Search

The paper obtained during the study was mainly obtained from wheat straw cellulose and Jerusalem artichoke cellulose, which contained chitosan of various concentrations. An increase in the mechanical properties of the obtained papers was observed in samples using the substance chitosan. A 1.0% chitosan was added to the paper, mainly based on various plant celluloses. It should be noted that the obtained paper products were used without bleaching due to the fact that it was recommended to use them for wrapping paper. The youngest results were observed in samples prepared from a composition of wheat straw and artichoke pulp. From the fiber morphology, it was observed that the sized paper fibers became stronger, denser and smoother. Keywords: chytazone, Natural polymers, fibers, cellulose. Biocomposites of chitosan (CS)/cellulose nanocrystals (CN) were prepared by using solution casting method. Influences of solution preparation method and CN content on the properties of composites were investigated. Mechanical stirring/ultrasonication or micro fluidization were used to disperse nanocrystals in the chitosan matrix. The prepared nanocomposites were characterized by FTIR, XRD, SEM, DSC, TGA, TMA and contact angle measurements.

The filter paper bio-templating method has become a promising pathway in the fabrication of MgO with tunned physicochemical features. The filter paper-templated MgO (MgO-FPT) has been subjected to several characterisation analyses, and it has revealed that filter paper templating has demonstrated a positive outcome toward an improvement of physicochemical features, i.e., improved surface reactivity and surface area compared to MgO prepared via direct thermal degradation method of magnesium salt (MgO-CT). As the evidence of the FTIR spectra, the MgO-FPT has demonstrated a surface rich CO2-associated functional group, which indicate the enhanced surface reactivity of the MgO, which increase of the adsorbent affinity toward CO2 (even from atmospheric surrounding). Together with the improved structural features compared to MgO-CT (two-fold high surface area), it has significantly refined the CO2 adsorption uptake capacity to almost 15 times higher than MgO-CT with only 0.247 mmol/g. This shows the potential filter paper bio-templating method for the metal oxide-based adsorbent fabrication for CO2 adsorption application.

A chitosan based coating was prepared where eggshell powder was added. Eggshell is a product that appears in large numbers in everyday life, so it has great potential as waste, which can be used to turn it into a valuable material. Cellulose sheets were made from secondary fiber, and after coated with the chitosan based solution to investigate the properties of the sheets. The results of the treated handsheets were compared with the results of the control sheet. The control sheets were compared with 4 different type of paper: coatings of chitosan with 5wt% and 10wt% eggshell powder, only chitosan coating, and paper where eggshell powder was added to the paper pulp. The use of the eggshell powder as an additive in the coating would be a promising material, because it can improve in a large extent the water resistance and the air barrier properties of the paper.

The Paper industry is an energy-intensive and one of the most energy-consuming industries in Indonesia. In this study, Paper Mill energy sources come from coal and renewable energy such as black liquor as a substitute for coal and on-grid 9MW PV system are reassessed by using optimization software, HOMER. This study aims to present a feasibility study of increasing the use of renewable energy sources in Paper Mill to reduce coal consumption for more sustainability. The software HOMER is used as a tool to determine the most feasible combination of component considered in the study. It is feasible to reduce 10,84% coal consumption kg per year with the optimal renewable energy mix consisting of additional 24MW rooftop PV system and 5,94kW hydrokinetic energy from Kampar River located 6 km from the plant. Renewable fraction increased to 16%. This study result is good for sustainable growth of Paper Mill business that investments in climate and nature to support the Indonesian government in achieving net zero emissions.

In this study, cellulose was extracted from Heliánthus tuberósus (Jerusalem artichoke) stems, and its quality indicators were thoroughly investigated. The isolation process involved the removal of impurities and non-cellulosic components, resulting in a purified cellulose sample suitable for further analysis and application.To explore the potential of Heliánthus tuberósus cellulose, composite paper was produced by incorporating basalt fiber into the cellulose matrix. The resulting paper was subjected to comprehensive testing to evaluate its mechanical properties, with a particular focus on tensile strength and tensile length.The tensile strength of the composite paper was determined using standardized testing methods, providing quantitative data on the material's ability to withstand applied forces without breaking or deforming. Tensile length, on the other hand, refers to the maximum elongation the paper can undergo before rupture occurs. These properties were assessed to gauge the overall performance and suitability of the composite paper for various applications.The obtained results were presented in a clear and concise manner, utilizing tables and graphs to facilitate data interpretation and comparison. Tables allowed for the tabulation of the measured tensile strength and tensile length values, providing a comprehensive overview of the material's mechanical characteristics. Graphs were employed to visualize trends, patterns, and potential correlations between different variables, aiding in a deeper understanding of the composite paper's behavior under various loading conditions.

Abstract. In this study, a composite material was successfully produced by incorporating waste paper and basalt fibers. The utilization of waste paper as a raw material contributes to sustainable practices and waste reduction. The physical and mechanical properties of the obtained composite material were comprehensively investigated to evaluate its potential for various applications.The physical parameters of the composite material, such as density and porosity, were measured to assess its structural characteristics. Density provides insights into the compactness and mass per unit volume of the composite, while porosity indicates the presence of voids or open spaces within the material. These parameters play a crucial role in determining the overall performance and suitability of the composite for specific applications.Furthermore, the mechanical properties of the composite material were examined to evaluate its strength, stiffness, and durability. Tensile strength, flexural strength, and impact resistance were among the key mechanical parameters studied. Tensile strength determines the material's ability to withstand pulling forces, while flexural strength measures its resistance to bending or deformation. Impact resistance evaluates the material's ability to absorb energy when subjected to sudden or dynamic loads.

