Tor (The Onion Routing) network was designed to enable users to browse the Internet anonymously. It is known for its anonymity and privacy security feature against many agents who desire to observe the area of users or chase users’ browsing conventions. This anonymity stems from the encryption and decryption of Tor traffic. That is, the client’s traffic should be subject to encryption and decryption before the sending and receiving process, which leads to delay and even interruption in data flow. The exchange of cryptographic keys between network devices plays a pivotal and critical role in facilitating secure communication and ensuring the integrity of cryptographic procedures. This essential process is time-consuming, which causes delay and discontinuity of data flow. To overcome delay or interruption problems, we utilized the Software-Defined Network (SDN), Machine Learning (ML), and Blockchain (BC) techniques, which support the Tor network to intelligently speed up exchanging the public key via the proactive processing of the Tor network security management information. Consequently, the combination network (ITor-SDN) keeps data flow continuity to a Tor client. We simulated and emulated the proposed network by using Mininet and Shadow simulations. The findings of the performed analysis illustrate that the proposed network architecture enhances the overall performance metrics, showcasing a remarkable advancement of around 55%. This substantial enhancement is achieved through the seamless execution of the innovative ITor-SDN network combination approach.
The oil and gas industry relies heavily on IT innovations to manage business processes, but the exponential generation of data has led to concerns about processing big data, generating valuable insights, and making timely decisions. Many companies have adopted Big Data Analytics (BDA) solutions to address these challenges. However, determining the adoption of BDA solutions requires a thorough understanding of the contextual factors influencing these decisions. This research explores these factors using a new Technology-Organisation-Environment (TOE) framework, presenting technological, organisational, and environmental factors. The study used a Delphi research method and seven heterogeneous panelists from an Oman oil and gas company
... Show MoreNoor oil field is one of smallest fields in Missan province. Twelve well penetrates the Mishrif Formation in Noor field and eight of them were selected for this study. Mishrif formation is one of the most important reservoirs in Noor field and it consists of one anticline dome and bounded by the Khasib formation at the top and the Rumaila formation at the bottom. The reservoir was divided into eight units separated by isolated units according to partition taken by a rounding fields.
In this paper histograms frequency distribution of the porosity, permeability, and water saturation were plotted for MA unit of Mishrif formation in Noor field, and then transformed to the normal distribution by applying the Box-Cox transformation alg
... Show MoreOne of the most significant elements influencing weather, climate, and the environment is vegetation cover. Normalized Difference Vegetation Index (NDVI) and Normalized Difference Built-up Index (NDBI) over the years 2019–2022 were estimated based on four Landsat 8 TIRS’s images covering Duhok City. Using the radiative transfer model, the city's land surface temperature (LST) during the next four years was calculated. The aim of this study is to compute the temperature at the land's surface (LST) from the years 2019-2022 and understand the link, between LST, NDVI, and NDBI and the capability for mapping by LANDSAT-8 TIRS's. The findings revealed that the NDBI and the NDVI had the strongest correlation with the
... Show MoreThe purpose of this paper is to apply different transportation models in their minimum and maximum values by finding starting basic feasible solution and finding the optimal solution. The requirements of transportation models were presented with one of their applications in the case of minimizing the objective function, which was conducted by the researcher as real data, which took place one month in 2015, in one of the poultry farms for the production of eggs
... Show MoreData scarcity is a major challenge when training deep learning (DL) models. DL demands a large amount of data to achieve exceptional performance. Unfortunately, many applications have small or inadequate data to train DL frameworks. Usually, manual labeling is needed to provide labeled data, which typically involves human annotators with a vast background of knowledge. This annotation process is costly, time-consuming, and error-prone. Usually, every DL framework is fed by a significant amount of labeled data to automatically learn representations. Ultimately, a larger amount of data would generate a better DL model and its performance is also application dependent. This issue is the main barrier for
Coumarins have been recognized as anticancer competitors. HDACis are one of the interesting issues in the field of antitumor research. In order to achieve an increased anticancer efficacy, a series of hybrid compounds bearing coumarin scaffolds have been designed and synthesized as novel HDACis, In this review we present a series of novel HDAC inhibitors comprising coumarin as a core e of cap group of HDAC inhibitors that have been designed, synthesized and assessed for their enzyme inhibitory activity as well as antiproliferative activity. Most of them exhibited potent HDAC inhibitory activity and significant cytotoxicity
Audio classification is the process to classify different audio types according to contents. It is implemented in a large variety of real world problems, all classification applications allowed the target subjects to be viewed as a specific type of audio and hence, there is a variety in the audio types and every type has to be treatedcarefully according to its significant properties.Feature extraction is an important process for audio classification. This workintroduces several sets of features according to the type, two types of audio (datasets) were studied. Two different features sets are proposed: (i) firstorder gradient feature vector, and (ii) Local roughness feature vector, the experimentsshowed that the results are competitive to
... Show MoreCompression for color image is now necessary for transmission and storage in the data bases since the color gives a pleasing nature and natural for any object, so three composite techniques based color image compression is implemented to achieve image with high compression, no loss in original image, better performance and good image quality. These techniques are composite stationary wavelet technique (S), composite wavelet technique (W) and composite multi-wavelet technique (M). For the high energy sub-band of the 3 rd level of each composite transform in each composite technique, the compression parameters are calculated. The best composite transform among the 27 types is the three levels of multi-wavelet transform (MMM) in M technique wh
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