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An Improved Evolutionary Algorithm in Formulating a Diet for Grouper 石斑鱼饲料配方的改进进化算法
Q2 Computer Science Pub Date : 2023-10-05 DOI: 10.33166/aetic.2023.05.006
Cai-Juan Soong, Rosshairy Abd Rahman, Razamin Ramli
This paper reveals the high demand of fish products in many countries, which subsequently highlighted the high demand of grouper fish species for human consumption. This high demand leads to the insufficient supply of wild ocean grouper fish in the market, thus justifying the need for farmed or cultured grouper fish. Basically, in grouper fish farming, large amounts of trash fish are needed as the feed for grouper fish, which is the carnivorous type of fish. However, since the cost of trash fish is too high, searching for alternative ingredients for the feed through modelling of feed formulation is an option for reducing or minimizing the farming cost. This led to the search for methods in giving the best combination of feedstuff ingredients with appropriate nutrients in formulating the feed. One prospective method is the Evolutionary Algorithm (EA) that has been applied in solving similar problems of diet formulation for several types of animals including livestock, poultry and shrimp. Hence, in this paper, an improved EA method known as the SR-SD-EA is proposed highlighting three important EA operators, which are initialization, selection and mutation. A semi random initialization operator is introduced to filter some important constraints thus increase the chances of obtaining feasible formulations or solutions. Subsequently, the novel selection operator embeds the concept of standard deviation in the SR-SD-EA as part of the function in minimizing the total cost of the formulated grouper fish feed. Eventually, the enhanced boundary-based mutation is also introduced in the algorithm to ensure the crucial constraint of the ingredients’ total weight must be met. The overall structure of the SR-SD-EA is presented as a framework, where the three methodological contributions are embedded. The preliminary findings of SR-SD-EA show that the obtained cost computed based on the Best-So-Far feed formulation as the solution is comparable, while all the crucial constraints are fulfilled.
本文揭示了许多国家对鱼类产品的高需求,随后突出了人类消费对石斑鱼的高需求。这种高需求导致市场上野生海洋石斑鱼供应不足,因此有理由需要养殖或养殖石斑鱼。基本上,在石斑鱼养殖中,需要大量的垃圾鱼作为石斑鱼的饲料,石斑鱼是肉食性鱼类。然而,由于垃圾鱼的成本太高,通过饲料配方建模来寻找饲料的替代成分是减少或最小化养殖成本的一种选择。这促使人们寻找在饲料配方中给予饲料成分与适当营养成分最佳组合的方法。一种有前景的方法是进化算法(EA),该方法已应用于解决家畜、家禽和虾等几种动物的日粮配方类似问题。因此,本文提出了一种改进的EA方法SR-SD-EA,突出了三个重要的EA算子,即初始化、选择和突变。引入半随机初始化算子来过滤一些重要的约束条件,从而增加获得可行公式或解的机会。随后,新的选择算子在SR-SD-EA中嵌入了标准偏差的概念,作为最小化配方石斑鱼饲料总成本的功能的一部分。最后,算法还引入了增强的基于边界的突变,以确保必须满足原料总权的关键约束。SR-SD-EA的整体结构作为一个框架呈现,其中嵌入了三种方法贡献。SR-SD-EA的初步结果表明,基于迄今为止最佳饲料配方作为解决方案计算的所得成本具有可比性,同时满足所有关键约束条件。
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引用次数: 0
The Application of Computer-Aided Under-Resourced Language Translation for Malay into Kadazandusun 马来语卡达山都逊语计算机辅助资源不足语言翻译的应用
Q2 Computer Science Pub Date : 2023-10-05 DOI: 10.33166/aetic.2023.05.002
Mohd Shamrie Sainin, Minah Sintian, Suraya Alias, Asni Tahir
A computer-aided language translation using a Machine translation (MT) is an application performed by computers (machines) that translates one natural language to another. There are many online language translation tools, but thus far none offers a sequence of text translations for the under-resourced Kadazandusun language. Although there are web-based and mobile applications of Kadazandusun dictionaries available, the systems do not translate more than one word. Hence, this paper aims to present the discussion of the preliminary translation of Malay to Kadazandusun. The basic word-to-word with dictionary alignment translation based on Direct Machine Translation (DMT) is selected to begin the exploration of the translation domain where DMT is one of the earliest translation methods which relies on the word-to-word approach (sequence-to-sequence model). This paper aims to investigate the under-resourced language and the task of translating from the Malay language to the Kadazandusun language or vice versa. This paper presents the application and the process as well as the results of the system according to the basic Kadazandusun word arrangement (Verb-Subject-Object) and its translation quality using the Bilingual Evaluation Understudy (BLEU) score. Several phases are involved during the process, including data collection (word pair translation), preprocessing, text selection, translation procedures, and performance evaluation. The preliminary language translation approach is proven to be capable of producing up to 0.5 BLEU scores which indicate that the translation is readable, however, requires post-editing for better comprehension. The findings are significant for the quality of the under-resourced language translation and as a starting point for other machine translation methodologies such as statistical or deep learning-based translation.
