An Intelligent Intrusion Detection System for Internet of Things Attack Detection and Identification Using Machine Learning

The usability and scalability of Internet of things (IoT) technology are expanding in such a way that they facilitate human living standards. However, they increase the vulnerabilities and attack vectors over IoT networks as well. Thus, more security challenges could be expected and encountered, and more security services and solutions should be provided. Although many security techniques propose and promise good solutions for that intrusion detection systems IDSs still considered the best. Many works proposed machine learning (ML)-based IDSs for IoT attack detection and classification. Nevertheless, they suffer from two main gaps. First, few of the works utilized or could analyze an up-to-date version of IoT-based attack behaviors. Second, few of the works can be considered as multi-class attack detection and classification. Therefore, this work proposes an intelligent IDS (IIDS) by exploiting the ability of ML algorithms to classify and identify malicious from benign behaviors among IoT network packets. Three ML classifier algorithms are investigated, which are K-Nearest Neighbor, support vector machine, and artificial neural network. The developed models have been trained and tested as binary and multi-class classifiers against 15 types of attacks and benign. This work employs an up-to-date dataset known as IoT23, which covers millions of malicious and benign behaviors of IoT-connected devices. The process of developing the proposed IIDSs goes under different preprocessing phases and methods, such as null value solving, SMOTE method for the imbalanced datasets, data normalization, and feature selections. The results present IIDSs as good binary and multi-class classifiers even for zero-day attacks

The Plant Regulator Soaking Seeds and its Reflections on Growth and Yield Quality of Wheat

A greenhouse pot experiment was carried out during November 2013 to May 2014. Winter wheat grains (Triticum aestivum L.), cultivars Abu-Ghureb and Cham6 were used to investigate the effect of soaking seeds in 300ppm of benzyl adenine (BA) or daminozide solutions for 6 hours before sowing vegetative, yield components, leaf chlorophylls and some chemical constituents of seeds. BA treatment led to significant increases in tiller number plant-1, chlorophyll b, P, dry gluten, N and protein contents of seeds. It also led to significant decreases in number of leaves plant-1. In addition, the number of tillers plant-1, shoots dry weight plant-1, P, N and protein contents of seeds were increased by daminozide treatment, but this caused a significant decrease in the plant height, number of leaves plant-1 and flag leaf area. Number of grains plant-1, weight of 1000 grains and grains yield were significantly increased by both treatments. Cultivar variability was noted for some tested parameters. The tall, N, P content and protein content of Abu-Ghureb cultivar were higher significantly than Sham6. The case was opposite with number of leaves plant-1, flag leaf area, shoots dry weight plant-1, spike length and grain number plant-1

Assessment of Chemical and Bacteriological Parameters of Leek in Sulaymaniyah City, Iraq

In the current study, leek samples were collected seasonally from October 2021 to July 2022 from three sites; site 1 (Tanjaro aera), site 2 (Kanaswra), and site 3 (Aziz Awa) in Sulaymaniyah city, Iraq. Cl- rate recorded the maximum mean values in leek, which was 0.05 mg/kg. The Na+ level recorded the highest mean value, at 393.00 mg/kg. The K+ ratio showed the highest mean value, measuring 3614 mg/kg. SO42- concentration had a mean value of 762.33 mg/kg. PO43- level recorded the maximum mean value at 16.13. Regarding heavy metals in vegetables, the results indicated no contamination in leek, except for Pb, which had a high level in the vegetables. In terms of bacteriology, leek samples exhibited total aerobic bacteria and total coliform counts above the normal range. Based on the biochemical test findings, E. coli and Salmonella species were not detected in leek. Different species were isolated from leek, including Citobacter freundii, Citobacter braakii, Acinetobacter baumannii complex, Enterobacter cloacae complex. There is a notable correlation between total aerobic bacteria and lead (r = 0.60) in leek. Copper shows a negative correlation with total aerobic bacteria (r = -0.59), while iron also exhibits a negative relationship with total aerobic bacteria (r = -0.60). Total coliform demonstrates a positive relationship with manganese (r = 0.64)

Dynamic Control of a Robotic Swarm using a Service-Oriented Architecture

The development, deployment, and control of groups of robots is a tedious process even for experienced roboticists. Particularly in heterogeneous systems a high granularity of control and visibility is difficult to achieve. The lack of standardized interfaces and communication protocols to interconnect robots from different manufacturers makes it very difficult to develop flexible robotic applications. We propose an efficient system suited to support heterogeneous robotic swarms that can be used as a toolkit for fast prototyping of robust distributed applications. This system offers a flexible interface allowing external users to remotely control the swarm over the internet by using standardized communication protocols such as Web Services

Effects of nitrogen rates on grain yield and nitrogen agronomic efficiency of durum wheat genotypes under different environments

Durum wheat is an important staple food crop in Tunisia and other Mediterranean countries and is grown in various climatic conditions. Production and yield are however severely limited not only by drought events but also by reduced levels of nitrogen fertilisation. A study was carried out at two locations in the sub-humid area of Tunisia: Mateur in 2009–10 and 2010–11 and Beja in 2011–12 and 2012–13 under rainfed conditions. Four durum wheat genotypes (landraces: Bidi, Azizi; improved: Om Rabia, Khiar) were evaluated for nitrogen agronomic efficiency and related agronomic traits under various nitrogen rates: 0, 50, 100, 150, 200 and 250 kgNha−1, with three replications. There was a significant interaction effect (P ≤ 0.001) environments × genotypes ×N treatments for grain yield (GY), biomass yield (BY), harvest index (HI), partial factor productivity of applied nitrogen (PFPN) and nitrogen agronomic use efficiencies (NAE). GY was the most affected trait by nitrogen applied showing an increase of 94% under high N treatment (250 kgNha−1) compared to control plots without N treatments. A significant linear regression exists between GY (0 N) and GY for the different N rates (r =0.70; P < 0.001). This effect was more pronounced for improved genotypes than landraces for all parameters excepting BY and NAEBY. BY showed +11% increase in landraces than improved genotypes. PFPN showed an average decrease of 65% under high-N fertilisation with 10% prevalence for improved genotypes. Landraces tend to promote vegetative growth while grain filling efficiency was higher for improved genotype

