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2017 11th International Conference on Intelligent Systems and Control (ISCO)最新文献

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Revamped Market-Basket Analysis using In-Memory Computation framework 改进的基于内存计算框架的购物篮分析
Pub Date : 1900-01-01 DOI: 10.1109/ISCO.2017.7855955
Thanmayee, H. Prasad
Data sets are growing day by day as they are being captured by information sensing devices such as mobiles, computers, wireless sensor networks, cameras, software logs, weblogs, remote sensing in various fields such as medical, engineering, science and many more. These large data sets are now called Big Data. Working with Big Data is not a common task. As this large data set has information hidden within them, researchers cannot and they have not ignored the large data set. Data mining is an interdisciplinary field in Computer Science which extracts information or the hidden patterns from data. Association rule mining and frequent itemset mining are popular data mining techniques that requires entire data to be in main memory. But large datasets does not fit into main memory. To handle this drawback, Hadoop MapReduce approach is used which has scalability and robustness features to handle large datasets. Apriori, Eclat and FP Growth are well known Frequent Itemset Mining algorithms. These algorithms are revised to work with Big Data using Hadoop MapReduce. But MapReduce framework has problems such as it stores the intermediate data in local disk. So the data needs to be accessed from the local disk which results in high latency problem. To address this issue Spark follows a general execution model that helps in in-memory computing and optimization of arbitrary operator graphs so that querying data becomes much faster when compared to the disk based engines like MapReduce. Thus the paper focuses on enhancing the performance of Frequent Itemset Mining using Apache Spark architecture and study the performance of this Revamped Market Basket Analysis based on FP-Growth by comparing it with Hadoop MapReduce implementation of Frequent Itemset Mining task, BigFIM and also with different datasets.
数据集每天都在增长,因为它们被信息传感设备捕获,如手机、计算机、无线传感器网络、相机、软件日志、网络日志、遥感等各个领域,如医疗、工程、科学等。这些大数据集现在被称为大数据。处理大数据并不是一项常见的任务。由于这个大数据集中隐藏着信息,研究人员不能也没有忽视这个大数据集。数据挖掘是计算机科学中的一个跨学科领域,它从数据中提取信息或隐藏模式。关联规则挖掘和频繁项集挖掘是常用的数据挖掘技术,它们需要将整个数据存储在主内存中。但是大型数据集不适合放在主存储器中。为了解决这个问题,使用了Hadoop MapReduce方法,该方法具有可伸缩性和鲁棒性,可以处理大型数据集。Apriori、Eclat和FP Growth是众所周知的频繁项集挖掘算法。这些算法被修改为使用Hadoop MapReduce处理大数据。但MapReduce框架存在将中间数据存储在本地磁盘等问题。因此需要从本地磁盘访问数据,这就导致了高延迟问题。为了解决这个问题,Spark遵循了一个通用的执行模型,该模型有助于内存计算和任意运算符图的优化,因此与基于磁盘的引擎(如MapReduce)相比,查询数据变得更快。因此,本文着重于利用Apache Spark架构增强频繁项集挖掘的性能,并通过与Hadoop MapReduce实现的频繁项集挖掘任务BigFIM以及不同数据集的比较,研究了基于FP-Growth的改进购物篮分析的性能。
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引用次数: 2
Coherence analysis between heart and brain of healthy and unhealthy subjects 健康与不健康受试者心、脑的一致性分析
Pub Date : 1900-01-01 DOI: 10.1109/ISCO.2017.7856015
P. Rajesh, K. Umamaheswari
This paper presents the coupling of frequency spectra or degree of association between the EEG and ECG signals at a particular frequency. Coherence is often interpreted as a measure of a functional association and ‘coupling’ between two signals. An electrocardiogram (ECG) is an electrical recording of the heart and is used in the investigation of heart disease. An electrocardiogram (ECG) is a graphic tracing of the electric current generated by the heart muscle during heart beat. It has been used extensively in medicine since it has been proven to be invaluable in various diagnostics applications and clinical applications. An EEG signal reflects the electrical activity of human brain. EEG signals arises from the fact that these waveforms provide the non-invasive diagnostic tool in a wealth of disorders that include epilepsy and comma assessment in intensive e care unit. In this paper, we analyzed the association of heart with brain signals (ECG and EEG) of fundamental animals like Dog and Cow by obtaining magnitude squared coherence and phase coherence parameters at a certain range of frequency. We also analyzed the coherence between heart and brain signals of Healthy subject, Comatic patient and Brain dead person.