使用机器翻译(MT)的计算机辅助语言翻译是由计算机(机器)执行的将一种自然语言翻译成另一种自然语言的应用程序。有许多在线语言翻译工具,但到目前为止,没有一个提供资源不足的卡达赞都孙语的文本翻译序列。虽然有基于网络和移动应用程序的Kadazandusun词典,但这些系统只能翻译一个单词。因此,本文旨在探讨马来语对卡达山都逊语的初步翻译。选择基于直接机器翻译(DMT)的字典对齐的基本词对词翻译,开始对翻译领域的探索,其中DMT是最早依赖于词对词方法(序列对序列模型)的翻译方法之一。本文旨在探讨资源不足的语言和从马来语到卡达山都孙语或反之亦然的翻译任务。本文介绍了该系统的应用、过程和结果,根据卡达赞杜孙语基本词序(动词-主-宾)及其翻译质量,使用BLEU(双语评价Understudy)评分。翻译过程涉及几个阶段,包括数据收集(词对翻译)、预处理、文本选择、翻译程序和性能评估。初步的语言翻译方法被证明能够产生高达0.5的BLEU分数,这表明翻译是可读的,但需要后期编辑以更好地理解。这些发现对于资源不足的语言翻译的质量具有重要意义,并作为其他机器翻译方法(如统计或基于深度学习的翻译)的起点。
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引用次数: 0
Chest X-Ray Image Annotation based on Spatial Relationship Feature Extraction 基于空间关系特征提取的胸部x射线图像标注
Q2 Computer Science Pub Date : 2023-10-05 DOI: 10.33166/aetic.2023.05.007
Mohd Nizam Saad, Mohamad Farhan Mohamad Mohsin, Hamzaini Abdul Hamid, Zurina Muda
Digital imaging has become an essential element in every medical institution. Therefore, medical image retrieval such as chest X-ray (CXR) must be improved via novel feature extraction and annotation activities before they are stored into image databases. To date, many methods have been introduced to annotate medical images using spatial relationships after these features are extracted. However, the annotation performance for each method is inconsistent and does not show promising achievement to retrieve images. It is noticed that each method is still struggling with at least two big problems. Firstly, the recommended annotation model is weak because the method does not consider the object shape and rely on gross object shape estimation. Secondly, the suggested annotation model can only be functional for simple object placement. As a result, it is difficult to determine the spatial relationship feature after they are extracted to annotate images accurately. Hence, this study aims to propose a new model to annotate nodule location within lung zone for CXR image with extracted spatial relationship feature to improve image retrieval. In order to achieve the aim, a methodology that consists of six phases of CXR image annotation using the extracted spatial relationship features is introduced. This comprehensive methodology covers all cycles for image annotation tasks starting from image pre-processing until determination of spatial relationship features for the lung zone in the CXR. The outcome from applying the methodology also enables us to produce a new semi-automatic annotation system named CHEXRIARS which acts as a tool to annotate the extracted spatial relationship features in CXR images. The CHEXRIARS performance is tested using a retrieval test with two common tests namely the precision and recall (PNR). Apart from CHEXRIARS, three other annotation methods that are object slope, object projection and comparison of region boundaries are also included in the retrieval performance test. Overall, the CHEXRIARS interpolated PNR curve shows the best shape because it is the closest curve approaching the value of 1 on the X-axis and Y-axis. Meanwhile the value of area under curve for CHEXRIARS also revealed that this system attained the highest score at 0.856 as compared to the other three annotation methods. The outcome from the retrieval performance test indicated that the proposed annotation model has produced outstanding outcome and improved the image retrieval.
