The ever-increasing impact of ICT on the socio-economic development of the European Union Member States and the growth in their use mean that the products and services offered are now increasingly dependent on ensuring cybersecurity. The extensive architecture of ICT systems, including operations on large data resources, serve the development of communication, trade, transport and constitute the basis for the functioning of key, digital services and services provided by public administration. Unfortunately, the possibilities offered by modern digital technologies are also used to apply unfair competition practices, interrupt the continuity of selected services, commit crimes using the Internet, or conduct cyberterrorist activities. Based on the analysis of the issue, the following research theses will be verified. Firstly, the evolution of policy is a reaction to the increase in instability and threats in this area and the lack of appropriate mechanisms and regulations in this area. Determining the definitional discrepancies of the concept of "incident" will allow us to determine how it affects the digitalization policy. It will also show that the reason for the creation of this policy was the lack of regulations in this area and the existence of appropriate mechanisms in this area. Therefore, we are dealing with both the process of institutionalization and transformation. However, the NIS 2 Directive constitutes lex generaliin relation to other legal acts, because each legal act adopted subsequently is a particularisation of it, i.e. it constitutes lex speclis.
Existing statistical and Artificial Intelligence (AI) models for the path-loss studies in GSM communication systems are quite large and it becomes a problem identifying suitable ones for solving the PLMP. In this research, an alternative purely mathematical and very simple approach to solving the PLMP based on three Rao-type algorithms is proposed. The approach is applied to modeling a case study dataset with the integration of Cost-232 Hata model in an error-loss minimization objective. The results agree with those reported in similar studies and using available case data. The results further show that Rao-1 and Rao-2 techniques have better fitness error response than the Rao-1 and should be considered for future path-loss problems
Cosmetic products are gaining attention due to the difficulty in identifying the toxicity status of animal-based ingredients commonly used in the market. Medicinal plants offer a natural and viable alternative for cosmetic formulations. Pereskia bleo (Kunt) DC, known locally in Malaysia as “Pokok Jarum Tujuh Bilah” is a medicinal plant from the Cactaceae family, traditionally used for treating various ailments because of its high antioxidant, anti-inflammatory, and antimicrobial properties. Despite its known medicinal uses, its potential as a cosmeceutical ingredient has not been widely studied. A non-conventional microwave-assisted extraction (MAE) method was used to prepare P. bleo leaf extract. The extract demonstrated significant cosmeceutical properties, showing 80.14% anti-collagenase, 74.04% anti-tyrosinase, and 48.03% anti-elastase inhibition activities. It also exhibited a sun protection factor (SPF) value of 23.74, indicating strong potential for use in functional cosmetics. The proximate composition of the leaves was analyzed, consisting of 20.26% crude protein, 3.55% crude fat, 11.13% crude fiber, 16.5% ash, 9.36% moisture, and 39.2% carbohydrates. Toxicity evaluations, including heavy metal analysis via ICP-MS and a brine shrimp lethality bioassay, showed that concentrations of arsenic, cadmium, chromium, lead, and mercury were all below the specific release limits set by FAO, WHO, and EFSA. No lethal concentration of minerals or heavy metals was detected, and the extract exhibited no cytotoxicity. These findings suggest that P. bleo leaves are safe and have excellent potential as a plant-based ingredient in cosmetic products due to their beneficial properties and safety profile
The paper presents research on modeling of an electrohydraulic servo system with friction load by using experimental data. According to the step command input signal on the system and the velocity output of the cylinder piston, the order and the delay time of the servo system model were determined. And then the discretetime linear models with and without friction load were identified by means of the Least Squares (LS) method. Finally, the validation of the constructed model was performed and results shown the proposed models to be excellent.