本文介绍了在特定频率下脑电图和心电信号之间的频谱耦合或关联度。相干性通常被解释为两个信号之间功能关联和“耦合”的度量。心电图(ECG)是一种心脏的电记录,用于心脏病的调查。心电图(ECG)是在心脏跳动时由心肌产生的电流的图形追踪。它已被广泛应用于医学,因为它已被证明是无价的各种诊断应用和临床应用。脑电图信号反映了人脑的电活动。脑电图信号源于这样一个事实,即这些波形为包括癫痫和重症监护病房的逗号评估在内的大量疾病提供了非侵入性诊断工具。本文通过获得一定频率范围内的幅度平方相干性和相位相干性参数,分析了狗和牛等基础动物心脏与脑信号(心电和脑电图)的关联。我们还分析了健康受试者、昏迷患者和脑死亡患者心脑信号的一致性。
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引用次数: 1
Comparative analysis of similarity measures in Heterogeneous Information Network 异构信息网络中相似性度量的比较分析
Pub Date : 1900-01-01 DOI: 10.1109/ISCO.2017.7856002
Vaishali Patil, Ramesh Vasappanavara, T. Ghorpade
Information network derived from various domains are studied recently. Searching for Similarity is a major task into such types Information Network. Lot of research on computing similar objects is done in Homogeneous Information Network. But real world scenario can be described easily by Heterogeneous Information Network (HIN) which consists of different types of entities and relationship among them. Due to multiple type of entities and links between them in HIN, it is necessary to find the similarities between the nodes of HIN. In Homogeneous Information Network, there is only single type of node and links in between them. There are many existing methods by which similarity among the nodes of Homogeneous Information Network can be calculated. But those methods cannot be applied for the HIN because semantic meaning behind each path cannot be considered. If we want to apply techniques of Homogeneous Information Network on HIN then we need to project HIN into Homogeneous Information Network which causes loss of Information. So there is a need to apply different techniques or similarity measures on HIN to calculate the similarities between nodes in HIN. There are many similarity measures implemented by researchers for HIN. Similarity search basically concentrates on discovering the most similarity objects for a given query entity. In a comparative analysis section, we have discussed some of the measures used for similarity.
近年来,人们对各个领域衍生的信息网络进行了研究。相似度搜索是这类信息网络的主要任务。在同构信息网络中对相似对象的计算进行了大量的研究。而异构信息网络(HIN)是由不同类型的实体及其之间的关系组成的,可以很容易地描述真实世界的场景。由于HIN中存在多种类型的实体及其之间的联系,因此有必要找出HIN中各节点之间的相似性。在同构信息网络中,只有单一类型的节点和节点之间的链路。计算同质信息网络节点间相似度的方法有很多。但是这些方法不能应用于HIN,因为不能考虑每个路径背后的语义含义。如果要将同构信息网络技术应用到HIN上,就需要将HIN投影到同构信息网络中,这就造成了信息的丢失。因此,需要在HIN上应用不同的技术或相似度度量来计算HIN中节点之间的相似度。研究人员针对HIN实现了许多相似度度量。相似度搜索基本上集中于发现给定查询实体中最相似的对象。在比较分析部分,我们讨论了用于相似性的一些度量。
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引用次数: 1
Multi BSF layer InGaP/GaAs high efficiency solar cell 多BSF层InGaP/GaAs高效太阳能电池
Pub Date : 1900-01-01 DOI: 10.1109/ISCO.2017.7855998
Jivesh Verma, P. Dey, A. Prajapati, T. Das
Back Surface Field layer is very much important for both single and multi-junction solar cells for controlling the recombination rate. In this work multi BSF layers are used at both top and bottom cells to get higher external quantum efficiency from the cell. The work is done taking double junction InGaP/GaAs Solar cell and the optimization of the BSF layers is done using the computational numerical modeling with Silvaco ATLAS simulation technique. The structure, photo-generation rate, thickness of BSF layers is discussed in this paper. For this optimized cell structure, the maximum available short circuit current density is 17.35 mA/cm2 and is obtained at an open circuit voltage of 2.69 V which leads to a higher conversion efficiency.
后表面场层对于控制单结和多结太阳能电池的复合率都是非常重要的。在本研究中,为了获得更高的外部量子效率,在电池的顶部和底部都使用了多个BSF层。本文以双结InGaP/GaAs太阳能电池为研究对象,利用Silvaco ATLAS模拟技术对BSF层进行了优化。本文讨论了BSF层的结构、产光速率和厚度。对于这种优化的电池结构,在2.69 V开路电压下获得的最大可用短路电流密度为17.35 mA/cm2,从而提高了转换效率。
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引用次数: 2
Microcontroller based digital meter with alert system using GSM 基于单片机的数字电表报警系统
Pub Date : 1900-01-01 DOI: 10.1109/ISCO.2017.7856033
Bharathkumar V., Irshad Sm, G. S., R. Geethamani
The objective of this paper is to design and implement the low cost digital meter using PIC microcontroller, which could be used for monitoring the temperature and humidity of our environment. In this paper, it is focused mainly for our homes. The temperature is measured using LM35 temperature sensor and the humidity is measured using DHT11 humidity sensor. The measured parameters are displayed through LCD screens, normally like a digital meter. Apart from acting as a meter, it performs the function of automated control system which controls the motor driver connected to the fan, based on the temperature sensed using the microcontroller. When the fire catches the home and the sensor values exceeds the limit, an alert SMS will be sent to the person living in the home through the SIM900 GSM module. Also, an SMS carrying the home address will be sent to the fire department which alerts the fire fighters to urge to the location so that they can protect the home from fire. This paper also proposes the idea of automatic humidity controller using dehumidifier controlled by the microcontroller through the relay module. Thus, the proposed microcontroller based automated digital meter model has been discussed in the paper.
