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Comparative analysis of ANFIS models in Prediction of Streamflow: the case of Seyhan Basin ANFIS模型在河流流量预测中的比较分析——以塞汉盆地为例
Pub Date : 2023-06-05 DOI: 10.18100/ijamec.1308666
F. Özkan, B. Haznedar
In order to sustain human life without problems, a rational planning is required for the conservation and use of existing water resources. The potential of future water sources should be determined as the first step in such planning. Therefore, river flow forecasting is necessary to provide basic information about a variety of problems related to the operation of river systems. In this study, the long-term daily flow values of the Zamantı River-Değirmenocağı, Zamantı River-Ergenuşağı, and Eğlence River-Eğribük stations in the Seyhan Basin in Turkey were examined. In order to predict the forward flow rate from past flow measurement values, the Adaptative Neuro-Fuzzy Inference System (ANFIS) model was trained using Backpropagation (BP), Hybrid Learning (HB), and Simulated Annealing (SA) algorithms, and the results were compared. The performance of ANFIS models created with different input parameters using Grid Partitioning (GP) and Fuzzy C-Means Clustering (FCM) methods was also examined. The evaluation criteria used for comparison were Mean Absolute Error (MAE), Root Mean Squared Error (RMSE), Determination Coefficient (R2), and Mean Absolute Percentage Error (MAPE). The best results for R2 values of 0.6854, 0.9242, and 0.9373 were obtained for FMSs using the BP model. As a result of the analysis, it was concluded that the BP algorithm could be used more successfully and effectively than other algorithms for training ANFIS parameters in nonlinear problems.
为了使人类的生活没有问题,需要对现有水资源的保护和利用进行合理的规划。未来水源的潜力应作为这种规划的第一步加以确定。因此,河流流量预报对于提供与水系运行有关的各种问题的基本信息是必要的。本文对土耳其Seyhan盆地的zamantyRiver-Değirmenocağı、zamantyRiver-Ergenuşağı和Eğlence River-Eğribük站的长期日流量进行了研究。为了从过去的流量测量值预测前向流量,采用反向传播(BP)、混合学习(HB)和模拟退火(SA)算法对自适应神经模糊推理系统(ANFIS)模型进行了训练,并对结果进行了比较。使用网格划分(GP)和模糊c均值聚类(FCM)方法创建不同输入参数的ANFIS模型的性能也进行了测试。比较的评价标准为平均绝对误差(MAE)、均方根误差(RMSE)、决定系数(R2)和平均绝对百分比误差(MAPE)。采用BP模型对FMSs的R2值分别为0.6854、0.9242和0.9373,结果最佳。分析结果表明,BP算法比其他算法更能成功有效地训练非线性问题中的ANFIS参数。
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引用次数: 1
Prediction of electromagnetic power density emitted from GSM base stations by using multiple linear regression 基于多元线性回归的GSM基站电磁功率密度预测
Pub Date : 2023-05-30 DOI: 10.18100/ijamec.1242024
Sema Atasever, U. Sorgucu
Today, smart phones based on different mobile communication technologies such as GSM, GPRS/EDGE, 3G, 4G, 5G and 6G have become an indispensable element for various services such as communication, entertainment, and banking. In this context, determining the base station power level is important in terms of limit values and public health, especially in places with high power density. In this study, electromagnetic power density of 31 different base stations was measured at 900 MHz frequency at 20, 40 and 60 meters distances from base stations. Since it is practically not possible to measure each base station from every distance, 3 different distances were chosen randomly. Then, using the power density values measured from different distances, electromagnetic power density estimation was made with multiple linear regression (MLR) analysis method for distances at intermediate distances (25, 30, 35, 45, 50 and 55 meters). In this study, MLR analysis method was applied for power density estimation for the first time in the literature and adjusted R-square value above 0.99 was obtained for each intermediate distance.
