检索结果-内蒙古大学图书馆

1st International Conference on Design, Energy, Materials and Manufacture, ICDEMM 2018

作者： Swamardika, I.B.A. Winaya, I.N.S. Hartati, R.S. Study Program of Electrical Engineering Faculty of Engineering University of Udayana Indonesia Study Program of Mechanical Engineering Faculty of Engineering University of Udayana Indonesia

This investigative research aims to convert urban non-organic waste fuels such as plastic waste into energy using fixed bed pyrolysis technology. Pyrolysis fixed bed (PFB) is one of the most efficient technologies for converting various types of undegradable solid waste into thermal energy and liquid fuels with high efficiency. The study was conducted on a lab-scale PFB reactor with dimensions of 15 cm and 55 cm in diameter and bed height respectively. The reactor is equipped with a cooling and decomposition system to accommodate liquid and gas products. Reactor temperature variations using an external heater were tested and quartz sands were selected as a bed material to improve the temperature function of the PFB reactor so as the maximum quality and quantity of liquid product were obtained. The fuel properties of the derived oil were tested including their physical properties, calorific value, elemental measurement (CHNOS) analysis. The results of the study showed that the increase in temperature resulted in an increased pyrolysis performance which was indicated by the increased volume and liquid caloric value. © Published under licence by IOP Publishing Ltd.

关键词： Pyrolysis

来源：评论

学校读者我要写书评

暂无评论

Electricity Savings Using Passive Filters 1

Electricity Savings Using Passive Filters

引用

1st International Conference on Vocational education and Technology, ICONVET 2018

作者： Ratnaya, I.G. Santiyadnya, N. Suka Arsa, I.P. Electrical Engineering Education Study Program Technical and Vocational Faculty Universitas Pendidikan Ganesha Indonesia

This study aims to provide knowledge in order to save electricity consumption. The use of electrical energy is recorded at KWH meters. Saving electricity means limiting the use of electrical energy according to need. The use of electrical energy is based on the use of electrical power. Technically, this dimmer serves to regulate the use of electrical power. Some electrical equipment has been equipped with dimmers to regulate the operation of the equipment in accordance with the user's want, yet there are still many electrical equipment that is not equipped with dimmers. This is a problem in the efforts to save electricity. The method used in this study is applying passive components in electricity such as inductors, capacitors and resistors. These passive components are arranged to be used as filter circuits. With a 21 mH inductor with an air core, Farad's 12.5 micro capacitor, and 4.7 ohm resistor can be made as a passive filter that is installed before electric loads. The use of this filter circuit can save the use of electricity up to 15% at a load current of 2 amperes. Thus, electricity bill payments can be reduced by up to 15%. In the future, this research can be continued to improve the efficiency of electricity consumption by modifying passive filters. © 2019 Published under licence by IOP Publishing Ltd.

关键词： Passive filters

来源：评论

学校读者我要写书评

暂无评论

The environmental challenges of urban living: Why willingness to pay for apartments matters

引用

Environmental Challenges 2023年 13卷

作者： Tehupeiory, Aarce Mulyana, Rachmat Sianipar, Imelda Masni Juniaty Suryawan, I Wayan Koko Septiariva, Iva Yenis Prayogo, Wisnu Doctor of Law Program Universitas Kristen Indonesia Jakarta Cawang 13630 Indonesia Department of Building Engineering Education Universitas Negeri Medan Medan Indonesia PhD Student in Asia-Pacific Regional Studies College of Humanities and Social Sciences National Dong Hwa University Hualien 974 Taiwan Department of International Relations Faculty of Social Science and Political Science Universitas Kristen Indonesia Jakarta 13630 Indonesia Department of Environmental Engineering Faculty of Infrastructure Planning Universitas Pertamina Jakarta 12220 Indonesia Civil Engineering Study Program Faculty of Engineering Universitas Sebelas Maret Surakarta 57126 Indonesia