This review paper presents a comprehensive analysis of the mitochondrial DNA (mtDNA) of Apis mellifera, commonly referred to as the Western honey bee. The present study aims to examine the genetic diversity, population structure, and evolutionary history of a species of insect that holds economic significance. This study elucidates the genetic determinants that impact the adaptive capacity, behavioral patterns, and overall well-being of honey bees through the examination of mitochondrial DNA (mtDNA) sequences derived from diverse honey bee populations across the globe. Furthermore, this study examines the potential implications of mitochondrial DNA (mtDNA) research on various aspects of beekeeping practices, conservation initiatives, and the comprehension of honey bee biology. This paper serves as a significant asset for researchers, beekeepers, and conservationists with a keen interest in exploring the genetic characteristics of Apis mellifera

A worldwide evaluation of the present status of renewable-energy generation, with a focus on photo-voltaic (PV) solar energy for the production of electricity. The most pertinent elements of the development and experiences of nations working to build and use these technologies are covered in this article. It also cites studies that highlight the efforts made by nations to reduce their emissions of green-house gas or to enhance the quality and accessibility of electric energy generation in light of their unique geographic and environmental circumstances. These studies focus in particular on remote communities that have limited access to the national power grid due to technological or financial constraints. This paper focusses on renewable-energy might serve as a starting point for assessing how clean energy affects the world's energy supply and demand, they are becoming an increasingly popular option in terms of cost and efficiency, which can attract new investors. By analysing recent data, case studies, and literature, this review aims to provide stakeholders with insights into the achievements and hurdles of solar energy, fostering informed decisions towards a sustainable and resilient energy future.

Inulin is a source of fiber that can be used as a functional food. Foods that contain inulin can help overcome health problems such as obesity, colon cancer risk, lower blood sugar levels and reduce insulin resistance. The purpose of this paper is to summarize some research results on inulin content in tubers and their extraction methods. The inulin content in dahlia, gembili, uwi, potato, sweet potato, jicama, onion and garlic tubers are 74%; 15%; 12%; 7%; 13%; 41% and 33%, respectively. Extraction methods used include ethanol:water precipitation, microwave-assisted extraction, hot water extraction and ultrasound. In the future, inulin is expected to contribute to the treatment of digestive-related diseases.

The integration of solarcellsinto construction materials, such roof tiles, isgaining traction. Nevertheless, solarcells' conversion efficiencyistemperature-dependent, and a high temperaturewouldlowerit. This study examines the functionality of mortar roof tilesthat have builtinsolarcells and safety glass. To control the temperature of the solar cells, phase modifying materials (P CM) are added to the first roof tiles at a concentration of 3% by weight.For solar roof tiles, the impact ofPhase change materials on the generation of solar-to-electrical power isassessed, and life cycle costanalysisiscarried out to determine the viabilityfrom an economicstandpoint.During six summerdays, the electricalenergy production of the solartileswith PCM appliedwas 4.1% higherthanthat of the tileswithout the component modification material. In contrast, during six winterdays, the improvementisbetween 2.2 and 4.3%. With the cost of the inverterincluded, the solar roof tileswith Phase change materials have an economicalpaybackperiod of 5.7 years. The application of Phase change materialsraises the initial cost of roof tiles by 1.2% ;nevertheless, the paybackperiodispredicted to bethreemonths shorter thanthat of the equivalentwithout PCM, given an overallimprovement in energy production of 4.1%.Whilemany countries are takingsteps to reducetheiremissions, the IEA’slatest report on global and carbonemissionsshowed an increase of 1.7 percent in emissionsyear-onyear2018 to 33.1 billion tons (IEA, 2019). Australia's 2018 increase in carbondioxideequivalentemissions of 0.7% raisesseriousconcerns about the countrysability to meetitsemissionreductioncommitmentunder the Paris Agreement (Cox, 2019).

Copyright of Revue Française de Géotechnique is the property of EDP Sciences and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Revue Française de Géotechnique is the property of EDP Sciences and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The production of alternative fuels is a promising direction in the development of energy. Nowadays, in science the technology of heat treatment of various materials, including household solid waste is used. In order to obtain an alternative type of fuel from waste, the technology of heat treatment of raw materials without access to oxygen – thermolysis is used. Under the influence of low temperatures (400–500ºС) and without access to oxygen, the material decomposes into several components: water, gas, fuel oil and dark heating oil. To ensure the correct operation of such a line, it is required to supply finely divided raw materials to form the required plug in the loading zone from raw materials. Moreover, raw material should not be homogeneous. It is known that a mixture of rubber and paper gives cleaner results during heat treatment. To ensure proper operation and obtain the desired mixed raw materials, a rotary centrifugal unit with a complex dynamic effect on the material was developed. Calculations and studies showed that such a grinder design is capable of qualitatively grinding raw materials and mixing it in the right proportions. Small dimensions and a design solution in the form of a single rotor with several mechanisms of action on the material allow reducing energy consumption for grinding. The practical value of the paper is in the creation of an improved design of a rotary centrifugal unit on the basis of theoretical and experimental studies. It increases the productivity and quality of the resulting mixture. The results of the study can be used in the industry of waste processing plants.

