Big data analysis is essential for modern applications in areas such as healthcare, assistive technology, intelligent transportation, environment and climate monitoring. Traditional algorithms in data mining and machine learning do not scale well with data size. Mining and learning from big data need time and memory efficient techniques, albeit the cost of possible loss in accuracy. We have developed a data aggregation structure to summarize data with large number of instances and data generated from multiple data sources. Data are aggregated at multiple resolutions and resolution provides a trade-off between efficiency and accuracy. The structure is built once, updated incrementally, and serves as a common data input for multiple mining and learning algorithms. Data mining algorithms are modified to accept the aggregated data as input. Hierarchical data aggregation serves as a paradigm under which novel …
Abstract
The aim of the research to define the concept of moral intelligence and its dimensions and its relationship to some personal characteristics with the internal auditors and identify the importance of the employment of moral intelligence dimensions of (empathy, conscience, self- control, respect, kindness, tolerance, fairness) in the internal audit and the extent of support for the performance of the internal audit process in light of these dimensions. And that by answering the following question : Is there a role for moral intelligence of internal auditors in support the performance of internal audit process ? How are employ these dimensions i
... Show MoreConstitutional Review of 1992 and 1996 and the role of the Party of Progress and Socialism
In this paper, the goal of proposed method is to protect data against different types of attacks by unauthorized parties. The basic idea of proposed method is generating a private key from a specific features of digital color image such as color (Red, Green and Blue); the generating process of private key from colors of digital color image performed via the computing process of color frequencies for blue color of an image then computing the maximum frequency of blue color, multiplying it by its number and adding process will performed to produce a generated key. After that the private key is generated, must be converting it into the binary representation form. The generated key is extracted from blue color of keyed image then we selects a c
... Show MoreArab heritage have teem much of the literature value, written by evacuated, who had a legacy of linguistic great scientists, but the circumstances are unknown, did not write those books or authors emerge, chose to search for a book of those compositions, he did not write to him and his book emerge, fell hands a book (Altvsh in the language) to Abu Sufyan grammar, a fourth-century scientists, as it is Abu Sufyan grammar of scientists who rolled up the time their impact, and the cryptic revelations among the stars, preferring to stand on this book and its author, a statement of the most important grammatical aspects contained therein; to notch the curtain for this world, and his book (Altvsh in strewn language and Mnzawmha and express the
... Show MoreEmergency vehicle (EV) services save lives around the world. The necessary fast response of EVs requires minimising travel time. Preempting traffic signals can enable EVs to reach the desired location quickly. Most of the current research tries to decrease EV delays but neglects the resulting negative impacts of the preemption on other vehicles in the side roads. This paper proposes a dynamic preemption algorithm to control the traffic signal by adjusting some cycles to balance between the two critical goals: minimal delay for EVs with no stop, and a small additional delay to the vehicles on the side roads. This method is applicable to preempt traffic lights for EVs through an Intelli
A hand gesture recognition system provides a robust and innovative solution to nonverbal communication through human–computer interaction. Deep learning models have excellent potential for usage in recognition applications. To overcome related issues, most previous studies have proposed new model architectures or have fine-tuned pre-trained models. Furthermore, these studies relied on one standard dataset for both training and testing. Thus, the accuracy of these studies is reasonable. Unlike these works, the current study investigates two deep learning models with intermediate layers to recognize static hand gesture images. Both models were tested on different datasets, adjusted to suit the dataset, and then trained under different m
... Show MoreAspect categorisation and its utmost importance in the eld of Aspectbased Sentiment Analysis (ABSA) has encouraged researchers to improve topic model performance for modelling the aspects into categories. In general, a majority of its current methods implement parametric models requiring a pre-determined number of topics beforehand. However, this is not e ciently undertaken with unannotated text data as they lack any class label. Therefore, the current work presented a novel non-parametric model drawing a number of topics based on the semantic association present between opinion-targets (i.e., aspects) and their respective expressed sentiments. The model incorporated the Semantic Association Rules (SAR) into the Hierarchical Dirichlet Proce
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