The purpose of a car jack is lifting the car and maintaining it at a certain height during different repairs. This paper focuses on the design of car jack, which belongs to the basic equipment of cars. Cars jacks are used mainly for changing tires and small repairs of a car. The aim of this paper was to create a parametric CAD model of a car jack and carry out numerical structural analysis of the car jack using the created parametric CAD model. The development of the parametric CAD model and structural analysis was performed using the CATIA V5 system. This paper describes the modern way of creating more complex mechanisms, which support quick modification of its parameters, and thus the entire design. The whole model of the car jack was parametrized. The stresses obtained by finite element method (FEM) analysis were confirmed with the analytical calculation in characteristic parts of the design, with some exceptions. At the end of the paper, an analysis of the obtained results was performed, on the basis of which specified conclusions were made.

Changing the optical fiber parameters during long-term use can not be mathematically calculated. This paper analyses the change of optical fibers from the aspect of ageing under the influence of transmitted signals and the aspect of water influences. The analysis was carried out in such a way as to compare the measurements carried out after the installation of optical cables and measurements after 16 years of use. The analysis has been shown to vary greatly the loss of fiber optic splice for different wavelengths. These different loss for wavelengths 1310 nm and 1550 nm suggest that the loss of optical fiber has increased due to the impact of water.

This paper addresses the problem of 3D registration of outdoor environments combining heterogeneous datasets acquired from unmanned aerial (UAV) and ground (UGV) vehicles. In order to solve this problem, we introduced a novel Scale Invariant Registration Method (SIRM) for semi-automated registration of 3D point clouds. The method is capable of coping with an arbitrary scale difference between the point clouds, without any information about their initial position and orientation. Furthermore, the SIRM does not require having a good initial overlap between two heterogeneous datasets. Our method strikes an elegant balance between the existing fully automated 3D registration systems (which often fail in the case of heterogeneous datasets and harsh outdoor environments) and fully manual registration approaches (which are labour-intensive). The experimental validation of the proposed 3D heterogeneous registration system was performed on large-scale datasets representing unstructured and harsh outdoor environments, demonstrating the potential and benefits of the proposed 3D registration system in real-world environments.

IoT devices have a wide spectrum of applications in the real-life environment. While these applications range based on the area covered, having the best scenario related to the devices covering the optimal area is a challenge. In this work, we consider the improvement of the industrial laboratory by transferring it to the smart lab using the IoT devices. We analyzed the tradeoffs between different scenarios of the smart lab with the focus on the security and congestion of the network and its effects on the overall performance. For the smart lab case study we can conclude that security-enabled feature will not significantly affect the performance of the smart lab compared to the benefits of the IoT-integrated devices on the overall improvement of the lab experience given that the traditional lab had significant time delay.

In process automation installations, the I/O system connect the field devices to the process controller over a fieldbus, a reliable, real-time capable communication link with signal values cyclical being exchanged with a 10–100 millisecond rate. If a deviation from intended behaviour occurs, analyzing the potentially vast data recordings from the field can be a time consuming and cumbersome task for an engineer. For the engineer to be able to get a full understanding of the problem, knowledge of the used I/O configuration is required. In the problem report, the configuration description is sometimes missing. In such cases it is difficult to use the recorded data for analysis of the problem.In this paper we present our ongoing work towards using neural network models as assistance in the interpretation of an industrial fieldbus communication recording. To show the potential of such an approach we present an example using an industrial setup where fieldbus data is collected and classified. In this context we present an evaluation of the suitability of different neural net configurations and sizes for the problem at hand.

