International Journal of Innovations in Science & Technology
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Optimization of Production Planning with Python’s SciPy: A Computational Study
Full text linkProduction planning optimization is the act of effectively distributing limited resources, including labor, materials, and equipment, to achieve production targets while optimizing profit and reducing waste. This study analyzes how optimization methods can be applied to production planning models in the cooking oil sector, with a particular emphasis on how linear programming (LP) can be used to handle usable quality limitations to maximize gross profit. The goal of this study is to find the best values for decision variables across a variety of inventory-based production frameworks. It is important in a manufacturing zone where input bound must be weighed against consumer needs, such as the industry of cooking oil. In order to provide a computational method for determining the perfect production levels, the study establishes a linear programming (LP) model and solves it using Python’s SciPy package. This optimization method uses objective functions involving dense matrices and numerical equations to solve the production planning problem. In calculating output levels and profit margins, the numerical results show a significant convergence, rating the effectiveness and credibility of the suggested approach in providing the optimal solution for practical industrial planning
Design of a Novel Compact and High-Efficiency T-Slot Microstrip Antenna for 28 GHz
Full text linkIn this paper, a novel microstrip patch antenna incorporating a T-shaped slot in the radiating patch is proposed to achieve high radiation efficiency and excellent impedance matching for 28 GHz millimeter-wave 5G applications. Utilizing the Rogers RT5880 substrate with a dielectric constant of 2.2, loss tangent of 0.0009, and 0.8mm thickness, the proposed antenna achieves a radiation efficiency of 81.18%, total efficiency of 81.17%, and a peak gain of 7.23 dB over a 2 GHz impedance bandwidth (27–29 GHz). A T-shaped slot is incorporated in the radiating patch to enhance impedance matching and bandwidth. Comparative analysis across ten substrates demonstrates the superiority of Rogers RT5880 in balancing performance, cost, and compactness for mm Wave 5G applications. This innovative microstrip patch antenna design marks a significant advancement in the field, delivering enhanced performance tailored for 5G wireless communication systems
Effects of Exogenous Calcium and Magnesium on Physio-Hormonal Attributes of Trigonella Foenum-Graecum l. Under Polyethylene Glycol (Peg) Induce Drought Stress
Full text linkDrought stress is one of the abiotic stresses that adversely affect the plant growth parameters and physio-hormonal attributes. In the current work, we study the adverse effects of induced PEG drought stress in Trigonella foenum-graecum L. in the presence of calcium and magnesium concentration. The experiment was conducted in the botanical garden of Abdul Wali Khan University Mardan in a completely random design. There are eight treatments and one control having each of the trees replicated. The nutrients of calcium and magnesium ratio (4, 2, and 0.18) were added to the plant after 30 days adding the polyethylene glycol of concentration of (0.6 Mpa and 0.2 MPa) for 8 days. The results show that drought stress induced by PEG had a significant effect on the growth and physio-hormonal indices of the plant. It was found that calcium and magnesium both reduce the adverse effects of polyethylene glycol. All treatments helped ascorbic acid, salicylic acid, and auxins to give plant possible growth and development in due time reducing the effects of PEG. Similarly, in enzymatic activities, the maximum lipid peroxidase contents at p >0.05 are found in calcium and magnesium ratio 0.18 and polyethylene glycol 0.2 Mpa. The maximum ascorbic acid peroxidase was found at p>0.05 in Ca/Mg ratio 4. It is concluded from the study that the calcium and magnesium ratio mitigated the adverse effects of polyethylene glycol on Trigonella foenum-graecum L. growth by promoting hormones and enzymatic activities under PEG-induced drought stress
Tablet Guard: Load Cell based Quality Assurance with Image Processing
Full text linkEvery week, the pharmaceutical business manufactures thousands of pills, each of which must be thoroughly checked before being distributed to customers. The proposed Tablet-Guard project addresses this issue through innovative integration of multiple advanced technologies including load cell technology, artificial intelligence, and a servo motor-based removal mechanism for pharmaceutical quality assurance. The system incorporates deep learning-based image processing, coupled with a load cell using an HX711 module to inspect and assess the quality of each tablet in a blister strip as it moves along the conveyor belt. It inspects defects including irregular shapes and incomplete blister strips. The utilization of YOLOv8 enables real-time defect detection with high accuracy (mAP of 0.995), enhancing efficiency and minimizing production line disruptions. By accurately detecting and addressing defects such as broken, missing, or cracked tablets within blister strips, the system significantly minimizes the likelihood of substandard products being distributed to consumers
Lower Limb Exo-Skeleton for Rehabilitation
Full text linkAbove-knee amputation remains a significant global issue, leaving many people physically disabled due to various natural and man-made causes, such as diseases, wars, and disasters. This article presents a novel, non-invasive active prosthesis based on electromyography (EMG). The proposed method offers a major advancement by achieving higher classification accuracy with minimal hardware requirements. Using EMG input signals, the active prosthesis controls three body postures: Sit, Stand, and Walk. These EMG signals are classified through two machine learning models: Support Vector Machine (SVM) and Long Short-Term Memory (LSTM) networks. Both models are evaluated based on accuracy. The results show that SVM outperforms LSTM, achieving a classification accuracy of 82%, while LSTM reaches 63%
Vortex Powerplant Implementation in A Coastal Community
Full text linkA gravitational water vortex power plant is an eco-friendly device that generates electricity from renewable energy sources. In this system, a turbine extracts energy from the vortex created by tangentially channeling water into a circular basin. This article aims to explore the feasibility of implementing vortex power plant technology in coastal communities using an experimental model. The study investigates the potential of wastewater as a renewable energy resource by analyzing the relationship between flow rate, torque, and efficiency under different material and pipe configurations, particularly in urban areas. For experimental purposes, Gujrat city was selected. The wastewater outlet points near Bolley Bridge discharge approximately 74,714,000 liters per day. Based on our survey, the average household water usage in Gujrat city is 500 liters per day. An experimental model was designed to estimate potential energy generation. The model\u27s design focused on optimizing the basin shape, inlets, outlets, and turbine configuration.
