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2019 5th International Conference on Advanced Computing & Communication Systems (ICACCS)最新文献

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Emotion Classification: Novel Deep Learning Architectures 情感分类:新的深度学习架构
Inthiyaz Basha Kattubadi, Dr. Rama Murthy Garimella
Emotion Classification is an important task for the machines to understand the emotional changes in human beings. In this research paper, we utilize a combination of Convolutional Neural Networks and Auto-Encoders to extract features for Emotion Classification. We proposed a total of six architectures. Among them, two architectures are trained on JAFFE (Japanese Female Facial Expressions), remaining four architectures are trained with Berlin Database of Emotional Speech. Good classification accuracy is attained with these architectures.
情绪分类是机器理解人类情绪变化的一项重要任务。在这篇研究论文中,我们利用卷积神经网络和自动编码器的组合来提取情感分类的特征。我们总共提出了六个架构。其中2个架构使用JAFFE (Japanese Female Facial expression)进行训练,其余4个架构使用Berlin Database of Emotional Speech进行训练。使用这些体系结构可以获得良好的分类精度。
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引用次数: 8
Secure Digital Service Payments using Zero Knowledge Proof in Distributed Network 分布式网络中基于零知识证明的安全数字服务支付
M. Harikrishnan, K. Lakshmy
Performing a fair exchange without a Trusted Third Party (TTP) was considered to be impossible. With multi party computation and practices like Proof-of-Work (PoW), blockchain accomplishes a fair exchange in a trustless network. Data confidentiality is a key challenge that has to be resolved before adopting blockchain for enterprise applications where tokenized assets will be transferred. Protocols like Zcash are already providing the same for financial transactions but lacks flexibility required to apply in most of the potential use cases of blockchain. Most of the real world application work in a way where a transaction is carried out when a particular action is performed. Also, the zero knowledge proof method used in Zcash, ZKSNARK has certain weaknesses restricting its adoption. One of the major drawbacks of ZKSNARK is that it requires an initial trust setup phase which is difficult to achieve in blockchain ecosystem. ZKSTARK, an interactive zero knowledge proof does not require this phase and also provides security against post quantum attacks. We propose a system that uses two indistinguishable hash functions along with ZKSTARK to improve the flexibility of blockchain platforms. The two indistinguishable hash functions are chosen from SHA3-finalists based on their security, performance and inner designs.
在没有可信第三方(TTP)的情况下进行公平交换被认为是不可能的。通过多方计算和工作量证明(PoW)等实践,区块链在无信任网络中实现了公平交换。数据保密性是一个关键的挑战,在将区块链用于企业应用程序之前,必须解决这个挑战,因为企业应用程序将转移标记化的资产。像Zcash这样的协议已经为金融交易提供了相同的功能,但缺乏在大多数区块链潜在用例中应用所需的灵活性。大多数实际应用程序的工作方式都是在执行特定操作时执行事务。此外,Zcash, ZKSNARK中使用的零知识证明方法也存在一定的弱点,限制了其采用。ZKSNARK的主要缺点之一是它需要初始信任建立阶段,这在区块链生态系统中很难实现。ZKSTARK是一种交互式零知识证明,不需要这个阶段,还提供了针对后量子攻击的安全性。我们提出了一个使用两个不可区分的哈希函数和ZKSTARK的系统,以提高区块链平台的灵活性。这两个难以区分的哈希函数是根据其安全性、性能和内部设计从sha3决赛中选择的。
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引用次数: 12
Health Trackers in Current Market: A Systematic Review, Trends and Challenges 健康追踪器在当前市场:系统回顾,趋势和挑战
K. Revathi, A. Samydurai, N. Kumar, K. Keerthana
The World Health Organization (WHO) in their statistical report on 2018 stated that the heart and pulmonary diseases are continuing to be at the top global causes of death. These diseases are known as non- communicable diseases (NCD) as it progresses slowly and exists for long duration of time. The early detection of NCD diseases could help in saving the life of human especially the aged ones. The continuous monitoring of crucial signs of human body like heart rate, blood oxygen level, blood pressure and blood glucose level assists in timely discovery and also provides room for the proposed treatment. Evolution of technologies like wireless sensor network, embedded systems, computing and storage which are grouped under the name of one umbrella technology called as ‘Internet of Things’ (IoT), brought various health trackers that monitors the physiological measures of human and also keep track of their daily activities in real without the need of the person to be in hospital, but those measures are updated to the medical experts concern time-to-time for their valuable suggestions and follow-ups. This paper is aimed to present the detailed study of such health trackers in the recent market and the scope for improvements owing to the medical equipment’s widely used in the hospital are also addressed.