This study aims to understand the willingness of urban communities in Jabodetabek (Jakarta, Bogor, Depok, Tangerang, Bekasi) to move to apartment dwellings, and a study was conducted using a quantitative survey method. The study aimed to analyze the sociodemographic factors influencing the decision to switch to vertical housing. The survey collected data from a sample of individuals representing the entire population in Jabodetabek. The participants in the study were selected from various locations within Jabodetabek, including Jakarta, Bogor, Depok, Tangerang, and Bekasi. These areas were chosen to comprehensively represent the metropolitan region and its urban communities. By including participants from different locations within Jabodetabek, the study aimed to capture individuals' diverse perspectives and experiences in this region. The survey covered a range of sociodemographic factors such as gender, income, education level, marital status, occupancy, and residence ownership. The participants were divided into two groups: those willing to pay for an apartment and those who wereilling to pay for an apartment and those not. By comparing the characteristics of these two groups, the study aimed to identify significant differences and understand the factors influencing the willingness to move to apartment dwellings. The study results showed significant differences in income level, education level, marital status, and occupancy between the two groups. Income level was the most significant factor affecting an individual's willingness to pay for an apartment. Additionally, the perception of better apartment productivity, which includes reduced transportation time and costs associated with work or other business purposes, increased the demand for apartments. The study found that income level was the most significant factor affecting an individual's willingness to pay for an apartment. The perception of better apartment productivity also increased demand for apartments,

关键词： Apartments Better productivity Jabodetabek Metropolitan cities Sociodemographics Willingness to Pay

来源：评论

学校读者我要写书评

暂无评论

Organizational Culture's Significance in Technology and Innovation Management

Organizational Culture's Significance in Technology and Inno...

引用

Trends in Quantum Computing and Emerging Business Technologies (TQCEBT), International Conference on

作者： Somanchi Hari Krishna Ulfah Fajarini Arun Kant Painoli C. Visvesvaran K. N. Jahnavi Melanie Lourens Department of Business Management Vignana Bharathi Institute of Technology India Faculty of Education Social Science Study Program Syarif Hidayatullah State Islamic University Jakarta Indonesia School of Management Studies Baddi University of Emerging Sciences and Technology Baddi Himachal Pradesh India Sri Krishna College of Engineering and Technology Coimbatore India SIndhi Institute of Management Bangalore Faculty of Management Sciences Durban University of Technology South Africa

ISBN: (数字)9798350384277

ISBN: (纸本)9798350384284

Several studies have examined the connection between innovation, technology, and organizational culture in recent years. Management of technology and innovation is crucial to an organization's expansion and success. The development of an innovative organizational culture comes before technology and innovation management. This study's primary goal was to assess how organizational culture affects innovation in the Indian service sector. The study made use of a paradigm for understanding organisational culture created by Cameron and Quinn, which looks at culture as a collection of conflicting values from four angles. A descriptive survey research design was used in the investigation. Employees of service industries made up the study's population. More than twenty IT organizations participated in the survey, and 120 out of 180 respondents returned completed questionnaires. This indicated a response rate of 66%.The collected data was analyzed using inferential data analysis techniques and descriptive statistics. Tables and figures were created after analysis with IBM SPSS software. The results demonstrated that the strongest associations with innovation and technology were found in companies with flexible, collaborative, and employee-friendly cultures. Lastly, the study suggests areas for additional research, such as employing a new organizational culture model for the study or qualitative techniques for data collecting and analysis to reveal deeper cultural features.

关键词： Surveys Industries Technological innovation Technology management Quantum computing Sociology Innovation management

来源：评论

学校读者我要写书评

暂无评论

Supervised Learning Models for Early Detection of Albuminuria Risk in Type-2 Diabetes Mellitus Patients

arXiv

引用

arXiv 2023年

作者： Muharram, Arief Purnama Tahapary, Dicky Levenus Lestari, Yeni Dwi Sarayar, Randy Dirjayanto, Valerie Josephine Master Program of Informatics School of Electrical Engineering and Informatics Institut Teknologi Bandung Bandung Indonesia Metabolic Disorder Cardiovascular and Aging Research Center Indonesia Medical Education and Research Institute Faculty of Medicine Universitas Indonesia Jakarta Indonesia Ophthalmology Department Faculty of Medicine Universitas Indonesia Cipto Mangunkusumo General Hospital Jakarta Indonesia Faculty of Medicine Universitas Indonesia Jakarta Indonesia