This paper poses the problem of fuel energy and ecology in Russia. The paper discusses in detail the operation of biogas production plants. Advantages and disadvantages of such production, material costs, and raw material costs are presented. The statistics of biofuel production in the countries of the world is visualised. The paper compares different types of propulsion systems using different fuels, identifies the advantages and disadvantages, and examines the operation of one of the largest biogas plants in the world.

The paper deals with the determination and study of the drying rate. The authors believe that it is necessary to present the curves for changing the mass of the product and time, to take into account the possible ranges of changes in the parameters of the coolant. In addition, the paper discusses the actual speeds of airflow around the product, the required drying modes will become known owing to the knowledge of the features of the drying process. In this regard, the authors of the paper consider the volumetric and hydrodynamic characteristics of the product layer. The purpose of the study was to determine the area of the free section in the layer of products, the speed of air movement, the pressure loss in the layer. The results of computational and experimental studies have shown the possibility of determining the true speed of drying of various products.

Opportunity of access to higher education is related to personal development, as well as to the future status of the individual in the social hierarchy. Therefore, to ensure the opportunity equality of access to higher education is very important and has been a research focus. However, the existing research on the deep causes affecting the opportunity equality of access to higher education is still limited. As a supplement, this paper takes Japan as the research object, analyzes the current situation of higher education enrollment in Japan from three dimensions of material value, cultural value and thinking value, and finds out that there is also the problem of inequality of access to higher education in Japan. Through the analysis of survey data and qualitative analysis, the paper finds out that educational resources, comprehensive quality, cultural atmosphere of growth environment and students’ thinking patterns are all important factors leading to such inequality, and these factors are all related to family income. Therefore, it can be inferred that family income affects the opportunity equality of access to higher education from multiple dimensions in Japan. In order to promote the equality of access to higher education, this paper puts forward some countermeasures to reduce the influence of family income. In the material dimension, it should improve the existing scholarship structure and increase its popularization rate, reduce the part-time job restriction, and alleviate the imbalance of educational resources caused by income difference. In the cultural dimension, it is necessary to balance the differences in the cultivation of comprehensive quality in different schools and families, and create a proper cultural atmosphere of growth environment for students through various methods. In the thinking dimension, families and schools should make more efforts to cultivate the educational thinking of students.

This paper explores the aesthetic function of integrating educational drama practice into English teaching. It aims to shed light on the potential benefits and implications of using drama techniques to enhance students’ language acquisition and overall learning experience. Through a comprehensive literature review and analysis, this study examines the relationship between aesthetics and education, highlighting drama’s unique capacity to engage students emotionally, intellectually, and creatively. By immersing learners in meaningful and contextually relevant theatrical experiences, drama practice encourages active participation, builds linguistic proficiency, fosters cultural understanding, and develops key soft skills. Furthermore, this research investigates various drama techniques, such as role-playing, improvisation, and performance, and illustrates how they can be effectively incorporated into English language curricula. Additionally, this paper highlights the importance of the teacher’s role as a facilitator in creating a supportive and inclusive learning environment for students to explore their individual voices through drama. Ultimately, this study advocates for the wider implementation of educational drama in English teaching as a means to enhance students’ language proficiency, cognitive abilities, and socio-cultural competencies, ultimately promoting a more engaging and effective learning experience.

The article examines current trends in the use of green technologies in construction in order to create sustainable and environmentally friendly cities. The authors highlight various aspects of green innovation, such as energy-efficient building materials, waste management systems, sustainable infrastructure and energy efficiency of buildings. The paper also condemns the benefits of green innovation, including reducing environmental impacts, improving the energy efficiency of buildings, improving air and water quality in urban environments, and examines examples of successful implementation of green technologies in various countries and cities. The researchers call for the active introduction of green innovations in construction in order to create sustainable cities that can combine modern amenities with minimal impact on natural resources. The article emphasizes that green innovations in construction not only contribute to reducing the negative impact on the environment, but can also significantly save resources and costs for the operation of buildings in the long term. The authors draw attention to the fact that the support and development of green technologies in construction can lead to job creation, stimulate innovation and improve the quality of life in cities. The role of state and municipal authorities in promoting green initiatives, implementing sustainable construction standards, as well as providing financial incentives for enterprises actively involved in creating environmentally sustainable urban environments is also highlighted. In general, the paper notes the need to understand the importance of the transition to green innovations in construction in order to ensure the sustainability of cities, improve the quality of life of citizens, and, what is especially important in the modern world, to cope with the challenges of climate change.

