Industrial production generates enormous amounts of wastewaters with a high content of organic and inorganic substances, which must be treated before discharging into a natural recipient to such a quality that it will not have a negative impact on the aquatic environment. This paper shows the possibility of applying a multi-stage process with Fenton reagents in combination with bentonite as an adsorbent in the treatment of ammonia-phenolic wastewater. The role of bentonite clay in this study was dye removal. The investigation was carried out under laboratory conditions, and the efficiency of the process was determined on the following parameters of COD, ammonia, phenol and thiocyanate. Also, the influence of the pH value, the concentration of oxidant hydrogen peroxide and catalyst iron sulphate heptahydrate was examined. The optimal values obtained for the pH, concentration of hydrogen peroxide and the catalyst iron sulphate heptahydrate was: 3; 30% and 23 g/l, where the efficiency of removal of the COD, ammonia, phenol and thiocyanate was: 96.42 %; 85.17 %; 100 % i 99.13 %.

In this article, an upgraded version of CUDA-Quicksort - an iterative implementation of the quicksort algorithm suitable for highly parallel multicore graphics processors, is described and evaluated. Three key changes which lead to improved performance are proposed. The main goal was to provide an implementation with increased scalability with the size of data sets and number of cores with modern GPU architectures, which was successfully achieved. The proposed changes also lead to significant reduction in execution time. The execution times were measured on an NVIDIA graphics card, taking into account the possible distributions of the input data.

With the progress of technology and mankind, demand for different job positions has emerged. Reports indicating various new job types in the last decade are continuously published, giving us perspective on where we were a decade ago and where we are now. Most of the jobs are created around new technologies, yet not exclusively as jobs within technology production or usage (e.g., machine learning engineers, data scientists, app developers, etc.), but also as a type of jobs built atop of new technologies (e.g., social media manager, podcast producer, content moderator, etc.). With new job types, there is a gap between qualified employees and employers demands created. Taking into consideration trends that we have seen in the last years, more and more new job types will be created, and we can predict that this gap will become larger as time passes.

Vulnerability Assessment and Penetration Testing (VAPT) is an important component of an organization's overall security strategy. VAPT helps identify security vulnerabilities in a computer system, network, or web application, allowing organizations to take corrective measures to address these vulnerabilities and prevent potential security breaches. By conducting regular VAPT, organizations can improve their security posture and reduce the likelihood of successful attacks. In this paper Metasploit was used to show importance of regular vulnerability assessment of critical systems in order to discover vulnerabilities before attacker do it and exploit them. The authors showed Metasploit beside its usage to conduct a vulnerability assessment, it can be utilized by attackers to harm systems. VAPT is not a one-time event, but rather a ongoing process. As new vulnerabilities are discovered and new threats emerge, organizations need to regularly assess their systems to ensure they are protected.

Air pollution represents one of the most complex problems of humanity. Traffic contributes significantly to this by emitting large amounts of harmful gases. This problem is particularly pronounced at urban intersections due to frequent changes in vehicle movement dynamics. This paper primarily presents the influence of intersection geometry on pollutant emissions levels. In addition, the influence of various traffic policies promoting greater use of public transport and zero-emission vehicles is also examined. The research combines the field part of recording existing intersections in Sarajevo, Bosnia and Herzegovina with traffic microsimulation. Detailed data on vehicles’ movements were obtained by advanced video processing using the DataFromSky tool, while the PTV Vissim 2022 and Bosch ESTM (2022) software were used to simulate traffic and estimate emissions at geometrically different intersections. The results showed that, in saturated traffic conditions, signalized intersections cause up to 50% lower emissions compared with two-lane and turbo roundabouts and that the impact of the geometric change is more significant than the impact of zero-emission vehicles. In unsaturated conditions, the differences in emissions at different intersections are negligible, with the highest reductions in pollution achieved by using zero-emission vehicles.

The increased volume of initiatives and investments in the framework of smart cities, as well as strong investments in AI/ML technology together with the IoT industry, undoubtedly represent the future of practical activities and the implementation of new generation technological solutions in cities. By analyzing the previous literature and related works, in the field of smart waste management solutions, the focus of research was placed on isolated problems at lower levels of technology implementation on individual subsystems with individual environments. The purpose of this paper is to emphasize the need for a systematic integrated approach in the process of designing a model of practical application of technology to solve the problem of waste management in cities with a special aspect on business processes and the end user. The paper presents an analysis of related works and commercial solutions implemented so far and proposes a practical implementation model that, among other things, includes a component of a higher level of abstraction that should perform an additional iteration of the AI/ML process and make a final decision in the prediction process and controls in smart waste management solutions.

In this study, the implementation of Free Route Airspace (FRA) in Europe is presented, with special reference to the merge of SECSI FRA (South East Common Sky Initiative Free Route Airspace) and FRA IT(Free Route Airspace in Italy) in to the SECSI IT FRA. Free Route Airspace is a certain volume of airspace in which users are free to plan a route between defined entry and exit points. Depending on the availability of airspace, routing is possible via waypoints, without calling the Air Traffic Service (ATS) route network. The purpose of this paper is to show how the implementation of free route airspace in Europe, affects traffic indicators in terms of flight length, fuel consumption, environmental impact and economy. This paper will also show a slight decrease in air traffic controller load as a result of the implementation of free route airspace. We also wanted to show how, the merge of SECSI FRA and FRA IT, affects Bosnia and Herzegovina airspace. When fully implemented at European level, it should allow the following savings, compared to the current situation: 1 billion nautical miles in terms of flight length, 6 million tons of fuel savings, and 5 billion euros less costs in in terms of fuel savings.