Fluvial ecosystems, a colorful platform of the interactions between human being and environment. The hydrologists and the geomorphologists summarize the idea of relevant factors of regional context, which including watershed hydrology, watershed geomorphology, water quality, stream and riparian ecology and stream/river hydraulics, such as water depth, width of channel, flow velocity, bed material and slope of stream/river, to transport nutrient and thermal regimes changing temporally and spatial, make the ecosystem alive. And they are obviously important of watershed management on decision support for the necessities to manage water resources in environments, fluvial ecosystem diversity, explaining watershed processes and the effects of disturbances across different regions including the human behaviors. Turbulence as a scalar quantity is a useful descriptor of turbulence in complex 3D flows characterized by non-zero vorticity. There is no general rule on when, why and which hydraulic model should be applied for eco-hydraulic studies but fundamentally the accurate topographical survey at the resolution of the scale of the processes investigated is more essential. All of them own uncertainties. Understanding the fundamental associations and relationships between hydraulic forces and floral and faunal communities, species, and their habitats, modelling them and using this information to provide management recommendations continues to be important and challenging goals for river scientists, managers, and other end users. In this paper, the characteristics of fluvial ecosystem with its variable factors will be illustrated and then the functions of fluvial ecosystem are following. Finally, the impact mechanisms resulting uncertainties on the platform are emphasized with their conceptual solving strategies.
The H.265 video coding standard promotes the realization of 4K/8K ultrahigh definition (UHD) video applications.To further improve the coding efficiency, H.265 allows motion estimation (ME) performing on multiple reference frame (MRF). Although the MRF can enhance the performance and allow the encoder to search a better reference frame from several previous pictures, the computational complexity of the MRF-based ME (MRF-ME) module dramatically increases. Toimprove the coding performance of H.265 according to the high spatiotemporal correlation existing in the MRF, we firstly proposeneighboring-block-based reference frame decision algorithm(NRFDA) and priority-based reference frame selection algorithm(PRFSA) to reduce the computational complexity of ME-MRF module. The NRFDA utilizes the selected reference frames information among encoded neighboring blocksand the variance of the current block to predict the best reference frame. Therefore, PRFSA define the priority for each reference frame so that ME can perform on the reference frames along the descending order of priority according to the rate distortion cost (RDcost)rank.Finally, we integrate NRFDA and PRFSA into a fast reference frame decision algorithm (FRFDA) to further speed up the ME-MRF module. Simulationresults show that the proposed FRFDA can achieve an average time improving ratio (TIR) about 68.23% when compared to H.265 (HM16.7) under MRF=4. It is clear that the proposed algorithm can efficiently increase the encoding speed of H.265 with insignificant loss of image quality
Poverty detection remains a critical challenge in socio-economic development, necessitating innovative, scalable, and efficient methodologies for accurate assessment and intervention. Traditional poverty assessment techniques, such as household surveys and economic censuses, suffer from limited scalability, delayed updates, and inherent biases, reducing their effectiveness in dynamic socio-economic landscapes. Advances in Machine Learning (ML) and big data analytics offer promising alternatives by integrating multimodal data sources, including geospatial information, mobile network metadata, financial indicators, and social media analytics. However, existing ML-based poverty detection models face challenges in real-time adaptability, bias mitigation, computational efficiency, and scalability. This study introduces the Multidimensional Data-Driven Approach (MDDA), an optimized ML framework that integrates multimodal data fusion, fairness-aware ML techniques, and hyperparameter optimization to improve poverty classification accuracy. The MDDA methodology follows five key phases: synthetic data generation and preprocessing, feature engineering and selection, ML model development, bias mitigation, and performance evaluation. The approach is tested on a synthetic dataset of 100,000 records, simulating socio-economic indicators across diverse geographic and economic contexts. Performance evaluation metrics include classification accuracy, fairness measures (Demographic Parity, Equalized Odds), computational efficiency, and real-time adaptability. Experimental results confirm that MDDA achieves a classification accuracy of 91.2%, reduces bias by 15-20%, and improves computational efficiency by 30% compared to baseline ML models. Additionally, MDDA is compared against established ML approaches such as CRISP-DM, SCRUB, KDD, TDSP, SEMMA, and KID, demonstrating superior performance in real-time adaptability, bias mitigation, multimodal data integration, and scalability. These findings highlight MDDA as a real-time, unbiased, and scalable solution for poverty detection, with direct implications for policymaking, economic planning, and humanitarian aid distribution. The study underscores the transformative potential of AI-driven poverty classification, bridging the gap between fairness, efficiency, and real-time adaptability in socio-economic analysis
The problem of existing modern path loss minimization AI models borders on the aspect of needless complexity and unwarranted use of metaphors. This research proposes an alternative strategy that is purely mathematical based and very simple to apply. The strategy employs the Rao-type optimizer (RaoO) and the Sine Cosine Optimizer (SCO) proposed. The approach is applied to modeling a case study dataset with the integration of Cost-232 Hata model in an error-loss minimization objective. The results agree with those reported in similar studies and using available case data. The results further show that the SCO approach gives better fit with lower path loss when compared to the RaoO.
