the lack of emotive recognition coupled with a dearth of personalized and pervasive health applications and emotive smart devices calls for the integration of intelligent sensors health systems through emerging *** there has been significant progress in smart and connected health care,more research innovation,dissemination and technologies are needed to unbundle new opportunities and move towards healthcare *** is at the dawn of a paradigm change to reach the new era of smart disease control and detection,virtual care,smart health management,smart monitoring,and ***,this study discusses the roles and capacities of sensors,their capabilities and other emerging technologies such as nanotechnology,5 G technologies,drone technology,blockchain,robotics,big data,internet of things,artificial intelligence,and cloud *** 5.0 provides healthcare services including patient remote *** and virtual clinics,emotive telemedicine,ambient assisted living,smart self-management,wellness monitoring and control,smart treatment reminders,compliance and adherence,and personalized and connected health ***,building resilience and robust healthcare 5.0 is not immune to *** challenges,technological and infrastructural barriers,lack of legal and regulatory frameworks and e-health policies,individual perceptions,misalignment with hospitals'strategy,lack of funding,religious and cultural bariers are identified as potential barriers to the successful implementation of healthcare ***,there is a need for building resilient technology-driven healthcare *** achieve this,there is a need for expanding technological infrastructure,provision of budgetary support based o

关键词： Healthcare 5.0 Sensors Smart devices Virtual care Emerging technologies Coronavirus disease 2019(COVID-19)

来源：评论

学校读者我要写书评

暂无评论

Clustering the Academician Knowledge Qualification: K-Means for Performance Measurement Analysis

Clustering the Academician Knowledge Qualification: K-Means ...

引用

Student Conference on Research and Development (SCOReD)

作者： Novi Yanti Sarjon Defit Okfalisa Department of Informatics Engineering Faculty of Science and Technology Universitas Islam Negeri Sultan Syarif Kasim Riau Pekanbaru Riau Indonesia Department of Information Technology Faculty of Computer Science Universitas Putra Indonesia YPTK Padang Padang Sumatera Barat Indonesia

ISBN: (数字)9798331510077

ISBN: (纸本)9798331510084

The assessment of an academic’s performance is not solely based on the tangible results achieved. Nonetheless, the formation aspect of the Knowledge Management (KM) process, which arises in the pursuit of outcomes, must be acknowledged. This emphasizes the significance of KM process development for academics in achieving their essential responsibilities including teaching and learning, research and publishing, and community service. Consequently, it is essential to develop a KM model for assessing the accomplishments of academics in higher education. An evaluation of academic performance in higher education was conducted to identify the success factors of knowledge management, by considering five key elements viz, knowledge creation, knowledge acquisition, knowledge storage, knowledge sharing, and knowledge application. Accordingly, sixty-five sub-variables were identified as success model factors for evaluating academic knowledge management performance. A K-Means clustering method was utilized to assess the KM qualifications of academics at an Islamic public institution in Indonesia (University X) as the primary study. Herein, a 5-point Likert scale questionnaire was administered to 500 academics and subsequently categorized into three performance levels such as low, medium, and high performance. As a result, 140 academicians were categorized as low KM performance, 139 were clustered as medium qualification, and 221 academicians were positioned in high performance. Furthermore, a recommendation analysis is presented to elucidate the accomplishments of academic credentials for each cluster and propose corrective actions for enhancement. Therefore, the scholars at University X might enhance their knowledge management practices to get a superior quality university.

关键词： Measurement Technological innovation Publishing Knowledge acquisition Education Knowledge management Filling Space exploration Research and development Qualifications

来源：评论

学校读者我要写书评

暂无评论

Extending Kryszkiewicz’s Formula of Missing Values in Terms of Lipski’s Approach 1

引用

10th International Symposium on Integrated Uncertainty in Knowledge Modelling and Decision Making, IUKM 2023

作者： Nakata, Michinori Saito, Norio Sakai, Hiroshi Fujiwara, Takeshi Faculty of Management and Information Science Josai International University 1 Gumyo Chiba Togane283-8555 Japan Department of Mathematics and Computer Aided Sciences Faculty of Engineering Kyushu Institute of Technology Tobata Kitakyushu804-8550 Japan Faculty of Informatics Tokyo University of Information Sciences 4-1 Onaridai Wakaba-ku Chiba265-8501 Japan

ISBN: (数字)9783031467813

ISBN: (纸本)9783031467806

When extracting any information from a data table with incomplete information, following Lipski we only know the lower and the upper bound of the information. Methods of rough sets that are applied to data tables containing incomplete information are examined from the viewpoint of Lipski’s approach based on possible world semantics. It is clarified that the formula that is first used by Kryszkiewicz, which most of the authors use, only gives the lower bound of the lower approximation and the upper bound of the upper approximation. When we focus on a value, this is because it is only considered that a missing value can be equal to that value. We extend Kryszkiewicz’s formula to consider that the missing value may not be equal to the value. As a result, the extended Kryszkiewicz’s formula gives the same approximations as those in terms of Lipski’s approach. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2023.