A muon collider would enable the big jump ahead in energy reach that is needed for a fruitful exploration of fundamental interactions. The challenges of producing muon collisions at high luminosity and 10 TeV centre of mass energy are being investigated by the recently-formed International Muon Collider Collaboration. This Review summarises the status and the recent advances on muon colliders design, physics and detector studies. The aim is to provide a global perspective of the field and to outline directions for future work.

Many different methods are used for generating blackbox test case suites. Test case minimization is used for reducing the feasible test case suite size in order to minimize the cost of testing while ensuring maximum fault detection. This paper presents an optimization of the existing test case minimization algorithm based on forward-propagation of the cause-effect graphing method. The algorithm performs test case prioritization based on test case strength, a newly introduced test case selection metric. The optimized version of the minimization algorithm was evaluated by using thirteen different examples from the available literature. In cases where the existing algorithm did not generate the minimum test case subsets, significant improvements of test effect coverage metric values were achieved. Test effect coverage metric values were not improved only in cases where maximum optimization was already achieved by using the existing algorithm.

This paper presents unified force and position control based on sliding mode control (SMC) for a series elastic actuator (SEA). Compliant motion of robotic systems is crucial when dealing with unstructured environments as in the case of physical human-robot interaction. Therefore, not only traditional mechanical systems with stiff joints but also mechanically compliant systems such as SEAs have been actively studied. In order to accomplish versatile tasks, the strategy enabling both position control and force control is favorable. In this paper, the controller synthesizing position and force controllers on the basis of SMC for the control problem of SEAs is proposed by extending our previous work. Simulation results demonstrate the feasibility of the proposed method.

In primary hyperoxaluria type 1 excessive endogenous production of oxalate and glycolate leads to increased urinary excretion of these metabolites. Although genetic testing is the most definitive and preferred diagnostic method, quantification of these metabolites is important for the diagnosis and evaluation of potential therapeutic interventions. Current metabolite quantification methods use laborious, technically highly complex and expensive liquid, gas or ion chromatography tandem mass spectrometry, which are available only in selected laboratories worldwide. Incubation of ortho-aminobenzaldehyde (oABA) with glyoxylate generated from glycolate using recombinant mouse glycolate oxidase (GO) and glycine leads to the formation of a stable dihydroquinazoline double aromatic ring chromophore with specific peak absorption at 440 nm. The urinary limit of detection and estimated limit of quantification derived from eight standard curves were 14.3 and 28.7 µmol glycolate per mmol creatinine, respectively. High concentrations of oxalate, lactate and L-glycerate do not interfere in this assay format. The correlation coefficient between the absorption and an ion chromatography tandem mass spectrometry method is 93% with a p value < 0.00001. The Bland–Altmann plot indicates acceptable agreement between the two methods. The glycolate quantification method using conversion of glycolate via recombinant mouse GO and fusion of oABA and glycine with glyoxylate is fast, simple, robust and inexpensive. Furthermore this method might be readily implemented into routine clinical diagnostic laboratories for glycolate measurements in primary hyperoxaluria type 1.

Paper covers image classification using the Keras API in TensorFlow. The dataset used is a set of labelled images consisting of characters from the Pokémon media franchise. In order to artificially generate additional data, the process of data augmentation has been applied on the initial dataset to reduce overfitting. A comparison between DenseNet-121, DenseNet-169 and DenseNet-201 has been made to observe which of the models scores a greater accuracy. A Graphics Processing Unit (GPU) has been set up to work with TensorFlow in order to efficiently train the model.

This paper presents the use of different prediction algorithms in order to recognise the popularity of a song. That recognition gives features that are directly affecting popularity of a song. For this research, data from several hundreds of the most popular songs were used in combination with songs that often appear on different playlists from different musicians. The reason for this mixing of songs is done to ensure that the model works as efficiently as possible by comparing popular songs features with those of that are no longer trending. The processing of the collected data gave an excellent insight into the importance of certain factors on the popularity of a certain song. As a result of research, month of release, acoustics and tempo were represented as features that are mostly correlated with popularity. Through the processing and analysis of a large amount of data, four models were created using different algorithms. Algorithms that were used are Decision Tree, Nearest Neighbour Classifier, Random Forest and Support Vector Classifier algorithms. The best results were achieved by training the model with the Decision Tree algorithm and accuracy of 100%.

Predictive modelling and AI have become a ubiquitous part of many modern industries and provide promising opportunities for more accurate analysis, better decision-making, reducing risk and improving profitability. One of the most promising applications for these technologies is in the financial sector as these could be influential for fraud detection, credit risk, creditworthiness and payment analysis. By using machine learning algorithms for analysing larger datasets, financial institutions could identify patterns and anomalies that could indicate fraudulent activity, allowing them to take action in real-time and minimize losses. This paper aims to explore the application of predictive models for assessing customer worthiness, identify the benefits and risks involved with this approach and compare their results in order to provide insights into which model performs best in the given context.

Web developers utilize responsive web design principles and frameworks to develop websites that are accessible on various platforms. As consumers often access websites through laptops, tablets, mobile phones, and desktop computers, it is necessary for the website to adjust its appearance according to the device's display frame width. However, the quality assurance process for responsive web pages is typically manual, time-consuming, and error prone. This study introduces ReDeCheck, an open-source automated website layout checking tool developed by Thomas A. Walsh, Gregory M. Kapfhammer, and Phil McMinn. The tool identifies the most common types of responsive design failures by utilizing a set of display frame widths based on the presentation of the website's dynamic layout, also known as the Responsive Layout Graph. This paper verifies the tool's functionality and its underlying concepts.