Exploitation Process Research Articles

THE DEVELOPMENT OF EXPLOITATION: FROM THE PAST TO THE PRESENT

Purpose. The aim of the article is to explore the problems of exploitation and their solutions: an excursion into the past and a modern view in various manifestations and forms. Methodology of research. Research on the chosen topic was carried out using various methods of detailed study of the main components of this topic. At the same time, preference was given to the following methods: historical (the phenomenon of exploitation is considered in historical retrospect), dialogic (processes of exploitation are studied from the standpoint of the formation of the author’s questions, and the answers are from the appropriate source), system and structural, abstract and logical (all structural components of the study are presented in certain logical and abstract sequence). All research processes were closely related from the standpoint of their dialectical development. Findings. A study of the development of exploitation was carried out with an emphasis on the processes of the origin of this social and economic phenomenon in various spheres of mutual relations in human society. The importance and role of exploitation processes in various spheres of social relations and, at the same time, the insufficient volume and level of research into this phenomenon are emphasized. In the research processes, the main attention was focused on: clarifying the essence and phenomena of the development of exploitation and its interpretation in scientific publications; periods and conditions of exploitation in various production methods; combination of economic and non-economic forms of exploitation; the development of new forms of exploitation and their influence on views and statements regarding the development of the processes of this social and economic phenomenon. Originality. On the basis of the obtained research data, specific conclusions and proposals regarding further steps in the study of the patterns of the development of new forms of exploitation in modern conditions have been formed. Practical value. Proposals to expand the range of research on exploitation processes, focusing special attention on such an important component of this socio-economic phenomenon as self-exploitation, deserve attention. It is also necessary in modern conditions and for the future to provide for the study of the basics of exploitation in educational institutions of Ukraine. This is especially important when training managerial specialists. Key words: exploitation, social relations, essence, forms of exploitation, methods of production, past, present, research

Modeling the Impact of Habituation and Breaks in Exploitation Process on Multi-Armed Bandits Performance

Habituation is a common phenomenon in learning, where the response to a repeated stimulus decreases over time. In Multi-Armed Bandits (MAB) algorithms used for visual content delivery optimization, habituation can lead to suboptimal performance. For example, if an agent becomes habituated to a suboptimal arm, it may continue to choose that arm even if better options are available. Habituation can be modeled as a form of ”forgetting”, where the agent gradually loses confidence in its estimates of the reward probabilities for each arm as time passes. Proposed approach allows updating estimates according to habituation model, while also exploiting the arm with the highest estimated reward probability. The results showed that it is a very good solution to introduce breaks in the multi-armed bandit habit model, which was implemented and tested in our study.

Captivity's Commerce: The Theory and Methodology of Slaving and Capitalism

This article identifies new pathways for integrating African perspectives into debates about the historical relationship between slavery and capitalism. It focuses extensively on the work of African historian Joseph C. Miller (1939–2019), whose concept of “ethno political economics” combined ethnographic and quantitative data and offered a new perspective on Atlantic World history. Building on theorizations of early twentieth-century scholars W.E.B. Du Bois, C.L.R. James, Eric Williams, and others, Miller's analysis foregrounded the simultaneously local and global processes of credit expansion, commercialization, and labor exploitation as foundational to the consolidation of early modern capitalism.

A Novel Meta-Heuristic Algorithm for Numerical and Engineering Optimization Problems: Piranha Foraging Optimization Algorithm (PFOA)

This paper provides a novel meta-heuristic optimization algorithm for solving continuous optimization problems efficiently in the field of numerical and engineering optimization: Piranha Foraging Optimization Algorithm (PFOA). The algorithm is inspired by the flexible and mobile foraging behaviour of piranha swarm and divides their foraging behavior into three patterns: localized group attack, bloodthirsty cluster attack and scavenging foraging, simulates the above behaviors to construct two dynamic search processes for exploration and exploitation. PFOA uses three strategies of non-linear parameter control, population survival and reverse evasion search to enable populations to have better population diversity at different stages of the search and to help find better solutions. To gain insight into the performance of PFOA, visualization methods were used to assess the efficiency of PFOA optimization and to analyse the impact of the characteristics of the three foraging modes, the sensitivity of the parameters and the size of the piranha population on the algorithm. The algorithm performance was further tested with 27 CEC benchmark functions and four real engineering design optimization problems, and the results were compared with 13 well-known meta-heuristics. Test results based on statistical methods such as box-line plots, Wilcoxon rank sum test and Friedman test in multiple dimensions (30, 50, 100 and fixed dimensions) show significant differences compared to other algorithms and that the performance of the algorithm is stable and in significant improvement. The unique advantages of PFOA in terms of the equilibrium of convergence speed and exploration can avoid getting trapped in local optimum regions and effectively solve optimization problems in complex search spaces.