如今,基于GSM、GPRS/EDGE、3G、4G、5G、6G等不同移动通信技术的智能手机已经成为通信、娱乐、银行等各种业务不可或缺的元素。在这种情况下,确定基站的功率水平就限值和公共健康而言非常重要,特别是在功率密度高的地方。本研究测量了31个不同基站在900 MHz频率下距离基站20米、40米和60米的电磁功率密度。由于实际上不可能从每个距离测量每个基站,因此随机选择了3个不同的距离。然后,利用不同距离测得的功率密度值,采用多元线性回归(MLR)分析方法对中间距离(25、30、35、45、50和55 m)的电磁功率密度进行估计。本研究在文献中首次采用MLR分析法进行功率密度估计,各中间距离的调整后r方值均在0.99以上。
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引用次数: 0
Real-time Fast Selection System with Object Recognition and TSP algorithms 基于目标识别和TSP算法的实时快速选择系统
Pub Date : 2023-04-07 DOI: 10.18100/ijamec.1222732
M. Demi̇r
The stage before the conversion of agricultural products into post-harvest consumer products is the process of separating the raw products into appropriate classes. Today, this difficult manual separating process is a process in which a large number of workers work at an intense pace on the product line and the workforce is intensively spent. Disruptions in separating as a result of carelessness cause product loss, loss of time and cost increases. In this study, as an alternative to manual separating processes, a real-time separating system, which detects the products in the factory band with object recognition methods and enables fast positioning of the separating tool on the products, works simultaneously with object recognition and traveling salesman problem algorithms has been created. In this way, a low-budget separating system is recommended for large selecting processes with a time- and cost-effective selecting model. In the study, the creation of a real-time fast separating system with the support of the traveling salesman algorithm, performance evaluation and research and findings on the fast separating model are presented.
农产品转化为收获后消费品之前的阶段是将原料产品分成适当类别的过程。今天,这种困难的手工分离过程是一个过程,在这个过程中,大量工人在生产线上以紧张的速度工作,劳动力被密集地使用。由于粗心导致的分离中断会导致产品损失、时间损失和成本增加。在本研究中,作为人工分离过程的替代方案,创建了一种实时分离系统,该系统使用物体识别方法检测工厂带内的产品,并实现分离工具在产品上的快速定位,该系统与物体识别和旅行商问题算法同时工作。这样,对于具有时间和成本效益的选择模型的大型选择过程,建议使用低预算的分离系统。在本研究中,给出了基于旅行推销员算法的实时快速分离系统的构建、性能评价和快速分离模型的研究成果。
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引用次数: 0
Adaptive Neural-Fuzzy controller design combined with LQR to control the position of gantry crane 结合LQR的自适应神经模糊控制器设计对龙门起重机的位置进行控制
Pub Date : 2023-04-07 DOI: 10.18100/ijamec.1217697
Dinh Do Van
As the world grows, the demand for transporting goods is increasing, the number of goods in factories and ports is increasing, to transport all these goods, cranes are indispensable. In fact, currently, crane rigs working in factories and ports operate with low stability, when working or the phenomenon of swaying of the load occurs, leading to inaccurate positioning, loss of safe transportation of goods. To overcome these shortcomings, the paper proposes the design of a neural-fuzzy adaptive controller combined with an LQR controller (ANFIS-LQR) to control the forklift's position in the shortest time to achieve the desired exact position. At the same time, we want to control the deflection angle of the load so that the vibration when working is minimal. To check and evaluate the quality and stability of the system; the proposed design controller is simulated on MATLAB/Simulink software in the case of changes in system parameters and noise affecting the gantry crane system. To evaluate the superiority of the paper compared with published works, the author compares ANFIS-LQR with other published control methods such as DE-PID, Fuzzy-PD, Fuzzy dual and Fuzzy sliding, the simulation results show that the neural-fuzzy adaptive controller combined with the proposed LQR controller works well t_xlvt=2.1s , t_xlgt=3.5s, 0max=0.3(rad).