Combating eutrophication requires changes in land and water management in agricultural catchments and implementation of mitigation measures to reduce phosphorus (P), nitrogen (N) and suspended sediment (SS) losses. To date, such mitigation measures have been built in many agricultural catchments, but there is a lack of studies evaluating their effectiveness. Here we evaluated the effectiveness of mitigation measures in a clay soil-dominated headwater catchment by combining the evaluation of long-term and high-frequency data with punctual measurements upstream and downstream of three mitigation measures: lime-filter drains, a two-stage ditch, and a sedimentation pond. Long-term hydrochemical data at the catchment outlet showed a significant decrease in P (-15%) and SS (-28%) and an increase in nitrate nitrogen (NO-N, +13%) concentrations. High-frequency (hourly) measurements with a wet-chemistry analyzer (total and reactive P) and optical sensor (NO-N and SS) showed that the catchment is an abundant source of nutrients and sediments and that their transport is exacerbated by prolonged drought and resuspension of stream sediments during storm events. Lime-filter drains showed a decrease in SS by 76% and total P by 80% and an increase in NO-N by 45% compared with traditional drains, potentially indicating pollution swapping. The effectiveness of two-stage ditch and sedimentation pond was less evident and depended on the prevalent hydrometeorological conditions that drove the resuspension of bed sediments and associated sediment-bound P transport. These results suggest that increased frequency of prolonged drought due to changing weather patterns and resuspension of SS and sediment-bound P during storm events can override the generally positive effect of mitigation measures.

The evolution of phosphorus (P) management decision support tools (DSTs) and systems (DSS), in support of food and environmental security has been most strongly affected in developed regions by national strategies (i) to optimize levels of plant available P in agricultural soils, and (ii) to mitigate P runoff to water bodies. In the United States, Western Europe, and New Zealand, combinations of regulatory and voluntary strategies, sometimes backed by economic incentives, have often been driven by reactive legislation to protect water bodies. Farmer-specific DSSs, either based on modeling of P transfer source and transport mechanisms, or when coupled with farm-specific information or local knowledge, have typically guided best practices, education, and implementation, yet applying DSSs in data poor catchments and/or where user adoption is poor hampers the effectiveness of these systems. Recent developments focused on integrated digital mapping of hydrologically sensitive areas and critical source areas, sometimes using real-time data and weather forecasting, have rapidly advanced runoff modeling and education. Advances in technology related to monitoring, imaging, sensors, remote sensing, and analytical instrumentation will facilitate the development of DSSs that can predict heterogeneity over wider geographical areas. However, significant challenges remain in developing DSSs that incorporate "big data" in a format that is acceptable to users, and that adequately accounts for catchment variability, farming systems, and farmer behavior. Future efforts will undoubtedly focus on improving efficiency and conserving phosphate rock reserves in the face of future scarcity or prohibitive cost. Most importantly, the principles reviewed here are critical for sustainable agriculture.

To achieve efficient and flexible production at affordable prices, industrial automation is pushed towards a digital transformation. Such a transformation assumes an enhancement of current Industrial Automated Control Systems with a large amount of IoT-devices, forming an Industrial Internet of Things (IIoT). The aim is to enable a shift from automatic towards autonomous control in such systems. This paper discusses some of the main challenges IIoT systems are facing with respect to cybersecurity. We discuss our findings in an example of a flow-control loop, where we apply a simple threat model based on the STRIDE method to deduce cybersecurity requirements in an IIoT context. Moreover, the identified requirements are assessed in the light of current state of the art solutions, and a number of challenges are discussed with respect to a large-scale IIoT system, together with some suggestions for future work.

There is a growing interest in using the Blockchain for resolving IoT security and trustworthiness issues existing in today’s complex systems. Blockchain concerns trust in peer to peer networks by providing a distributed tamper-resistant ledger. However, the combination of these two emerging technologies might create new problems and vulnerabilities that attackers might abuse.In this paper, we aim to investigate the trust mechanism of Lightweight Scalable BlockChain (LSB), that is a Blockchain specifically designed for Internet of Things networks, to show that a malicious participant in a Blockchain architecture have possibility to pursue an On-Off attack and downgrade the integrity of the distributed ledger. We choose a remote software update process as an instance to represent this violation. Finally, using the actor-based language Rebeca, we provide a model of a system under attack and verify the described attack scenario.