Dizajni novog hibridnog kontrolera zasnovan na poboljšanoj verziji optimizacije sivi vuk za praćenje putanje mobilnog robota na točkovima

Nonholonomic wheeled mobile robots are considered to be multi-input multi-output systems that are performed in varying environments. This work presents the trajectory tracking control of a nonholonomic wheeled mobile robot (WMR). The Kinematic and the dynamic models of the robot were derived. A new hybrid controller was designed, which consisted of two controllers based on an optimization algorithm to solve the trajectory tracking problem. The first controller is the Fractional order PID controller, which is based on the kinematic model and has been applied to control the linear and the angular robot velocities, while the second controller is a linear quadratic regulator (LQR) and is based on the dynamic model used to control the motors' torques. A new, improved version of grey wolf optimization wasadopted to tune the parameters of the hybrid controller. The main goals of this improvement are rapid convergence towards a solution, reducing the effect of the wolves' random motion, and balancing exploitation and exploration processes. MATLAB software was used to simulate the results under an S-shape trajectory and to evaluate the robustness and performance of the proposed control unit. The simulation results demonstrated the adopted control system's activity and efficiency based on the mean square error (MSE) between the desired and actual trajectory. The values of MSE of trajectory in the X and Y directions and the orientation are [6.589*10-4(m) 8.421*10-5(m) 0.00401(rad)]T . Also, the adopted control system can generate smooth values of the control input signals without sharp spikes. The performance of the presented control system has been verified and compared with the results obtained from the other two control systems, and the simulation results have offered the superiority and effectiveness of the hybrid controller of this work.

The method of controlling the efficiency of the airworthiness assurance subsystem in the system of means of transport operation

In order to ensure proper and effective performance of tasks in complex systems of means of transport operation, it is necessary to maintain an appropriate number of buses that are capable of carrying out transport. This is achieved as a result of the implementation of maintenance and repair processes at the stations of the workability assurance subsystem. The ability to perform maintenance and repair tasks assigned to airworthiness assurance subsystems depends on their readiness to drive. Ensuring the required readiness of the tested subsystems is possible by adjusting the number and structure of maintenance and repair stations, adjusting the equipment of these stations in such a way that, if necessary, it is possible to perform specific tasks at various types of stations and the use of devices and tools with high reliability, durability and efficiency. The article presents a description of the method of determining the optimal strategy for controlling the process of exploitation of means of transport with the use of decisionmaking semiMarkov processes. The selection of the optimal (suboptimal) solution is carried out using a genetic algorithm. As a result implementation numerical calculations , a set of solutions in the form of the so-called Pareto front is obtained for the applied criterion functions.

Influencing factors and measures of water drive oilfield development effect

Oil field is a very important non-renewable resource in China, which plays a very important role in economic strategy. In the process of oil field development, water flooding technology can effectively improve the production quality, provide a strong technical support for our oil field exploitation, and help to promote the sustainable development of oil field enterprises. However, there are many influencing factors in the exploitation process of water flooding oilfield, so the workers need to deeply explore the root cause of the problem from different angles and all aspects, and take scientific and reasonable countermeasures to improve the exploitation effect of water flooding oilfield. This paper mainly introduces the factors affecting the development effect of water flooding oilfield and puts forward the corresponding solutions. At the same time, combined with practical cases, the measures to improve the development effect of water flooding oilfield are analyzed in detail.