关键词： Semantics

来源：评论

学校读者我要写书评

暂无评论

The applied principles of EEG analysis methods in neuroscience and clinical neurology

引用

Military Medical Research 2024年第6期11卷 907-941页

作者： Hao Zhang Qing-Qi Zhou He Chen Xiao-Qing Hu Wei-Guang Li Yang Bai Jun-Xia Han Yao Wang Zhen-Hu Liang Dan Chen Feng-Yu Cong Jia-Qing Yan Xiao-Li Li School of Systems Science Beijing Normal UniversityBeijing 100875China College of Electrical and Control Engineering North China University of TechnologyBeijing 100041China School of Automation Science and Engineering South China University of TechnologyGuangzhou 510641China Department of Psychology the State Key Laboratory of Brain and Cognitive Sciencesthe University of Hong KongHong Kong SAR 999077China HKU-Shenzhen Institute of Research and Innovation Shenzhen 518057GuangdongChina Department of Health Technology and Informatics the Hong Kong Polytechnic UniversityHong Kong SAR 999077China Department of Rehabilitation Medicine the First Afliated Hospital of Nanchang UniversityNanchang 330006China Rehabilitation Medicine Clinical Research Center of Jiangxi Province Nanchang 330006China Beijing Key Laboratory of Learning and Cognition School of PsychologyCapital Normal UniversityBeijing 100048China School of Communication Science Beijing Language and Culture UniversityBeijing 100083China Institute of Electrical Engineering Yanshan UniversityQinhuangdao 066004HebeiChina School of Computer Science Wuhan UniversityWuhan 430072China School of Biomedical Engineering Faculty of Electronic Information and Electrical EngineeringDalian University of TechnologyDalian 116081LiaoningChina Guangdong Artifcial Intelligence and Digital Economy Laboratory(Guangzhou) Guangzhou 510335China.

Electroencephalography(EEG)is a non-invasive measurement method for brain *** to its safety,high resolution,and hypersensitivity to dynamic changes in brain neural signals,EEG has aroused much interest in scientific research and medical *** article reviews the types of EEG signals,multiple EEG signal analysis methods,and the application of relevant methods in the neuroscience feld and for diagnosing neurological ***,3 types of EEG signals,including time-invariant EEG,accurate event-related EEG,and random event-related EEG,are ***,5 main directions for the methods of EEG analysis,including power spectrum analysis,time-frequency analysis,connectivity analysis,source localization methods,and machine learning methods,are described in the main section,along with diferent sub-methods and effect evaluations for solving the same ***,the application scenarios of different EEG analysis methods are emphasized,and the advantages and disadvantages of similar methods are *** article is expected to assist researchers in selecting suitable EEG analysis methods based on their research objectives,provide references for subsequent research,and summarize current issues and prospects for the future.

关键词： Electroencephalogram analysis methods Applied principles Neuroscience Diagnosis Neurological diseases

来源：评论

学校读者我要写书评

暂无评论

A deep learning fusion model for accurate classification of brain tumours in Magnetic Resonance images

引用

CAAI Transactions on Intelligence technology 2024年第4期9卷 790-804页

作者： Nechirvan Asaad Zebari Chira Nadheef Mohammed Dilovan Asaad Zebari Mazin Abed Mohammed Diyar Qader Zeebaree Haydar Abdulameer Marhoon Karrar Hameed Abdulkareem Seifedine Kadry Wattana Viriyasitavat Jan Nedoma Radek Martinek Department of Information Technology Lebanese French UniversityErbilIraq Department of Computer Science University of ZakhoZakhoKurdistan RegionIraq Department of Computer Science College of ScienceNawroz UniversityDuhokKurdistan RegionIraq Department of Artificial Intelligence College of Computer Science and Information TechnologyUniversity of AnbarRamadiIraq Department of Telecommunications VSB‐Technical University of OstravaOstravaCzech Republic Department of Cybernetics and Biomedical Engineering VSB‐Technical University of OstravaOstravaCzech Republic Department of Computer Network and Information Security Technical College of Informatics-AkreDuhok Polytechnic UniversityDuhokIraq Information and Communication Technology Research Group Scientific Research CenterAl‐Ayen UniversityThi‐QarIraq College of Computer Sciences and Information Technology University of KerbalaKarbalaIraq College of Agriculture Al‐Muthanna UniversitySamawahIraq Department of Applied Data Science Noroff University CollegeKristiansandNorway Faculty of Commerce and Accountancy Chulalongkorn Business SchoolChulalongkorn UniversityBangkokThailand

