Optimal Deep Learning Based Intruder Identification in Industrial Internet of Things Environment

With the increased advancements of smart industries, cybersecurity has become a vital growth factor in the success of industrial transformation. The Industrial Internet of Things (IIoT) or Industry 4.0 has revolutionized the concepts of manufacturing and production altogether. In industry 4.0, powerful Intrusion Detection Systems (IDS) play a significant role in ensuring network security. Though various intrusion detection techniques have been developed so far, it is challenging to protect the intricate data of networks. This is because conventional Machine Learning (ML) approaches are inadequate and insufficient to address the demands of dynamic IIoT networks. Further, the existing Deep Learning (DL) can be employed to identify anonymous intrusions. Therefore, the current study proposes a Hunger Games Search Optimization with Deep Learning-Driven Intrusion Detection (HGSODL-ID) model for the IIoT environment. The presented HGSODL-ID model exploits the linear normalization approach to transform the input data into a useful format. The HGSO algorithm is employed for Feature Selection (HGSO-FS) to reduce the curse of dimensionality. Moreover, Sparrow Search Optimization (SSO) is utilized with a Graph Convolutional Network (GCN) to classify and identify intrusions in the network. Finally, the SSO technique is exploited to fine-tune the hyper-parameters involved in the GCN model. The proposed HGSODL-ID model was experimentally validated using a benchmark dataset, and the results confirmed the superiority of the proposed HGSODL-ID method over recent approaches.     

A new supervised classification algorithm in artificial immune systems with its application to carotid artery Doppler signals to diagnose atherosclerosis

Because of its self-regulating nature, immune system has been an inspiration source for usually unsupervised learning methods in classification applications of Artificial Immune Systems (AIS). But classification with supervision can bring some advantages to AIS like other classification systems. Indeed, there have been some studies, which have obtained reasonable results and include supervision in this branch of AIS. In this study, we have proposed a new supervised AIS named as Supervised Affinity Maturation Algorithm (SAMA) and have presented its performance results through applying it to diagnose atherosclerosis using carotid artery Doppler signals as a real-world medical classification problem. We have employed the maximum envelope of the carotid artery Doppler sonograms derived from Autoregressive (AR) method as an input of proposed classification system and reached a maximum average classification accuracy of 98.93% with 10-fold cross-validation method used in training-test portioning. To evaluate this result, comparison was done with Artificial Neural Networks and Decision Trees. Our system was found to be comparable with those systems, which are used effectively in literature with respect to classification accuracy and classification time. Effects of system's parameters were also analyzed in performance evaluation applications. With this study and other possible contributions to AIS, classification algorithms with effective performances can be developed and potential of AIS in classification can be further revealed.     

Combining docking, scoring and molecular field analyses to probe influenza neuraminidase-ligand interactions

In this project, several docking conditions, scoring functions and corresponding protein-aligned molecular field analysis (CoMFA) models were evaluated for a diverse set of neuraminidase (NA) inhibitors. To this end, a group of inhibitors were docked into the active site of NA. The docked structures were utilized to construct a corresponding protein-aligned CoMFA models by employing probe-based (H+, OH, CH3) energy grids and genetic partial least squares (G/PLS) statistical analysis. A total of 16 different docking configurations were evaluated, of which some succeeded in producing self-consistent and predictive CoMFA models. However, the best model coincided with docking the ionized ligands into the hydrated form of the binding site via PLP1 scoring function (r2LOO=0.735, r2PRESS against 24 test compounds=0.828). The highest-ranking CoMFA models were employed to probe NA-ligand interactions. Further validation by comparison with a co-crystallized ligand-NA crystallographic structure was performed. This combination of docking/scoring/CoMFA modeling provided interesting insights into the binding of different NA inhibitors.     

Anticonvulsant activity of furanocoumarins and the essential oil obtained from the fruits of Heracleum crenatifolium

The anticonvulsant activity of furanocoumarins, coumarin mixture and the essential oil obtained from the fruits of Heracleum crenatifolium was examined against maximal electroshock (MES)-induced seizures in mice. Bergapten showed significant anticonvulsant activity. The furanocoumarins isolated from the fruits of the plant were identified using thin-layer chromatography, melting points and spectroscopic methods (IR, MS, ¹H NMR) as isobergapten (1), pimpinellin (2), bergapten (3), isopimpinellin (4), sphondin (5) and byak-angelicol (6). The essential oil content of the fruits were found as 5.5%. Twenty-two compounds representing 99.3% of the essential oil obtained from the fruits of H. crenatifolium were determined and the major components were identified as octanol and octyl acetate (3.1% and 88.4% respectively) by GC and GC–MS.     

Determination of Menbutone in Bovine Milk and Meat Using Micellar Liquid Chromatography: Application to Injectable Dosage Forms

A simple, sensitive, and rapid method was developed for the routine identification and quantification of menbutone in different matrices by micellar liquid chromatography. Separation was performed in less than 4 min using a C₁₈ column with UV detection at 234 nm. A micellar solution composed of 0.12 M sodium dodecyl sulfate, 8 % n-butanol, and 0.3 % triethylamine in 0.02 M phosphoric acid at pH 6.0 was used as the mobile phase. The method was fully validated in accordance with International Conference on Harmonization (ICH) guidelines. The limits of detection and quantitation were 0.95 and 2.86 ng mL^?1, respectively. The method showed good repeatability, linearity, and sensitivity according to the evaluation of the validation parameters. The micellar method was successfully applied for the analysis of menbutone in its commercial injections with a mean % recovery value of 99.73?±?1.634 % and in spiked bovine milk and meat samples with a mean % recovery values in the range of 98.00–100.60 %. High extraction efficiency was obtained without matrix interference in the extraction process and in the subsequent chromatographic determination. No organic solvent was used during the pretreatment step. Hence, this method can be considered as an interesting example for green chemistry.     