An innovative computational algorithm for modelling technical readiness coefficient: A case study in automotive industry

Modelling technical availability is particularly important in systems characterised by randomness in the occurrence of tasks. The aim of the article was to develop an innovative solution using the Laplace transform and the R programming language in the form of an algorithm designed to determine a reliability measure, the technical readiness coefficient. First, the literature on the most important theorems and definitions concerning the theory of reliability was reviewed to develop assumptions and a mathematical model of the actual process of using means of transport. The subject of the research, along with the availability of actual numerical data used for calculations and analyses were presented. An algorithm based on the Laplace transform was proposed to evaluate the reliability of the system. Furthermore, the sensitivity analysis of the model was performed and the results were discussed to identify final conclusions and directions for future research. The results show that the exploitation process of the vehicle fleet studied was correctly organised and that the proposed algorithm eliminates the need to perform complex calculations using traditional methods and enables the visualisation of the achieved results. Additionally, the algorithm is universal and can be used to determine both the functional and numerical reliability characteristics of any technical object. Moreover, this solution is free of charge, and its implementation requires only the installation of the RStudio editor (version 1.4.1106).

Prototype of Instrumented Rock Bolt for Continuous Monitoring of Roof Fall Hazard in Deep Underground Mines

Roof falls are currently one of the most dangerous threats associated with underground mining at great depth. Every occurrence of such an event poses a significant risk to the mining crew and disturbs the continuity of the mining process, which clearly affects the economy of the exploitation process. The development of a reliable monitoring system may significantly reduce the impact of eventual roof failure and will have a positive effect on the sustainability of the extraction process. Within this research study, a prototype of an instrumented rock bolt developed for continuous stress measurement is presented. The procedure of a 4-groove multilevel instrumented rock bolt is described and the calibration process is shown. Then, preliminary results of long-term in situ monitoring are presented. Based on the continuous monitoring of stress distribution within immediate roof strata, it was concluded that the developed instrumented rock bolt provides reliable results and is a very useful device, ensuring the possibility of early warning for miners about increasing roof fall risk.

CYBERSECURITY STRATEGIES IN INDUSTRY 4.0

Cybersecurity is now the one of the highest important part of the Industry 4.0 and to all the design and manufacturing companies. This paper presents new cybersecurity strategies in Industry 4.0, where current vulnerabilities and exploitation processes, possible attack vectors, attack, compromise, and performance indicators should be considered. Also, cyber risk in product lifecycle management is a very important aspect. This revealed authentication issues, unsecured communications, default deployment issues, susceptibility to physical attacks. For example, a successful cyberattack could bring subtle changes to the control parameters of a robot or of a manufacturing process. This can further change the robot's operating mode in an almost undetectable way, but instead alters the efficiency and integrity of the final product. By monitoring these behaviours, cataloguing indicators, and inspecting potential risks, we can determine how an attacker gains access to the network and predict the intent they had. We need well-trained staff in any enterprise to drastically reduce the risk of cyberattacks. For this reason, appropriate measures must be taken to solve these problems, and one of these is cybersecurity education. It is necessary to implement appropriate policies and risk reduction plans in the product lifecycle management to prevent possible cyber-attacks.

A coupled DEM‐IMB‐LBM model for simulating methane hydrate exploitation involving particle dissolution

AbstractThe coupled discrete element and lattice Boltzmann method using an immersed moving boundary scheme was extended to simulate methane hydrate exploitation involving mass transport and particle dissolution. In this coupled DEM‐IMB‐LBM model, a new Dirichlet‐type thermal boundary condition is extended to simulate moving curved boundaries with constant concentration. A novel periodic boundary including an efficient searching algorithm for particle contact is proposed to reduce the computational cost and boundary effect. Then this model is validated by two numerical examples: a circular particle with concentration convection‐diffusion moving in a horizontal channel and mass transport from a cylinder particle in a simple shear flow. The numerical results obtained from the proposed model agree well with previous studies. To further demonstrate the capacity of the proposed model, simulations of methane hydrate exploitation including two formations in marine sediments are carried out. The numerical results indicate that the coupled DEM‐IMB‐LBM is not only capable of simulating the dissolution of hydrate particles at the grain level, but also recover the sand erosion and migration process in a fundamental perspective during the methane hydrate exploitation process.