Efficient use of agricultural tractors is largely determined by the operating modes of its power units. Taking into account the variable nature of external loads, it is necessary to provide structural devices in the tractor, which smooth out changes in hook load, thus reducing the negative impact of external conditions on the operation of its power plant. The present paper is devoted to the design of a tractor attachment with variable characteristics. The methods of studying the variable traction force are analyzed on the output parameters of the technological process, as well as on the power and economic indicators of the power unit. Force analysis of the proposed attachment device is carried out and formulas are obtained to determine the forces and moments at the characteristic points of the device. The paper is of interest to engineers and technicians involved in the creation of promising design schemes for tractor tractors of various operational purposes.

A growing concern over climate change and the depletion of conventional energy resources have led to the urgent need for sustainable and resilient energy solutions. The optimization of the size of renewable sources is crucial to maximizing their effectiveness. In contrast to conventional single-objective optimization, the multi-objective technique aims to achieve a trade-off between energy cost and power supply reliability. Due to this need, microgrids (MG) have emerged as a promising paradigm, allowing for localized and decentralized energy generation and distribution. Consequently, the conventional techniques for modelling and optimizing exhibit numerous limitations as the power grid continues to produce substantial volumes of high-dimensional and diverse data types. This review paper examines the use of metaheuristic algorithms in the context of multi-objective energy optimization for hybrid renewable energy-integrated microgrids. A comparative analysis of diverse metaheuristic algorithms for microgrid optimization is provided in this paper, which emulates natural phenomena, such as evolutionary processes and swarm dynamics. Based on the findings of case studies, it can be concluded that trade-offs exist between various objectives, eventually leading to the development of both resilient and efficient microgrid designs. By reviewing sustainable energy solutions, and advocating microgrids as viable alternatives to conventional centralized power systems, the review enhances the advancement of sustainable energy solutions.

Urbanization in Indonesia has led to increased waste generation, posing significant challenges to sustainability. Until now, the method for collecting and transporting waste in Indonesia is still done manually. Nusantara, the New State Capital of Indonesia, aims to address these challenges through the adoption of a Smart Waste Management System (SWMS), leveraging IoT and ICT technologies. This paper reviews the current state of technology research in this field. The proposed SWMS framework integrates various types of sensors for waste monitoring, categorizing, and real-time tracking. This system enhances operational efficiency by triggering waste pickup when bin fill levels exceed a set threshold and directing waste pickup vehicles equipped with GPS and surveillance systems to specific locations. Managed by a central management system accessible via web or mobile applications, this framework exemplifies an innovative approach to waste management in Nusantara, aligning with the city’s vision of becoming a smart and sustainable urban area. The paper concludes that integrating IoT and ICT in waste management is crucial for achieving sustainable urban environments. The successful implementation of SWMS in Nusantara could serve as a model for other cities globally.

This paper addresses the challenges posed by Industry 4.0 and the COVID-19 pandemic, which necessitate digital transformation in educational institutions. It focuses on the specific issues of integrating enterprise information systems to facilitate this transformation. The solution proposed is the development of an integrated information system to manage operational processes within educational institutions. This system targets key domains including student admissions, academics, finance, and human resources, utilizing role-based access control (RBAC) and Single Sign-On (SSO) for efficiency and security. The methodology involves a collaborative effort under the Matching Fund program by the Ministry of Education, Culture, Research, and Technology of Indonesia. This collaboration includes the Universitas Islam Indonesia and the Salman Alfarisi Yogyakarta educational institution. The approach includes defining the project, collecting, and reviewing lessons, creating a repository of these lessons, and disseminating the findings. The project successfully developed and implemented an integrated information system, addressing the initial challenges and improving organizational efficiency in the participating educational institution. The system’s deployment covered multiple key operational domains, significantly digitizing the institution’s processes. This paper contributes valuable insights and best practices from the integration project, serving as a model for other universities and educational institutions. It showcases the potential of collaborative efforts in accelerating digital transformation in education, especially in the context of Indonesia’s vast network of universities and educational institutions.

The country’s economic development and people’s lives require reliable transportation and logistics services. Therefore, road maintenance policies and techniques must be more comprehensive to ensure transportation infrastructure operations’ efficiency. The inefficiency of road maintenance, among others, is due to the failure to identify and predict the level of damage that can cause fundamental data anomalies. Therefore, the current scientific development of road maintenance must be able to take advantage of the convenience of technology. Widespread technology implementation on the Internet of Think (IoT), big data, and data mining (DM) can be a solution to developing a better pavement management system. However, implementing these technologies is challenging due to the weak conception and availability of currently available resources. This paper offers a pavement system management implementation concept that can be developed in Indonesia to improve the existing system. The study results show that IoT, big data, and DM are believed to support a more intelligent and comprehensive pavement management system. The concept offered consists of three main things: identification of damage and 3D pavement modeling, data analysis, decision support systems, and collaboration of intelligent solutions in implementing maintenance in the field. This paper is equipped with an illustration of the concept of road maintenance based on IoT, big data, and DM, which can be implemented intelligently and simply in Indonesia.