随着世界的发展,运输货物的需求越来越大,工厂和港口的货物数量越来越多,要运输所有这些货物,起重机是必不可少的。事实上,目前在工厂和港口工作的起重机运行稳定性较低,在工作时或出现载荷摇摆的现象,导致定位不准确,失去货物的安全运输。为了克服这些缺点,本文提出了一种结合LQR控制器的神经模糊自适应控制器(ANFIS-LQR)的设计,以在最短的时间内控制叉车的位置,以达到期望的精确位置。同时,我们要控制负载的偏转角度,使工作时的振动最小。检查和评价系统的质量和稳定性;在MATLAB/Simulink软件上对所设计的控制器进行了系统参数和噪声变化对龙门起重机系统影响的仿真。为了评价本文与已发表的文献相比的优越性,作者将anfiss -LQR与其他已发表的控制方法如DE-PID、Fuzzy- pd、Fuzzy对偶和Fuzzy滑动进行了比较,仿真结果表明,与所提出的LQR控制器相结合的神经模糊自适应控制器效果良好(t_xlvt=2.1s, t_xlgt=3.5s, 0max=0.3(rad))。
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引用次数: 0
Design and Analysis of a Four DoF Robotic Arm with Two Grippers Used in Agricultural Operations 农业作业中四自由度双夹持机械臂的设计与分析
Pub Date : 2023-04-07 DOI: 10.18100/ijamec.1217072
Basheer Altawi̇l, F. C. Can
Both academic and commercial interest in agricultural robots has increased recently. This is due to the fact that agricultural robots address significant issues such as seasonal labor shortages during harvest and the rising concern over environmentally friendly practices. Because of these, several distinct agricultural robots have already been created for a variety of purposes, with varying degrees of success, including monitoring, spraying, harvesting, transport, etc. As a result, agriculture automation became unfeasible and unprofitable. The purpose of this study is to provide a new methodology for multitasking in performing agriculture operations by designing a 4 Degrees of freedom (4DoF) robotic arm with a new mechanism that has a different configuration with 2 grippers. We did kinematics and kinetics calculations using Denavit-Hardenberg (D-H) method with Lagrangian mechanics, and with the help of Christoffel Symbols of the First Kind, also We used Robot Operating System (ROS) to provide potential solutions using it. It is easy to be paired with other open-source technologies, such as android or IoT technologies. The robot arm can work synchronously with other hardware, sensors, cameras, and agricultural machines concerning farming operations. In conclusion, we believe that this new configuration will open a door for agricultural tasks to be easily automated and achieved using robotic technologies.
最近,学术界和商界对农业机器人的兴趣都有所增加。这是由于农业机器人解决了诸如收获期间季节性劳动力短缺以及对环保实践日益关注等重大问题。正因为如此,一些不同的农业机器人已经被创造出来,用于各种各样的目的,取得了不同程度的成功,包括监控、喷洒、收获、运输等。因此,农业自动化变得不可行,无利可图。本研究的目的是通过设计一种具有不同结构的带有两个夹持器的4自由度(4DoF)机械臂,为农业作业中的多任务处理提供一种新的方法。利用拉格朗日力学的Denavit-Hardenberg (D-H)方法进行运动学和动力学计算,并借助第一类Christoffel符号,利用机器人操作系统(ROS)提供潜在的解决方案。它很容易与其他开源技术(如android或IoT技术)配对。机器人手臂可以与其他硬件、传感器、相机和农业机械同步工作。总之,我们相信这种新的配置将为农业任务的自动化打开一扇大门,并使用机器人技术实现自动化。
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引用次数: 0
Epileptic seizure detection combining power spectral density and high-frequency oscillations 结合功率谱密度和高频振荡的癫痫发作检测
Pub Date : 2023-04-07 DOI: 10.18100/ijamec.1229907
Rabia Tutuk, Reyhan Zengi̇n
Detection of pre-seizure signs in epileptic signals may help patients to survive the seizure with minimal damage. This study aims to detect epileptic seizure patterns using EEG datasets of five patients. The signals' maximum power spectral density (PSD) and high-frequency oscillations (HFOs) signals are investigated. The PSDs of all patients' signals are calculated, and the subbands of the maximum PSD are examined. It is observed that 95%, 85%, 85%, 75%, and 80% of the channels of the five patients are in the sum of delta and theta subbands of the maximum PSD, respectively. All patients' maximum power frequency subbands of F4 and T3 channels included only delta and theta subbands. Furthermore, frequency increase rates of pre-ictal and ictal signals are investigated, and increasing PSDs of ripples and fast ripples are then calculated. A much higher-frequency ripple follows the low-frequency ripple in 75%, 75%, 65%, 85%, and 75% of the channels of the first, second, third, fourth, and fifth patients, respectively. For the pre-ictal data, a much higher frequency ripple is not seen, followed by a low-frequency ripple in 90%, 85%, 75%, 90%, and 90% of all channels of five patients, respectively. In addition, in this study, the frequency of signals is observed to be 80 Hz and above in the Fp2, C4, P4, O2, and Pz channels, which are common to all patients. Consequently, examining PSD and HFO signals ensures the detection of the differences between the data sets and detects the epileptic seizure patterns in all five patients.
