Journal of Mechanical, Civil and Industrial Engineering
Journal of Mechanical, Civil and Industrial Engineering (ISSN: 2710-1436) is an international peer-reviewed monthly journal published by Al-Kindi Center for Research and Development. The journal welcomes publications of high-quality papers on theoretical developments and practical applications in mechanical, civil and industrial engineering. Original research papers, state-of-the-art reviews, and high-quality technical notes are invited for publication. The scopes of the journal include, but are not limited to Mechanism Design, Manufacturing Engineering, Engineering Design, Electrotechnology, Fluid Dynamics, Thermodynamics, Automotive Engines, Engineering Mathematics, Mechatronics, Control Theory [...] Read More
Al-Kindi Center for Research and Development
Analysis of Hydrological Station Rationalization in Dompu Regency
This study aims to rationalize the hydrological station network in Dompu Regency in order to establish an efficient, effective, and regionally representative hydrological monitoring system for the watershed. The analysis was carried out using the Kagan–Rodda Method, the Stepwise Method, and the World Meteorological Organization (WMO) Density Standard. The dataset consists of rainfall observations, river discharge data, and climatological variables sourced from the Nusa Tenggara I River Basin Authority I, the Indonesian Agency for Meteorology, Climatology, and Geophysics, and the Agency for Food and Horticultural Crop Protection. The results show that the existing hydrological station network does not meet the minimum World Meteorological Organization standards for station density and spatial distribution. Based on the Kagan Method, the ideal number of rainfall stations in Dompu Regency is 19, with an interpolation error of 1.01%. Meanwhile, the Stepwise Method indicates that the correlation between rainfall stations and water level gauging station remains low. According to WMO guidelines, Dompu Regency requires at least 93 rainfall stations, 8 water level gauging stations, and 8 climate stations to meet the representativeness standards for small mountainous island regions. Therefore, additional stations are needed along with the revitalization of hydrological equipment to improve data accuracy and the operational efficiency of the network.
Rationalization, Hydrological Stations, Network Efficiency
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Optimization of Irrigation Water Allocation at The Meninting Dam to Substitute The Water Discharge to The Jangkok - Babak HLD
Water resources are vital components for sustaining life and supporting economic development; therefore, their management must be carried out in an integrated and sustainable manner. The Lombok River Basin (WS Lombok), as one of Indonesia’s National Strategic River Basins, comprises 197 watersheds (DAS), 52 of which have been utilized for water supply. The imbalance of water distribution between the western region (which tends to have a surplus) and the southern region (which faces a deficit) necessitates an efficient and equitable water management system. One of the key solutions developed to address this issue is the construction of the Meninting Dam, designed to balance water availability through the High-Level Diversion (HLD) Jangkok–Babak Channel. This study aims to simulate and optimize water allocation from the Meninting Dam to several major irrigation areas, namely D.I. Sesaot, D.I. Jurang Sate Hulu, D.I. Jurang Sate Hilir, and D.I. Jurang Batu. The methodology includes hydrological simulation and water allocation optimization using a trial-and-error approach to achieve flow balance between the supplying rivers (Meninting, Jangkok, and Sesaot) and the HLD as the receiving system. The results indicate that water availability in each irrigation area reaches 2,480 L/s for D.I. Sesaot, 10,049 L/s for D.I. Jurang Sate Hulu, 8,596 L/s for D.I. Jurang Sate Hilir, and 4,536 L/s for D.I. Jurang Batu, with a total inflow to the HLD system of 13,970 L/s. Following the operation of the Meninting Dam, irrigation efficiency (K Factor) increased from 85.6% to 98.3% in D.I. Sesaot, and from 86.3% to 87.7% in the Jurang Sate–Jurang Batu system. Water distribution also shifted, with 61.4% of the flow directed to the HLD system and 38.6% to D.I. Sesaot, as the dam fully meets the irrigation demand in D.I. Sesaot. These findings demonstrate that integrated inter-watershed water management through the operation of the Meninting Dam and the HLD system significantly improves water distribution efficiency and supports the enhancement of cropping intensity in southern Lombok.