Aim of this paper is to explore the development of mining operations in deep quarries utilizing automobile and combined transport systems to overcome these challenges. The use of automobiles in mining has been a growing trend, offering flexibility, maneuverability, and increased productivity. In deep quarries, traditional automobile transport faces limitations in terms of reach and efficiency, combined transport systems incorporating a combination of automobiles, conveyor belts, and other transport mechanisms have been proposed. This paper discusses the advantages of automobile transport in deep quarries, including its ability to navigate narrow passages and transport smaller loads efficiently. It examines the integration of combined transport systems, which leverage the strengths of automobiles alongside other modes of transportation to optimize mining operations. Key considerations in the development of these systems include infrastructure design, vehicle specifications, safety protocols, and environmental impact. By implementing innovative solutions tailored to the specific challenges of deep quarry mining, such as automated vehicle control and monitoring systems, it is possible to enhance efficiency, reduce operational costs, and improve safety standards. Also, this paper highlights case studies and examples of successful implementations of automobile and combined transport systems in deep quarries around the world. These real-world examples demonstrate the feasibility and benefits of adopting such approaches in challenging mining environments. In the paper criteria requirements and recommendations for the implementation of this process are presented in the technological processes of compaction using separators, which are carried out during the construction of highways, and the interdependence of indicators is presented through tables, graphs and calculation expressions.

This paper describes an approach to the automatic generation of a mivar knowledge base of a three-dimensional logic space. This knowledge base is created to provide three-dimensional robot movement. Automatic generation of mivar knowledge bases is necessary for the further solution of the problem of planning three-dimensional routes of robots and robotic complexes. This work is the basis for solving problems of resource allocation optimization in the field of transport logistics and machine learning artificial intelligence based on the application of mivar technologies. The variant of practical realization of the automated technique of sequential removal of mivar network rules and search for new robot motion trajectories for their further comparison by the number of activated transition rules on the way from the initial location to the target one is considered. Mivar-based logic artificial intelligence technologies offer great opportunities for dynamic route finding in real time, which will help in further development of machine learning artificial intelligence in the field of transport systems. The paper is intended for researchers involved in the development of mivar expert systems for solving problems of three-dimensional movement of robots and optimizing production planning systems.

The paper considers options for reducing environmental losses in Polotsk and Novopolotsk through the development of trolleybus and tram systems – various types of urban electric transport. In order to reduce the costs of creating transport (including charging) infrastructure, as well as operating costs, the effectiveness of such systems has been determined when using not only classic types of transport, but also hybrid buses, electric buses, duo-buses. Approaches and methods have been developed to improve the quality of passenger service without deteriorating the environmental situation – this will become possible thanks to the development of tram and trolleybus traffic in Polotsk and Novopolotsk. Variants of scenarios for the use of various types of urban eclectic transport in the cities under study are presented, which will reduce investment in vehicles and the cost of creating an operational base at the expense of existing production facilities, for example, a tram fleet. The proposals outlined in the paper are aimed at improving the environmental situation in these cities by reducing the volume of emissions of harmful substances by buses, especially on the central streets

The purpose of this paper is to study the application of ChatGPT and BERT models in the field of mechanical engineering. In the context of machine learning, the ChatGPT and BERT models can be applied to various natural language processing tasks such as analyzing technical documentation and building instructions according to a particular version of the documentation, diagnosing malfunctions or customer service. The paper discusses the fundamental features of BERT and ChatGPT models, their origin, and also investigates the main architectural features and identifies the main advantages and disadvantages of the models. The paper analyzes and selects various natural language processing tasks to test the models’ ability to understand natural language in the context of machine learning. The selected criterion tasks are divided into semantic groups to identify the capabilities of ChatGPT and BERT models in each of three areas: logical inference tasks, paraphrasing tasks, and text similarity tasks. The paper also discusses the concept of operational design, which involves developing inputs that guide the models to produce desired outputs. The paper quantitatively analyzes and compares the performance of BERT and ChatGPT based models. The reasons for the bottlenecks of ChatGPT model in natural language understanding tasks are discovered and investigated. Possible improvements of ChatGPT model performance using the mivar approach are considered.

The paper provides research on the use of modern drones or unmanned aerial vehicles (UAVs) for effective work in the fields of architectural design, construction management and monitoring. The authors examined the theoretical foundations and practical features of modern unmanned aerial vehicles (UAVs) or drones. Statistics on the structure of the global UAV market are presented. The detailed description of the primary applications of drones in the construction sector is provided. The main advantages of new technologies over traditional ones are noted. The paper pays attention to the issues of increasing safety at construction sites. The introduction of innovative technologies is necessary for the development of the construction industry. The use of such technologies will reduce task completion times, improve work quality, improve safety standards and reduce costs. At the same time, the authors noted some shortcomings of modern unmanned technologies. In the conclusion of the paper, insights are presented regarding the future possibilities for integrating unmanned aerial vehicles in construction projects.

In engineering, the use of mobile robots to teach automatic control is becoming more common because of the interesting experiments that can be conducted with them. In this paper, a mobile robot that applies reinforcement learning in different scenarios is shown, to get rewards, the agent learns by acting in the environment. creating a balance between new information and our current understanding of the environment. In this way, the algorithm can be divided into two stages: the learning stage and the operational stage. In the first phase, the robot learns how to go from where it is to a known destination, it builds a learning matrix that is subsequently utilized during the operational stage using the rewards and environment data. In this paper, the algorithm was studied in terms of rapid learning for the mobile robot and reducing the process of repetition in learning by specifying the values of alpha (α) and gamma (γ) in a way that is appropriate for preserving the variance and differentiation between them. To evaluate the robot’s adaptability to various dynamic situations, several simulated test scenarios were executed. In the testing situations, several target motion kinds and numbers of obstacles with various dynamicity patterns were used. The test scenarios illustrated the robot’s adaptability to various settings.

