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Assessment of Observed Building Structure Setback of Shops along an Arterial Road and Noise Intrusion Level
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Roads irrespective of the type have specific standard horizontal distance measured at 90 degrees from a lot boundary to a development known as a setback. Non-observance of the recommended setbacks accommodated in any urban center’s master plan creates noise hazard to the public health and safety as the movement of vehicular traffic is not without the attendant noise. This study assessed noise intrusion level in shops along a section of Ibadan-Abeokuta road with due consideration to compliance with the recommended building structure setback. Analysis of noise descriptors evaluated in this study gave A-weighted equivalent sound pressure level average of 91.3 dBA, the daytime average sound level (LD) 92.27 dBA, traffic noise index (TNI) 41.63 dBA, the noise pollution level (LNP) 85.91 dBA and noise climate (NC) 5.38 dBA. Correlation analysis between the observed setbacks and the noise levels gave an “r” value of -.496 significant at p < .05. The paired t-test analysis showed a mean ± SD difference of 15.90 ± 7.08, and t-value of 32.99, corresponding to a two-tailed p < .05 with 215 degrees of freedom. This implies that there was a significant statistical difference between the noise levels measured at the observed and recommended setbacks

 

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Publication Date
Wed Sep 22 2021
Journal Name
Samarra Journal Of Pure And Applied Science
Toward Constructing a Balanced Intrusion Detection Dataset
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Several Intrusion Detection Systems (IDS) have been proposed in the current decade. Most datasets which associate with intrusion detection dataset suffer from an imbalance class problem. This problem limits the performance of classifier for minority classes. This paper has presented a novel class imbalance processing technology for large scale multiclass dataset, referred to as BMCD. Our algorithm is based on adapting the Synthetic Minority Over-Sampling Technique (SMOTE) with multiclass dataset to improve the detection rate of minority classes while ensuring efficiency. In this work we have been combined five individual CICIDS2017 dataset to create one multiclass dataset which contains several types of attacks. To prove the eff

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Publication Date
Thu Jan 20 2022
Journal Name
Webology
Hybrid Intrusion Detection System based on DNA Encoding, Teiresias Algorithm and Clustering Method
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Until recently, researchers have utilized and applied various techniques for intrusion detection system (IDS), including DNA encoding and clustering that are widely used for this purpose. In addition to the other two major techniques for detection are anomaly and misuse detection, where anomaly detection is done based on user behavior, while misuse detection is done based on known attacks signatures. However, both techniques have some drawbacks, such as a high false alarm rate. Therefore, hybrid IDS takes advantage of combining the strength of both techniques to overcome their limitations. In this paper, a hybrid IDS is proposed based on the DNA encoding and clustering method. The proposed DNA encoding is done based on the UNSW-NB15

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Publication Date
Sun Mar 07 2010
Journal Name
Baghdad Science Journal
Comparison of Mercury Intrusion and Nitrogen Adsorption Measurements for the Characterization of Certain Natural Raw Materials Deposits
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The porosity of materials is important in many applications, products and processes, such as electrochemical devices (electrodes, separator, active components in batteries), porous thin film, ceramics, soils, construction materials, ..etc. This can be characterized in many different methods, and the most important methods for industrial purposes are the N2 gas adsorption and mercury porosimetry. In the present paper, both of these techniques have been used to characterize some of Iraqi natural raw materials deposits. These are Glass Sand, Standard Sand, Flint Clay and Bentonite. Data from both analyses on the different types of natural raw materials deposits are critically examined and discussed. The results of specific surface are

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Publication Date
Sun Dec 01 2002
Journal Name
Iraqi Journal Of Physics
Low-Rate High-Quality Parametric Audio Coder based on Sinusoidal plus Noise Representations
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This paper presents a parametric audio compression scheme intended for scalable audio coding applications, and is particularly well suited for operation at low rates, in the vicinity of 5 to 32 Kbps. The model consists of two complementary components: Sines plus Noise (SN). The principal component of the system is an. overlap-add analysis-by-synthesis sinusoidal model based on conjugate matching pursuits. Perceptual information about human hearing is explicitly included into the model by psychoacoustically weighting the pursuit metric. Once analyzed, SN parameters are efficiently quantized and coded. Our informal listening tests demonstrated that our coder gave competitive performance to the-state-of-the- art HelixTM Producer Plus 9 from