Copyright (c) 2025 Journal of Mechanical, Civil and Industrial Engineering
Sensitivity Analysis of Mock andSensitivity Analysis of Mock and NRECA Method Parameters on Water Availability in the Jangkok Hulu Watershed NRECA Method Parameters on Water Availability in The Jangkok Hulu Watershed
The Jangkok watershed, as one of the watersheds with high utility, plays an important role as a supplier of supplementary water to the communities living in the surrounding area. If there is a decrease in base flow in the Jangkok Watershed, it will have a significant impact on the irrigation water supply in Jangkok-Babak-Jurang Sate, raw water supply, and industrial water in Mataram City and West Lombok Regency. Because the Jangkok watershed is widely used for low flow management in the form of river and spring water, water flow availability can be obtained using the F.J Mock and NRECA methods. Each parameter has its own sensitivity that can directly affect changes in water availability. The parameter with the greatest sensitivity is determined based on the average deviation percentage and discharge change. The initial stage involved a calibration process with Qdefault results for the Mock and NRECA methods of 1.261 m³/dt and 0.968 m³/dt, respectively. Next, sensitivity analysis was performed using calibrated default parameters with overestimate and underestimate conditions of 5%, 10%, 15%, and 20%. Based on the results of the sensitivity analysis of the F.J. Mock Method, the parameter with the highest sensitivity was the Groundwater Recession Constant (k) under an underestimate condition of 20%, which affected the increase in water availability discharge in January 2024 to 6.457 m³/dt with an average deviation of 245.90%. In the NRECA Method, the parameter with the highest sensitivity was Percent Sub Surface (PSUB) under the 20% underestimate condition, which influenced the increase in water availability discharge in January 2024 to 0.993 m³/dt with an average deviation of 20.08%.
Automated Pick & Stow Robot System for Sorting in an e-Commerce Warehouse
Technology is an important factor influencing the development of a company. The Industrial Revolution 4.0 is a new era with an independent field of science in the form of data digitization. Reliable technology has the ability of a flexible, customer-oriented control system with the Just in Time (JIT) concept, and can function as a continuous control system process. Problems that often occur in e-commerce warehouses are improper management, lack of inventory control carried out by machines, and lack of integration with operators, so it takes a long time to analyze errors in the logistics process. This study proposes a sorting robot to reduce the workload in a logistics warehouse. The system consists of three main modules, including a six-axis arm and its controller, software, and flexible end-effectors. The robot automates the picking and storing of objects from and to shelves in an e-commerce warehouse. The prototype system can be demonstrated through several simulations and real-world experiments with real robots.
Integration of nature-based solutions in urban planning: policy, governance, and institutional frameworks
The concept of the Nature-Based Solutions (NBS) inclusion in urban planning has become one of the strategic avenues towards the attainment of sustainable, climate-resilient, and habitable urban areas. Nevertheless, even with the increased understanding of their environmental and social importance, NBS are not uniformly reflected in urban policies and institutions. This paper focuses on the convergence of policy framework, governance systems and institutional structures that influence mainstreaming of NBS in urban settings. On the basis of an extensive analysis of the current state of empirical and conceptual research, the paper reveals the main problems of governance, namely the fragmentation of regulatory tools, lack of cross-sectoral coordination, and institutional capacity. The review indicates that a successful NBS integration relies on adaptive governance schemes, coherent multilevel alignment of policy, and participatory institutional schemes that are conducive to innovation and accountability. In addition, European and world case studies have shown that policy planning (collaboration), long-term funding approach and inter-agency collaboration are important to maintain NBS outcomes. The paper suggests that to entrench NBS into more inclusive urban governance and planning systems, regulatory reform is necessary, as well as, the development of inclusive and knowledge-based institutional ecosystems with the potential of bridging science, policy, and community practice.
Nature-Based Solutions (NBS), Urban Planning, Policy Integration, Governance, Institutional Frameworks, Sustainability
Safety Analysis of Construction Projects in Kabul Using the FMEA Method with a Worker Behavioral–Psychological Approach
Construction safety in developing countries such as Afghanistan is a major concern due to weak regulations and cultural influences that significantly increase risks. This field-based study employed the Failure Modes and Effects Analysis (FMEA) method to identify hazards, with particular emphasis on both technical and behavioral aspects.An analytical investigation was conducted across ten construction projects, including governmental, residential, and commercial buildings, to identify, assess, and prioritize hazards. Initially, the primary risk factors within the projects were identified. For each hazard, three parameters—severity, occurrence probability, and detectability—were determined. Subsequently, prioritization criteria were applied, and hazards were ranked based on the Risk Priority Number (RPN).The findings revealed that the highest RPN value (560) was associated with work at heights. Contributing factors included discomfort caused by personal protective equipment (PPE), lack of safety harnesses, rushing, and a culture of indifference, along with managerial negligence driven by cost reduction and underestimation of worker health. Conversely, the lowest RPN value (180) was linked to disregard for PPE, stemming from weak work culture, lack of incentive and penalty systems, and insufficient training. The results also highlighted significant risks posed by crane operations, temporary electrical work, and the absence of a reporting culture. The RPN findings suggest that Afghan authorities should implement supervisory controls, enforce regulations, provide crane operation training, ensure the use of PPE, and strengthen the reporting culture to mitigate critical hazards and enhance the culture of construction safety in Kabul.