世界卫生组织(世卫组织)在2018年统计报告中指出,心脏和肺部疾病仍然是全球最大的死亡原因。这些疾病被称为非传染性疾病(NCD),因为它进展缓慢,持续时间长。非传染性疾病的早期发现有助于挽救人类特别是老年人的生命。对心率、血氧、血压、血糖等人体关键体征的持续监测有助于及时发现,也为提出治疗方案提供了空间。无线传感器网络、嵌入式系统、计算和存储等技术的发展统称为“物联网”(IoT),带来了各种健康追踪器,这些追踪器可以监测人类的生理指标,并在现实中跟踪他们的日常活动,而无需患者住院。但这些措施都是及时更新到医学专家关注的,以便他们提供宝贵的建议和后续跟进。本文旨在介绍这种健康跟踪器在最近的市场上的详细研究,并指出由于医疗设备在医院的广泛使用,需要改进的范围。
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引用次数: 2
Question Answering on Structured Data using NLIDB Approach 基于NLIDB方法的结构化数据问答
Vishal Wudaru, Nikhil Koditala, A. Reddy, R. Mamidi
In this paper we present our work in building Natural Language Interface to Database (NLIDB) system using Intermediate query approach. This approach is demonstrated using Movie domain chatbot and can also be extended to different domains. The need of NLIDB System has increased in this fast paced world where more number of users are accessing databases through their Smart phones and web browsers.NLIDB System maps user’s Natural Language query to database query allowing user to extract information without any prior experience with databases. Results obtained are very promising and can tackle most of the user queries regarding target database.
本文介绍了采用中间查询方法构建自然语言数据库接口(NLIDB)系统的工作。使用Movie域聊天机器人演示了这种方法,也可以扩展到不同的域。在这个快节奏的世界里,越来越多的用户通过智能手机和网络浏览器访问数据库,NLIDB系统的需求也在增加。NLIDB系统将用户的自然语言查询映射到数据库查询,允许用户在没有任何数据库经验的情况下提取信息。得到的结果非常有希望,可以处理关于目标数据库的大多数用户查询。
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引用次数: 4
Arrhythmia classification on ECG using Deep Learning 基于深度学习的心电心律失常分类
A. Rajkumar, M. Ganesan, R. Lavanya
In this paper, an intellectual based electrocardiogram (ECG) signal classification approach utilizing Deep Learning(DL) is being developed. ECG plays important role in diagnosing various Cardiac ailments. The ECG signal with irregular rhythm is known as Arrhythmia such as Atrial Fibrillation, Ventricular Tachycardia, Ventricular Fibrillation, and so on. The main aspire of this task is to screen and distinguish the patient with various cardio vascular arrhythmia. This examination encourages us to recognize diverse kinds of arrhythmia utilizing Deep Learning algorithm. Here we use Convolutional Neural Network(CNN) a DL algorithm which is efficient in classifying signals. Utilizing CNN, features are learned Automatically from the time domain ECG signals which are acquired from MIT-BIH Database from Physiobank.com. The feature adapted specifically replaces manually extracted features and this analysis will help the Cardiologists in screening the patient with Cardiac illness effectively. The CNN is trained, tested using ECG Dataset obtained from MIT-BIH Database and from the signal 7 of arrhythmia were classified. The proposed system is compared for Various Activation function by varying the number of epochs. From the result obtained we came to know that ELU activation function gives better result with an accuracy of 93.6% and with a loss of 0.2.
本文提出了一种基于深度学习(DL)的智能心电图信号分类方法。心电图在诊断各种心脏疾病中起着重要的作用。具有不规则节律的心电信号被称为心律失常,如心房颤动、室性心动过速、心室颤动等。这项任务的主要目的是筛选和区分各种心律失常患者。这项检查鼓励我们利用深度学习算法识别各种心律失常。在这里,我们使用卷积神经网络(CNN)一种对信号进行有效分类的深度学习算法。利用CNN,从从Physiobank.com的MIT-BIH数据库中获取的时域心电信号中自动学习特征。特别适应的特征取代了人工提取的特征,这种分析将有助于心脏病专家有效地筛查心脏病患者。对CNN进行训练,使用从MIT-BIH数据库获得的ECG Dataset进行测试,并从心律失常信号7中进行分类。通过改变epoch的个数,对不同的激活函数进行了比较。从得到的结果可知,ELU激活函数具有较好的结果,准确率为93.6%,损失为0.2。
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引用次数: 44
Simulation and Implementation of Solar Power Penetration in an IEEE 5 bus System 太阳能在ieee5总线系统中的渗透仿真与实现
R. Jayabarathi, R. Sivaramakrishnan, S. Sruthi, M. Raakesh, B. Manoj
As the grid supply is not reliable and the price of electricity is increasing, it is necessary to introduce renewable energy sources like solar into the grid .The impact of solar penetrations into the grid has to be studied and analyzed. This paper deals with the simulation and hardware implementation of solar panel penetration in an IEEE 5 bus system. The simulation has been performed for different conditions with the help of ETAP (Electrical Transient Analysis Program) software. The power flow in the bus system is analyzed and impact of solar penetration in the system has been observed. Transient stability of the system is performed by creating a fault and observing the response of system in the absence of PV panels and also with different levels of PV penetration. The hardware implementation is conducted on a laboratory model of a 5 bus system with and without PV penetration to the grid. The power flow in the various buses and transmission lines are analyzed.