本文的目的是设计并实现一种基于PIC单片机的低成本数字仪表,用于环境温湿度的监测。在本文中,它主要针对我们的家庭。温度测量采用LM35温度传感器,湿度测量采用DHT11湿度传感器。测量参数通过LCD屏幕显示,通常像数字仪表一样。除了作为一个仪表,它执行自动控制系统的功能,控制连接到风扇的电机驱动器,基于使用单片机感知的温度。当火灾发生时,当传感器值超过限制值时,将通过SIM900 GSM模块向居住在家中的人发送警报短信。此外,带有家庭地址的短信将被发送到消防部门,提醒消防员赶到该地点,以便他们能够保护房屋免受火灾。本文还提出了利用单片机通过继电器模块控制除湿机实现自动湿度控制器的思想。因此,本文讨论了基于单片机的自动数字电表模型。
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引用次数: 18
Interference aware downlink scheduling algorithm in Mobile networks 移动网络中干扰感知下行链路调度算法
Pub Date : 1900-01-01 DOI: 10.1109/ISCO.2017.7855999
K. Ramkumar, P. Newton
Scheduling process is a tedious task in heterogeneous networks because of the large number of users and the reduced radio resource facilities. Scheduling is nothing but granting certain number of sources to the users in a frequency and timing fashion. Resources define the symbols and subcarriers for transmitting the bits in scheduling. There are many ways to assign these things to the subscribers. Interference is one of the biggest issues in downlink scheduling algorithms. Due to high demands of the user requirement and speed, the network fails to validate their interference ranges and finally it assigns the resources wrongly. This cause the Non-Interference users get more number of blocks when comparing with the Interference users. This paper proposes a new technique to overcome the above issue and assign the resources starting from the users who are in non-interference range to interference range users. The outcome of the proposed work properly assigns the resources and increases the system throughput of the standard subscribers and also mitigates the wrong resource block assignment of the interference users.
在异构网络中,由于用户数量庞大和无线资源设施的减少,调度过程是一项繁琐的任务。调度只不过是以频率和定时的方式向用户授予一定数量的源。资源定义了在调度中传输比特的符号和子载波。有很多方法可以将这些东西分配给订阅者。干扰是下行链路调度算法中最大的问题之一。由于对用户需求和速度的要求较高,网络无法验证其干扰范围,最终导致资源分配错误。这导致非干扰用户比干扰用户获得更多的区块数量。本文提出了一种克服上述问题的新技术,将资源从非干扰范围内的用户分配给干扰范围内的用户。该方法合理地分配了资源,提高了标准用户的系统吞吐量,减少了干扰用户的资源块分配错误。
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引用次数: 1
Recent trends in energy management of wireless wearable bio sensor design 能量管理无线可穿戴生物传感器设计的最新趋势
Pub Date : 1900-01-01 DOI: 10.1109/ISCO.2017.7856027
Dhanashri H. Gawali, V. Wadhai
Mobile healthcare systems have great potential for continuous monitoring. These devices are often battery operated. Thus energy management in these wearable, wireless devices is a big challenge for longer durations. In this paper a systematic review of various techniques suggested in literature for energy efficiency and management in such wireless devices is presented. Various research efforts made to optimize the power of wearable, wireless devices at system level, algorithm level and circuit level have been presented. It is followed by energy harvesting technology and wireless power transfer technology useful for energy management in wearable devices.
移动医疗保健系统具有持续监测的巨大潜力。这些设备通常由电池供电。因此,在这些可穿戴的无线设备中,长时间的能量管理是一个巨大的挑战。在本文中,系统地回顾了文献中提出的各种技术,以提高此类无线设备的能源效率和管理。在系统级、算法级和电路级为优化可穿戴无线设备的功率所做的各种研究工作已经被提出。其次是可穿戴设备能源管理的能量收集技术和无线电力传输技术。
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引用次数: 6
An advance system for emergency vehicles: Based on M2M communication 一种基于M2M通信的先进应急车辆系统
Pub Date : 1900-01-01 DOI: 10.1109/ISCO.2017.7856020
Saurabh Barthwal, Piyush Menghani
Today's traffic system is struggling for emergency vehicles like Ambulance, ICU on wheel, fire brigade's van etc. Presently we have “Move over Law” [1] which is also known as “Right Lane Life Lane”. This system works only for continuous flow of traffic but fails when any life savior vehicle stuck in a long traffic queue due to traffic light. This paper proposes new approach on managing all emergency vehicles of a city The basic idea behind this system is to keep the traffic flow continuous at every traffic light for life saving vehicle by using machine to machine (M2M) communication with aggregation and processing of vehicle and traffic light data to ensure continuous flow of traffic.
