The ongoing development of various lightweight and portable EEG signal acquisition devices provides the opportunity to implement home-based epilepsy monitoring. However, it is essential to apply a highly effective met...
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ISBN:
(纸本)9781728117096
The ongoing development of various lightweight and portable EEG signal acquisition devices provides the opportunity to implement home-based epilepsy monitoring. However, it is essential to apply a highly effective method to handle the limited computational power of such devices. In this paper, we propose a cost-effective method to classify epileptic seizure using stratified sampling technique. Additionally, to reduce the required computational power, this paper proposes a novel correlation and threshold-based feature selection algorithm. For evaluating the performance of our proposed method, five different classification algorithms are applied to classify the epileptic seizure from the reduced feature set. In our experiment, the random forest classifier shows the highest accuracy compared to other classifiers.
This paper introduces an approach for pre-screening manufactured batteries before system deployment, with the goal of reducing higher lifecycle maintenance costs attributed to failure-prone batteries. The method emplo...
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This paper introduces an approach for pre-screening manufactured batteries before system deployment, with the goal of reducing higher lifecycle maintenance costs attributed to failure-prone batteries. The method employs a pattern recognition algorithm for classifying parts for acceptance or rejection. The paper describes the classification algorithm and demonstrates its performance on example pre-acceptance test data. Using an example system maintenance concept, the economic and operational impacts of the classification are also demonstrated.
This study seeks to identify differences between textual samples written in isolation and controls. Isolation is the state of deprivation of one's typical level of social interaction and falls into three categorie...
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ISBN:
(纸本)9781538633090
This study seeks to identify differences between textual samples written in isolation and controls. Isolation is the state of deprivation of one's typical level of social interaction and falls into three categories: prison, seclusion, and isolation. We coded a Naive Bayesian Classifier using the Python package NLTK and ran it with different training to test set ratios and a Leave One Out with authors. The results yielded that accuracy is proportional to training set size. Currently we are analyzing the key features the classifier used to sort the texts and calculating a chance value for the classifier. This is a highly relevant area of study because we hope to elucidate key differences in the thoughts and cognitive states of isolated people, which could predict behavior for socially isolated people.
The usage of the Android Operating System (OS) has surpassed all other operating systems and as a result, it has become the primary target of attackers. Many attacks can be geared towards Android phones mainly using a...
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ISBN:
(数字)9781728151601
ISBN:
(纸本)9781728151618
The usage of the Android Operating System (OS) has surpassed all other operating systems and as a result, it has become the primary target of attackers. Many attacks can be geared towards Android phones mainly using application installation. These third-party applications first seek permission from the user before installation. Some of the permissions can be elusive evading the users' attention. With the type of harm that can be done which include illegal extraction and transfer of the users' data, spying on the users and so on there is a need to have a heuristic approach in the detection of malware. In this research work, some classification algorithms were tested to determine the best performing algorithm when it comes to the detection of android malware detection. An android application dataset was obtained from figshare and used in the Waikato Environment for Knowledge Analysis (WEKA) for training and testing, it was measured under accuracy, false-positive rate, precision, recall, f-measure, Receiver Operating Curve (ROC) and Root Mean Square Error (RMSE). It was discovered that multi-layer perceptron performs best with an accuracy of 99.4%.
sorting is technique by which elements are arranged in a particular order following some characteristic or law [1]. In this paper we presented an algorithm called as Relative Concatenate Sort, which is based on the id...
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作者：
Long, ZouZhang, ZhenrongGuangxi Univ
Sch Comp Elect & Informat Nanning 530004 Peoples R China Guangxi Univ
Guangxi Key Lab Multimedia Commun & Network Techn Cultivating Base Nanning 530004 Peoples R China Guangxi Univ
Guangxi Coll & Univ Key Lab Multimedia Commun & I Nanning 530004 Peoples R China
In recent years there has been a growing interest in Internet of Thing, Big Data and Mobile Internet. With the rapid growth of the amount of data in the embedded environment, using a traditional embedded processor is ...
