large-scale distributed training of deep neural networks results in models with worse generalization performance as a result of the increase in the effective mini-batch size. previous approaches attempt to address this problem by varying the learning rate and batch size over epochs and layers, or ad hoc modifications of batch normalization we propo...
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Cerebellar ataxia (CA) is concerned with the incoordination of movement caused by cerebellar dysfunction. Movements of the eyes, speech, trunk, and limbs are affected. Conventional machine learning approaches utilizing centralised databases have been used to objectively diagnose and quantify the severity of CA . Although these approaches achieved ...
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large-scale distributed training of deep neural networks results in models with worse generalization performance as a result of the increase in the effective mini-batch size. previous approaches attempt to address this problem by varying the learning rate and batch size over epochs and layers, or ad hoc modifications of batch normalization we propo...
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Environmental monitoring is must for all industries as its conditions majorly affect our prosperity, solace and efficiency. Because it is such an essential aspect that have an immense effect on health of operating personnel & other parameters like fire, smoke, dust and intruder detection along with weather forecasting in industries. But the systems...
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This study has been undertaken to develop Sustainable Waste Water treatment. Most of the river basins in India and elsewhere are closing or closed and experiencing moderate to severe water shortages, brought on by the simultaneous effects of agricultural growth, industrialization and urbanization. Current and future fresh water demand could be met ...
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Portable automatic seizure detection system is very convenient for epilepsy patients to carry. In order to make the system on-chip trainable with high efficiency and attain high detection accuracy, this paper presents a very large scale integration (VLSI) design based on the nonlinear support vector machine (SVM). The proposed design mainly consist...
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This paper describes a low cost and holistic approach to the water quality monitoring problem for drinking water distribution systems as well as for consumer sites. Our approach is to develop sensor nodes for real time and in-pipe monitoring, assessment of water quality on the fly and to calculate the amount of water delivered. The main sensor node...
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In this paper, we proposed an LPG Gas Weight and Leakage Detection System Using GSM .This is useful in various applications in homes and hotels. Many times it happens that because of the rush or due to the shortage of cylinder, there is a delay in providing the gas cylinder. Main reason behind this is delay in informing to the gas provider or we in...
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The development of telemonitoring via wireless body area networks (WBANs) is an evolving direction in personalized medicine and home-based mobile health. A WBAN consists of small, intelligent medical sensors which collect physiological parameters such as EKG (electrocardiogram), EEG (electroencephalography) and blood pressure. The recorded physiolo...
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This paper assesses the problems of financing Central and Eastern European agriculture during the present transitionary period and what the role of government is in this process. Initially the paper looks at why credit markets work imperfectly, even in well developed market economies, focusing on the problems related to asymmetric information, adve...
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The Indian construction industry is known to be inefficient and highly resistant to change. Even with a changing market and increasing competition, there are no obvious signs of commensurate changes in methods and approach. Project management, on the other hand, seems to offer what is needed in terms of tools and techniques to raise industry standa...
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Tendering processes are considered to be a suitable mechanism for governments to fairly assign contracts for construction projects and procurement. The demand for efficiencies to be created in the process has resulted in a significant number of governments implementing e-tendering systems. E-tendering systems generally involve the submission of ten...
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Now a days Attacker’s launch attack campaigns targeting the zero day vulnerability, compromising internet users on a large scale. The first response to such campaigns is to detect them and collect sufficient information regarding tools, techniques used to exploit the vulnerability. Hence effective capturing of the attack data and its timely dissemi...
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The time series data generated by massive sensors in Internet of Things (IoT) is extremely dynamic, heterogeneous, large scale and time-dependent. It poses great challenges (e.g. accuracy, reliability, stability) on the real-time analysis and decision making for different IoT applications. In this paper, we design, implement and evaluate EdgeLSTM, ...
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Replicating data across geo-distributed datacenters is usually necessary for large scale cloud services to achieve high locality, durability and availability. One of the major challenges in such geo-replicated data services lies in consistency maintenance, which usually suffers from long latency due to costly coordination across datacenters. Among ...
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Workflow scheduling in cloud environments has become a significant topic in both commercial and industrial applications. However, it is still an extraordinarily challenge to generate effective and economical scheduling schemes under the deadline constraint especially for the large scale workflow applications. To address the issue, this paper invest...
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The population of cloud computing greatly facilitates the sharing of explosively generated image today. While benefiting from the convenient of cloud, the privacy protection mechanism that commonly applied in cloud service makes the spreading of illegal and harmful data very hard to be detected or controlled. Such a realistic threat should be serio...
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Multiview fuzzy systems aim to deal with fuzzy modeling in multiview scenarios effectively and to obtain the interpretable model through multiview learning. However, current studies of multiview fuzzy systems still face several challenges, one of which is how to achieve efficient collaboration between multiple views when there are few labeled data....
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The rapid development of the Industrial Internet of Things (IIoT) has led to the explosive growth of industrial control data. Cloud computing-based industrial control models cause vast energy consumption. Most existing solutions try to reduce the overall energy consumption by optimizing task scheduling and disregard how to reduce the load of comput...
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Non-orthogonal multiple access (NOMA) exploits the potential of power domain to enhance the connectivity for Internet of Things (IoT). Due to time-varying communication channels, dynamic user clustering is a promising method to increase the throughput of NOMA-IoT networks. This paper develops an intelligent resource allocation scheme for uplink NOM...
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Point clouds are the most general data representations of real and abstract objects, and have a wide variety of applications in many science and engineering fields. Point clouds also provide the most scalable multi-resolution composition for geometric structures. Although point cloud learning has shown remarkable results in shape estimation and sem...
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Recently, supervised cross-modal hashing has attracted much attention and achieved promising performance. To learn hash functions and binary codes, most methods globally exploit the supervised information, for example, preserving an at-least-one pairwise similarity into hash codes or reconstructing the label matrix with binary codes. However, due t...
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Inverter Based Generators (IBGs) have been increasing significantly in power systems. Due to the demanding thermal rating of Power Electronics (PE), their contribution to the system Short Circuit Current (SCC) is much less than that from the conventional Synchronous Generators (SGs) thus reducing the system strength and posing challenges to sys...
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Large blackouts in power grids are often the consequence of uncontrolled failure cascades. The ability to predict the failure cascade process in an efficient and accurate manner is important for power system contingency analysis. In this paper, we propose to apply the influence model for the prediction and screening of failure cascades in large...
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Large blackouts in power grids are often the consequence of uncontrolled failure cascades. The ability to predict the failure cascade process in an efficient and accurate manner is important for power system contingency analysis. In this paper, we propose to apply the influence model for the prediction and screening of failure cascades in large...
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In past years, cloud storage systems saw an enormous rise in usage. However, despite their popularity and importance as underlying infrastructure for more complex cloud services, today’s cloud storage systems do not account for compliance with regulatory, organizational, or contractual data handling requirements by design. Since legislation increas...
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