Encryption is vital for data security, converting information into an unreadable format to ensure privacy in online communication and sensitive sectors. Advanced encryption balances innovation and security in user-friendly applications. Image encryption employs techniques to protect image data from unauthorized access during transmission or storage, particularly crucial for safeguarding sensitive images in various applications. The goal is to prevent unauthorized access and ensure the safety of associated information. In this paper, I present a study on previous research related to my investigation, which focuses on encryption in general and image encryption in particular. The paper also discusses the methods used, particularly those closely related to my work, involving either SHA-256, MD5, or a combination of both. The review will look at the many strategies and techniques employed, as well as how precisely the task was completed by applying a set of parameters in comparison to earlier studies.

Individual Home Address is considered as an important sub set of attributes, and never find personnel record, whether a person is student, patient, or employee, etc. without having a home address. It is required to be recorded, registered, and documented in all personnel information systems, whether the system is manual or computerized. This research concern on the Coding, and Digitization of home address of Iraqi personnel in order to enhancing storage efficiency and reduce processing time. The conventional method of maintaining paper-based records for personnel home addresses has proven to be costly, and timeconsuming, and in most cases inefficient. The proposed solution involves the conversion of physical addresses into digital formats, allowing for streamlined data storage and faster retrieval, and update processes. The work starting by indicate the current challenges related to the paper-based address systems, including the demands on physical storage space and the delays incurred during information retrieval. Subsequently, it explores the potential benefits of digitizing home addresses, such as reduced storage requirements, improved data accessibility, and enhanced overall organizational efficiency. To implement this digitization process, the research investigates various technological solutions, including geographic information systems (GIS), databases, and data management protocols. The study also addresses potential concerns related to data security and privacy, proposing measures to safeguard sensitive information. The proposed solution for Digitization, Coding, with Optimizing the Personnel Home Address provide at least 85% of Optimizing Factor for each individual personnel record required storage space and processing time, this solution subsequently leed to better daily decision-making process in most business organizations.

Human face recognition and tracking (FRT) plays a vital role in various fields, including security, authentication, and human-computer interaction. The main modules of the FRT system are detection, feature extraction, and FRT. Using a database, these units recognize faces as well as their location, movement, and visible features. The framework aims to process large visual data in real-time, enabling accurate and fast FRT. The paper develops a real-time FRT framework using a lightweight CNN convolutional neural network to accurately match images of faces and environments with different illumination and expression differences to improve performance. This paper focused on the development of real-time facial recognition and tracking systems. The model used to achieve this is based on deep learning (DL) using a lightweight convolutional neural network (CNN) and post-feature extraction using linear discriminant analysis (LDA). Histogram of Oriented Gradients (HOG) experiments demonstrate that DL with lightweight CNN models provides a good solution for FRT tasks, even in challenging situations including changes in position, expression, illumination, and occlusion. The results of CNN-based DL were compared with several experiments. The model was also compared with many modern methods and achieved better results. The lightweight CNN model for DL outperformed it 100% of the time. When the split rate is 70:30 and the learning rate is 0.001, the epoch is 100. This demonstrates the dominance of DL over other techniques and shows how well it handles FRT tasks using lightweight and even real-time CNN methods.

Visible Light Communications (VLC) represents a new technology of wireless communications allowing high data rate, high-speed internet access, green and friendly communication system, especially for indoor users, where the use of Light Emitting Diodes (LEDs) is growing as a viable alternative to traditional illumination. Orthogonal frequency division multiplexing (OFDM) is a promising modulation format for optical wireless communication (OWC); however, precise channel estimation is required for synchronization and equalization. Moreover, one of the challenging issues for OFDM is its high Peak-to-Average Power Ratio (PAPR) due to the superposition of all subcarriers; therefore, the system requires a high linearity and dynamic range. This paper provides a systematic overview of OFDM-based VLC systems, highlighting the essential aspects of PAPR reduction and channel estimation techniques. Several technical challenges have been addressed to realize the full potential of OFDM-based VLC technology. Moreover, we provide new insights into the over-explored and under-explored areas, which lead us to identify open research problems of VLC based on OFDM. Concisely, this paper serves as a guide and a starting point for researchers willing to research VLC using OFDM.

Cryptography and Steganography are two main components of information security. Utilizing encryption and Steganography to establish many layers of protection is a commendable approach. Our main objective of this paper is to build an integrated method of securely transmitting data through a combination of cryptography and Steganography. Cryptography and Steganography are two common methods of secretly transmitting information. RC4 is used in this paper to change information from plaintext to cipher, and then cipher text is integrated into the image by Least Significant Bit (LSB). The results are defined in terms of the processing time, the peak signal-to-noise ratio (PSNR), and mean square error (MSE). The experimental results showed the stego image’s acceptable quality and combining the two techniques provides additional security in the original Steganography.

