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Sawdust-Based Concrete Composite-Filled Steel Tube Beams: An Experimental and Analytical Investigation
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Incorporating waste byproducts into concrete is an innovative and promising way to minimize the environmental impact of waste material while maintaining and/or improving concrete’s mechanical characteristics and strength. The proper application of sawdust as a pozzolan in the building industry remains a significant challenge. Consequently, this study conducted an experimental evaluation of sawdust as a fill material. In particular, sawdust as a fine aggregate in concrete offers a realistic structural and economical possibility for the construction of lightweight structural systems. Failure under four-point loads was investigated for six concrete-filled steel tube (CFST) specimens. The results indicated that recycled lightweight concrete performed similarly to conventional concrete when used as a filler material in composite steel tube beams. The structural effects of sawdust substitution on ultimate load and initial stiffness were less substantial than the relative changes in the material properties, and the ultimate capacity of the tested samples decreased moderately as the substitution percentage of sawdust increased. Moreover, the maximum load capacity was observed to decrease by 6.43–30.71% for sawdust replacement levels between 5% and 45.1% across all tested samples. Additionally, when using lightweight concrete with 5% sawdust, the moment value of the CFST sample was reduced by 6.4%. Notably, the sawdust CFST samples exhibited a flexural behavior that was relatively comparable to that of the standard CFST samples.

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Publication Date
Thu Feb 01 2024
Journal Name
International Journal Of Electrical And Computer Engineering (ijece)
Wireless channel-based ciphering key generation: effect of aging and treatment
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Key generation for data cryptography is vital in wireless communications security. This key must be generated in a random way so that can not be regenerated by a third party other than the intended receiver. The random nature of the wireless channel is utilized to generate the encryption key. However, the randomness of wireless channels deteriorated over time due to channel aging which casing security threats, particularly for spatially correlated channels. In this paper, the effect of channel aging on the ciphering key generations is addressed. A proposed method to randomize the encryption key each coherence time is developed which decreases the correlation between keys generated at consecutive coherence times. When compared to the

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Publication Date
Thu Jun 15 2023
Journal Name
International Journal Of Nanoscience
Fabrication and Enhancement of Organic Photodetectors Based on Iron Phthalocyanine Films
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Iron–phthalocyanine (FePc) organic photoconductive detector was fabricated using pulsed laser deposition (PLD) technique to work in ultraviolet (UV) and visible regions. The organic semiconductor material (iron phthalocyanine) was deposited on n-type silicon wafer (Si) substrates at different thicknesses (100, 200 and 300) nm. FePc organic photoconductive detector has been improved by two methods: the first is to manufacture the detector on PSi substrates, and the second is by coating the detector with polyamide–nylon polymer to enhance the photoconductivity of the FePc detector. The current–voltage (I–V) characteristics, responsivity, photocurrent gain, response time and the quantum efficiency of the fabricated photoconduc

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Publication Date
Mon May 01 2023
Journal Name
Indonesian Journal Of Electrical Engineering And Computer Science
Comparison hybrid techniques-based mixed transform using compression and quality metrics
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Image quality plays a vital role in improving and assessing image compression performance. Image compression represents big image data to a new image with a smaller size suitable for storage and transmission. This paper aims to evaluate the implementation of the hybrid techniques-based tensor product mixed transform. Compression and quality metrics such as compression-ratio (CR), rate-distortion (RD), peak signal-to-noise ratio (PSNR), and Structural Content (SC) are utilized for evaluating the hybrid techniques. Then, a comparison between techniques is achieved according to these metrics to estimate the best technique. The main contribution is to improve the hybrid techniques. The proposed hybrid techniques are consisting of discrete wavel

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Publication Date
Mon Dec 14 2020
Journal Name
2020 13th International Conference On Developments In Esystems Engineering (dese)
Anomaly Based Intrusion Detection System Using Hierarchical Classification and Clustering Techniques
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With the rapid development of computers and network technologies, the security of information in the internet becomes compromise and many threats may affect the integrity of such information. Many researches are focused theirs works on providing solution to this threat. Machine learning and data mining are widely used in anomaly-detection schemes to decide whether or not a malicious activity is taking place on a network. In this paper a hierarchical classification for anomaly based intrusion detection system is proposed. Two levels of features selection and classification are used. In the first level, the global feature vector for detection the basic attacks (DoS, U2R, R2L and Probe) is selected. In the second level, four local feature vect