数字成像已经成为每个医疗机构的基本要素。因此,医学图像检索,如胸部x射线(CXR),必须通过新的特征提取和注释活动来改进,然后将其存储到图像数据库中。迄今为止,已经引入了许多方法来利用提取这些特征后的空间关系对医学图像进行注释。然而,每种方法的标注性能不一致,在检索图像方面表现不佳。值得注意的是,每种方法仍在努力解决至少两个大问题。首先,推荐的标注模型不考虑物体形状,依赖于物体粗形状估计,存在一定的缺陷。其次,建议的注释模型只能用于简单的对象放置。因此,提取空间关系特征后,难以确定空间关系特征,难以对图像进行准确标注。因此,本研究旨在提出一种新的模型,利用提取的空间关系特征对CXR图像进行肺区结节位置标注,以提高图像检索能力。为了实现这一目标,介绍了一种利用提取的空间关系特征对CXR图像进行六阶段标注的方法。这种全面的方法涵盖了从图像预处理到确定CXR中肺区空间关系特征的图像注释任务的所有周期。应用该方法的结果还使我们能够生成一个名为CHEXRIARS的新型半自动注释系统,该系统可作为注释CXR图像中提取的空间关系特征的工具。CHEXRIARS的性能测试采用两个常见的检索测试,即准确性和召回率(PNR)。除CHEXRIARS外,检索性能测试还包括物体斜率、物体投影和区域边界比较三种标注方法。总的来说,CHEXRIARS插值的PNR曲线显示出最好的形状,因为它是x轴和y轴上最接近1的曲线。同时,CHEXRIARS的曲线下面积值也显示,与其他三种标注方法相比,该系统的得分最高,为0.856。检索性能测试结果表明,所提出的标注模型取得了较好的效果,提高了图像检索的效率。
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引用次数: 0
Development of a Wearable Sensor Glove for Real-Time Sign Language Translation 用于实时手语翻译的可穿戴传感器手套的研制
Q2 Computer Science Pub Date : 2023-10-05 DOI: 10.33166/aetic.2023.05.003
Radzi Ambar, Safyzan Salim, Mohd Helmy Abd Wahab, Muhammad Mahadi Abdul Jamil, Tan Ching Phing
This article describes the development of a wearable sensor glove for sign language translation and an Android-based application that can display words and produce speech of the translated gestures in real-time. The objective of this project is to enable a conversation between a deaf person and another person who does not know sign language. The glove is composed of five (5) flexible sensors and an inertial sensor. This article also elaborates the development of an Android-based application using the MIT App Inventor software that produces words and speech of the translated gestures in real-time. The sign language gestures were measured by sensors and transmitted to an Arduino Nano microcontroller to be translated into words. Then, the processed data was transmitted to the Android application via Bluetooth. The application displayed the words and produced the sound of the gesture. Furthermore, preliminary experimental results demonstrated that the glove successfully displayed words and produced the sound of thirteen (13) translated sign languages via the developed application. In the future, it is hoped that further upgrades can produce a device to assist a deaf person communicates with normal people without over-reliance on sign language interpreters.