Construction Safety, FMEA, RPN, PPE, Kabul
Case Accuracy for Offshore Assets Using the Nkansah Reconciliation Model: Technical Report & Case Study
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Re-Imagining the Spaces In-Between: Design Interventions to Transform Urban Voids in Downtown Dayton into Active, Breathing Areas
In today's rapidly expanding urban landscapes, space paradoxically grows scarce, yet underutilized voids remain overlooked. Downtown Dayton, like many cities, faces the challenge of meaningfully integrating these neglected spaces into its urban fabric. With its dense concentration of offices, downtown Dayton needs places of tranquility-areas where employees and residents alike can engage in psychogeographical exploration, experiencing moments of personal solitude and quiet reflection. Such subtle, personal interactions with the city can emerge in liminal spaces, akin to what Roland Barthes calls the punctum - moments that "prick" individual consciousness, creating personal significance. To address this lack of tranquil spaces, I propose transforming Dayton's neglected urban voids into areas where solitude and fresh air can be deeply experienced. Rather than focusing solely on high-activity spaces, a balanced emphasis on areas for solitary exploration and contemplation, alongside active public spaces, is essential. My design interventions aim to reclaim Dayton's overlooked voids, forming a network of "breathing spaces" that invite exploration of the downtown's architecture and social fabric. As Michel de Certeau describes, pedestrians' unpredictable movements through these spaces will carve "rhetorical" paths that challenge Dayton's urban order, reimagining it as a dynamic landscape enriched by personal stories and experiences.
Rethinking Sprawl: How High-Density, Low-Rise Housing Can Reshape Small Cities like Baton Rouge
This paper examines the potential of low-rise, high-density housing as a solution to urban sprawl in Baton Rouge, Louisiana. Driven by zoning regulations that favor single-family homes, Baton Rouge's outward expansion contributes to environmental harm and car dependency. Arguing for a shift towards higher-density living, this paper proposes low-rise, mixed-use developments as a more sustainable and community-focused approach. By analyzing case studies and examining the benefits of mixed-use integration, this paper demonstrates how such developments can create a more vibrant, walkable, and environmentally conscious urban environment for Baton Rouge. Furthermore, it addresses concerns related to traffic and infrastructure, highlighting how thoughtful design and planning can mitigate potential challenges. Finally, the paper proposes policy recommendations, including zoning reform, incentivizing affordable housing, investing in public transportation, and community engagement, to facilitate this transition towards denser, more resilient urban growth.
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Sustainable Building Materials in the Traditional Architecture of Nuristan Province, Afghanistan: A Case Study of Wood, Stone, and Indigenous Materials in Parun and Wama Districts
In many developing countries, construction methods differ significantly from those in developed regions, often relying on readily available but low-quality materials. Afghanistan, as a developing country, displays a wide range of traditional construction practices, particularly in remote provinces. This study focuses on the traditional residential construction techniques of Nuristan Province, with an emphasis on the use of wood, stone, and other indigenous materials in the Parun and Wama districts. The research investigates how these materials are applied in local building practices and evaluates their performance in terms of sustainability, structural resilience, and climatic suitability. Data were collected through field observations, interviews, questionnaires, and physical measurements conducted during site visits in 2025. The findings reveal that the indigenous materials used in Nuristan are not only practical and cost-effective but also environmentally sustainable and culturally significant.
Nuristan Province, Traditional Architecture, Indigenous Building Materials, Wood and Stone Construction, Sustainability, Seismic Adaptation, Vernacular Techniques
As is clear, the human body is mainly composed of water and electrolyte fluids. Accordingly, we can say that the human body generally acts as a conductor. The body also has resistance, due to which part of the electrical energy inside the body is converted into heat. The main factors affecting electric shock are voltage, current, resistance and other factors. Voltage, current and electrical safety are considered vital aspects in the design and operation of electrical systems. This article examines the effects of current-voltage and related matters on electrical safety and analyzes voltage drops and power fluctuations in cables and transmission lines, as well as the effects of different currents on the body. The main objective of this research is to evaluate the effects of high voltage and different currents on the health and safety of the body, maintain equipment and investigate methods for reducing voltage drops in electrical circuits. To achieve this goal, analytical and computational methods have been used to examine the effects of current and voltage drops and compare them with existing safety and security standards. The results of the study show that voltage drops in many of the systems studied are beyond the permissible limits of the standards, which can lead to reduced efficiency and increased electrical safety risks. Based on these findings, suggestions are made to improve the design and appropriate selection of cables and protective systems. This research can help improve the understanding and management of electrical safety and protection in various systems and help designers and engineers reduce risks and increase the efficiency of electrical systems.