Bacteriological effects of functionalized cotton dressings

This study aims to achieve effects of improved hydrophilicity and microorganism inhibition, which are rarely simultaneously present in wound dressings. Cotton gauzes were modified using the grafting of a polymer-based β-cyclodextrin. After optimizing the grafting conditions, the untreated and modified cellulosic samples were principally characterized using FT-IR spectroscopy, TGA/DTA analysis, in vitro drug release, and wettability measurements. In light of desired characteristics of wound dressings, the effectiveness of procedures was evaluated. It was found that contact angles for cotton gauzes decreased after functionalization, which means that hydrophilicity was proven to become excellent. A successful Methylene Blue complexation was confirmed through measure of the dyebath exhaustion using UV-spectrophotometry. Then, during Methylen Blue release test, we reported an initial burst release of active ingredient over 7?h, followed by zero-order release. The treatment effect on antimicrobial activity was investigated by growth inhibition, which was proven against Staphylococcus aureus and Escherichia coli.     

Effective prediction and resource allocation method (EPRAM) in fog computing environment for smart healthcare system

Multimedia Tools and Applications - Recently, many concepts in technology has been changed. According to the digital transformation trends, Internet of Things (IoT) represents an interested...     

Synthesis,Thermal Properties and Electrical Conductivity of Na-Sialate Geopolymer

This work aims to study the thermal behavior of basic-geopolymers derived from metakaolin (clay). The geopolymers were characterized by different techniques: thermal analysis (DTA, TGA), X-ray diffraction (XRD), Fourier transform infrared spectroscopy (FTIR) and impedance spectroscopy. Some physicochemical properties of the products were also determined: the phases obtained after geopolymer heat treatment and their electrical properties. The results obtained after drying and heat treatment showed that the products kept their initial shapes, but revealed variable colors depending on the temperatures at which they were treated. The products obtained are amorphous between 300 up to 600 °C with peaks relating to the presence of nanocrystallites of muscovites and zeolite, thus at 900 °C it is quite amorphous but only contains nanocrystallites of muscovites. From the temperature of 950 °C, we notice that the geopolymer has been transformed into a crystalline compound predominated by the Nepheline (NaAlSiO₄) with the presence of a crystalline phase by minor peaks of Muscovite, this crystalline character has been increased at 1100 °C to obtain a whole phase crystalline of a Nepheline. The treatment of this geopolymer for one hour at 1200 °C shows an amorphous phase again corresponding to corundum (α-Al₂O₃). This indicates that the dissolution of the grains by the liquid phase induces the conversion of the material structure from sialate [–Si–O–Al–O] to sialate siloxo [–Si–O–Al–O–Si–O–] and the formation of a new crystalline phase (α-Al₂O₃). This development of sialate to sialate-siloxo was confirmed by IR spectroscopy. As mentioned above, from 300 to 900 °C, Na-sialate geopolymer exhibits the same disorder structure of nepheline. The crystal structure of nepheline is characterized by layers of six-membered tetrahedral rings of exclusively oval conformation. The rings are built by Regularly alternating tetrahedral AlO₄ and SiO₄. Stacking the layer’s parallel to the c axis gives a three-dimensional network containing channels occupied by Na cations. This topology favors easy movement of Na⁺ ions throughout the structure. For this reason, ionic migration in nepheline is widely reported. The refinement of Na-Sialate geopolymer at room temperature gives bulk high ionic conductivity of about 5 × 10^?5 S cm^?1 and this is due to the probable joint contribution of H⁺ and Na⁺ ions. Above 200 °C, Na⁺ seems to remain the only charge carrier with a low activation energy of about Ea?=?0.26 eV. At higher temperatures, the characteristic frequencies become so close that it is impossible to distinguish the contributions. A total resistance comprising both grain and grain boundaries contribution is then determined.

     

Biodegradation of low‐density polyethylene/thermoplastic starch foams before and after electron beam irradiation

Foamy low‐density polyethylene/plasticized starch (LDPE/PLST) blends at different compositions were produced in the presence of azodicarbonamide (ACA) compound as foaming agent. The LDPE/PLST blends before and after electron beam irradiation were investigated in terms of mechanical properties, bulk density, and structure morphology. Moreover, the biodegradability of these materials was evaluated by the soil burial test for 2 months, in which the buried sheets were also examined by scanning electron microscopy (SEM). The results showed that the increase of PLST content from 24 to 30% was accompanied by a decrease in the yield and break stresses of 10 and 20% for the unirradiated blends without the foaming agent, respectively. Further decrease in these mechanical parameters was observed after the foaming process. The bulk density, void fraction, cell size measurements as well as the examination by SEM illustrate clearly the cell growth of the foam structure. The soil burial test and SEM micrographs indicate the growth of microorganisms overall the blend sheets and that the blend was completely damaged after two months of burying. © 2007 Wiley Periodicals, Inc. J Appl Polym Sci 2007