Variation of Grain Yield, Grain Protein Content and Nitrogen Use Efficiency Components under Different Nitrogen Rates in Mediterranean Durum Wheat Genotypes

Nitrogen (N) is a crucial nutrient for plant growth and development. To optimize agricultural environments, N fertilizers represent a critical tool to regulate crop productivity. The improvement of nitrogen use efficiency (NUE) represents a promising tool that may enable cereal production to meet future food demand. Wheat reported contrasting behaviors in N utilization showing specific abilities depending on genotype. This study selected two landraces and two improved genotypes from Northern Africa to investigate grain yield (GY), grain protein content (GPC) and NUE. Plants were grown under three levels of N supply: 0, 75, 150 kg N ha−1 and for two consecutive years. Results reported a better NUE (0.40 kg.kg N−1) obtained under 150 kg N ha−1, while N utilization efficiency (NUtE) showed a 13% increase using 75 kg N ha−1 compared with 150 kg N ha−1. Under low nitrogen rate (0 N), crop N supply (CNS) and N uptake efficiency (NUpE) were shown as determinant factors for improved genotypes GY (R2 = 0.72), while NUtE represented the most determinant component for GPC in landraces (R2 = 0.92). Multivariate regression models explained the dependence in GPC on NUE, NUpE, and NUtE. In conclusion, our results recognize GPC and NUtE as suitable selection traits to identify durum wheat with higher NUE

LifeCLEF 2016: Multimedia Life Species Identification Challenges

International audienceUsing multimedia identification tools is considered as one of the most promising solutions to help bridge the taxonomic gap and build accurate knowledge of the identity, the geographic distribution and the evolution of living species. Large and structured communities of nature observers (e.g., iSpot, Xeno-canto, Tela Botanica, etc.) as well as big monitoring equipment have actually started to produce outstanding collections of multimedia records. Unfortunately, the performance of the state-of-the-art analysis techniques on such data is still not well understood and is far from reaching real world requirements. The LifeCLEF lab proposes to evaluate these challenges around 3 tasks related to multimedia information retrieval and fine-grained classification problems in 3 domains. Each task is based on large volumes of real-world data and the measured challenges are defined in collaboration with biologists and environmental stakeholders to reflect realistic usage scenarios. For each task, we report the methodology, the data sets as well as the results and the main outcom

Curative Effects of Pomegranate and Ginger on Hepatic and Renal Functions of Indomethacin-Induced Peptic Ulcers in Albino Rats

A peptic ulcer is one of the more severe diseases and most classic treatment protocol produce adverse drug reactions. Therefore, this study aimed to examine the therapeutic effects of two natural extracts, namely Pomegranate and Ginger, on indomethacin-induced gastric ulcer in rats. Animals were divided into five groups; 1. Normal control group, 2. An ulcer control group Indomethacin (0.3 mg /rats), 3. Omeprazole (3 mg /rats), a4. Pomegranate (40 mg /rats), 5. Ginger (20 mg /rats).  The ulcers were induced made from groups 2 - 5 by oral administration of Indomethacin. Rats subjected to indomethacin administration showed significant ulceration in the glandular area of their stomachs compared to normal control rats. In addition, significant elevations S.GPT, S.GOT, S. creatinine and S. Urea (P< 0.05) were observed. Alternatively, pretreatment with pomegranate and ginger significantly corrected macroscopic and biochemical parameters. These results demonstrate that administration of either pomegranate and ginger supplementation have an essential role in the prevention of ulceration induced by NSAIDs. Furthermore improved liver and kidney functions and reduced hepatoto and nephrotoxicities

Increased efficacy for in-house validation of real-time PCR GMO detection methods

To improve the efficacy of the in-house validation of GMO detection methods (DNA isolation and real-time PCR, polymerase chain reaction), a study was performed to gain insight in the contribution of the different steps of the GMO detection method to the repeatability and in-house reproducibility. In the present study, 19 methods for (GM) soy, maize canola and potato were validated in-house of which 14 on the basis of an 8-day validation scheme using eight different samples and five on the basis of a more concise validation protocol. In this way, data was obtained with respect to the detection limit, accuracy and precision. Also, decision limits were calculated for declaring non-conformance (>0.9%) with 95% reliability. In order to estimate the contribution of the different steps in the GMO analysis to the total variation variance components were estimated using REML (residual maximum likelihood method). From these components, relative standard deviations for repeatability and reproducibility (RSDr and RSDR) were calculated. The results showed that not only the PCR reaction but also the factors ‘DNA isolation’ and ‘PCR day’ are important factors for the total variance and should therefore be included in the in-house validation. It is proposed to use a statistical model to estimate these factors from a large dataset of initial validations so that for similar GMO methods in the future, only the PCR step needs to be validated. The resulting data are discussed in the light of agreed European criteria for qualified GMO detection methods