Dynamic real-time risk analytics of uncontrollable states in complex internet of things systems: cyber risk at the edge

The Internet of Things (IoT) triggers new types of cyber risks. Therefore, the integration of new IoT devices and services requires a self-assessment of IoT cyber security posture. By security posture this article refers to the cybersecurity strength of an organisation to predict, prevent and respond to cyberthreats. At present, there is a gap in the state of the art, because there are no self-assessment methods for quantifying IoT cyber risk posture. To address this gap, an empirical analysis is performed of 12 cyber risk assessment approaches. The results and the main findings from the analysis is presented as the current and a target risk state for IoT systems, followed by conclusions and recommendations on a transformation roadmap, describing how IoT systems can achieve the target state with a new goal-oriented dependency model. By target state, we refer to the cyber security target that matches the generic security requirements of an organisation. The research paper studies and adapts four alternatives for IoT risk assessment and identifies the goal-oriented dependency modelling as a dominant approach among the risk assessment models studied. The new goal-oriented dependency model in this article enables the assessment of uncontrollable risk states in complex IoT systems and can be used for a quantitative self-assessment of IoT cyber risk posture.

     

Creating Pedestrian Crash Scenarios in a Driving Simulator Environment

Objective: In 2012 in the United States, pedestrian injuries accounted for 3.3% of all traffic injuries but, disproportionately, pedestrian fatalities accounted for roughly 14% of traffic-related deaths (NHTSA 2014 NHTSA. Traffic Safety Facts 2012 Pedestrians. Washington, DC: Author; 2014. DOT HS 811 888. [Google Scholar]). In many other countries, pedestrians make up more than 50% of those injured and killed in crashes. This research project examined driver response to crash-imminent situations involving pedestrians in a high-fidelity, full-motion driving simulator. This article presents a scenario development method and discusses experimental design and control issues in conducting pedestrian crash research in a simulation environment. Driving simulators offer a safe environment in which to test driver response and offer the advantage of having virtual pedestrian models that move realistically, unlike test track studies, which by nature must use pedestrian dummies on some moving track.

Methods: An analysis of pedestrian crash trajectories, speeds, roadside features, and pedestrian behavior was used to create 18 unique crash scenarios representative of the most frequent and most costly crash types. For the study reported here, we only considered scenarios where the car is traveling straight because these represent the majority of fatalities. We manipulated driver expectation of a pedestrian both by presenting intersection and mid-block crossing as well as by using features in the scene to direct the driver's visual attention toward or away from the crossing pedestrian. Three visual environments for the scenarios were used to provide a variety of roadside environments and speed: a 20–30 mph residential area, a 55 mph rural undivided highway, and a 40 mph urban area.

Results: Many variables of crash situations were considered in selecting and developing the scenarios, including vehicle and pedestrian movements; roadway and roadside features; environmental conditions; and characteristics of the pedestrian, driver, and vehicle. The driving simulator scenarios were subjected to iterative testing to adjust time to arrival triggers for the pedestrian actions. This article discusses the rationale behind creating the simulator scenarios and some of the procedural considerations for conducting this type of research.

Conclusions: Crash analyses can be used to construct test scenarios for driver behavior evaluations using driving simulators. By considering trajectories, roadway, and environmental conditions of real-world crashes, representative virtual scenarios can serve as safe test beds for advanced driver assistance systems. The results of such research can be used to inform pedestrian crash avoidance/mitigation systems by identifying driver error, driver response time, and driver response choice (i.e., steering vs. braking).     

