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2020 3rd International Conference on Computer and Informatics Engineering (IC2IE)最新文献

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The Development of IoT-Smart Basket: Performance Comparison between Edge Computing and Cloud Computing System 物联网智能篮子的发展:边缘计算与云计算系统的性能比较
Pub Date : 2020-09-15 DOI: 10.1109/IC2IE50715.2020.9274596
Nandiwardhana Waranugraha, M. Suryanegara
This paper aims to develop the Internet-of Things (IoT) Smart-Basket, working on 2 different systems, i.e. Edge Computing and Cloud Computing. To identify the best system, we compare the performance between “Edge Computing” system and “Cloud Computing” system. The system consists of Raspberry Pi hardware and webcam. Python, TFLite, OpenCV, and Google Cloud Vision API software to detect shopping objects. The object detection results are calculated and sent to end-users through the Telegram application. Discussions are presented concerning the Time Performance and RSSI Value between two systems. The results show “Edge Computing” systems have a more stable system with an average processing time of 1.74 sec on Line-of-Sight (LOS) condition and 1.75 sec on Non-Line-of-Sight (NLOS) condition compared to “Cloud Computing” systems with an average processing time of 10.46 sec on LOS condition and 5.36 sec on NLOS condition.
本文旨在开发物联网(IoT)智能篮,工作在两个不同的系统上,即边缘计算和云计算。为了确定最佳系统,我们比较了“边缘计算”系统和“云计算”系统的性能。系统由树莓派硬件和网络摄像头组成。Python, TFLite, OpenCV,和谷歌云视觉API软件来检测购物对象。计算对象检测结果并通过Telegram应用程序发送给最终用户。讨论了两个系统之间的时间性能和RSSI值。结果表明,“边缘计算”系统在视距条件下的平均处理时间为1.74秒,在非视距条件下的平均处理时间为1.75秒,而“云计算”系统在视距条件下的平均处理时间为10.46秒,在非视距条件下的平均处理时间为5.36秒。
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引用次数: 3
Reducing Computational Cost of Pair-Polar Coordinate-based Cancelable Fingerprint Template Matching 降低基于对极坐标的可取消指纹模板匹配的计算成本
Pub Date : 2020-09-15 DOI: 10.1109/IC2IE50715.2020.9274665
L. Susanto, T. Ahmad
Since a long time ago, biometrics has become a popular authentication method to verify users easily. Despite this advantage, the user’s biometric data must be stored securely because those data cannot be replaced once it has been compromised. It is because humans cannot alter parts of his or her body. Many methods can be used to secure biometric data. One of them is the cancelable fingerprint template. However, its matching computation process is quite expensive, as many minutia points need to compare. In this paper, we optimize the number of minutia points in its selection process using a new threshold. It is to reduce the computational cost of pair-polar coordinate-based cancelable fingerprint template’s matching. The experiment result shows that the proposed method achieves five times better performance than the previous method.
长期以来,生物识别技术已经成为一种流行的身份验证方法,可以方便地验证用户。尽管有这样的优势,用户的生物特征数据必须安全存储,因为这些数据一旦被泄露就无法被替换。这是因为人类不能改变自己身体的某些部位。有许多方法可以用来保护生物特征数据。其中之一是可取消的指纹模板。但是,它的匹配计算过程非常昂贵,因为需要比较很多细节点。在本文中,我们使用一个新的阈值来优化其选择过程中的细节点数量。目的是减少基于对极坐标的可取消指纹模板匹配的计算量。实验结果表明,该方法的性能是原有方法的5倍。
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引用次数: 0
Local Adaptive Thresholding Techniques for Binarizing Scanned Lampung Aksara Document Images 扫描南榜Aksara文档图像二值化的局部自适应阈值技术
Pub Date : 2020-09-15 DOI: 10.1109/IC2IE50715.2020.9274658
F. Kurniadi, Desty Septyani, I. Pratama