由于电网供应不可靠,电价不断上涨,有必要将太阳能等可再生能源引入电网,太阳能渗透电网的影响必须进行研究和分析。本文研究了在ieee5总线系统中太阳能板穿透的仿真和硬件实现。利用ETAP (Electrical Transient Analysis Program)软件对不同工况进行了仿真。分析了母线系统的潮流,并观察了太阳能穿透对系统的影响。系统的暂态稳定是通过创建一个故障并观察系统在没有光伏板和不同水平的光伏渗透下的响应来实现的。硬件实现是在一个5总线系统的实验室模型上进行的,该系统有和没有光伏渗透到电网。分析了各种母线和输电线路的潮流。
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引用次数: 5
Digital circuit simulation study of Lossy source coding for PAPR reduction 降低PAPR的有损源编码的数字电路仿真研究
M. V. Lakshmi, B. Kanmani
Telecommunication field is emerging rapidly with the huge demand for data communication and orthogonal frequency division multiplexing is one such modulation. The efficiency of an OFDM technique is high and multipath fading is improved to a greater extent. In spite of these benefits with an OFDM technique the instantaneous increase in the power output is the major drawback of an OFDM which results in high Peak to average power ratio. Due to this high PAPR the signal quality will degrade and reduces the efficiency. To reduce the PAPR in the OFDM symbol, a Lossy Coding method was proposed and implemented in Lab VIEW. OFDM symbols are generated for different symbol lengths and peak power is calculated for all possible combinations of the symbol lengths. The observation made was that only four combinations had high value of peak power compared with the other possible combinations. The proposed method reduces the peak power of the four combinations which in turn reduces the PAPR but with the signal distortion. This enforces Bit error rate. We also observed that as the length of the symbol increases the bit error rate will decrease.
随着对数据通信的巨大需求,电信领域正在迅速兴起,而正交频分复用就是其中一种调制方式。OFDM技术的效率高,多径衰落得到较大程度的改善。尽管OFDM技术具有这些优点,但功率输出的瞬时增加是OFDM的主要缺点,它导致峰值与平均功率比高。由于这种高PAPR,信号质量会下降,降低了效率。为了降低OFDM码元的PAPR,提出了一种有损编码方法,并在Lab VIEW中实现。为不同的符号长度生成OFDM符号,并为符号长度的所有可能组合计算峰值功率。观察结果表明,与其他可能的组合相比,只有四种组合具有较高的峰值功率值。该方法降低了四种组合的峰值功率,从而降低了PAPR,但增加了信号失真。这强制误码率。我们还观察到,随着符号长度的增加,误码率将降低。
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引用次数: 0
An Effective Swarm Optimization Based Intrusion Detection Classifier System for Cloud Computing 一种有效的基于群优化的云计算入侵检测分类系统
S. Kalaivani, A. Vikram, G. Gopinath
Most of the swarm optimization techniques are inspired by the characteristics as well as behaviour of flock of birds whereas Artificial Bee Colony is based on the foraging characteristics of the bees. However, certain problems which are solved by ABC do not yield desired results in-terms of performance. ABC is a new devised swarm intelligence algorithm and predominately employed for optimization of numerical problems. The main reason for the success of ABC algorithm is that it consists of feature such as fathomable and flexibility when compared to other swarm optimization algorithms and there are many possible applications of ABC. Cloud computing has their limitation in their application and functionality. The cloud computing environment experiences several security issues such as Dos attack, replay attack, flooding attack. In this paper, an effective classifier is proposed based on Artificial Bee Colony for cloud computing. It is evident in the evaluation results that the proposed classifier achieved a higher accuracy rate.