Detecting brain tumours is complex due to the natural variation in their location, shape, and intensity in images. While having accurate detection and segmentation of brain tumours would be beneficial, current methods still need to solve this problem despite the numerous available approaches. Precise analysis of Magnetic Resonance Imaging (MRI) is crucial for detecting, segmenting, and classifying brain tumours in medical diagnostics. Magnetic Resonance Imaging is a vital component in medical diagnosis, and it requires precise, efficient, careful, efficient, and reliable image analysis techniques. The authors developed a Deep Learning (DL) fusion model to classify brain tumours reliably. Deep Learning models require large amounts of training data to achieve good results, so the researchers utilised data augmentation techniques to increase the dataset size for training models. VGG16, ResNet50, and convolutional deep belief networks networks extracted deep features from MRI images. Softmax was used as the classifier, and the training set was supplemented with intentionally created MRI images of brain tumours in addition to the genuine ones. The features of two DL models were combined in the proposed model to generate a fusion model, which significantly increased classification accuracy. An openly accessible dataset from the internet was used to test the model's performance, and the experimental results showed that the proposed fusion model achieved a classification accuracy of 98.98%. Finally, the results were compared with existing methods, and the proposed model outperformed them significantly.

关键词： brain tumour deep learning feature fusion model MRI images multi‐classification

来源：评论

学校读者我要写书评

暂无评论

Analysis of denial of service attack on web security systems 2

Analysis of denial of service attack on web security systems

引用

2nd International Conference on sciences and technology Applications, ICOSTA 2020

作者： Iswandi Walad, S. Zarlis, Muhammad Syahril Efendi, M.I.T. Department of Information and Technology Faculty of Computer Science and Information Technology University of Sumatera Utara Medan Indonesia of Informatics Engineering Faculty of Computer Science and Information Technology University of Sumatera Utara Medan Indonesia

In this study, an analysis of the Web security system from a Denial-of-Service Attack (DoS) with SYN Attack, Ping of Death, Land Attack, Smurf Attack and UDP Flood types. The server computer that will be tested for DoS attacks is a local web server including *** IP: 54.169.71.56, *** IP: 104.152.168.14, *** IP: 156.67.210.132, *** IP: 202.162. 207,101 and *** with IP Address 213.136.83.52 port 80. The attack on the local web server computer was carried out through attacking cloned computers as many as 5 zombie computers and then observing data traffic on each Web server computer. The test results use ping to the local web server computer, where the target web server sends a replay request time out and the check results in the Google Chrome browser are slow to inaccessible conditions. Ping access time the greater the packet, the greater the average time when accessing a local web server with 5,000 packets is 242.68 seconds, 10,000 packets is 310.28 seconds, 20,000 packets are 337.4 seconds, 30,000 packets are 377.2 seconds, 40,000 packets are 398.4 seconds, 50,000 packets are 545.4 seconds and 100,000 packets are above 600 seconds with the condition that the web server will recover after 600 seconds where the system recovery process depends on each local web server. © Published under licence by IOP Publishing Ltd.

关键词： Denial-of-service attack

来源：评论

学校读者我要写书评

暂无评论

High-Isolation Compact Frequency Reconfigurable Cavity-Backed Antenna Based on Dielectric Fluids With Self-Diplexing Property

High-Isolation Compact Frequency Reconfigurable Cavity-Backe...

引用

IEEE International Wireless Symposium (IWS)

作者： Rusan Kumar Barik Xiaohu Wu Xiaoguang Liu Slawomir Koziel School of Microelectronics Southern University of Science and Technology Shenzhen China Dept. of Engineering Reykjavik University Reykjavk Iceland Faculty of Electronics Telecommunications and Informatics Gdansk University of Technology Poland

ISBN: (数字)9798350389999

ISBN: (纸本)9798350390001

A highly-isolated compact cavity-backed frequency reconfigurable antenna employing dielectric fluids with self-diplexing property is presented. The proposed antenna is implemented using two adjacent half-mode substrate-integrated rectangular cavities, radiating slots, microstrip feed lines, and fluidic vias. A detailed explanation is provided for better understanding of the radiation mechanism, self-diplexing property, and tuning process. The frequency reconfigurable is achieved by pouring different dielectric liquids into the fluidic packets. The realization and optimization of the antenna structure are carried out using Ansys HFSS software. The proposed antenna occupies a compact footprint area of ${\text{0}}{\text{.09}}\lambda _g^2$. The proposed antenna allows a tuning of 3.5–4.09 GHz and 6.0–6.98 GHz at lower and upper frequency bands with isolations varies of 49.4–49.7 dB and 38.2–44.6 dB, respectively. Additionally, the front-to-back-ratios and cross-polarization levels of the antenna are greater than –18 dB and –20 dB at all the frequency bands, respectively.

关键词： Wireless communication Slot antennas Fluids Resonant frequency Microstrip antennas Dielectric resonator antennas Software Dielectrics Tuning Substrates

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：