Using different pipes (cast iron and steel), the average water velocity and discharge rates were evaluated. The steel pipe produced higher velocity. Efficiency and production were further analyzed using LED lights, revealing that at 60 RPM, the system achieved significant efficiency and output voltage
Enhancing Quranic Ethics and Morality: An NLP- Based Semantic Search Model for Urdu Translation
Full text linkThe Quran offers unparalleled guidance on ethics and morality, but extracting relevant teachings from its Urdu translations remains a challenge due to conventional keyword-based search methods that lack contextual understanding. This research proposes a Natural Language Processing (NLP)--based query model designed to improve the retrieval of Quranic verses related to ethics and morality in Urdu translations. By integrating Sentence Transformers for semantic search and a custom synonym expansion module, the model enhances accuracy and relevance in retrieving verses. The dataset widely accepted Urdu translation of the Quran, and the system is evaluated using precision, recall, and relevance scoring metrics to ensure effectiveness. The study demonstrates how NLP techniques can bridge the gap between traditional Quranic studies and modern computational methods, providing scholars, educators, and researchers with an advanced tool for exploring Quranic ethics. The proposed system achieves high precision and recall, offering a more effective approach to Quranic verse retrieval compared to conventional keyword-based searches. The research also highlights future opportunities for expanding the model to support multiple languages and broader thematic searches, further enhancing accessibility to Quranic knowledge
Enhancing Open-Source Projects: The Synergy Between Code Readability Metrics and User Experience
Full text linkIntroduction /Importance of Study: The open-source project is a key driver of innovation in the so-called open ecosystem. However, the readability of code is still a major obstacle in having users successfully engaged and contributing.
Objective: This study explores how Code Readability Metrics Impact User Experience (UX) in OSS projects.
Novelty Statement: We examine code comments, structure of the code, and version control to discover their impact on user understanding and satisfaction.
Material and Method: For this, a survey has been conducted. In this survey, handed out to upper division (computing major) or first-year computer science students at university/graduates and post-grads in similar positions), we gathered feedback on projects written in Kotlin, Python, Swift, JavaScript, and Flutter.
Results and Discussion: Results show that readability correlates positively with a user\u27s perceived experience. The clarity in your structure, commenting on all parts of the code, and great version control lead to better user reception. The study’s findings show that when code is well-organized and understandable, users tend to have more positive experiences and like to use the software.
Concluding Remarks: Our study has demonstrated that better code readability translates into enhanced user experiences, which can inform developers and project managers on how best they can improve their practices
Sequestration of Carbon Dioxide via Mineral Carbonation to Produce Magnesium Carbonate: A Design Study
Full text linkThe rapid increase in atmospheric carbon dioxide (CO₂) due to industrialization and fossil fuel combustion has raised significant concerns about global warming. Carbon capture and storage (CCS) is a crucial technology for reducing greenhouse gas (GHG) emissions. This study presents the design of a mineral carbonation plant capable of sequestering 30 tons of CO₂ per day to produce magnesium carbonate (MgCO₃) using olivine as the feedstock.The process follows an ex-situ carbonation approach, where a mineral slurry reacts with CO₂ under controlled conditions. The plant design includes the development of key equipment such as a reactor, heat exchanger, and flash column, with a detailed process flow diagram (PFD) modeled in Aspen Plus. Material and energy balances ensure the operational feasibility of the system.With an effective conversion rate of 50%, the process accounts for realistic industrial limitations while maintaining reliability at scale. Heat recovery mechanisms, including a shell-and-tube heat exchanger, improve energy efficiency by minimizing heat loss. Optimized equipment design ensures process scalability and aligns with performance criteria to meet sequestration targets and product quality standards.The reliance on olivine, an abundant and cost-effective silicate mineral, highlights the economic and environmental advantages of this approach. The findings contribute to advancing sustainable CCS technologies, offering a viable solution for CO₂ mitigation while producing valuable industrial products such as MgCO₃ and by-product SiO₂
Investigation of Improvement in Current Carrying Capacity of Various Power Cables Using a Novel Arrangement
Full text linkPower cables are essential components of electrical systems, and their ability to carry current depends directly on the size of the conductor. With the rising cost of copper, efficiently utilizing a conductor\u27s current-carrying capacity has become increasingly important. To maximize this capacity, it is crucial to limit the temperature rise, either through effective heat dissipation or by optimizing the cable orientation in a trench. This study introduces new cable arrangements designed to lower the operating temperature of power cables, which in turn increases their current-carrying capacity. Different cable orientations for laying three-phase power cables in both single and double circuit configurations were examined. A high-resolution thermal imager was used to accurately measure the temperature. Two of the proposed orientations led to a significant reduction in operating temperature compared to the cable arrangements specified in BS 7671. These novel orientations can increase the current-carrying capacity by approximately 6% without the need to increase the cable size