Diabetes, especially T2DM, continues to be a significant health problem. One of the major concerns associated with diabetes is the development of its complications. Diabetic nephropathy, one of the chronic complication of diabetes, adversely affects the kidneys, leading to kidney damage. Diagnosing diabetic nephropathy involves considering various criteria, one of which is the presence of a pathologically significant quantity of albumin in urine, known as albuminuria. Thus, early prediction of albuminuria in diabetic patients holds the potential for timely preventive measures. This study aimed to develop a supervised learning model to predict the risk of developing albuminuria in T2DM patients. The selected supervised learning algorithms included Naïve Bayes, Support Vector Machine (SVM), decision tree, random forest, AdaBoost, XGBoost, and Multi-Layer Perceptron (MLP). Our private dataset, comprising 184 entries of diabetes complications risk factors, was used to train the algorithms. It consisted of 10 attributes as features and 1 attribute as the target (albuminuria). Upon conducting the experiments, the MLP demonstrated superior performance compared to the other algorithms. It achieved accuracy and f1-score values as high as 0.74 and 0.75, respectively, making it suitable for screening purposes in predicting albuminuria in T2DM. Nonetheless, further studies are warranted to enhance the model’s performance. © 2023, CC BY-SA.

关键词： Decision trees

来源：评论

学校读者我要写书评

暂无评论

Supervised Learning Models for Early Detection of Albuminuria Risk in Type-2 Diabetes Mellitus Patients

Supervised Learning Models for Early Detection of Albuminuri...

引用

International Conference of Advanced Informatics: Concept, Theory and Application (ICAICTA)

作者： Arief Purnama Muharram Dicky Levenus Tahapary Yeni Dwi Lestari Randy Sarayar Valerie Josephine Dirjayanto Master Program of Informatics School of Electrical Engineering and Informatics Institut Teknologi Bandung Bandung Indonesia Metabolic Disorder Cardiovascular and Aging Research Center Faculty of Medicine Indonesia Medical Education and Research Institute Universitas Indonesia Jakarta Indonesia Ophthalmology Department Faculty of Medicine Cipto Mangunkusumo General Hospital Universitas Indonesia Jakarta Indonesia Faculty of Medicine Universitas Indonesia Jakarta Indonesia

Diabetes, especially T2DM, continues to be a significant health problem. One of the major concerns associated with diabetes is the development of its complications. Diabetic nephropathy, one of the chronic complication of diabetes, adversely affects the kidneys, leading to kidney damage. Diagnosing diabetic nephropathy involves considering various criteria, one of which is the presence of a pathologically significant quantity of albumin in urine, known as albuminuria. Thus, early prediction of albuminuria in diabetic patients holds the potential for timely preventive measures. This study aimed to develop a supervised learning model to predict the risk of developing albuminuria in T2DM patients. The selected supervised learning algorithms included Naive Bayes, Support Vector Machine (SVM), decision tree, random forest, AdaBoost, XGBoost, and Multi-Layer Perceptron (MLP). Our private dataset, comprising 184 entries of diabetes complications risk factors, was used to train the algorithms. It consisted of 10 attributes as features and 1 attribute as the target (albuminuria). Upon conducting the experiments, the MLP demonstrated superior performance compared to the other algorithms. It achieved accuracy and f1-score values as high as 0.74 and 0.75, respectively, making it suitable for screening purposes in predicting albuminuria in T2DM. Nonetheless, further studies are warranted to enhance the model's performance.

关键词：

来源：评论

学校读者我要写书评

暂无评论

A comparison on the use of Perlin-noise and Gaussian noise based augmentation on X-ray classification of lung cancer patient 1

A comparison on the use of Perlin-noise and Gaussian noise b...

引用

1st International Symposium on Physics and Applications, ISPA 2020

作者： Haekal, M. Septiawan, R.R. Haryanto, F. Arif, I. Department of Physics Faculty of Sciences and Data Analytics Institut Teknologi Sepuluh Nopember Kampus ITS Sukolilo-Surabaya Jawa Timur60111 Indonesia Computer Engineering Study Program School of Electrical Engineering Telkom University Jl. Telekomunikasi No.1 Jawa Barat Bandung40257 Indonesia Faculty of Mathematics and Natural Sciences Institut Teknologi Bandung Jl. Ganeca 10 Jawa Barat Bandung40132 Indonesia