Indoor air pollution evaluation with emphasize on HDI and biological assessment of HDA in the polyurethane factories

Today, many raw materials used in factories may have a dangerous effect on the physiological system of workers. One of them which is widely used in the polyurethane factories is diisocyanates. These compounds are widely used in surface coatings, polyurethane foams, adhesives, resins, elastomers, binders, and sealants. Exposure to diisocyanates causes irritation to the skin, mucous membranes, eyes, and respiratory tract. Hexamethylene diamine (HDA) is metabolite of hexamethylene diisocyanate (HDI). It is an excretory material by worker’s urine who is exposed to HDI. Around 100 air samples were collected from five defined factories by midget impinger which contained dimethyl sulfoxide absorbent as a solvent and tryptamine as reagent. Samples were analyzed by high-performance liquid chromatography with EC\UV detector using NIOSH 5522 method of sampling. Also, 50 urine samples collected from workers were also analyzed using William’s biological analysis method. The concentration of HDI into all air samples were more than 88 xxxμg/m³, and they have shown high concentration of pollutant in the workplaces in comparison with NIOSH standard, and all of the workers’ urine were contaminated by HDA. The correlation and regression test were used to obtain statistical model for HDI and HDA, which is useful for the prediction of diisocyanates pollution situation in the polyurethane factories.     

Organohalogen compounds in blubber of Indo-Pacific bottlenose dolphin (Tursiops aduncus) and spinner dolphin (Stenella longirostris) from Zanzibar, Tanzania

Blubber samples of Indo-Pacific bottlenose (Tursiops aduncus) and spinner (Stenella longirostris) dolphins from Zanzibar, East Africa, were analyzed for a wide range of organohalogen compounds. Methoxylated polybrominated diphenyl ethers (MeO-BDEs), presumably biogenic, were found at higher concentrations than anthropogenic organochlorine pesticides (OCPs). Only traces of industrial pollutants, such as polychlorinated biphenyls, were detected. The OCP levels found off Zanzibar were lower than those reported from other regions while MeO-BDE levels were higher. The relative composition of the OCPs indicated recent use of lindane (γ-hexachlorocyclohexane) and aged residues of DDT and technical HCH. Placental transfer was estimated to 2.5% and 0.5% of the total burden of OCPs and MeO-BDEs, respectively. Overall transfer from mother to calf in Indo-Pacific bottlenose dolphins was estimated to 72% and 85% for the OCPs and MeO-BDEs burdens, respectively. Health effects of MeO-BDEs are not known, but structural similarities with well-known environmental toxins are cause for concern.     

Investigation of physico-chemical properties and microbial community during poultry manure co-composting process

Co-composting of poultry manure and rubber wood sawdust was performed with the ratio of 2:1 (V/V) for a period of 60 days. An investigation was carried out to study the extracellular enzymatic activities and structural degradation utilizing Fourier transform infrared spectroscopy (FT-IR), thermogravimetry and differential thermal analysis (TG/DTA) and scanning electron microscopy (SEM). The microbial succession was also determined by using denaturing gel gradient electrophoresis (DGGE). The compost was able to reach its highest temperature of 71°C at day 3 and stabilized between 30 and 40°C for 8 weeks. CMCase, FPase and β-glucosidase acted synergistically in order to degrade the cellulosic substrate. The xylanase activities increased gradually during the composting and reached the peak value of 11.637 U/g on day 35, followed by a sharp decline. Both LiP and MnP activities reached their peak values on day 35 with 0.431 and 0.132 U/g respectively. The FT-IR spectra revealed an increase in aromaticity and a decrease in aliphatic compounds such as carbohydrates as decomposition proceeded. TGA/DTG data exhibited significant changes in weight loss in compost samples, indicating degradation of organic matter. SEM micrographs showed higher amounts of parenchyma exposed on the surface of rubber wood sawdust at day 60, showing significant degradation. DGGE and 16S rDNA analyses showed that Burkholderia sp., Pandoraea sp., and Pseudomonas sp. were present throughout the composting process. Ornithinibacillus sp. and Castellaniella ginsengisoli were only found in the initial stage of the composting, while different strains of Burkholderia sp. also occurred in the later stage of composting.     

Effects of metolachlor on activities of enzymes in a malaysian soil

Abstract

Effects of metolachlor on the activities of cellulase, phosphatase, urease and protease in a loamy sand soil, were evaluated for up to 28 days. Metolachlor at 10 ppm and above caused a reduction in phosphatase and urease activities for the entire period of study. The cellulase activity decreased during the very first day of incubation compared to that of the control but a recovery trend was obvious at all concentrations from day 14 onwards. Protease activity was also reduced in the metolachlor treated soil and the lower activity was observed during the entire study.