Lampung characters are one of the region-heritage characters from Indonesia. However, the current trend makes these characters becoming unknown. The concern about the extinction of these characters makes several researchers tried to digitized the documents which contained Lampung Character. Nevertheless, the process of digitalization is not free from noise. This problem makes us want to handle the noise from the scanned documents using binarization and noise removal techniques, especially in Lampung characters' documents. In this paper, we implemented local adaptive thresholding using the Niblack method and the Sauvola method for thresholding value. We also implemented Adaptive Wavelet Thresholding for Bayes Shrink for removing salt and pepper noise from the binarization process. The result showed that the Sauvola thresholding gives better results compared to Niblack thresholding. Our contribution in this paper is the implementation of both processes in Lampung Characters document
楠榜字是印尼地区遗产文字之一。然而,目前的趋势使这些角色变得不为人知。由于担心这些文字的灭绝,一些研究人员试图将包含楠榜文字的文件数字化。然而,数字化的过程并不是没有噪声的。这个问题使得我们需要使用二值化和去噪技术来处理扫描文档中的噪声,特别是在楠榜字符文档中。本文采用Niblack方法和Sauvola方法实现了局部自适应阈值分割。我们还实现了用于贝叶斯收缩的自适应小波阈值化,用于从二值化过程中去除盐和胡椒噪声。结果表明,与Niblack阈值法相比,Sauvola阈值法得到了更好的结果。我们在本文中的贡献是在楠榜字符文档中实现这两个过程
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引用次数: 0
Variability and Commonality Requirement Specification on Agile Software Development: Scrum, XP, Lean, and Kanban 敏捷软件开发中的可变性和共性需求规范:Scrum、XP、精益和看板
Pub Date : 2020-09-15 DOI: 10.1109/IC2IE50715.2020.9274564
Hana Rizky Herdika, E. K. Budiardjo
The user story widely studied insufficiently describes the software requirements. Many studies discuss the challenges of requirements specifications and proposed solutions. However, there are many agile methods and each method embraces different practices. Therefore, the solution has to follow each method’s ceremonies. Only a few studies discuss conducted practices in requirements specification development with the agile method and there are no studies that discuss practices comparisons among these methods. In this paper, we performed a systematic literature review to gather the available studies in procuring a current insight into the requirements engineering practices incorporate into the agile method. This study aims to map the variability and commonality practices among agile methods. The various and standard agile RE practices show crucial practices in the requirements specification development process. Moreover, it gives information on practices from other methods that increase the success of requirements specification development. From the systematic literature review, we found a total of 12 studies relevant to the study. There are eight variability and commonality practices between Scrum, XP, and Lean methods.
广泛研究的用户故事不足以描述软件需求。许多研究讨论了需求规范的挑战和提出的解决方案。然而,有许多敏捷方法,每种方法都包含不同的实践。因此,解决方案必须遵循每种方法的仪式。只有少数研究讨论了敏捷方法在需求规范开发中的实践,没有研究讨论这些方法之间的实践比较。在本文中,我们进行了系统的文献回顾,以收集可用的研究,以获得对敏捷方法中包含的需求工程实践的当前见解。本研究旨在映射敏捷方法之间的可变性和共性实践。各种标准的敏捷可重构实践展示了需求规范开发过程中的关键实践。此外,它还提供了来自其他方法的实践信息,这些方法增加了需求规范开发的成功。从系统文献综述中,我们共发现12项与本研究相关的研究。Scrum、XP和精益方法之间有8种可变性和共性实践。
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引用次数: 9
Change Detection of Floating Net Cages Quantities Utilizing Faster R-CNN 基于更快R-CNN的浮动网箱数量变化检测
Pub Date : 2020-09-15 DOI: 10.1109/IC2IE50715.2020.9274685
I. Priyanto, C. A. Hartanto, A. M. Arymurthy
The aquaculture method uses floating net cages are the most productive fish farming techniques. We utilize deep learning for change detection and monitoring of floating net cages quantities by detecting & counting the number of floating net cages plots on the same Region of Interest (RoI) in different years using google earth satellite imagery. The proposed methods apply Faster R-CNN for detection purposes and compare Faster R-CNN between using NASNet-A and inception-v2 as the feature extractor. Our experiments have been conducted on annotation images by cropping google earth images to demonstrate the effectiveness and efficiency of the proposed method. The results show that Faster R-CNN using NASNet-A achieves higher accuracy with longer training time. In addition, Faster R-CNN with inception-v2 network also provided promising results with lower training time.