Competition at the Bio-nano Interface: A Protein, a Polysaccharide, and a Fatty Acid Adsorb onto Magnetic Nanoparticles.

Magnetic nanoparticles are an attractive bioseparation tool due to their magnetic susceptibility and high adsorption capacity for different types of molecules. A major challenge for separation is to generate selectivity for a target molecule, or for a group of molecules in complex environments such as cell lysates. It is crucial to understand the factors that determine the targets' adsorption behavior in mixtures for triggering intended interactions and selectivity. Here we use a model system containing three molecules, each of them a common representative of the more abundant types of macromolecules in living systems: sodium oleate (SO), a fatty acid; bovine serum albumin (BSA), a protein; and dextran, a polysaccharide. Our results show that (a) the BSA adsorption capacity on the iron oxide material depends markedly on the pH, with the maximum capacity at the pI of the protein (0.39 g gMNP-1 ); (b) sodium oleate, a strongly negatively charged molecule, an organic anion, renders a maximum adsorption capacity of 0.40 g gMNP-1, even at pHs at which oleate as well as the nanoparticle surface are negatively charged; (c) the adsorbed masses of dextran, a neutral sugar, are lower than for the other two molecules, between 0.09 and 0.13 g gMNP-1, regardless of the system's pH. We observe an unexpected behavior in mixtures: SO completely prevents the adsorption of BSA, and dextran decreases the adsorption of the other competitors, SO and BSA, while adsorbing at the same capacities, unaffected by either the presence of the other two molecules or the pH. BSA does not decrease the oleate adsorption capacity. We demonstrate the essential role of pH in the adsorption of BSA (a protein) and SO (a fatty acid), as well as its impact in the structural organization of the oleate molecules in water. Moreover, we present exciting data on the adsorption of the molecules in competition, revealing the need to focus on interaction studies in more complex environments. This study attempts to open the scope of the current research of bio-nano interactions to not only proteins but also to mixtures, and generally to molecules with other physicochemical characteristics. Furthermore, we contribute to the understanding of multicomponent systems with the vision set in enhancing biomass exploitation and biofractionation processes.

TIN EXPLOITATION: AN ECOCRITICISM APPROACH IN ANDREA HIRATA’S RAINBOW TROOPS

This research was aimed at reflecting how Hirata reveals the tin exploitation in Belitung Island through his debut novel, Laskar Pelangi. It is significant and worthy research as it is an effort to raise awareness and understanding of human beings about the importance of nature and the environment, especially awareness for people who have the power to determine nature protection policies and the importance of nature conservation for the preservation of ecosystems for future generations. This research applied the theory of ecocriticism proposed by Gerrard supported by the theory offered by Gutti, Aji and Magaji. This research uses descriptive qualitative in which the data obtained from the novel are analyzed to reveal the process of tin exploitation in Belitung Island. The research results show that tin exploitation in Belitung Island is carried out both in traditional and modern ways. Traditional tools used to mine tin are phok, aichang, khaknai and kiaw to make water embankments and shovels to dig soil, while modern tools used to mine tin are machines in the forms of heavy equipment, such as dredgers and excavators. Traditional tin mining activities in Belitung which are carried out without a Mining Business Permit or Unlicensed Mining is also revealed in the novel.

Data clustering using leaders and followers optimization and differential evolution

Data clustering is an important research topic in data mining. Although cluster analysis based on optimization algorithms has attracted great attention, optimization-based techniques face difficulties due to the non-linear objective function and complicated search space. Leaders and followers optimization (LaF) introduced in the 2015 IEEE Congress on Evolutionary Computation, and differential evolution algorithm (DE) are two efficient evolutionary computation methods, and they own some special advantages. The key power of LaF is the exploration in multi-modal search spaces, but it has a poor performance in the exploitation. On the other hand, DE based on the DE/best/1 mutation operator significantly promotes the exploitation process. In this study, the strong properties of LaF and DE are combined to balance exploration and exploitation in the search space to discover the cluster centroids. Besides, the proposed clustering method, i.e., LaF-DE, does not need parameter settings, unlike the existing optimization-based partitional clustering methods. Hence, this study proposes a straightforward, parameter-free, and efficient novel hybrid algorithm for the optimization-based partitional data clustering problem. Many experiments on the functions from CEC2017 test suite show that LaF-DE has better optimization performance and higher stability than the state-of-the-art metaheuristic algorithms. LaF-DE has been compared with well-known clustering techniques on the UCI and Shape datasets. The experimental results and statistical tests indicate that LaF-DE outperforms the well-known partitional clustering methods on 8 of 12 datasets in terms of internal performance metrics. Besides, LaF-DE performs better than density peaks clustering on 9 of 12 datasets in terms of external performance metrics.