Current, Electrical safety, Human body, Hazards, Voltage
Particle Swarm Optimized Robust Backstepping Control of a Quadrotor Unmanned Aerial Vehicle under Pink Noise
Technological developments in sensors, actuators, and energy storage devices have allowed the development of quadrotor unmanned aerial vehicles (UAVs). Quadrotor UAVs are used in sensitive tasks such as surveillance, search and rescue, mapping, mining, cargo carriage, agricultural spraying, firefighting, and photography. Quadrotor UAVs are exposed to effects such as noise and vibration while performing these sensitive tasks. Therefore, robust controller design that is resistant to noise and vibration gains great importance. Noise and vibration can be caused by the sensors, actuator, and propellers of the quadrotor. Background noise in electronic devices is called pink noise. The primary sources of pink noise in electronic devices are generally slow fluctuations of the properties of the condensed matter materials of the devices. These contain fluctuating defect configurations in metals, fluctuating trap occupancy in semiconductors, and fluctuating field structures in magnetic materials. In this study, a particle swarm optimized (PSO) robust backstepping controller is designed for a quadrotor that can follow altitude and attitude references under pink noise. The rise time, overshoot, and settling time of the PSO-optimized proposed backstepping controller and classical PID controller were compared. It has been proven by simulations that the designed PSO-optimized backstepping controller performs more successfully than the classical PID controller.
Study and Evaluation of the Extraction of Northern Oil Fields on Income Generation in the Afghan Economy
The study and investigation of oil extraction processes play a key role in improving economic productivity and increasing national income. As the main sources of income in many countries, these activities play an important role in economic development, creating employment, and providing financial resources for development projects. Economic analyses show that proper management and advanced technologies in oil and gas extraction can have a significant impact on improving productivity and reducing costs, and as a result, increasing the income generation of the economy. In addition, policies based on sustainable financial principles and proper utilization of resources can prevent price fluctuations and the decline of fossil fuels and ensure economic stability. Afghanistan, as one of the countries rich in natural resources, has significant potential in the oil sector, although major extraction and exploitation has not been carried out in this sector so far. Lack of infrastructure, lack of modern technologies, and internal insecurity are major obstacles to the development of this sector. The release and identification of oil reserves in parts such as the northern and western regions of the country provide great economic opportunities. If these resources are extracted in sustainable and effective ways, they can play an important role in increasing government revenues and improving the livelihoods of the people. If properly and fairly exploited, oil revenues can be an important source of finance for development projects, education, health, and infrastructure. Job creation and poverty reduction as a result of extraction activities are among the direct benefits of these resources. Despite the high potential, Afghanistan faces challenges such as insecurity, weak technology, lack of appropriate investment, and inability to manage resources. These factors prevent full and profitable exploitation and limit economic opportunities. By improving security, developing modern technologies, and attracting international investment, Afghanistan can exploit its oil resources, which can be effective in increasing national income, reducing poverty, and improving public welfare. Attention to proper management, transparency, and compliance with environmental standards are crucial in this path.
Extraction, Oil, Job Creation, Economy, Social Welfare, Northern Afghanistan
A look at the oil and gas industry of Afghanistan
Afghanistan is one of the oil and gas-rich countries in the world, especially Asian countries. Also, one of the reasons for the periodic developments and instability of Afghanistan's political currents is the presence of hidden and even untouched mines, especially oil and gas. Oil exploration in Afghanistan dates back to the 1950s, when in 1958, Afghan and Soviet experts conducted a topographic and geological survey in the northern provinces of Afghanistan, then two years later announced the discovery of oil and gas in the cities of Sheberghan, Sar-e-Pul and Faryab. Oil and gas play a vital role in the sustainable development of a country, because they provide the main energy sources and have a wide impact on the economy, technology and environment. Proper exploitation of these resources can lead to economic growth, job creation and improvement of people's living standards. On the other hand, the importance of oil and gas in sustainable development leads to a balance between economic exploitation and environmental protection. The main objective of this article is the importance of oil and gas in defining Afghanistan’s position in the world, especially in Asia. The research method in this study is considered by separating the research and statistical perspectives, which was selected from the perspective of the development goal, from the perspective of the qualitative method, and from the perspective of the nature of the data, descriptive-analytical. In this study, a questionnaire was distributed to experts, specialists in the oil and gas field, graduates of this field, and university professors and analysed with SPSS software. The results of this study showed that Afghanistan is in the category of rich and mineral-rich countries; but a suitable percentage has not yet been used to provide community facilities and government self-sufficiency. The reason for this is political instability, lack of relative security, lack of technical and skilled personnel, and also the lack of technical facilities for mining. Fortunately, recently, necessary investments have been made in the extraction of oil and gas mines in the northern provinces of the country (Jawzjan and Sar-e-Pul).