大多数蜂群优化技术的灵感来自于鸟群的特性和行为,而人工蜂群是基于蜜蜂的觅食特性。然而,ABC解决的某些问题在性能上并没有产生预期的结果。ABC算法是一种新的群体智能算法,主要用于数值问题的优化。ABC算法取得成功的主要原因在于,与其他群优化算法相比,ABC算法具有深不可测和灵活性等特征,并且ABC算法有许多可能的应用。云计算在应用程序和功能上有其局限性。云计算环境存在Dos攻击、重放攻击、泛洪攻击等安全问题。本文提出了一种有效的基于人工蜂群的云计算分类器。从评价结果可以明显看出,本文提出的分类器取得了较高的准确率。
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引用次数: 20
A Systematic Literature Review for Early Detection of Type II Diabetes 2型糖尿病早期检测的系统文献综述
M. S, S. Verma
Diabetes Mellitus is a syndrome that occurs due to insulin deficiency but there is no absolute cure for diabetes. There are larger effects of long term diabetes on human body such as eyes as cataracts, kidney failures, nerve damaging, ulcers in feet and gangrene. Hence there is need to understand that, this disease can be prevented through normal physiological process for avoiding greater damage. Thermography is identified as a potential tool to predict and detect the disease progression in an earlier stage in automated way. Actually this type of imaging maps the superficial temperature from the human body and able to identify the disease complications accurately. This paper discusses the recent literature studies with different intervention and comparison of appropriate methods used in detection of diabetes mellitus accurately. The intervention features of different works have been carried out with suitable analysis in identifying the issues and problems associated in medical diagnosis of Diabetic foot neuropathy. This work summarizes the use of thermography in diagnosis process and defines the scope for further improvement in the related research work.
糖尿病是由于胰岛素缺乏而引起的一种综合征,但没有绝对的治疗方法。长期糖尿病对人体的影响更大,如白内障、肾衰竭、神经损伤、足部溃疡和坏疽等。因此,有必要了解,这种疾病可以通过正常的生理过程来预防,以避免更大的损害。热成像被认为是一种潜在的工具,可以自动预测和检测疾病的早期进展。实际上,这种类型的成像可以绘制人体的表面温度,并能够准确地识别疾病并发症。本文讨论了近年来文献研究中采用不同干预手段对糖尿病进行准确检测的方法及比较。对不同作品的干预特点进行了适当的分析,以确定糖尿病足神经病变医学诊断中的相关问题和问题。本文总结了热成像技术在诊断过程中的应用,并明确了相关研究工作有待进一步完善的领域。
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引用次数: 5
Survey for Interlinking of DNA Models with Aadhaar Real-Time Records for Enhanced Authentication DNA模型与Aadhaar实时记录互联的研究进展
S. Rafi, N. Kumar, D. J. Kumar
Aadhaar is a unique identification issued by the Indian government to every resident of India. The Unique Identification Authority of India (UIDAI), which functions under the planning commission of India, is responsible for managing Aadhaar identification cards. The Aadhaar project was initiated as an attempt to have a unique identification document which would capture all the details including the demographic and biometric (fingerprints and iris scan) information. In some cases Biometric verification can even be faked remotely, with no product or equipment hack. Fingerprints can be duplicated from an assortment of surfaces and used to make a fake finger. Also, iris picture could be skimmed from photos and supplanted on a simulated eye-like protest. DNA (deoxyribonucleic acid), is the hereditary material and is unique in every person. As the DNA can’t be duplicated by any morphing techniques it will be more useful if we interlink the DNA samples to Aadhaar cards as an identification criteria.
Aadhaar是印度政府发给每位印度居民的唯一身份证件。印度唯一身份识别机构(UIDAI)隶属于印度计划委员会,负责管理Aadhaar身份证。Aadhaar项目的启动是为了拥有一种独特的身份证件,可以捕捉包括人口统计和生物特征(指纹和虹膜扫描)信息在内的所有细节。在某些情况下,生物识别验证甚至可以远程伪造,而无需入侵产品或设备。指纹可以从各种各样的表面上复制出来,用来制作假手指。此外,虹膜图像可以从照片中掠过并替换为模拟眼睛状抗议。DNA(脱氧核糖核酸)是遗传物质,在每个人身上都是独一无二的。由于DNA不能被任何变形技术复制,如果我们将DNA样本与Aadhaar卡连接起来作为识别标准,将会更有用。
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引用次数: 1
期刊
2019 5th International Conference on Advanced Computing & Communication Systems (ICACCS)
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