本文介绍了用于手语翻译的可穿戴传感器手套和基于android的应用程序的开发,该应用程序可以实时显示单词并生成翻译手势的语音。这个项目的目标是让一个聋哑人和另一个不懂手语的人之间进行对话。手套由五(5)个柔性传感器和一个惯性传感器组成。本文还详细介绍了使用MIT App Inventor软件开发基于android的应用程序,该应用程序可以实时生成翻译手势的单词和语音。这些手势由传感器测量,并传输到Arduino Nano微控制器,然后被翻译成文字。然后,将处理后的数据通过蓝牙传输到Android应用程序。该应用程序会显示单词并发出手势的声音。此外,初步的实验结果表明,手套通过开发的应用程序成功地显示单词并产生十三(13)种翻译的手语声音。未来,希望进一步的升级可以生产出一种设备,帮助聋哑人与正常人交流,而不必过度依赖手语翻译。
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引用次数: 0
Integration of Home Automation and Security System Controller with FPGA Implementation 家庭自动化与安防系统控制器集成与FPGA实现
Q2 Computer Science Pub Date : 2023-10-05 DOI: 10.33166/aetic.2023.05.001
Bryna Ngieng Sing Yii, Nabihah Ahmad, Mohd Helmy Abd Wahab, Warsuzarina Mat Jubadi, Chessda Uttraphan, Syed Zulkarnain Syed Idrus
A home automation system is essential for promoting a safe and comfortable living environment and notable energy conservation for the user. However, the system’s favour had been obstructed by cost, power usage, inadequate security, complexity, and no emergency backup power. Current home automation systems with controllers were limited by their number of ports, fixed architecture, non-durable and non-parallel executions. Keeping this in view, integration of home comfort system, security system, and the automatic load transfer switch features are proposed using the base of Cyclone IV E: EP4CE115F29C7 FPGA Board (DE2-115). The top-level module is developed via Verilog Hardware Descriptive Language (HDL) with the bottom-up technique and used test bench for functional verification via ModelSim-Altera. The PWM method was applied to the lighting system to control the dimming of light through its digital signals via a maximum 500000 counter to improve energy efficiency for the proposed design. In this project, 200Hz pulses are successfully simulated to prevent visible flickering of lights in duty cycle generation. The light intensity of 40% and 100% are verified and successfully generated according to the inputs provided by the status of the LDR sensor and IR sensor. The proposed controller gives correct corresponding outputs to the 13 actuators based on the detected input stimuli. The proposed design utilized a total of 162 (<1%) logic elements, 32 registers, and total pins of 74 (14%). The proposed design successfully integrated the three-sub module and provided control on comfort and security system operations to prevent service failure during power blackout conditions at the top-level and utilized a low ratio of the FPGA.
家庭自动化系统对于促进用户安全舒适的生活环境和显著的节能是必不可少的。然而,该系统受到成本、电力使用、安全性不足、复杂性和无应急备用电源等因素的阻碍。当前带有控制器的家庭自动化系统受到端口数量、固定架构、非持久和非并行执行的限制。基于此,本文提出了以Cyclone IV E: EP4CE115F29C7 FPGA板(DE2-115)为基础,集成家庭舒适系统、安防系统和负荷自动转换开关功能。顶层模块采用Verilog硬件描述语言(HDL)和自底向上技术开发,并使用ModelSim-Altera测试平台进行功能验证。将PWM方法应用于照明系统,通过最大500000计数器通过其数字信号控制光的调光,以提高所提出设计的能源效率。在这个项目中,成功地模拟了200Hz脉冲,以防止占空比产生中可见的闪烁。根据LDR传感器和IR传感器状态提供的输入,验证并成功生成40%和100%的光强。所提出的控制器根据检测到的输入刺激向13个执行器提供正确的相应输出。所提出的设计总共使用了162个(<1%)逻辑元件,32个寄存器和74个总引脚(14%)。该设计成功地集成了三个子模块,并提供了对舒适和安全系统操作的控制,以防止在顶层停电情况下的服务故障,并利用了低比例的FPGA。
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引用次数: 0
Prediction of MUET Results Based on K-Nearest Neighbour Algorithm 基于k近邻算法的MUET结果预测
Q2 Computer Science Pub Date : 2023-10-05 DOI: 10.33166/aetic.2023.05.005
Norlina Mohd Sabri, Siti Fatimah Azzahra Hamrizan
The machine learning based prediction has been applied in various fields to solve different kind of problems. In education, the research on the predictions of examination results is gaining more attentions among the researchers. The adaptation of machine learning for the prediction of students’ achievement enables the educational institutions to identify the high failure rate, learning problems, and reasons for low student performance. This research is proposing the prediction of the Malaysian University English Test (MUET) results based on the K-Nearest Neighbour Algorithm (KNN). KNN is a powerful algorithm that has been applied in various prediction problems. The prediction of the MUET results would help the students and lecturers to be more well prepared and could improve the required English language skills accordingly before the actual examination. The MUET result prediction is based on the student’s English courses grades and there are 516 data of students’ results that have been collected from Universiti Teknologi MARA (UiTM) Dungun campus. The performance measurement that has been used are the mean accuracy, percentage error and mean squared error (MSE). In this research, the KNN prediction model has generated an acceptable performance with 65.29% accuracy. For future work, KNN could be modified or hybridized to further improve its performance. Furthermore, other algorithms could also be explored into this problem to further validate the best predictive model for the prediction of the MUET results.