Soil is an important basic natural resource in human production and life. Studying the micro-structure of soil, understanding various types of soil and grasping its specific data are of great guiding significance and reference value for the growth and development of plants and crops. Therefore, the systematic classification of soil is particularly important. There is no study on Soil Taxonomy in Renhe District of Panzhihua City, so this study will make up for this gap.The soil samples of 8 towns and townships in Renhe District of Panzhihua City were collected and analyzed. The main nutrient components were soil water content, soil ammonium nitrogen, soil available phosphorus, soil effective potassium, soil organic matter and soil pH value. The characteristics of soil were obtained through data analysis, and the soil types in the study area were also analyzed. Types were named and classified. Complete the task of land resources survey in Renhe District, clarify the types and distribution of soil in Renhe District, and enrich the content of soil science. The nutrient contents of various soils were analyzed by laboratory tests, which provided scientific basis for soil classification.Through the analysis of experimental data, it is found that the soil water content in Renhe District is low, the soil is weak alkaline, the content of organic matter is generally high, the content of ammonium nitrogen is low, the content of available phosphorus is generally high, and the content of effective potassium is relatively low
The advancement of Internet of Things (IoT) technology offers significant potential for improving safety and efficiency in various industrial applications. This project presents the development and implementation of an automated blasting system designed for the mining industry, utilizing IoT technology to remotely trigger the blasting process. The system integrates several key components: Node MCU for wireless communication, Relay Module for high-voltage control, a 12V Battery for power supply, and Arduino for managing the electronic detonator. The primary objective was to create a reliable and efficient remote blasting system that minimizes human intervention and enhances operational safety. Through rigorous testing, the system demonstrated a high success rate of 98% in successfully initiating detonations with an average response time of 1.2 seconds. The IoT-based approach allows for remote operation up to 200 meters, significantly reducing the risks associated with manual triggering. The results indicate that the automated system not only improves precision and safety but also offers substantial operational flexibility. This project underscores the potential of IoT in transforming traditional industrial processes and sets the stage for future advancements in automated systems for hazardous environments
The current monetary models are mainly based on gold, petroleum, food, mine, government credit and so on. In the last hundreds of years, a lot of legal tenders have faced depreciation and worthless. In addition, when the value of money is bound to foreign objects, money will overuse the greedy, jealous, angry, and other parts of human nature.As humanity's understanding of genes deepens, the context of human beings becoming the hegemon of the earth is gradually becoming clear, and also the genes bounded features. Therefore, the author tries to build a simple monetary model based on human gene mine, or in other words, human gene monetization
The comparative studies of the physicochemical and functional properties of black, brown and white (local and improved varieties) of sesame seeds grown in Nigeria were carried out. The Physicochemical and functional properties were determined using standard analytical methods of AOAC. The results indicated that the physicochemical and functional properties varied with colors of the seeds. The physical analysis for the appearance of 1000 seed weight, seed volume and true density for black, brown and white ranged from 0.92- 2.91, 3.13-10.56 and 0.22-0.31 respectively. The values for proximate analysis ranged from 2.82-4.5%, 19.67- 28.42%, 8.23-31.12% 87-48.02%, 7.32-20.42 %, 3.43-5.37% for moisture, protein, fibre, fat, ash and carbohydrate contents respectively. The mineral analysis of the samples revealed that the potassium was dominant among the macro minerals while Manganese was the highest among the micro minerals in the samples. The phytochemicals analysis showed that oxalates, phytates, tannins, phenols and flavonoids had values ranging from 0.43- 0.96 mg/100g, 0.11-0.27 mg/100g, 7.8- 9.07 mg/100g, 1.10-1.69 mg/100g and 2.01- 2.45 mg/100g respectively. The functional properties had values ranging from 0.47-0.93 g/ml, 1.2-1.67 g/ml, 0.83-1.56 g/ml, 49.00-50.00 % and 4.00-12.00 % for bulk density, water absorption capacities, oil absorption capacities, emulsion capacity, foam capacity and foam stability respectively. The study conclude that sesame seeds have diverse nutrient contents which is greatly dependent on the colour of the seeds and an understanding of this fact would help in the design of appropriate formulation strategies for the resulting products