Innovative Simulation Model for Analyzing the Effects of Supplier Disruptions on Supply Chain Distributors
In the current business landscape, supply chain disruptions, have become increasingly prevalent, impacting operational efficiency and profitability. These disruptions have resulted in significant ripple effects throughout the supply chain, resulting in increased delivery times and lost sales that, in extreme cases, can reach Statistics up to 76,169 units. Despite the growing recognition of the importance of managing these disruptions, comprehensive models that quantitatively assess their propagation and impact on downstream distributors are lacking. This study aims to address this gap by developing a discrete-time Markov chain model integrated with a Baye.sian network to analyze the ripple effects of supplier disruptions on distributors. The research focuses on key metrics such as lead times and lost sales, revealing that disruptions can increase lost sales by up to 44% in definite scenarios. By employing this dynamic modeling approach, the study illustrates the pathways through which disruptions propagate, identifies critical risk factors, and evaluates supplier vulnerabilities. The findings underscore the necessity for robust supply chain strategies to mitigate the effects of disruptions, providing valuable insights for managers to make informed decisions regarding supplier selection and inventory management. The scientific implications of this research contribute to the evolution of more comprehensive frameworks for disruption management in multi-tier supply chains, paving the way for future studies to expand on these insights and enhance supply chain resilience.
Supplier Disruptions, Supply Chain, Simulation Model, Ripple Effect, Distributors
Optimization of complex dynamic DC Microgrid using non-linear Bang Bang control
DC microgrids are gaining importance in various power electronics applications because of their efficiency in integrating diverse distributed energy sources. However, designing such complex systems is a great challenge, especially when it comes to high efficiency with minimum power losses and signal distortions that would affect the quality of the output. These systems are inherently dynamic and nonlinear, requiring robust control strategies to accomplish stability and quick dynamics under changing load and operating conditions. Linear and nonlinear control techniques can adopt solutions to the present challenges. For a proposed system, a nonlinear bang- bang control strategy is adopted for DC microgrid performance enhancement. It provides fast operation and enhances the system's overall stability. The performance of the system has been rigorously evaluated and analyzed under different scenarios to validate its effectiveness and reliability. Results are stated in favor of the feasibility and efficiency of the proposed control in the maintenance of the desired output characteristics.
DC Microgrid, Power Electronics, Non-linear Control, Bang-Bang Control, System Optimization, Signal Distortion, Dynamic Systems, Control Techniques, System Stability, Efficiency Enhancement
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Predictive Maintenance in Telecom: Artificial Intelligence for predicting and preventing network failures, reducing downtime and maintenance costs, and maximizing efficiency
Predictive maintenance (PdM), leveraging Artificial Intelligence (AI), is transforming the telecommunications industry by enabling the prediction and prevention of network failures. This proactive strategy reduces network outages and maintenance costs while enhancing overall system performance. By employing AI technologies such as machine learning algorithms, big data analytics, and sensor data analysis, telecom operators can identify patterns and anomalies indicative of potential component failures. AI-driven models continuously monitor network health, facilitating highly accurate failure predictions and enabling timely interventions. This article examines the application of AI for PdM within the telecom sector, focusing on its impact on operational efficiency, resource optimization, and service stability. The findings highlight significant cost reductions and operational improvements achievable with PdM systems. Furthermore, the paper discusses implementation challenges and key considerations for transitioning to these systems. The future outlook for telecom PdM suggests a continued evolution towards more automated, seamless network management and an improved customer experience.