基于机器学习的预测已被应用于各个领域,以解决不同类型的问题。在教育领域,对考试成绩预测的研究越来越受到研究者的关注。将机器学习应用于学生成绩预测,使教育机构能够识别高不及格率、学习问题和学生成绩低的原因。本研究提出基于k近邻算法(KNN)的马来西亚大学英语测试(MUET)结果预测。KNN是一种功能强大的预测算法,已应用于各种预测问题。对MUET成绩的预测可以帮助学生和老师在实际考试前做更充分的准备,从而提高所需的英语语言技能。MUET成绩预测是基于学生的英语课程成绩,有516个学生成绩数据是从Universiti technologii MARA (UiTM) Dungun校区收集的。所使用的性能度量是平均精度、百分比误差和均方误差(MSE)。在本研究中,KNN预测模型产生了一个可接受的性能,准确率为65.29%。在未来的工作中,可以对KNN进行修饰或杂交,以进一步提高其性能。此外,还可以探索其他算法来解决这个问题,以进一步验证MUET结果预测的最佳预测模型。
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引用次数: 0
Automated Platelet Counter with Detection Using K-Means Clustering 使用k均值聚类检测的自动血小板计数器
Q2 Computer Science Pub Date : 2023-10-05 DOI: 10.33166/aetic.2023.05.004
Shafaf Ibrahim, Muhammad Faris Afiq Fauzi, Nur Nabilah Abu Mangshor, Raihah Aminuddin, Budi Sunarko
Platelet is a blood cell type that is stored and circulated in the human body. It acts as a blood thickening agent and prevents blood from overflowing whenever bleeding occurs. An excessive or inadequate number of platelets could lead to platelet-related diseases. The current practice of platelet counting involves the manual counting process using a haemocytometer, Wright’s Stain which uses the dyes to facilitate the differentiation of blood cell types, and a tally counter. Yet, this process can be time-consuming, demanding, and exhausting for haematologists, and likely to be prone to errors. Thus, this paper presents a study on automated platelet counter and detection using image processing techniques. The K-Means Clustering was employed to count and detect the presence of platelets in microscopic blood smear images. Several processes were performed prior to the K-means clustering, including image enhancement and YCbCr image formatting. Subsequently, image masking, as well as area thresholding were applied to eliminate every unwanted entity and highlight the visibility of the platelets before the number of platelets could be detected and counted. A comparative experiment was designed in which the K-Means Clustering platelet count and detection were compared with the actual number of platelets reported by haematologists. The platelet counts and detection were categorized into three detection categories which are Less Detection (LD), Accurate Detection (AD), and Over Detection (OD). The proposed study was evaluated to 90 testing platelet images. Out of the 90 testing images, 75 platelet images were perfectly counted and detected which returned 91.67% of accuracy. This signifies that the K-Means Clustering algorithm was discovered to be efficient and dependable for automated platelet counter and detection
血小板是一种在人体内储存和循环的血细胞。它作为一种血液增稠剂,在出血时防止血液溢出。血小板数量过多或不足都可能导致血小板相关疾病。目前的血小板计数方法包括使用血球计、赖特染色(Wright’s Stain)(使用染料促进血细胞类型的分化)和计数计数器进行人工计数。然而,对于血液病学家来说,这个过程可能是耗时的,要求很高的,而且很容易出错。因此,本文提出了利用图像处理技术进行自动血小板计数和检测的研究。k均值聚类法用于计数和检测显微镜下血液涂片图像中血小板的存在。在K-means聚类之前进行了几个处理,包括图像增强和YCbCr图像格式化。随后,在检测和计数血小板数量之前,应用图像掩蔽和区域阈值来消除每个不需要的实体并突出血小板的可见性。设计了一项比较实验,将k均值聚类血小板计数和检测结果与血液学家报告的实际血小板数量进行比较。血小板计数和检测分为低检(LD)、准检(AD)和超检(OD)三种检测类型。该研究被评估为90个测试血小板图像。在90张检测图像中,有75张血小板图像完全计数和检测,准确率为91.67%。这表明K-Means聚类算法对于血小板自动计数和检测是高效可靠的
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引用次数: 0
A Comparative Analysis of Community Detection Agglomerative Technique Algorithms and Metrics on Citation Network 引文网络上社区检测聚合技术、算法和度量的比较分析
Q2 Computer Science Pub Date : 2023-10-01 DOI: 10.33166/aetic.2023.04.001
Sandeep Kumar Rachamadugu, Pushphavathi Thotadara Parameshwarappa
Social Network Analysis is a discipline that represents social relationships as a network of nodes and edges. The construction of social network with clusters will contribute in sharing the common characteristics or behaviour of a group. Partitioning the graph into modules is said to be a community. Communities are meant to symbolize actual social groups that share common characteristics. Citation network is one of the social networks with directed graphs where one paper will cite another paper and so on. Citation networks will assist the researcher in choosing research directions and evaluating research impacts. By constructing the