今天的交通系统正为救护车、监护病房、消防队的货车等紧急车辆而挣扎。目前我们有“Move over Law”[1],也被称为“Right Lane Life Lane”。该系统只适用于持续的交通流量,但当任何救命车因交通灯而被困在长长的交通队列中时,该系统就会失效。本文提出了一种管理城市所有应急车辆的新方法,其基本思想是通过机器对机器(M2M)通信,通过对车辆和交通灯数据的聚合和处理,使每个交通灯处的交通流量保持连续,以保证交通的连续性。
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引用次数: 5
Process parameter effects in the friction surfacing of MONEL over mild steel 工艺参数对MONEL在低碳钢表面摩擦堆焊的影响
Pub Date : 1900-01-01 DOI: 10.1109/ISCO.2017.7855981
B. Murugan, V. Balusamy, R. Padmanaban
MONEL has very good corrosion resistance and is used for cladding marine components. However, to avoid hot cracking, nickel is first overlayed on the substrate before MONEL is overlayed. Friction surfacing (FS) is a new solid state technique that could be used to do the same cladding process without any nickel overlay. In this study, MONEL K500 was deposited on AISI 1012 substrate using FS. Three parameters namely the spindle speed, axial load and the horizontal feed rate were varied at five levels and FS trials were conducted. Thickness of the coatings was measured for all the surfacing trials. Response surface methodology is utilized to develop a mathematical model for the thickness of the surfaced layer in terms of the three chosen parameters. The significance of the spindle speed, axial load and the horizontal feed rate in producing coatings with good bond integrity is investigated.
MONEL具有很好的耐腐蚀性,用于包覆船舶部件。然而,为了避免热裂,镍在蒙乃尔覆盖之前首先覆盖在基板上。摩擦堆焊(FS)是一种新的固体堆焊技术,它可以在没有镍覆盖层的情况下完成相同的堆焊过程。本研究使用FS将MONEL K500沉积在AISI 1012衬底上。对主轴转速、轴向载荷、水平进给速度等3个参数进行了5个水平的变化,并进行了FS试验。在所有的堆焊试验中都测量了涂层的厚度。利用响应面法根据所选的三个参数建立了表面层厚度的数学模型。研究了主轴转速、轴向载荷和水平进给速度对生产粘结完整性好的涂层的意义。
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引用次数: 4
Learning visual saliency with statistical priors 学习统计先验的视觉显著性
Pub Date : 1900-01-01 DOI: 10.1109/ISCO.2017.7855958
Gauri Deshpande, Santosh V. Chapaneri, Deepak Jayaswal
Saliency is the quality by which any object or a pixel in an image stands out relative to its neighbours. Detecting such regions from an image is a crucial problem of research, since it has wide applications in advertising, automatic image compression, image thumbnailing, etc. In this paper, a salient region detection approach is proposed by using machine learning. In order to train the saliency model, low level features such as color channels and their probabilities, also probabilities using 3D color histograms, subband features along with statistical priors such as frequency prior, color prior, chance of happening (CoH) and center bias prior (CBP) are used. The proposed model is compared with existing state of art algorithms. Human eye fixation points are used to compare the models by estimating area under ROC curves. Other parameters such as precision, recall, F-measure are also used for comparison. This comparison shows that the proposed saliency model gives better performance than the existing salient region detection approaches.
显着性是指图像中任何物体或像素相对于其邻居脱颖而出的质量。从图像中检测这些区域是一个关键的研究问题,因为它在广告、自动图像压缩、图像缩略等方面有着广泛的应用。本文提出了一种基于机器学习的显著区域检测方法。为了训练显著性模型,使用了低级别特征,如颜色通道及其概率,以及使用3D颜色直方图的概率,子带特征以及统计先验,如频率先验,颜色先验,发生机会(CoH)和中心偏差先验(CBP)。将该模型与现有算法进行了比较。人眼注视点通过估计ROC曲线下的面积来比较模型。其他参数如精度、召回率、f值也用于比较。结果表明,所提出的显著性模型比现有的显著性区域检测方法具有更好的性能。
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引用次数: 0
期刊
2017 11th International Conference on Intelligent Systems and Control (ISCO)
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