ICONTECH INTERNATIONAL JOURNAL

Awareness and Use of Solar Energy as Alternative Power Source for ICT Facilities in Kogi State, Nigeria

Momoh Adams Momoh Ansuze — 2025-06-26

English

Unveiling The Ripple Effect: How Climate Change Transforms Our Abiotic Environment And Influences Regional Development

Igor TROFIMOV — 2025-06-26

Aim: Climate change represents one of the most profound global challenges of the 21st century, with far-reaching implications for abiotic environmental factors that shape the Earth's ecosystems. This paper examines the complex effects of climate change on essential abiotic elements, including temperature, precipitation, PH, and elucidates how these alterations are transforming global ecosystems. The discussion emphasizes the imperative for the implementation of adaptation and mitigation strategies, encompassing policy measures, conservation initiatives and sustainable practices, in order to address the detrimental impact of climate change on abiotic conditions and ensure the resilience of both natural and human systems.

Methodology; Through a comprehensive review of current research and modelling efforts, this paper highlights the critical importance of proactive measures to mitigate climate change and protect the environment. focusing mainly on aspects dealing with temperature variability tackling the Impact of increasing global temperatures, also alteration of thermal regimes, effects on soil and water temperatures as well as consequences for species' survival, migration patterns, and ecosystem productivity The article concludes with a presentation of particular examples of ecosystems affected by climate change, including coral reefs and Arctic tundra, in order to provide a more vivid illustration of the points being made. The addition of visuals in the form of graphs, some charts and infographics, are used to visually represent data on temperature changes, precipitation patterns or species migration trends. The article ends with considering approaches towards the problem of ocean acidification and PH changes

Nano Fertilization: Paving the Way for Sustainable Plant Nutrition

Marina TODOR STOJANOVA — 2025-06-26

Nanotechnology involves manipulating materials at the nanoscale (1 to 100 nm), resulting in enhanced physical, chemical, biological, mechanical, magnetic, optical, and electrical properties. In agriculture, nanotechnology has diverse applications, including in fertilization, irrigation, pest control, packaging, and food processing. Nano fertilizers are particularly important for advancing sustainable agriculture and promoting environmental health. These fertilizers utilize nanoparticles with unique properties that improve effectiveness, leading to increased fruit productivity, enhanced yield quality, and extended shelf life. Nano fertilizers achieve these benefits by influencing various plant traits, such as morphological, physiological, and molecular characteristics. They are created by combining plant nutrients with nanomaterials, coating nutrients with nanomaterial layers, or forming nano-sized emulsions. Additionally, nano biofertilizers, which combine both natural and synthetic elements, enhance nutrient bioavailability and soil fertility, making them more efficient than traditional fertilizers. By improving sustainability in global food production, nano fertilizers represent a promising solution for addressing agricultural challenges. This review aims to explore the role of nano fertilizers in agricultural production, discussing their advantages over conventional fertilizers and distinguishing between different types of nano fertilizers.

Sustainable Metallurgy: Innovations In Green Processing, Recycling, And Alloy Development

Paul Nehemiah Ojoaliwa PAUL OMALE — 2025-06-26

The metallurgical industry is facing growing pressure to adopt sustainable practices due to
environmental concerns and resource depletion. This paper explores recent advancements in
green processing technologies, metal recycling, and the development of eco-friendly alloys. Key
innovations include energy-efficient extraction techniques, circular economy approaches, and
sustainable alloy design. These developments are crucial for reducing carbon footprints and
ensuring resource efficiency. This study highlights industry best practices, emerging
technologies, and future directions for sustainable metallurgy. And also aims to bring together
researchers, industry experts, and policymakers to explore the latest advancements in sustainable
metal production. By fostering collaboration and knowledge exchange, this event will contribute
to shaping a greener, more resilient metallurgical industry that meets the demands of the future.