ERACE: Toward Facilitating Exploit Generation for Kernel Race Vulnerabilities

Since a large number of Linux kernel vulnerabilities are discovered every year, many vulnerabilities cannot be patched in time. Security vendors often prioritize patching high-risk vulnerabilities, and the ratings of vulnerabilities need to be evaluated based on factors such as exploitability and the scope of influence. However, evaluating exploitability is challenging and time-consuming, especially for race vulnerabilities, whose exploitation process is complicated and the success rate of exploitation is low, making them more likely to be overlooked. In this paper, we propose a new framework, called ERACE, to facilitate the process of exploiting kernel race vulnerabilities. Given a program called a proof of concept (PoC) that can trigger a race vulnerability, ERACE first applies a combination of dynamic and static analysis techniques to locate the instruction that causes the race. Then, it applies code instrumentation and static analysis to determine the timing relationship between the race instructions and the triggering type of the vulnerability and records the vulnerability context information. Next, it uses backward taint analysis to identify checkpoints that can be used to determine whether the race condition and heap spraying are satisfied and records the system calls to which the checkpoints belong. Finally, we can generate exploits based on the information collected above. To demonstrate the utility of ERACE, we tested it on 23 real-world vulnerabilities. As a result, we successfully detected the race points of 19 vulnerabilities, the timing relationship among the race instructions, and the triggering types of 17 vulnerabilities and succeeded in generating exploits for 13 vulnerabilities. ERACE can effectively help security researchers simplify the analysis process of kernel race vulnerabilities, select appropriate exploitation methods, and use checkpoints to increase the success rates of exploitations.

Collaborative Gold Mining Algorithm: An Optimization Algorithm Based on the Natural Gold Mining Process

In optimization algorithms, there are some challenges, including lack of optimal solution, slow convergence, lack of scalability, partial search space, and high computational demand. Inspired by the process of gold exploration and exploitation, we propose a new meta-heuristic and stochastic optimization algorithm called collaborative gold mining (CGM). The proposed algorithm has several iterations; in each of these, the center of mass of points with the highest amount of gold is calculated for each miner (agent), with this process continuing until the point with the highest amount of gold or when the optimal solution is found. In an n-dimensional geographic space, the CGM algorithm can locate the best position with the highest amount of gold in the entire search space by collaborating with several gold miners. The proposed CGM algorithm was applied to solve several continuous mathematical functions and several practical problems, namely, the optimal placement of resources, the traveling salesman problem, and bag-of-tasks scheduling. In order to evaluate its efficiency, the CGM results were compared with the outputs of some famous optimization algorithms, such as the genetic algorithm, simulated annealing, particle swarm optimization, and invasive weed optimization. In addition to determining the optimal solutions for all the evaluated problems, the experimental results show that the CGM mechanism has an acceptable performance in terms of optimal solution, convergence, scalability, search space, and computational demand for solving continuous and discrete problems.

Fuzzy Clustering Algorithm Based on Improved Global Best-Guided Artificial Bee Colony with New Search Probability Model for Image Segmentation.

Clustering using fuzzy C-means (FCM) is a soft segmentation method that has been extensively investigated and successfully implemented in image segmentation. FCM is useful in various aspects, such as the segmentation of grayscale images. However, FCM has some limitations in terms of its selection of the initial cluster center. It can be easily trapped into local optima and is sensitive to noise, which is considered the most challenging issue in the FCM clustering algorithm. This paper proposes an approach to solve FCM problems in two phases. Firstly, to improve the balance between the exploration and exploitation of improved global best-guided artificial bee colony algorithm (IABC). This is achieved using a new search probability model called PIABC that improves the exploration process by choosing the best source of food which directly affects the exploitation process in IABC. Secondly, the fuzzy clustering algorithm based on PIABC, abbreviated as PIABC-FCM, uses the balancing of PIABC to avoid getting stuck into local optima while searching for the best solution having a set of cluster center locations of FCM. The proposed method was evaluated using grayscale images. The performance of the proposed approach shows promising outcomes when compared with other related works.