在癫痫信号中检测出癫痫发作前的迹象可能有助于患者以最小的损害度过癫痫发作。本研究旨在利用5例患者的脑电图数据集检测癫痫发作模式。研究了信号的最大功率谱密度(PSD)和高频振荡(HFOs)信号。计算所有患者信号的PSD,并检测最大PSD的子带。观察到,5例患者的通道分别有95%、85%、85%、75%和80%位于最大PSD的delta和theta亚带之和。所有患者F4和T3通道的最大功率频率子带均仅包括delta和theta子带。此外,研究了临界前和临界信号的频率增加率,并计算了波纹和快速波纹的增加psd。在第一、第二、第三、第四和第五名患者的75%、75%、65%、85%和75%的通道中,低频纹波之后分别出现了频率更高的纹波。对于孕前数据,没有看到更高频率的纹波,随后在5例患者的所有通道中分别有90%、85%、75%、90%和90%出现低频纹波。此外,在本研究中,Fp2、C4、P4、O2和Pz通道的信号频率均在80 Hz及以上,这些信号在所有患者中都是常见的。因此,检查PSD和HFO信号确保检测数据集之间的差异,并检测所有5例患者的癫痫发作模式。
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引用次数: 0
Evaluation of the performance of an unmanned aerial vehicle with artificial intelligence support and Mavlink protocol designed for response to social incidents response 基于人工智能支持和Mavlink协议的无人机性能评估,用于应对社会事件
Pub Date : 2023-04-07 DOI: 10.18100/ijamec.1216914
Murat Toren, Hakki Mollahasanoglu, Mehmet Çepni̇, Mücahit Kina
The unmanned aerial vehicle name is TOMHA, which was developed to be used in the response of social incidents, aims to support the operational activities of security forces in response to social incidents, to expand their domination areas, to detect incidents that may disturb social peace in advance and to provide rapid intervention with the new unmanned aerial vehicle technologies developed. The scope of the TOMHA system designed was kept comprehensive compared to other unmanned aerial vehicles and the scope includes intervention to social events, ordering in local administrations, defense, reconnaissance and attack activities in military operations, inspections arranged for public interest, AFAD and service areas, forest fires detection and intervention, and public order operations. This TOMHA is being developed using the Pixhawk flight control card and the jetson nano artificial intelligence card. In addition to these cards, it has the feature of manual or artificial intelligence supported autonomous flight thanks to GPS, telemetry, FPV transceiver module, camera systems and national software to be used. It is controlled through the controller using RC communication channel for manual use. TOMHA has a flight time of 13.6 minutes, a thrust of 4.45G and a speed of 78 km and a mileage of 4993 meters in optimum conditions. The findings obtained by the tests performed with the designed TOMHA prototype show similar results with the literature. Thanks to the national design, TOMHA stands out when it encounters other unmanned aerial vehicles. It is seen that the response of the system to the sudden changes caused by the maneuver movements in the simulation environment is very fast and it follows the changes.