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ISBN:
(纸本)9781538612309
In recent years there has been a growing interest in Internet of Thing, Big Data and Mobile Internet. With the rapid growth of the amount of data in the embedded environment, using a traditional embedded processor is hard to satisfy the requirements of big data processing. sorting is one of the fundamental operation in data processing and is also frequently used for search, filter, feature analysis and so on. It can contribute significantly to the overall execution time in a system. Existing techniques accelerate sorting using multiprocessor or GPUs, but it is impractical for embedded systems. In this paper, we propose a FPGA-based collaborative hardware sorting unit for embedded data processing. The waiting data is transferred from the embedded processor to our hardware sorting unit by the data bus, then a ordered sequence is given form hardware sorting unit and is returned to the embedded processor by data bus. The waiting data is processed in a pure hardware circuit, do not need anything software operation, so the calculating speed depends on the delay time of hardware circuit, which is faster than traditional iterative algorithm by software method. By the collaborative hardware unit, we can greatly reduce the processor load and improve the operation efficiency significantly. In addition, we can define the size of the data bit flexibly, we can also expend the scale of the unit by circuit topology.
Modular multilevel converters (MMCs) are made up of many submodules (SMs) connected in series. In order to avoid semiconductor over-voltages, SM capacitors should be kept within strict voltage limits. The capacitor ba...
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ISBN:
(纸本)9781509064267;9781509064250
Modular multilevel converters (MMCs) are made up of many submodules (SMs) connected in series. In order to avoid semiconductor over-voltages, SM capacitors should be kept within strict voltage limits. The capacitor balancing controller (CBC) is used to sort SM capacitor voltages prior to modulation. This paper investigates the variation in sorting complexity at steady state and transient conditions for a brute-force and past-position methodology based on the bubble sort algorithm. A focus is placed on the potential for 'worst-case' sorting, requiring increased computational effort. This paper forms part of ongoing research to analyze the hardware constraints on MMCs with very large numbers of SMs. Simulation results based on a PSCAD/EMTDC detailed equivalent model are used for analysis and conclusions.
In the past few years, researchers have introduced several sorting algorithms to enhance time complexity, space complexity, and stability. A double hashing methodology first collects statistics about element distribut...
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In the past few years, researchers have introduced several sorting algorithms to enhance time complexity, space complexity, and stability. A double hashing methodology first collects statistics about element distribution and then maps between elements of the array and indexes based on the knowledge collected during the first hashing.
Spatial correlation is a decisive factor for pragmatic multiple-input multiple-output (MIMO) system, simultaneously bringing about some problems in the received signal modulation identification respect. In this study,...
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Spatial correlation is a decisive factor for pragmatic multiple-input multiple-output (MIMO) system, simultaneously bringing about some problems in the received signal modulation identification respect. In this study, the authors focus on blind digital modulation identification in the spatially correlated MIMO system and deliver a robust signal recognition algorithm based on extreme learning machine (ELM) and higher order statistical features for MIMO signal identification without a priori knowledge of the channel and signal parameters. The superiority of ELM lies in random selections of hidden nodes and ascertains output weights analytically, which result in lower computational complexity. Theoretically, this algorithm has a tendency to supply excellent generalisation performance at staggering learning rate. Further, the simulation results indicate that the ELM could reap a perfectly acceptable recognition performance and thus provides a solid ground structure for tackling MIMO modulation challenges in low signal-to-noise ratio.
The process of understanding acoustic properties of environments is important for several applications, such as spatial audio, augmented reality and source separation. In this paper, multichannel room impulse response...
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ISBN:
(纸本)9781538646595
The process of understanding acoustic properties of environments is important for several applications, such as spatial audio, augmented reality and source separation. In this paper, multichannel room impulse responses are recorded and transformed into their direction of arrival (DOA)-time domain, by employing a superdirective beamformer. This domain can be represented as a 2D image. Hence, a novel image processing method is proposed to analyze the DOA-time domain, and estimate the reflection times of arrival and DOAs. The main acoustically reflective objects are then localized. Recent studies in acoustic reflector localization usually assume the room to be free from furniture. Here, by analyzing the scattered reflections, an algorithm is also proposed to binary classify reflectors into room boundaries and interior furniture. Experiments were conducted in four rooms. The classification algorithm showed high quality performance, also improving the localization accuracy, for non-static listener scenarios.
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