Real-Time Experimental Monitoring for Water Absorption Evolution Behaviors of Sandstone in Mogao Grottoes, China

Rock mass has typical pore structure, and the induced coupling effects of fluid and solid matrix appear in the disaster evolution process of deep energy exploitation and overground rock hydration. As a representative case, influenced by the water absorption environment, the surrounding rock and murals of Mogao Grottoes produce hydration diseases, which may be related to unclear interaction mechanisms between the surrounding rock and water. In this study, the self-developed physical experimental system for real-time experimental monitoring was applied to test the water absorption evolution behaviors of sandstone. The experimental results showed that the water evaporation of the rock sample during the process of water absorption could be measured through this well-designed physical experimental system, and the actual water absorption of the rock sample is the difference between the decrease of water in the water storage bucket, measured by the balance and the water evaporation in the process of experiment; by drawing the actual water absorption curve of the rock sample, the time when the water absorption of the rock sample reaches saturation could be determined accurately; and the curve of water absorption with time could be expressed as an exponential function. The experimental techniques and methods in this study provide a feasible research idea for studying the water absorption evolution behaviors and mechanisms of the surrounding rock weathering when it meets water, and have significance for revealing the disease mechanisms of the surrounding sandstone in Mogao Grottoes, China.

Research on Gas Channeling Identification Method for Gas Injection Development in High-Pressure Heterogeneous Reservoir

In a typical ultra-deep high-temperature and high-pressure heterogeneous reservoir in Xinjiang, gas channeling quickly occurs during gas injection because of the heterogeneity of the reservoir, the low viscosity of gas injection, and the high gas-oil fluidity ratio. The identification and prediction methods of gas channeling in gas injection development were studied. First, gas channeling discrimination parameters were determined by the numerical simulation method. According to the ratio of gas to oil produced and the composition of oil and gas produced, the flow stages of formation fluid were divided into five regions: gas phase zone, two-phase zone, miscible zone, dissolved gas and oil zone, and original oil zone. The basis for gas channeling identification (namely, the field characterization parameters for gas channeling discrimination) was discovered through analysis and the knowledge of the operability of field monitoring data as the following two parameters: (1) the C1 content rising again on the previous platform when the trailing edge of the two-phase zone is produced and (2) the continuous rise of the gas-oil ratio in production. Then, considering the original high-pressure characteristics of the reservoir, the field characterization parameters of gas channeling under different formation pressures in the exploitation process (namely, C1 content and gas-oil ratio) were simulated and determined. Thus, a gas channeling discrimination method was established for gas injection development in ultra-deep high-temperature and high-pressure heterogeneous reservoirs. According to this gas injection approach, a gas channeling discrimination method was developed, and the field gas channeling judgment was carried out for a gas injection effective D1 well. The results of gas tracer detection were compared to verify the accuracy of this method, leading to strong support for this method in slowing down the gas channeling.

Moth Search: Variants, Hybrids, and Applications

Moth search (MS) is a nature-inspired metaheuristic optimization algorithm based on the most representative characteristics of moths, Lévy flights and phototaxis. Phototaxis signifies a movement which organism towards or away from a source of light, which is the representative features for moths. The best moth individual is seen as the light source in Moth search. The moths that have a smaller distance from the best one will fly around the best individual by Lévy flights. For reasons of phototaxis, the moths, far from the fittest one, will fly towards the best one with a big step. These two features, Lévy flights and phototaxis, correspond to the processes of exploitation and exploration for metaheuristic optimization. The superiority of the moth search has been demonstrated in many benchmark problems and various application areas. A comprehensive survey of the moth search was conducted in this paper, which included the three sections: statistical research studies about moth search, different variants of moth search, and engineering optimization/applications. The future insights and development direction in the area of moth search are also discussed.