Exploring the Impact of Yam Minisett Technology Adoption on the Income and Technical Efficiency of Yam Producers in Nigeria

Caleb ADEWALE — 2025-06-26

The yam minisett technique (YMT), designed to address the shortage of seed yams, has been widely adopted by farmers compared to other scientifically enhanced yam propagation methods. Yet, there remains a dearth of information regarding how its adoption impacts farmers' productivity. This study examined the impact of YMT adoption on the income and technical efficiency of yam producers in Nigeria. A multistage sampling technique was used to collect primary data from 120 farmers with the aid of a structured questionnaire. Data were analyzed using stochastic frontier and propensity score matching. Results revealed that gender, educational level, household size, adoption, and extension contact significantly influenced the technical efficiency of yam producers. The adoption of YMT had a significant effect on the technical efficiency and income of yam producers. Adopters and non-adopters had mean technical efficiency of 97% and 96% respectively however non-adopters had lower minimum individual technical efficiencies. It is recommended that the adoption of the yam minisett technology should be encouraged among farmers in Nigeria because of its potential to enhance their technical efficiency and income levels. The government should ensure that there is a provision of adequate planting materials for yam minisett technology as a measure to encourage the adoption of crop technologies.

Relatively Weighted Three Factor Novel Fitness Function for Multi-Objective Optimization of Mspa Using Genetic Algorithm

Manoj B — 2025-06-26

Micro Strip Patch Antenna (MPSA) is designed using standard design equations and multiple antenna parameters; mainly patch dimensions as variables. The theoretical values may not result in the desired performance. For over a quarter century, evolutionary algorithms have played a pivotal role in optimizing the design variables of MSPA, Genetic Algorithm (GA) being the most popular among them. The success of using GA for the optimization of MSPA lies in the right formation of fitness function (FF) using the right performance parameters. This study introduces a relatively weighted, three-factor novel FF for multi-objective performance optimization of MSPA by optimizing multiple antenna design parameters using GA. The proposed FF guided GA to simultaneously achieve multiple performance optimization objectives: resonance frequency fr of 5 GHz, bandwidth (BW) exceeding 300 MHz, and return loss S11 better than −50 dB by optimizing four critical design parameters—antenna width, length, and slot positions along the x and y axes. The performance of the proposed FF is then compared with six existing FFs from prior research, each with limited optimization capabilities. The results demonstrate that the proposed FF significantly improves optimization outcomes, yielding an MSPA that resonates exactly at 5 GHz, achieves a bandwidth of 315 MHz, and enhances return loss to −54.84 dB. These results confirm the effectiveness of the proposed FF in achieving high-performance, multi-objective, multi-parameter optimization of MSPAs using GA

A Comparative Study on the Wear Behaviour of TiN, TiAlN, and TiAlSiN Coatings on X100CrMoV5 Steel

Elif BAŞER — 2025-06-26

This study investigated the wear behaviour of TiN, TiAlN, and TiAlSiN-coated X100CrMoV5 steels, using physical vapour deposition, under a range of applied loads (2, 6, and 10 N) and sliding speeds (0.1, 0.2, and 0.3 m/s). Hardness measurements revealed a progressive increase in hardness from TiN to TiAlN, with TiAlSiN exhibiting the highest value, directly correlating with the observed wear performance. The TiAlN and TiAlSiN coatings achieved hardness values that were approximately 1.36 and 1.6 times greater than that of the TiN coating, respectively. Statistical analysis utilizing regression modelling and ANOVA demonstrated a strong and significant influence of both load and sliding speed, as well as their interaction effect, on the wear rate for all three coatings. Notably, the applied load exerted a more substantial impact on the wear rate compared to the sliding speed. The results of wear tests indicated that the TiAlSiN coating consistently yielded the lowest wear rate, signifying a significant enhancement in the wear resistance of the X100CrMoV5 steel. The findings underscore the potential of TiAlSiN coatings as a highly effective surface modification strategy for improving the durability and extending the lifespan of X100CrMoV5 steel components operating in tribologically demanding environments.

Bibliometric Analysis Of Prostate Cancer And Deep Learning

Nihan ÖZBALTAN — 2025-06-26

One of the most common tumors in men around the world, prostate cancer presents considerable obstacles to early detection, precise diagnosis, and efficient treatment planning. Innovative approaches to better managing prostate cancer have been made possible by recent developments in artificial intelligence (AI), especially deep learning. Deep learning algorithms provide previously unheard-of precision in pattern recognition, predictive modeling, and decision support systems due to their capacity to evaluate complicated datasets like clinical records, genetic profiles, and medical imaging. To thoroughly assess the corpus of literature on the relationship between deep learning and prostate cancer, this study performs a bibliometric analysis. Through an analysis of publishing patterns, highly referenced publications, well-known authors, top journals, and new fields of study, this report offers a thorough summary of the state of deep learning applications in prostate cancer.