无人机名称为TOMHA,是为应对社会事件而开发的,旨在支持安全部队应对社会事件的作战活动,扩大其统治范围,提前发现可能扰乱社会和平的事件,并提供快速干预的新型无人机技术。与其他无人机相比,设计的TOMHA系统的范围保持全面,范围包括社会事件干预,地方行政秩序,军事行动中的防御,侦察和攻击活动,公共利益安排的检查,AFAD和服务区域,森林火灾探测和干预,以及公共秩序行动。这款TOMHA是使用Pixhawk飞行控制卡和jetson纳米人工智能卡开发的。除了这些卡之外,由于GPS、遥测、FPV收发模块、摄像系统和国家软件的使用,它还具有手动或人工智能支持的自主飞行功能。它是通过控制器控制使用RC通信通道手动使用。TOMHA的飞行时间为13.6分钟,推力为4.45G,最佳条件下的速度为78公里,里程为4993米。用所设计的TOMHA原型进行的测试结果与文献的结果相似。多亏了国家设计,TOMHA在遇到其他无人驾驶飞行器时脱颖而出。可以看出,在仿真环境中,系统对机动运动引起的突然变化的响应非常快,并遵循这些变化。
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引用次数: 0
A Manhattan distance based hybrid recommendation system 基于曼哈顿距离的混合推荐系统
Pub Date : 2023-03-31 DOI: 10.18100/ijamec.1232090
Begüm Uyanik, Günce Keziban Orman
Many online service providers use a recommendation system to assist their customers' decision-making by generating recommendations. Accordingly, this paper proposes a new recommendation system for tourism customers to make online reservations for hotels with the features they need, saving customers time and increasing the impact of personalized hotel recommendations. This new system combined collaborative and content-based filtering approaches and created a new hybrid recommendation system. Two datasets containing customer information and hotel features were analyzed by Recency, Frequency, Monetary (RFM) method in order to identify customers according to their purchasing nature. The main idea of the recommendation system is to establish correlations between users and products and make the decision to choose the most suitable product or information for a particular user. As a result of the exponential growth of online data, this vast amount of information for use in the tourism industry can be leveraged by decision-makers to make purchasing decisions[20]. Filtering, prioritizing, and beneficially presenting relevant information reduces this overload. There are following three main ways that recommendation systems can generate a recommendation list for a user; content-based, collaborative-based, and hybrid approaches[1]. This paper describes each category and its techniques in detail. RFM Analysis is used to identify customer segments by measuring customers' purchasing habits. It is the process of labeling customers by determining the Recency, Frequency, and Monetary values of their purchases and ranking them on a scoring model. Scoring is based on how recently they bought (Recency), how often they bought (Frequency), and purchase size (Monetary). Experimental results show that the accuracy of behavior analysis using Manhattan distance-based hybrid filtering is greatly improved compared to collaborative and content-based algorithms.
许多在线服务提供商使用推荐系统,通过生成推荐来帮助客户做出决策。据此,本文提出了一种新的推荐系统,供旅游客户根据自己需要的功能在网上预订酒店,节省了客户的时间,增加了个性化酒店推荐的影响。这个新系统结合了协作和基于内容的过滤方法,创建了一个新的混合推荐系统。采用RFM (recent, Frequency, Monetary)方法对包含顾客信息和酒店特征的两个数据集进行分析,以便根据顾客的购买性质来识别顾客。推荐系统的主要思想是建立用户和产品之间的相关性,并决定为特定用户选择最合适的产品或信息。由于在线数据呈指数级增长,决策者可以利用旅游行业中使用的大量信息来做出购买决策[20]。过滤、确定优先级和有益地呈现相关信息可以减少这种过载。推荐系统可以通过以下三种主要方式为用户生成推荐列表;基于内容、基于协作和混合方法[1]。本文详细介绍了每个分类及其技术。RFM分析法通过测量顾客的购买习惯来识别顾客细分。它是通过确定客户购买的最近次数、频率和货币价值并在评分模型上对其进行排序来标记客户的过程。评分是基于他们最近购买的时间(Recency)、购买的频率(Frequency)和购买的规模(Monetary)。实验结果表明,与基于协作和基于内容的算法相比,基于曼哈顿距离的混合过滤算法的行为分析精度有很大提高。
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引用次数: 2
Clustering Application and Evaluation of the Countries' Word Risk and Climate Risk Indices 国家世界风险与气候风险指数的聚类应用与评价
Pub Date : 2023-03-31 DOI: 10.18100/ijamec.1217399
Nazmiye Eligüzel, S. Aydoğan, Ibrahim Miraç Eligüzel
Societies take various initiatives to reduce the impact of natural disasters. Unfortunately, certain nations and regions are better suited than others to finding solutions to the problem, whether for political, cultural, economic, or other factors. This paper deals with the cluster analysis of 170 countries based on world risk index and climate risk index data. We use the k-means approach for clustering in sequential stages of this work. Specifically, we first carry out both the elbow method and silhouette scores to determine the number of clusters. Then clustering analysis is carried out, taking into account the World Risk Index, which includes risks of both exposure and vulnerability. Second, the Climate Risk Index is implemented into the first stage results by clustering countries after determining the number of clusters. Lastly, statistical analyses on the change of clusters for exposure, vulnerability, and climate risk are investigated and discussed in detail. Taken together, each of the risk elements like earthquake, tsunami, socioeconomic development, health care capability, etc. differs by nation. Clusters of countries with similar risks are reported. When the climate risk index is included in the evaluation, the number of clusters increases. The Climate Risk Index has been determined as a variable that cannot be ignored when countries are clustered according to their risk profiles.