The Internet of Things (IoT), is changing practically every aspect of modern life. The proliferation of IoT has led to a rise in the frequency of cyber catastrophes. The threat landscape that security professionals face is dynamic, complex, and diversified. This paper proposes a novel approach to enhance Internet of Things applications by fusing the swarm intelligence of Salp Swarm Algorithms (SSA) with the predictive power of Random Forest (RF) and Decision Tree (DT) models Even though there is a lot of interest in the topic of explainable Artificial Intelligence (XAI) these days, more research is still needed to fully understand how successful XAI is at finding attack surfaces and vectors when implemented in cyber security applications. The growing use of machine/deep learning models in cyber defense, especially anomaly-based IDS, requires understanding the architecture of the models and providing evidence for their predictions to determine the probability of intrusions. Numerous approaches to interpretation have been proposed. They help researchers comprehend things like which variables have influenced the machine learning predictions. In this paper, we primarily address two popular local interpretation methods in machine learning: Shapley values and Local Interpretable Model-Agnostic Explanations (LIME).

With the rapid advance of the Internet of Things (IoT), technology has entered a new era. It is changing the way smart devices relate to such fields as healthcare, smart cities, and transport. However, such rapid expansion also challenges data processing, latency, and QoS. This paper aims to consider fog computing as a key solution for addressing these problems, with a special emphasis on the function of load balancing to improve the quality of service in IoT environments. In addition, we study the relationship between IoT devices and fog computing, highlighting why the latter acts as an intermediate layer that can not only reduce delays but also achieve efficient data processing by moving the computational resources closer to where they are needed. Its essence is to analyze various load balancing algorithms and their impact in fog computing environments on the performance of IoT applications. Static and dynamic load balancing strategies and algorithms have been tested in terms of their impact on throughput, energy efficiency, and overall system reliability. Ultimately, dynamic load balancing methods of this sort are better than static ones for managing load in fog computing scenarios since they are sensitive to changing workloads and changes in the system. The paper also discusses the state of the art of load balancing solutions, such as secure and sustainable techniques for Edge Data Centers (EDCs), It manages the allocation of resources for scheduling. We aim to provide a general overview of important recent developments in the literature while also pointing out limitation where improvements might be made. To this end, we set out to better understand and describe load balancing in fog computing and its importance for improving QoS. We thus hope that a better understanding of load balancing technologies can lead us towards more resilient and secure systems.

This paper presented a new technique for encrypting original texts based on multiplying the coefficients defined in the Taylor series of the logarithmic function by its equivalent index. As for decryption, a Sadik integral transform and its inverse were applied. Through this new technique, new mathematical techniques for encryption and decryption were discovered. This paper includes a practical example in order to demonstrate the efficiency of this technique.

Recognizing sign language is one of the most challenging tasks of our time. Researchers in this field have focused on different types of signaling applications to get to know typically, the goal of sign language recognition is to classify sign language recognition into specific classes of expression labels. This paper surveys sign language recognition classification based on machine learning (ML), deep learning (DL), and optimization algorithms. A technique called sign language recognition uses a computer as an assistant with specific algorithms to evaluate basic sign language recognition. The letters of the alphabet were represented through sign language, relying on hand movement to communicate between deaf people and normal people. This paper presents a literature survey of the most important techniques used in sign language recognition models

In this paper, the generation of green hydrogen utilizing the sun powered warm partition strategy is analyzed from a financial and natural point of view, and the arrangements of researchers and analysts to create this innovation and decrease its costs are considered, and insights are displayed for the generation of green hydrogen by this strategy. This paper analyzes the generation of green hydrogen utilizing sun oriented warm partition from a financial and natural point of view. It investigates the endeavors of researchers and analysts to create this innovation and decrease costs. The paper too presents insights on the generation of green hydrogen through this strategy.

Short Message Service (SMS) is widely used for its accessibility, simplicity, and cost-effectiveness in communication, bank notifications, and identity confirmation. The increase in spam text messages presents significant challenges, including time waste, potential financial scams, and annoyance for users and carriers. This paper proposes a novel deep learning model based on parallel structure in the feature extraction step to address this challenge, unlike the traditional models that only enhance the classifier. This parallel model fuses local and temporal features to enhance feature representation by combining convolutional neural networks (CNN) and long short-term memory networks (LSTM). The performance of this model has been evaluated on the UCI SMS Collection V.1 dataset, which comprises both spam and ham messages. The model achieves an accuracy of 99.28% on this dataset. Also, the model demonstrates good precision, recall, and F1 score. This paper aims to provide the best protection from unwanted messages for mobile phone users.

The purpose of this paper is to define and examine two novel forms of Nano βPC- continuity, namely Nano contra βPC- continuity and Nano almost contra βPC- continuity, and to provide several fundamental characteristics and attributes related to these mappings. Moreover, , paper is done on Nano almost continuously. The connections between these mappings and other well-known functions are found.