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Publication Date
Fri Apr 01 2022
Journal Name
Chemical Methodologies
Design, Synthesis of Imidazolone and Oxazepine Derivatives Bearing Imidazo (2, 1-b) Thiazole along with its Antimicrobial Activity
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A new methodology was applied to the synthesis of new imidazolones and oxyazepine derivatives containing imidazo thiazole fused rings. Starting with 5-(4-bromo phenyl) imidazo (2, 1-b) thiazole, which was synthesized using the standard procedure, the Carbaldehyed group was introduced at position 6 of 5-(4-bromo phenyl) imidazo (2, 1-b) thiazole. Then, this 6-carbaldehyed derivative was condensed with different substituted aromatic amines to afford new Schiff bases. The latter were cyclized into new oxazepine and imidazolone derivatives by using phthalic anhydride and glycine, respectively. These new derivatives were characterized by using FT-IR, 1HHNMR, and 13CNMR spectra, as well as examined (evaluated) for anti-bacterial and anti-fungal a

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Publication Date
Fri Apr 01 2016
Journal Name
Al–bahith Al–a'alami
Building Electoral Posters An Analytical Study of the Electoral Campaign's Posters of the Iraqi Representative Council in 2014
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The electoral poster is the most important means and methods of the electoral campaign because of its advantages and capabilities if it is organized properly. It is an intensive propaganda message with psychological figures and semiotic connotations belonging to sub-culture. Its construction depends on a group of elements (logo, photo symbols, color and picture) and their consistency is varying from one to another. Posters must be committed the determinants of attraction, excitement, simplicity and clarity. They are working according to the following base: (fixed audience X moved recipients) and walking towards (moving X moving) due to the technical development of optical screens. These developments require double the force of the impact

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Publication Date
Thu Jan 24 2019
Journal Name
Journal Of Education College Wasit University
Postmodernism and Technology in Don Delillo's Novel The White Noise
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This paper aims at investigating the effect of postmodernism and technology on the social life in Don Delillo's novel The White Noise. In this novel, Don Delillo portrays the chaotic life by using modern technology which has been presented by three ways. The first way is by television as being a source of information and entertainment. The second way is by the toxic event whereas the third is by Dylar's episode and its destructive consequences. He depicts that through the atmosphere of Jack's family plus its effects on the life and thoughts of the elders and society. He proves that technology is leading humanity not to safety, but to death. He further highlights that by showing the impact of technology on the life of the main charac

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Publication Date
Mon Oct 02 2023
Journal Name
Journal Of Engineering
The Applicability of Multiple MCDM Techniques for Implementation in the Priority of Road Maintenance
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Priority of road maintenance can be viewed as a process influenced by decision-makers with varying decision-making power. Each decision-maker may have their view and judgment depending on their function and responsibilities. Therefore, determining the priority of road maintenance can be thought of as a process of MCDM. Regarding the priority of road maintenance, this is a difficult MCDM problem involving uncertainty, qualitative criteria, and possible causal relationships between choice criteria. This paper aims to examine the applicability of multiple MCDM techniques, which are used for assessing the priority of road maintenance, by adapting them to this sector. Priority of road maintenance problems subject to internal

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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
Tue Jan 31 2023
Journal Name
International Journal Of Nonlinear Analysis And Applications
Survey on intrusion detection system based on analysis concept drift: Status and future directions
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Nowadays, internet security is a critical concern; the One of the most difficult study issues in network security is "intrusion detection". Fight against external threats. Intrusion detection is a novel method of securing computers and data networks that are already in use. To boost the efficacy of intrusion detection systems, machine learning and deep learning are widely deployed. While work on intrusion detection systems is already underway, based on data mining and machine learning is effective, it requires to detect intrusions by training static batch classifiers regardless considering the time-varying features of a regular data stream. Real-world problems, on the other hand, rarely fit into models that have such constraints. Furthermor

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