社会采取各种措施减少自然灾害的影响。不幸的是,某些国家和地区比其他国家和地区更适合寻找解决问题的办法,无论是出于政治、文化、经济还是其他因素。本文基于世界风险指数和气候风险指数数据,对170个国家进行了聚类分析。我们在这项工作的连续阶段使用k-means方法进行聚类。具体来说,我们首先采用肘部法和轮廓评分来确定聚类的数量。然后考虑世界风险指数(World Risk Index)进行聚类分析,其中包括暴露风险和脆弱性风险。其次,在确定聚类数量后,将气候风险指数通过聚类国家实施到第一阶段结果中。最后,对暴露度、脆弱性和气候风险聚类的变化进行了统计分析。总的来说,地震、海啸、社会经济发展、卫生保健能力等每一个风险因素都因国家而异。报告了具有类似风险的国家群。当将气候风险指数纳入评价时,聚类数量增加。气候风险指数已被确定为一个变量,在根据各国的风险概况对其进行聚类时,该变量不可忽视。
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引用次数: 0
A Novel Article Recommendation System Empowered by the Hybrid Combinations of Content-Based State-of-the-Art Methods 一种基于内容的新型文章推荐系统
Pub Date : 2023-03-31 DOI: 10.18100/ijamec.1199886
İlya Kuş, Sinem Bozkurt Keser, Savas Okyay
The initial literature reviewing step is of great importance during any scientific reporting. Nevertheless, finding relevant papers grows tough as the number of online scientific publications rapidly increases. Correspondingly, the need for article recommendation systems has emerged, which aim to recommend new papers suitable for the researchers’ interests. Using these systems provides researchers access to related publications quickly and effectively. In this study, a novel article recommendation system, which is empowered by the hybrid combinations of content-based state-of-the-art methods, is proposed. Various methods are utilized comparatively for an in-depth analysis, and user profiles are evaluated. 41,000 articles collected from the ARXIV dataset are used in the performance evaluation. In the experiments in which Word2vec and LDA are combined, Precision@50, Recall@50, and F1-score@50 achieve the highest performance with .206, .791, and .498 values, respectively. The in-depth analysis and the numerical findings justify that the proposed system is strong and promising compared to the literature.
在任何科学报告中,最初的文献回顾步骤都是非常重要的。然而,随着网上科学出版物数量的迅速增加,找到相关论文变得越来越困难。相应地,对文章推荐系统的需求也出现了,该系统旨在推荐适合研究人员兴趣的新论文。使用这些系统使研究人员能够快速有效地访问相关出版物。在本研究中,提出了一种新的文章推荐系统,该系统由基于内容的最先进的方法混合组合而成。比较使用了各种方法进行深入分析,并对用户概况进行了评估。从ARXIV数据集中收集的41,000篇文章用于性能评估。在结合Word2vec和LDA的实验中,Precision@50、Recall@50和F1-score@50的性能最高,分别为。206、。791和。498。深入的分析和数值结果证明,与文献相比,所提出的系统是强大的和有前途的。
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引用次数: 0
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International Journal of Applied Mathematics Electronics and Computers
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