Mineral reserve evaluation is an extremely important stage mineral exploration and exploitation as it directly affects the economy of the mineral reserve. The Nigerian mining and quarrying sector is under performing, as a result, the benefits (such as rapid industrialization, technological innovation, raw material provision for the manufacturing industry etc.) associated with a well performing mining sector is denied the Nigerian populace. The major cause of this under performance by the sector has been attributed to lack of local and foreign investment in the mining sector, and one of the chief causes of this lack of investment is the absence of mineral reserve reports that meet international specifications, that clearly shows the profitability or non-profitability of mineral reserves in Nigeria. This researchprovides a mineral (coal) reserve report, using geological models and sequential Gaussian co-simulation of isometric log-ratio (ilr) transformed compositions, of coal proximate analysis results from the Onupi coal field. Compositional data analysis and geostatistical studies reveals significant spatial correlation among the ilr balances as indicated by the cross-semi-variograms.Geostatistical resource estimation results using simple co-kriging and co-simulation in SGeMs and Surpac computer programmes gave an estimated coal resource of 2,147,270 cm3 in volume and a tonnage of 2,791,451 Mt. From resource classification, approximately 2,708, 250 Mt is classed as measured and indicated reserve, while 83,200 Mt is classified as inferred. Application of the simulated maps to the study area, delineates the coal boundary, and shows that high quality coals are found at the north-eastern and southern parts of the deposit, while low grade coals are concentered at the central part of the deposit.
The purpose of this report was to compare the numerical analysis for different cooling efficiency of a cable tunnel system when installing one additional cable trough or three cable troughs for cable circuit 100% or 70% heat load. Cable tunnel system is widely known for it is use for high voltage transmission in an underground. Due to the cables generating large quantities of heat, water pipes and air ventilation were used in the tunnel to cool down the transmission cable. To investigate the cooling efficiency of a tunnel, research for benchmark case was carried out. A Computational Fluid Dynamic (CFD) benchmark analysis about 2D natural convection inside the square cavity was investigated to further understand the air movement inside the square medium. Ansys Fluent was carried out for benchmark cases of heat transfer natural convection inside the square cavity and to check whether Ansys Fluent can be used for any CFD and heat transfer purposes by validating the results with previous studies. The benchmark case used a 2D square with different active temperature side walls and adiabatic walls for top and bottom side. From the benchmark simulations with different Rayleigh Number, a number representing buoyancy-driven of a fluid from 103 to 105 affected air differently and the heat transfer natural convection inside the square. At different Rayleigh Number air forms a recirculation passing the active walls and adiabatic walls. After investigated the benchmark, the results were used to validate with previous studies. To validate the results was by using Nusselt Number, ratio of convective to conductive. The benchmark case results were validated and Ansys Fluent proven can be used for CFD and heat transfer purposes. Two 3D cable tunnel were modelled with 100-meter length after concluded the benchmark. The two tunnel models were based on the number of cable troughs installed. The first tunnel was with one cable trough and two cable circuits on the bottom, as for the second tunnel was with one bottom cable circuit and three cable troughs. Cable tunnel simulations were based on cable circuit for 100% heat load and 70% heat load with each heat load case was given different water flow rate of 4.25 L/s and 6.5 L/s. A total of eight scenario cases were carried out to determine which provided a better cooling efficiency choice. The analysis for cable tunnel cases on how the copper cables cooled down through heat transfer of natural convection inside the cable trough, which the heat then was removed from the cable circuit by air and continue to the outside of the tunnel. During the heat transfer processes, conductivity was present as not all heat were removed by air and water, but continue to through the walls of the tunnel and to the ground soil. Based on the simulations, a cable tunnel with three cable troughs was proven more cooling efficiency compared tunnel with one cable trough. Some scenarios did not meet the criteria, due to insufficient heat relocation by air and water. The cooling efficiency was determined by which has the better balance heat relocation by air, water, and ground, also considering the comfort and safety of human inside the tunnel.