采用浮式网箱的水产养殖方法是产量最高的养鱼技术。我们利用谷歌地球卫星图像,通过检测和计算不同年份同一感兴趣区域(RoI)上的浮动网箱地块的数量,利用深度学习进行浮动网箱数量的变化检测和监测。提出的方法采用Faster R-CNN进行检测,并比较了使用NASNet-A和inception-v2作为特征提取器的Faster R-CNN。我们通过裁剪google earth图像对标注图像进行了实验,验证了所提出方法的有效性和效率。结果表明,使用NASNet-A的更快R-CNN在更长的训练时间内获得了更高的准确率。此外,采用inception-v2网络的更快R-CNN在更短的训练时间内也取得了令人满意的效果。
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引用次数: 1
Analysis of USB Based Spying Method Using Arduino and Metasploit Framework in Windows Operating System 基于Arduino和Metasploit框架在Windows操作系统下基于USB的间谍方法分析
Pub Date : 2020-09-15 DOI: 10.1109/IC2IE50715.2020.9274643
Ferryansa, Avon Budiono, A. Almaarif
The use of a very wide windows operating system is undeniably also followed by increasing attacks on the operating system. Universal Serial Bus (USB) is one of the mechanisms used by many people with plug and play functionality that is very easy to use, making data transfers fast and easy compared to other hardware. Some research shows that the Windows operating system has weaknesses so that it is often exploited by using various attacks and malware. There are various methods used to exploit the Windows operating system, one of them by using a USB device. By using a USB device, a criminal can plant a backdoor reverse shell to exploit the victim’s computer just by connecting the USB device to the victim’s computer without being noticed. This research was conducted by planting a reverse shell backdoor through a USB device to exploit the victim’s device, especially the webcam and microphone device on the target computer. From 35 experiments that have been carried out, it was found that 83% of spying attacks using USB devices on the Windows operating system were successfully carried out.
不可否认的是,随着windows操作系统的广泛使用,对该操作系统的攻击也越来越多。通用串行总线(USB)是许多人使用的即插即用功能的机制之一,它非常易于使用,与其他硬件相比,它使数据传输更快、更容易。一些研究表明,Windows操作系统存在弱点,因此经常被各种攻击和恶意软件利用。有多种方法可以利用Windows操作系统,其中一种方法是使用USB设备。通过使用USB设备,犯罪分子可以在不被发现的情况下,通过将USB设备连接到受害者的计算机上,植入后门反向壳来利用受害者的计算机。本研究通过USB设备植入反壳后门,利用受害者的设备,特别是目标计算机上的网络摄像头和麦克风设备进行研究。从已经进行的35次实验中发现,在Windows操作系统上使用USB设备的间谍攻击中,有83%成功实施。
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引用次数: 0
Machine Learning Approach for Sentiment Analysis in Crime Information Retrieval 犯罪信息检索中情感分析的机器学习方法
Pub Date : 2020-09-15 DOI: 10.1109/IC2IE50715.2020.9274607
T. Mantoro, M. A. Ayu, R. Handayanto
Crime information is usually announced periodically. To get the information in real-time, the information should be retrieved through the information retrieval system automatically. The system should choose some appropriate keywords for retrieving the crime data. Eight keywords have been chosen which represented the most viral topic. The keywords in this study were analyzed regarding their sentiment from the hashtags in twitter posts. The Machine Learning algorithms were utilised such as Multinomal Naive Bayes, Random Forest Classifier, Linear SVM, and Nearestneighborhood (kNN) finding a better classifier. Sentiments, both positive and negative, are usually have been used by the website content designer to attract the reader. Most keywords showed negative sentiment which showed the negative reaction from the people. The sentiment analysis in Bahasa Indonesia also useful for understanding the people’s view on the types of crime as well as for keyword selection in the crime information retrieval system. As the result, near-repeat crime effect as a condition where criminal activity tends to repeat in the near place and time, can be predicted.