Predictive Maintenance, Telecom, Artificial Intelligence, network failures, maintenance costs
Investigating the Drawbacks of Urban Trash in Taloqan City
According to a WHO report in 2012, five million people have died because of air pollution. It is estimated that air pollution reduces the quality of people's lives and the rate of efficiency; for this reason, the world pays 5 trillion dollars every year, and trash is the most influential reason for air pollution. In this research, which was done in Taloqan city, Takhar province, Afghanistan, we used a quantitative method consisting of a questionnaire paper among Taloqan city people from both male and female genders. We were looking for rules for trash in Taloqan city air pollution and strategies for getting people aware of trash drawbacks and strategies for trash prevention. We attached to the issue was accepted by the most percentage of Taloqan citizens, which trash is the most important factor of air pollution and destroyer the beauty of the city. for notifying people about religious erudite and educational organization teachers is the best option and about strategies for preventing from trash spreading, and it's disadvantage collecting the wastes separately is the most useful way also putting wastebasket among the city, processional work for trash removing and working individually for waste deleting are other ways that we found it in our research according to our research aims.
Environment pollution, Urban Trash, Air Quality, Solid Waste Management, Recycling Strategies, Health Hazards, Clean City Initiatives, Municipal Responsibility
Emerging Trends and Performance Evaluation of Eco-Friendly Construction Materials for Sustainable Urban Development
This work investigates the newest eco-friendly building materials, including bamboo, recycled concrete, insulation, and geopolymer cement and their importance for urban development. It analyzes ways that these innovations protect the environment even as buildings remain stable and functional. There is now a stronger emphasis on using green construction materials. The building and construction industry produces a lot of carbon and uses a lot of resources. It is needed to move towards greener building materials now more than ever. The research uses both a thorough literature review and a performance comparison of several selected eco-friendly materials. Valuable information was collected by reading academic studies, industry papers and environmental sources. It appears that many sustainable materials stand out for preserving the environment and benefiting the economy over time, but barriers to their use are expensive start-up prices, not being well recognized, and minimal formal support. The study emphasizes that using different steps together, such as making policies, giving incentives and educating people. It is important to make sure more sustainable materials are used in urban areas.
Eco-friendly construction materials, Green building, Construction innovation, Life cycle assessment , Green infrastructure, Building performance evaluation, Renewable materials
Copyright (c) 2021 https://creativecommons.org/licenses/by/4.0/
Quantity Take-Off Strategies: Reducing Errors in Roadway Construction Estimation
Accurate quantity take-off (QTO) plays a critical role in various phases of bridge construction projects, from bid preparation and cost management to project execution. This essay presents conventional QTO methods and com- pares them with technology-driven methods, namely the use of Bluebeam Revu software. It analyzes how new technology can make quantity take-offs more accurate and efficient. Typical issues such as errors of measurement in manual measurements, incorrect interpretation of plans, and differences in documentation are analyzed in their impact on accuracy of bids and cost overruns. With reviews of literature, case studies, and comparative studies, the study determines the extent to which automation, standard workflow, and integration of software can signifi- cantly reduce QTO-related mistakes. The study draws attention to the role of new QTO technologies to improve estimation accuracy and make processes leading towards better delivery and cost control in bridge construction.
quantity take-off, construction estimation, Bluebeam Revu, digital workflows, cost accuracy
Validation of the solder paste imprinting process: KOKI S3X58-M650-7 based on an experiment conducted with the use of the DoE methodology. experiment conducted at Universal Scientific Industrial Poland Sp. z o.o.
This paper presents an analysis of the influence of selected parameters of the wire bonding process on the occurrence of lift-off defects using the Design of Experiments (DOE) methodology. A structured experimental plan was used to evaluate the effect of key process factors, including ultrasonic power, bonding time, and bond force. Statistical analysis was performed to identify significant variables and optimize the process parameters. The results indicate specific interactions between variables that contribute to the minimization of lift-off defects, thus enhancing bond quality and production yield.
wire bonding, DOE, lift-off defect, process optimization, statistical analysis
Investigating the use of Axonometric Projection in Drawing Maps and its Effect on Students' Spatial Ability: A Case Study of Isometrics
The urgent need to acquire the spatial ability of students of Kabul Polytechnic University, which is considered one of the leading engineering universities in Afghanistan, constitutes the purpose of the research. Therefore, the main question is whether teaching axonometric in the traditional way can meet the main goal stated in the national curriculum, which is to increase the spatial ability of students. To answer this question, this article reviews axonometrics, its types, and application areas. It is worth mentioning that no research has been conducted in Afghanistan so far on the factors that develop students' spatial visualization skills together with applied geometry concepts and other graphic activities that strengthen or limit spatial ability. This article aims to investigate students' spatial visualization skills after completing the first year of teaching engineering graphics and its effect on strengthening spatial abilities, in which the role of axonometric teaching is appropriate. To verify the results of the case study approach, data were collected from the experiences of 7 professors of engineering graphics in the Department of Technical Drawing at Kabul Polytechnic University, and interviews were conducted with 42 first-year students of the Faculty of Civil Engineering at the end of the second semester. Data were collected through an open questionnaire, focused discussion on the topic, arrangement and organization of lessons, observations from the teaching process, and interviews. The results of the exams show that the professors were able to improve the spatial ability of the students by teaching different types of axonometric, especially isometrics.