citation networks with communities will direct the user to identify the similarity of documents which are interrelated to one or more domains. This paper introduces the agglomerative technique algorithms and metrics to a directed graph which determines the most influential nodes and group of similar nodes. The two stages required to construct the communities are how to generate network with communities and how to quantify the network performance. The strength and a quality of a network is quantified in terms of metrics like modularity, normalized mutual information (NMI), betweenness centrality, and F-Measure. The suitable community detection techniques and metrics for a citation graph were introduced in this paper. In the field of community detection, it is common practice to categorize algorithms according to the mathematical techniques they employ, and then compare them on benchmark graphs featuring a particular type of assortative community structure. The algorithms are applied for a sample citation sub data is extracted from DBLP, ACM, MAG and some additional sources which is taken from and consists of 101 nodes (nc) with 621 edges € and formed 64 communities. The key attributes in dataset are id, title, abstract, references SLM uses local optimisation and scalability to improve community detection in complicated networks. Unlike traditional methods, the proposed LS-SLM algorithm is identified that the modularity is increased by 12.65%, NMI increased by 2.31%, betweenness centrality by 3.18% and F-Score by 4.05%. The SLM algorithm outperforms existing methods in finding significant and well-defined communities, making it a promising community detection breakthrough.
社会网络分析是一门将社会关系表示为节点和边缘网络的学科。具有集群的社会网络的构建有助于共享群体的共同特征或行为。将图划分为模块称为社区。社区象征着具有共同特征的实际社会群体。引文网络是一篇论文引用另一篇论文等具有有向图的社交网络。引文网络将有助于研究者选择研究方向和评估研究影响。通过构建带有社区的引文网络,可以指导用户识别与一个或多个领域相关的文献的相似度。本文介绍了有向图的聚类技术、算法和度量,以确定最具影响力的节点和相似节点组。构建社区所需要的两个阶段是如何产生有社区的网络和如何量化网络绩效。网络的强度和质量可以用模块化、标准化互信息(NMI)、中间性中心性和F-Measure等指标来量化。本文介绍了适用于引文图的社区检测技术和指标。在社区检测领域,通常的做法是根据它们使用的数学技术对算法进行分类,然后在具有特定类型的分类社区结构的基准图上对它们进行比较。该算法应用于一个样本引用子数据,该子数据从DBLP、ACM、MAG和一些其他来源中提取,由101个节点(nc)组成,有621条边,形成64个社区。数据集的关键属性是id、title、abstract、references。SLM利用局部优化和可扩展性来提高复杂网络中的社区检测。与传统方法相比,本文提出的LS-SLM算法模块性提高了12.65%,NMI提高了2.31%,中间中心性提高了3.18%,F-Score提高了4.05%。SLM算法在寻找重要且定义良好的社区方面优于现有方法,使其成为有希望的社区检测突破。
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引用次数: 0
Text Clustering of Tafseer Translations by Using k-means Algorithm: An Al-Baqarah Chapter View 基于k-means算法的Tafseer译文文本聚类:一个Al-Baqarah章节视图
Q2 Computer Science Pub Date : 2023-10-01 DOI: 10.33166/aetic.2023.04.003
Mohammed A. Ahmed, Hanif Baharin, Puteri NE. Nohuddin
Al-Quran is Muslims’ main book of belief and behaviour. The Al-Quran is used as a reference book by millions of Muslims worldwide, and as such, it is useful for Muslims in general and Muslim academics to gain knowledge from it. Many translators have worked on the Quran’s translation into many different languages around the world, including English. Thus, every translator has his/her own perspectives, statements, and opinions when translating verses acquired from the (Tafseer) of the Quran. However, this work aims to cluster these variations among translations of the Tafseer by utilising text clustering. As a part of the text mining approach, text clustering includes clustering documents according to how similar they are. This study adapted the (k-means) clustering technique algorithm (unsupervised learning) to illustrate and discover the relationships between keywords called features or concepts for five different translators on the 286 verses of the Al-Baqarah chapter. The datasets have been preprocessed, and features extracted by applying TF-IDF (Term Frequency-Inverse Document Frequency). The findings show two/three-dimensional clustering plotting for the first two/three most frequent features assigned to seven cluster categories (k=7) for each of five translated Tafseer. The features ‘allah/god’, ‘believ’, and ‘said’ are the three most features shared by the five Tafseer.