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Publication Date
Wed Mar 01 2023
Journal Name
Iraqi Journal Of Physics
FTIR and Electrical Behavior of Blend Electrolytes Based on (PVA/PVP)
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Polymer electrolytes were prepared using the solution cast technology. Under some conditions, the electrolyte content of polymers was analyzed in constant percent of PVA/PVP (50:50), ethylene carbonate (EC), and propylene carbonate (PC) (1:1) with different proportions of potassium iodide (KI) (10, 20, 30, 40, 50 wt%) and iodine (I2) = 10 wt% of salt. Fourier Transmission Infrared (FTIR) studies confirmed the complex formation of polymer blends. Electrical conductivity was calculated with an impedance analyzer in the frequency range 50 Hz–1MHz and in the temperature range 293–343 K. The highest electrical conductivity value of 5.3 × 10-3 (S/cm) was observed for electrolytes with 50 wt% KI concentration at room

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Publication Date
Sun Jul 01 2018
Journal Name
2018 2nd International Conference On Imaging, Signal Processing And Communication (icispc)
Analogy-based Common-Sense Knowledge for Opinion-Target Identification and Aggregation
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The development of Web 2.0 has improved people's ability to share their opinions. These opinions serve as an important piece of knowledge for other reviewers. To figure out what the opinions is all about, an automatic system of analysis is needed. Aspect-based sentiment analysis is the most important research topic conducted to extract reviewers-opinions about certain attribute, for instance opinion-target (aspect). In aspect-based tasks, the identification of the implicit aspect such as aspects implicitly implied in a review, is the most challenging task to accomplish. However, this paper strives to identify the implicit aspects based on hierarchical algorithm incorporated with common-sense knowledge by means of dimensionality reduction.

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Publication Date
Sun Aug 06 2023
Journal Name
Journal Of Economics And Administrative Sciences
Probit and Improved Probit Transform-Based Kernel Estimator for Copula Density
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Copula modeling is widely used in modern statistics. The boundary bias problem is one of the problems faced when estimating by nonparametric methods, as kernel estimators are the most common in nonparametric estimation. In this paper, the copula density function was estimated using the probit transformation nonparametric method in order to get rid of the boundary bias problem that the kernel estimators suffer from. Using simulation for three nonparametric methods to estimate the copula density function and we proposed a new method that is better than the rest of the methods by five types of copulas with different sample sizes and different levels of correlation between the copula variables and the different parameters for the function. The

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Publication Date
Wed Jan 01 2020
Journal Name
Journal Of Information Hiding And Multimedia Signal Processing
Enhancement of lsb audio steganography based on carrier and message characteristics
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Data steganography is a technique used to hide data, secret message, within another data, cover carrier. It is considered as a part of information security. Audio steganography is a type of data steganography, where the secret message is hidden in audio carrier. This paper proposes an efficient audio steganography method that uses LSB technique. The proposed method enhances steganography performance by exploiting all carrier samples and balancing between hiding capacity and distortion ratio. It suggests an adaptive number of hiding bits for each audio sample depending on the secret message size, the cover carrier size, and the signal to noise ratio (SNR). Comparison results show that the proposed method outperforms state of the art methods

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Publication Date
Wed Jan 01 2020
Journal Name
Journal Of Information Hiding And Multimedia Signal Processing
Enhancement of lsb audio steganography based on carrier and message characteristics
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Data steganography is a technique used to hide data, secret message, within another data, cover carrier. It is considered as a part of information security. Audio steganography is a type of data steganography, where the secret message is hidden in audio carrier. This paper proposes an efficient audio steganography method that uses LSB technique. The proposed method enhances steganography performance by exploiting all carrier samples and balancing between hiding capacity and distortion ratio. It suggests an adaptive number of hiding bits for each audio sample depending on the secret message size, the cover carrier size, and the signal to noise ratio (SNR). Comparison results show that the proposed method outperforms state of the art methods

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Publication Date
Tue Jun 01 2021
Journal Name
Ieee Systems Journal
Intelligent Traffic Management and Load Balance Based on Spike ISDN-IoT
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An intelligent software defined network (ISDN) based on an intelligent controller can manage and control the network in a remarkable way. In this article, a methodology is proposed to estimate the packet flow at the sensing plane in the software defined network-Internet of Things based on a partial recurrent spike neural network (PRSNN) congestion controller, to predict the next step ahead of packet flow and thus, reduce the congestion that may occur. That is, the proposed model (spike ISDN-IoT) is enhanced with a congestion controller. This controller works as a proactive controller in the proposed model. In addition, we propose another intelligent clustering controller based on an artificial neural network, which operates as a reactive co

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