犯罪信息通常定期公布。为了实现信息的实时获取,需要通过信息检索系统对信息进行自动检索。系统应该选择一些合适的关键词来检索犯罪数据。8个关键词被选出来代表最具病毒性的话题。本研究中的关键词是根据twitter帖子中的标签来分析他们的情绪的。利用多项朴素贝叶斯、随机森林分类器、线性支持向量机和最近邻(kNN)等机器学习算法寻找更好的分类器。情绪,积极的和消极的,通常已经被网站内容设计师用来吸引读者。大多数关键词都表现出负面情绪,反映了人们的负面反应。印尼语的情感分析也有助于了解人们对犯罪类型的看法,以及在犯罪信息检索系统中选择关键字。因此,近似重复犯罪效应是指犯罪活动在最近的地点和时间内倾向于重复的一种情况,可以预测。
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引用次数: 4
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Pub Date : 2020-09-15 DOI: 10.1109/ic2ie50715.2020.9274652
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引用次数: 0
Emerging Knowledge Management Practice for Participative Govemment 参与式政府的新兴知识管理实践
Pub Date : 2020-09-15 DOI: 10.1109/IC2IE50715.2020.9274677
D. I. Sensuse, Hafizh Rafizal Adnan
Interaction between the government and the citizen is essential to improve public service and promote government openness. Knowledge resulted from e-participation initiatives is an asset for a government institution, especially to enable innovation. However, integrative study about knowledge management (KM) to support e-participation is currently lacking in the literature. Therefore, this study aimed to identify the state of the art of emerging knowledge management solution for participative government. The present study employed the Kitchenham method to explore literature related to knowledge management in the e-participation context. There were seventeen articles included in this study. Several alternatives to KM application, mechanism, and impacts were identified in this study. The findings of this study are expected to be a reference for further innovation in knowledge management, especially to optimize the potential of a combination of expert and public knowledge to enhance public service quality.
政府与公民的互动是改善公共服务、促进政府开放的必要条件。电子参与倡议产生的知识对政府机构来说是一笔财富,尤其是在促进创新方面。然而,目前文献中缺乏对知识管理支持电子参与的综合研究。因此,本研究旨在确定新兴的参与式政府知识管理解决方案的现状。本研究采用Kitchenham方法探讨电子参与情境下的知识管理相关文献。本研究共纳入了17篇文章。本研究确定了知识管理应用的几种替代方案、机制和影响。本研究结果可望为知识管理的进一步创新,特别是优化专家知识与公众知识结合的潜力,以提升公共服务品质提供参考。
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引用次数: 0
Pattern Detection in Heart Sound Signal Based on Android Application 基于Android应用的心音信号模式检测
Pub Date : 2020-09-15 DOI: 10.1109/IC2IE50715.2020.9274627
P. Oktivasari, Fikri Vallian, Riandini
The heart sound detector using an android-based electronic stethoscope is a development of an acoustic stethoscope. This tool converts the sound of the heartbeat into an electrical signal by wirelessly displaying the first heart sound signal S1 (Lub), and the second heart sound signal S2 (Dub) on the android application. A low-cost electronic stethoscope consisting of a condenser microphone that converts the sound of the heartbeat captured by the stethoscope into a heartbeat signal, a signal conditioning circuit that corrects the detected signal. The output signal from the conditioner circuit is processed by the ADC on the Arduino, which will then be sent to Android using Bluetooth. The open source software used to display heart rate detection results is Android Studio. S1 and S2 heart sound signal patterns have been recorded in real-time with intervals of 2-3 seconds duration, and no time delay. The resulting signals can be saved as graphs and WAV files.
使用基于机器人的电子听诊器的心音检测器是声学听诊器的一种发展。该工具通过在android应用程序上无线显示第一心音信号S1 (Lub)和第二心音信号S2 (Dub),将心跳的声音转换为电信号。一种低成本的电子听诊器,由一个电容式麦克风组成,它将听诊器捕捉到的心跳声音转换成心跳信号,信号调理电路校正检测到的信号。调理电路的输出信号由Arduino上的ADC处理,然后通过蓝牙发送给Android。显示心率检测结果的开源软件是Android Studio。实时记录S1和S2心音信号模式,间隔时间为2-3秒,无时间延迟。产生的信号可以保存为图形和WAV文件。
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引用次数: 0
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2020 3rd International Conference on Computer and Informatics Engineering (IC2IE)
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