The results of the study demonstrate the advancements made in applying deep learning to problems including survival analysis, tumor detection, segmentation, and treatment response prediction. These developments could improve patient outcomes, optimize treatment plans, and increase the accuracy of diagnoses. Additionally, this study highlights important research gaps and avenues for further investigation, promoting multidisciplinary cooperation among radiologists, oncologists, and AI researchers. This work intends to direct future research efforts and expedite the incorporation of AI-driven solutions into clinical practice by illuminating the revolutionary potential of deep learning in the management of prostate cancer.

A General Overvıew of Agrıcultural Measures That Can Be Taken to Reduces the Negatıve Effects That May Occur In Agrıculture Durıng the Adaptatıon Process to Global Clımate Change

Meltem AYAZ — 2025-06-26

Agriculture and climate are two concepts that we cannot think of separately. It is inevitable that climate change will be a threat to the Mediterranean Basin and Turkey, which is a part of it, as it is all over the world. Changes in temperature and rainfall, extreme weather events, and changes in the amount of carbon dioxide in the atmosphere are risks not only in social areas such as ecology, economy, transportation and tourism, but also in the field of agricultural production.

"Climate Scenarios" have been developed by the General Directorate of Meteorology (MGM) in order to support the activities carried out within the scope of adaptation and combat against climate change for all sectors in our country. By looking at the climate scenarios developed for various years using GFDL-ESM2M global climate model data and RegCM4.3.4 regional climate model, in the system considered, even in the most optimistic scenario (RCP4.5) for the years 2016-2040, the temperature will increase between 0.5°C and 1.5°C. It is estimated that there will be an increase between °C. It is estimated that the effects will be more noticeable especially in the Aegean and Mediterranean Regions during the summer seasons when we will be exposed to a temperature increase of over 1.5°C. It is estimated that the effects will be more noticeable, especially in the Aegean and Mediterranean Regions, during the summer seasons when we will be exposed to temperature increases above 1.5°C. If we look at precipitation, an increase of around 10% is expected throughout our country, excluding Southeastern Anatolia, the Lakes Region and the Marmara Region, especially in the spring season, and a decrease of around 20% in precipitation is expected in the autumn. It is predicted that there will be a decrease in precipitation in most of our country during the winter period.

It is estimated that the effects will be more noticeable, especially in the Aegean and Mediterranean Regions, during the summer seasons when we will be exposed to temperature increases above 1.5°C. If we look at precipitation, an increase of around 10% is expected throughout our country, excluding Southeastern Anatolia, the Lakes Region and the Marmara Region, especially in the spring season, and a decrease of around 20% in precipitation is expected in the autumn. It is predicted that there will be a decrease in precipitation in most of our country during the winter period.

Job Satisfaction as a Mediator in The Emotional Intelligence and Organizational Commitment Relationshıp: Evidence From The Manufacturing Sector in Jordan

Tolga TÜRKÖZ — 2025-06-26

The first aim of this article is to examine the effect of Emotional Intelligence (EI) on Organizational Commitment (OC), and the second aim is to understand whether Job Satisfaction (JS) has a mediating role in this relationship. The study was conducted with data obtained from different manufacturing companies in Jordan. The sample consists of 411 employees. The research was conducted with a quantitative method using reliable and valid scales to measure EI, JS and OC. Normality tests, descriptive statistics, correlation and regression analysis were performed on the obtained data using the SPSS program. In addition, the mediation test findings were confirmed using the SPSS PROCESS Macro application. According to the findings, EI has a significant and positive effect on both JS and OC. It was found that JS partially mediates the relationship between EI and OC. This finding shows that the positive effect of EI on OC works through increased JS. This result shows that employees with high emotional intelligence experience higher JS, which strengthens their commitment to the organization. The study supports the importance of EI and JS in promoting OC and contributes to the literature by providing empirical evidence. The results emphasize the need for manufacturing companies to develop workplace policies that can enhance employees' EI and JS, so that companies can cultivate a more committed workforce.