The use of deep learning in medical image classification has become an important study in the past few years. The proper use of this method, however, is still hindered by many problems, one of it being the imbalance of dataset available for training which resulted in small-set database. In this study, the effect of noise-based augmentation on the performance of deep learning based classification will be studied. The noises which were used for the augmentation method were Perlin-noise and Gaussian noise. The modality of medical image used in this study is X-ray. 174 X-ray images (87 cancer, 87 normal) were used in this study and will be classified by using transfer learning from previously trained deep learning architecture. The deep learning architecture used was vgg-19. The images were divided into two groups, 138 (69 cancer, 69 normal) images were used for training phase and 36 (18 cancer, 18 normal) were images used for testing phase. Three deep learning models were used for the classification tasks, the first one was retrained to classify the original images, the second one was retrained by using mix of original images and images with Perlin-noise, and the third one was retrained by using mix of original images and images with Gaussian noise. The results showed that the three models returned similar accuracy of 0.8 which indicate that the use of noise-based augmentation can increase the performance of deep learning in classifying medical images with small set training database. © Published under licence by IOP Publishing Ltd.

关键词： Classification (of information)

来源：评论

学校读者我要写书评

暂无评论

Development of coronary heart disease diagnosis system based on facial imagery

引用

AIP Conference Proceedings 2024年第1期2920卷

作者： Yudha Andriano Rismawan Agung Adi Firdaus Indah Novi Yarman Anisa Dwi Lutfi Yanti Anan Nugroho Rachelia Intan Merdina Andreas Arie Setiawan Informatics and Computer Engineering Education Study Program Universitas Negeri Semarang Semarang Indonesia Public Health Study Program Universitas Negeri Semarang Semarang Indonesia Faculty of Medicine Diponegoro University Semarang Indonesia

The effort of the community in early checkups for coronary heart disease is still very lacking. That is due to the less awareness and cost constraints so that heart disease is handled too late which causes the heart condition to get worse and even complications. A diagnosis of coronary heart risk based on facial texture has been done lately by researchers in China and produces pretty good output, but no similar study has been found in Indonesia. Therefore, this study aims to design several machine learning models and find out the performance of algorithms in diagnosing the risk of coronary heart disease with facial imagery. The research dataset was extracted using the Gray Level Co-occurrence Matrix on specific areas of the face. The areas taken are right crow’s feet, right canthus, bridge nose, forehead, left canthus and left crow’s feet. The main focus of this study was on the performance of the Support Vector Machine, Decision Tree, and Neural Network models. Dataset processing procedures are divided into two, namely model making (training) and performance testing (testing). The findings showed that the best performing model was NN with an AUC score of 92.8%, followed by SVM with 85.6%, and the lowest was DT with 68% AUC. NN became the model with the best performance with 76.9% accuracy, 81.7% precision, 76.9% recall, and an F1 score of 77.5%.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Analog Behavioral Model of Underdamped Free Oscillation of Cantilever Beams

Analog Behavioral Model of Underdamped Free Oscillation of C...

引用

2019 International Conference on Sustainable engineering and Creative Computing, ICSECC 2019

作者： Tarigan, Hendra J. Sitompul, Erwin President University Study Program of Electrical Engineering Faculty of Engineering Bekasi Indonesia

ISBN: (纸本)9781728151922

A physical model representing an underdamped free oscillation of a cantilever beam is constructed. The model is incorporated into a pSPICE Analog Behavioral Model (ABM) in order to construct a circuit schematic that generates a model-based waveform representing that of the experiment. A strain gage is employed to sense the change in strain in the oscillating cantilever beam. The frequency and damping ratio of oscillation of the cantilever are determined by means of curve fitting. Experiment and pSPICE ABM results show an excellent agreement. © 2019 IEEE.

关键词： Strain gages

来源：评论

学校读者我要写书评

暂无评论

System Modelling Using Neural Networks with External Recurrence and Exponential Quadratic Cost Function

System Modelling Using Neural Networks with External Recurre...

引用

2019 International Conference on Sustainable engineering and Creative Computing, ICSECC 2019

作者： Sitompul, Erwin President University Study Program of Electrical Engineering Faculty of Engineering Bekasi Indonesia

ISBN: (纸本)9781728151922

A novel cost function to improve the performance of neural networks in system modelling is proposed in this paper, the exponential quadratic cost function. This cost function combines the strength of penalizing errors exponentially and the feasibility of quadratic function in finding global minima. By applying the exponential quadratic cost function, the learning algorithm is expected to have an improved ability to minimize the difference between system output and model output. Simulations by using a test system with strong nonlinear dynamics were conducted to prove the effectiveness of the proposed cost function. The results show that the network trained using the exponential quadratic cost function performs better in emulating the test system in transient region. © 2019 IEEE.

关键词： Cost functions

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：