Graphene-based materials and their role in electrocatalysis related to hydrogen production have been intensively investigated by many authors, often justified through a low price of such materials. In this study we used single-step electrodeposition/graphene oxide reduction route to prepare Ni@reduced-graphene-oxide composites for electrochemical hydrogen evolution reaction (HER). As the precursors for reduced graphene oxide, two different home-made graphene oxides were used. When compared to pure electrodeposited Ni, composite catalysts show improved catalytic activity which depends on Ni electrodeposition time in a volcano-type fashion. Using electrochemically prepared graphene oxide, HER overvoltage needed to reach 10 mA cm −2 was reduced to only −97 mV, showing the improvement by roughly 200 mV when compared to pure electrodeposited Ni. It was concluded that structural disorder and surface oxidation of graphene-based materials are the key properties for reaching high HER activities of such prepared catalysts. Based on this observation, it was discussed whether it is economically justified to use high quality graphene oxide for the preparation of HER catalysts, as the price (production and commercial) of this material can be extremely high, often exceeding the price of platinum.

In this paper, we propose a two-dimensional pilot allocation scheme over frequency- and delay-time domains (2D-PFD) for channel estimation in massive multiple-input multiple-output (MIMO)/time division duplex (TDD) system, where two- dimensional pilot resources are simultaneously allocated to each user for their uplink channel estimation. We evaluate bit error rate (BER) performance of massive MIMO/TDD system using the 2D-PFD scheme by computer simulation in order to clarify the effectiveness of the proposed pilot allocation compared with single dimensional pilot allocation over either delay-time domain or frequency domain, respectively.

The aim of this paper is to determine the opinions of deaf workers on their labor capacity and the opinions of their hearing co-workers about the labor capacities of the deaf. The sample consisted of 247 respondents, of whom 127 were deaf and 120 were hearing workers. Qualitative and quantitative analysis were used in processing the results. Testing was performed by Wilks' Lambda, tested significance in discriminant analysis was done by F test, at the statistical significance of 0.01. It was found that the sub-sample of respondents had a statistically significant difference in views on claims regarding the exploitation of deaf workers by employers, the employment of deaf people in low-paid simple occupations, and the equally successful but insignificant productivity of deaf workers. The statistical differences found indicate that there are differences in the assessment of the labor capacity of deaf workers in the hearing work environment. Qualitative analysis found that hearing impairment and the subjective attitudes of colleagues without hearing impairment have the greatest impact on the assessment of the labor capacity of deaf workers.

In this paper, the frequency response metrics of interconnected electric power systems (EPS) of Slovenia, Croatia and Bosnia and Herzegovina (ENTSO-E SCB control block) is presented. In the upcoming period in this region significant integration of wind energy is expected. Increased wind integration has great impacts on EPS frequency response due to decreasing total system inertia. A frequency response metrics calculation in a short period after a disturbance occurred is essential for design of any further frequency control action. Comparison of local bus frequency and frequency of centers of inertia is in the focus of this work. The regional EPS of South East Europe (SEE) is modeled using PSS/E. Frequency response metrics calculations and plots are performed using Python simulation language.

A new control algorithm for Directly Interconnected offshore Wind Turbines with permanent magnet synchronous Generators (DIWTG) is presented. In the DΓWTG offshore wind park configuration, Wind Turbines with Permanent Magnet Synchronous Generators (WTPMSG) are directly connected to the offshore AC collection grid without using a power converter. The offshore AC collection grid is then connected, via a transformer, to the offshore AC transmission grid. In order to achieve maximum power point tracking, the (collective) speed of DΓWTGs is controlled by an onshore back to back converter. By measuring the active power and speed of the permanent magnet generators, wind speed at each turbine is estimated and used for calculation of the reference speed of WTPMSGs. Voltage control at the power converter side is performed in a way which allow the DΓWTGs to be operated at a constant V/f where the maximum resultant frequency at nominal wind speed is 16.67 Hz.

Internet of Things (IoT) devices such as Samsung Gear S3 Frontier smartwatch are great sources of potential digital evidence, due to their constant daily use. The main aim of this paper is to analyze the capabilities and limitations of IoT forensics of a Samsung Gear S3 Frontier smartwatch. Main concepts of IoT forensics, a summary of the current and future research progress and challenges, is given. A scenario of watch events during 3 hours of usage was recorded, which forensic analysis had to restore. Manual extraction and analysis of data, along with the detailed look at the discovered relevant files, and achieved results are presented. The primary contribution of this paper consists of a detailed approach to a particular smartwatch forensic, which supports future forensic investigations.