Application and Development of Artificial Intelligence in Optical Imaging
Artificial Intelligence (AI), a hot topic, plays an extremely important role in many fields. Studies have shown that AI plays a significant role in promoting the development of optical imaging technology and has great potential for future development. This study analyses the application of AI in superresolution, hyperspectral, and adaptive systems; summarizes the difficulties encountered by AI in automatic identification and active 3D imaging; and speculates on the future development trend of AI, which shows that AI has great potential for development in the fields of virtual reality and medical imaging and may become an important aspect of research in the future.
Artificial intelligence, optical imaging, superresolution imaging, hyperspectral imaging, computer vision
Triboelectric Nanogenerators for Sustainable Environmental Remediation: A Comprehensive Review
This review highlights the extensive applications of triboelectric nanogenerators (TENGs) in environmental remediation, such as water treatment, air purification, soil remediation, and waste management. TENGs harvest mechanical energy from ambient sources and convert it into electrical energy through the triboelectric effect, offering a sustainable solution to self-powered environmental systems. Recent advances in materials, particularly biopolymers and nanocomposites, have significantly enhanced energy conversion efficiency and eco-friendliness. Despite their promise, challenges such as material limitations, efficiency issues, and scalability remain. This review emphasizes the importance of interdisciplinary collaboration and innovation in overcoming these challenges and realizing the full potential of TENGs in addressing critical global environmental issues.
Triboelectric nanogenerators, environmental remediation, sustainable energy, water treatment, self-powered systems
Machine Learning-Based Drought Classification Using Meteorological Data: Toward Smarter Environmental Models for Site Exploration
Drought presents a significant challenge to sustainable water management, agriculture, and geotechnical site assessment. Accurate and timely classification of drought severity is essential for anticipating environmental changes that impact soil behavior, moisture conditions, and subsurface dynamics. This study introduces a machine learning framework utilizing the Random Forest algorithm to classify drought intensity based on multi-year meteorological datasets. The dataset, comprising over 3 million records and 18 meteorological features, includes variables such as temperature, humidity, wind speed, and precipitation, serving as environmental indicators for drought conditions. The model predicts drought severity across six discrete classes (0–5), evaluated using precision, recall, F1 score, and confusion matrices. While achieving an overall accuracy of 75%, the model reveals performance challenges in detecting minority drought classes, underscoring the importance of class balancing and feature selection. Beyond drought prediction, this work supports the integration of environmental intelligence into geotechnical and site exploration processes. By informing early-stage terrain assessment with climate-responsive data, the framework lays groundwork for adaptive modeling in subsurface analysis, simulation, and exploration planning. The study demonstrates the value of machine learning in developing scalable, data-driven environmental models that enhance decision-making in both civil and environmental engineering applications.
Machine Learning, Meteorological Data, Data-Driven Decision Making, Site Exploration, Geotechnical Applications, Drought Classification
Effective Factors in Applying Sustainable Design to Architectural Projects: Shiraz Case
There is currently significant interest in the concept of sustainability. Sustainable architecture often serves as a symbol of sustainability in contemporary cities. The negative environmental impacts of buildings are worsening, making it crucial to find ways to minimize these effects and maximize the use of sustainable building materials. Architects and builders use various construction methods to reduce the environmental impact of structures. In architectural practice, the three core principles of sustainability—social, economic, and environmental factors—are often overlooked by architects during the design phase. Furthermore, sustainability has not been prioritized in architectural education and practice. Given the growing construction activities to meet Shiraz's development needs, applying sustainable design principles is a necessity. The aim of this study is to examine how sustainable design principles are applied by architects in Shiraz in their projects. To this end, 106 building architects were surveyed using a questionnaire. The data was analyzed using SPSS software and Pearson correlation coefficient. The study's results revealed that a significant number of architects apply sustainable design principles in their projects. Additionally, economic and environmental factors were identified as the most important considerations for implementing sustainable design principles in architectural projects, according to respondents. Statistical analysis also indicated a meaningful relationship between awareness of architectural concepts and their implementation in architectural projects.