《古兰经》是穆斯林信仰和行为的主要书籍。《古兰经》是全世界数百万穆斯林的参考书,因此,它对穆斯林和穆斯林学者从中获取知识很有用。许多翻译者致力于将《古兰经》翻译成世界各地的多种语言,包括英语。因此,每个译者在翻译《古兰经》经文时都有自己的观点、陈述和观点。然而,这项工作的目的是通过利用文本聚类,聚类这些变化之间的翻译Tafseer。作为文本挖掘方法的一部分,文本聚类包括根据文档的相似度对文档进行聚类。本研究采用(k-means)聚类技术算法(无监督学习)对《Al-Baqarah》286节的5位不同译者的特征或概念关键词之间的关系进行了说明和发现。对数据集进行预处理,并采用TF-IDF (Term Frequency- inverse Document Frequency)提取特征。研究结果显示,对于五个翻译的Tafseer,将前两个/三个最常见的特征分配给七个聚类(k=7)的二维/三维聚类图。“真主/上帝”、“相信”和“说”是五个Tafseer共有的三个最常见的特征。
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引用次数: 0
Remote Augmented Reality Application: A Study on Cues and Behavioural Dimension 远程增强现实应用:线索和行为维度的研究
Q2 Computer Science Pub Date : 2023-10-01 DOI: 10.33166/aetic.2023.04.005
Nur Intan Adhani Binti Muhamad Nazri, Dayang Rohaya Awang Rambli
Remote augmented reality (AR) collaboration promotes an interactive way to present information to the user by conveying a message and instruction to the local and remote participants. Despite its advantages, it is found that due to the limited use of sensory modalities during the remote collaboration process, it can interrupt the transmission of information and interaction cues, by not conveying the right information in remote AR collaboration in which can affect focus, and responses between local and remote users. This study is intended to investigate the behavioural dimension of collaboration (collaborator’s behaviour) and cues involved between local and remote user for physical task. Six participants performed as local participants where they need to build a LEGO, while another 6 participants performed as remote participants that have a complete manual instruction. Participants were given maximum 60 minutes to complete the given task. The results shown that most of the time participants used gesture and speech cues to interact with each other. There are certain signals and keywords established by both participants to have mutual understanding in achieving desired goal. Moreover, it was shown that the task completed by using handsfree produce faster response.
远程增强现实(AR)协作通过向本地和远程参与者传递消息和指令,促进了一种向用户呈现信息的交互式方式。尽管有其优势,但研究发现,由于在远程协作过程中感官模式的使用有限,它可能会中断信息和交互线索的传递,而不是在远程AR协作中传达正确的信息,从而影响本地和远程用户之间的焦点和响应。本研究旨在探讨协作的行为维度(合作者的行为)和线索涉及本地和远程用户之间的物理任务。6名参与者扮演本地参与者,他们需要搭建一个乐高积木,而另外6名参与者扮演远程参与者,他们有完整的手工指导。参与者最多有60分钟的时间来完成给定的任务。结果表明,大多数情况下,参与者使用手势和语言线索来相互交流。参与者双方建立了一定的信号和关键词,以便在实现预期目标的过程中相互理解。此外,使用免提完成的任务产生更快的反应。
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引用次数: 0
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Annals of Emerging Technologies in Computing
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