The soil water characteristics curve (SWCC) demonstrates a link between soil moisture content and suction. The SWCC is almost treated as an index parameter in unsaturated soil. The soil permeability and shear strength can be linked to SWCC. SWCC is established using filter paper for the wetting path. This paper compares SWCC for both cases stress-dependent and no stress (reference) in the wetting path. The samples of soil are brought from Al-Najaf City with a gypsum content of 29%, Iraq. The stress-SWCC is studied using a modified Oedometer cell with controlled water and air entrance to apply a specific matric suction. While the reference SWCC is estimated using the filter paper method. Matric suction is conducted at a range of pressures from 90 kPa to 0 kPa. The tests use three net normal stresses of 100, 200, and 400 kPa. The results show that there are decreasing values of the SWCC with increasing normal stresses. An interesting result is that this decrease is high and has zero matric suction. The water entry value (WEV) with the most significant value of the water entry change is represented by the matric suction of 50 kPa.

The thermodynamic cycles for energy generation are the baseline for development in different types of energy generation, and they are the primary principle for the mix of fossil and renewable energy. In this paper, a detailed description of the organic Rankine and Brayton-Joule cycles has been presented as a comprehensive reference library for linking renewable energy and fossil energy, and an explanation of the governing and basic equations that formulate When developed to be flexible in the use of the research methodology used in this field. This paper provides a comprehensive reference library for linking renewable energy and fossil energy by presenting a detailed description of the organic Rankine and Brayton-Joule cycles. It includes an explanation of the governing equations and basic formulations, as well as a flexible research methodology for use in this field.

Extracting information from an information platform, site or system is possible if the information is structured or annotated in a way that is convenient for subsequent analysis and data processing, decision making and reasoning. The goal of this paper is to review and categorize various techniques, tools, and libraries for extracting information from unstructured web content (platforms, sites, systems), and to develop a JavaScript application that crawls and extracts data from dynamic web pages without the need to browse, read and search the page content. The paper presents an implementation of a particular JavaScript web scraper that retrieves a list of news headlines from the official European Union Agriculture and Rural Development website without the need for the content of the document to be read by users. The web scraper is configured to extract the searched content directly from the source HTML code of the document, regardless of whether the information is explicit or implicit. It also searches all pages related to the document. Finally exports data in a proper format. The benefits of such a tool for extracting web content from source code are related to saving time, manual labour and means of generating quality content in the biotech and agriculture industry.

This paper describes the basic aim of Ş -proximit space for non-empty sets. The relationship between approach space and Ş-proximit space has been clarified. This paper demonstrates that all metric spaces are Ş-proximit spaces. But the opposite is not always true. We define SA-contraction and present various features and the results. In addition, we define new Ş-proximit normed space. We demonstrate that any proximit normed space is normed. But the opposite is not always true. We define the concepts of the Ş -proximit semigroup, Ş-proximit group, and Ş-proximit vector space via instances of problem-solving techniques. We also discussed the definitions of Cauchy sequence, cluster point, Ş -convergent sequence, and Ş -complete.

This paper introduces a novel method of managing railway tracks by utilizing a control system based on microprocessors. The creation and deployment of an advanced system intended to improve the effectiveness, security, and dependability of railway operations is the main objective. The suggested system makes use of cutting-edge microprocessor technology to keep an eye on, manage, and repair a number of railway infrastructure components, such as train movements, signal operations, and track integrity. The system offers an automated approach to identify and resolve any problems such track defects, signal failures, and unwanted access through real-time data collecting and processing. Additionally, the integration of predictive maintenance algorithms helps in preemptive identification of wear and tear on tracks, thereby reducing the likelihood of accidents and improving overall service quality. The paper details the architectural design of the system, its operational mechanisms, and the results of a series of simulations and real-world tests conducted to validate its effectiveness. The findings demonstrate significant improvements in operational efficiency, reduced maintenance costs, and enhanced passenger safety, illustrating the potential of microprocessor-based systems in revolutionizing railway infrastructure management.

The exploration of the cutting edge of wastewater treatment, concentrating on the ever-changing field of heavy metal remediation uses of nanotechnology is a major requisite for sustainability. The investigation covers a wide range of nanotechnology topics, such as photocatalysis, adsorption, catalysis, and novel nanomembranes, providing a thorough grasp of its crucial function in water treatment. Examining specific nanomaterials such as nanoparticles, nanotubes, and nanofibers, the study evaluates their applications, highlighting their unique contributions to heavy metal removal. However, the paper meticulously dissects the challenges hindering the widespread use of nanoparticles in wastewater treatment, with a keen focus on graphene oxide nano-sheets, magnetic nanoparticles, polymeric hydrogels, and activated carbon. Novel techniques incorporating nanotechnology for heavy metal removal are also explored. The conclusion provides a synthesis of findings and offers recommendations for overcoming existing challenges, paving the way for an enhanced integration of nanotechnology in wastewater treatment practices. This paper serves as a vital resource for researchers, practitioners, and policymakers engaged in advancing sustainable and effective solutions for heavy metal remediation in wastewater treatment systems.

The sustainable development of container rail-water intermodal transport in China faces a series of deep-seated constraints. In this paper, we quantitatively summarize the development status of container rail-water intermodal transportation in China’s ports. Next, the typical problems faced by the sustainable development of rail-water intermodal transport are analyzed from the bottom constraints and direct constraints. Finally, this paper proposes strategic ideas to promote sustainable development of rail-water intermodal transport, taking into account network layout, technical equipment, data exchange rules, and policy environment.