Sustainable design principles, Renewable energy, Economic considerations, Environmental considerations, Shiraz city
Exploring the Development of Triboelectronic Nanogenerators in Wearable Devices
Given the growing demand for sustainable energy in the buildout of the Internet of Things (IoT) and the shortcomings of traditional energy generation methods for wearable electronic devices, this paper focuses on the application of triboelectric nanogenerators (TENGs) in the field of wearable devices. By utilizing the principle of interaction between contact electrification and electrostatic induction, we describe the various operating modes of TENGs in this paper, including the vertical contact separation mode, lateral sliding mode, single-electrode mode, and freestanding triboelectric-layer mode, and summarize the applications of TENGs in various fields. Wearable devices can be classified into fibre/yarn types, fabric types and patch types according to their morphology. For these categories, the progress made through material innovation and structural design, functional integration and performance optimization, as well as the enhancement of durability and comfort, are described in detail, while the effects of these approaches are discussed through specific application cases, including energy harvesting, flexible wearable and health monitoring aspects. Practical difficulties and challenges that hinder the development of TENGs in the wearable field are also discussed. Finally, future development trends and technological breakthroughs are proposed to provide new strategies and ideas for the development of TENGs.
triboelectric nanogenerator (TENG), wearable device, energy harvesting, wearable flexibility, healthcare monitoring
Investigating the Role of Graphic Geometry in Enhancing the Spatial Ability of Engineering Students
Graphical geometry is known as one of the basic subjects for improving spatial abilities of students at Kabul Polytechnic University and other engineering faculties. The main question is whether the methods of teaching graphic geometry with common methods at Kabul Polytechnic University meet all the demands that are included in the curriculum of various departments of this university? To answer this question, it is necessary to review and study basic studies on the factors of acquiring spatial abilities and the role of teaching the subject of graphic geometry as a main factor for learning and other inhibiting methods for increasing the spatial ability component. To verify the results of the research, two spatial ability tests were selected and, in these tests, pre-test and post-test were conducted using a quasi-experimental method with a control group in two disciplines with two different educational programs and the results of the tests were analysed. The results obtained from the tests on increasing spatial abilities show that the methods of teaching applied geometry have not significantly increased the spatial ability of students. In some cases, it has been tested with a significant reduction in both groups. One possible reason for these results can be attributed to the teaching of the subject of graphical geometry using conventional and classical methods at this university.
Spatial ability, conventional methods, applied geometry, spatial orientation
Remaining Useful Life Prediction of Turbofan Engines Using CNN-GRU: A Comparative Study on C-MAPSS Dataset
Accurate prediction of Remaining Useful Life (RUL) is crucial for effective predictive maintenance strategies in various industries. This study investigated the application of a combined Convolutional Neural Network (CNN) and Gated Recurrent Unit (GRU) architecture for predicting the RUL of turbofan engines using the C-MAPSS dataset. The CNN-GRU model leverages the complementary strengths of both components, with the CNN extracting spatial features from sensor data and the GRU capturing temporal dependencies in sequential engine data. Preprocessing techniques such as windowing and data reshaping were employed to optimize the input for the deep learning model. Six CNN-GRU configurations were tested to identify the optimal architecture for each C-MAPSS subset (FD001, FD002, FD003, and FD004). The model performance was evaluated using Root Mean Squared Error (RMSE) and Mean Squared Error (MSE) metrics. The results demonstrated that the CNN-GRU model effectively captured degradation patterns and accurately predicted RUL across all datasets, outperforming traditional machine learning methods, such as Multilayer Perceptron (MLP) and Support Vector Regression (SVR). The robustness and adaptability of the model to various operational scenarios highlight its potential for implementation in diverse industrial applications, enhancing predictive maintenance efforts, and improving overall operational efficiency. Future research should explore alternative configurations and consider increasing the number of training epochs to refine the prediction results further.
Remaining Useful Life (RUL); CNN (Convolutional Neural Network); GRU (Gated Recurrent Unit); PdM (Predictive Maintenance)
The Role of Sludge Dewatering Technologies in Modern Wastewater Management
Ever growing global population and water consumption levels are surging wastewater treatment demands to implement innovative technologies for sludge removal and dewatering. The process emphasizes protecting the ecosystem and the health of the population by making water free from effluents. This paper is a literature study about efficient use of sludge dewatering techniques to reduce the influence on the environment. Using qualitative study as a literature review process, the research continues to generate insights about different methods used for sludge dewatering processes. The study also creates insights into the advanced techniques for efficiency in operations. The outcomes highlights use of chemical, mechanical, and heating procedures for handling situations. The paper provides conclusions about the importance of emphasizing advanced water waste treatment procedures.
Waste water treatment, Sludge, dewatering, advanced sludge treatment, Sustainability, resource recovery, environmental impact, wastewater management