In this article, we tried to examine the energy of an object under different physical conditions. We demonstrated that the outcome is different from what physicists has so far believed. Basically, we showed that the net energy of an object in this universe is fixed and is not affected by the environment.
Ultra-wideband (UWB) technology is considered as a promising technique towards different applications of clinical infrastructure, delivers noteworthy features such as fine localization accuracy, very high data rates and low energy consumption. The paper systematically reviews the use of UWB technology in clinical environments: in healthcare monitoring, medical imaging, indoor positioning and wireless communication. Based on a set of high-quality data from UCI Machine Learning Repository, this paper gives empirical results involving the performance and capability of UWB-based systems in bettering healthcare outcomes. They additionally detail response and potential barriers, including integration challenges and regulatory constraints, as well as assets like the symbiosis of UWB technology to trigger future developments in patient care and healthcare disbursal. In addition, the authors combined feature selection and random forest model to obtain an accuracy of 91.8%.
The project "Collaboard" represents an innovative take on interactive whiteboards, designed primarily for collaborative use in web environments. Catering to a diverse audience, including students, educators, and professionals, the application mimics functionalities of popular tools like MS Paint, but with advanced features for teamwork. Users can adjust the canvas background, customize pen color and size, and utilize an eraser with adjustable thickness. By enabling simultaneous participation, the project aims to bridge traditional brainstorming methods with modern digital needs, fostering seamless real-time collaboration. I have named this whiteboard extend as "Collaboard" as it is a Whiteboard which is Collaborative implies numerous clients can all together talk about on a few thoughts or fair play around. The web application has different highlights like the client can "Alter the Foundation Colour of the Canvas or we can say the Whiteboard". Separated from this the client can moreover alter the "Colour of the Write or we can say Pointer that makes a difference to draw things on canvas". Most imperatively, the client can too alter the Pointer Estimate from more slender one to the thickest one and too Eraser instrument can be utilized to clear the canvas and that is too accessible in different.This investigate report dives into the advancement, mechanical establishment, and broad-spectrum applications of intelligently whiteboards (IWBs). It points to shed light on how these gadgets have changed instructive and corporate situations through interactivity, collaboration, and interactive media integration. The report too looks at the obstructions to broad selection, such as fetched suggestions, specialized challenges, and the require for proficient development
With the rapid development of intelligent construction technology, it has become a crucial task for higher education to cultivate professional talents who can meet the needs of the industry. The construction of a "dualqualified" intelligent construction teaching team plays a key role in improving the quality of talent training. This article analyzes the characteristics of the intelligent construction specialty and the necessity of building a "dualqualified" teaching team, discusses the current problems, including the single source of teachers, insufficient practical ability, and imperfect team collaboration mechanism, and proposes construction paths from optimizing the teacher recruitment and training system, strengthening school-enterprise cooperation, and improving team management and incentive mechanisms, aiming to provide theoretical reference and practical guidance for building a high-quality "dual-qualified" intelligent construction teaching team.
This research paper presents an innovative IoT-based home automation system aimed at enhancing the security, energy efficiency, and convenience of residential areas. By leveraging wireless technologies such as Wi-Fi and Bluetooth, the system enables users to remotely monitor and control various home appliances through a userfriendly mobile application. The study addresses critical challenges, including privacy vulnerabilities and data security risks associated with IoT devices. Additionally, it explores the system's potential to assist individuals with disabilities, promoting accessibility and independence. The findings underscore the transformative impact of IoT on modern living, paving the way for smarter, more efficient homes that cater to diverse user needs.
