GEOCHEMICAL AND GEOLOGICAL STUDIES OF OIL SHALES IN AB KASEH SECTION, KOUHRANG COUNTY, CHAHARMAHAL AND BAKHTIARI PROVINCE, IRAN
This study investigates the geochemistry of oil shales from the Ab Kaseh section in western Kohrang, Chaharmahal and Bakhtiari Province, Iran. Ten shale samples were collected for geochemical analyses, including Rock-Eval pyrolysis and XRF/ICP analyses. Ten thin sections were also prepared for petrographic analysis. A stratigraphic column and depos...
By Milad Tahmasebi, Farhad Ehya, Ghodratollah Rostami Paydar
POSSIBILITIES FOR MEASURING SMALL DISCHARGES USING A SIMPLE WEIR CONSTRUCTION
Measuring small flow rates often requires expensive equipment and is associated with inherent limitations. In practice, various measuring structures, such as weirs, are commonly constructed at specific locations to facilitate flow measurements. This paper proposes an innovative and low-cost measurement structure made from sewer pipes, incorporating...
By Petar Praštalo, Anica Milanović
COMBINING TRANSFORMERS AND FUZZY CLUSTERING BASED ON FUZZY FUNCTIONS FOR OPTIMAL UAV LOCALIZATION IN 5G WIRELESS NETWORKS
This paper introduces a new way to use UAVs in the 5G wireless network, based on Fuzzy C-Means (FCM) clustering and Transformer architecture for improved coverage, less energy consumption, and better Quality of Service (QoS). The new method improves user grouping by incorporating fuzzy distance functions into the FCM algorithm and it further trains...
By Sajjad H. Hasan, Mehdi Hamidkhani, Nasseer K. Bachache, Keyvan Mohebbi
THE SURVEY OF CLUSTER BASED DATA COLLECTION PROCESS FOR IOT ENABLED WIRELESS SENSOR NETWORK USING SEVERAL OPTIMIZATION TECHNIQUE
Offers a detailed analysis of optimization algorithms and routing protocols are created to overcome the issues on energy efficiency with the Internet of Things (IoT) Enabled Wireless Sensor Networks (WSNs). The study analyses nature-based metaheuristic methods such as the Genetic Algorithms, Particle Swarm Optimization, Firefly Optimization, Gray W...
By R. Abirami, K. Sathishkumar, Liu Guanzhou, M. Ramalingam, Wasim Ahmad, Ali Bostani
CROSS-PLATFORM HATE SPEECH DETECTION BY TARGET CATEGORY: EVALUATING TRADITIONAL AND TRANSFORMER MODELS ENHANCED WITH SMOTE
Societal and technological challenges are significant when it comes to cyberbullying, which is an ubiquitous issue in the social media space including Twitter, Facebook, YouTube, and Instagram. This paper will focus on the identification of hate speech that targets particular individuals, especially in the context of the data in Hindi language. It ...
By Rachna Narula, Poonam Chaudhary
BIO-INSPIRED ADAPTIVE ANOMALY DETECTION IN IOT USING ARTIFICIAL IMMUNE SYSTEMS AND DYNAMIC DETECTOR SELECTION
The rapid growth of the Internet of Things (IoT) brings new options to innovative healthcare, transportation, and industrial systems. However, this expansion also increases cyber threats to these infrastructures. Standard anomaly detection systems use fixed machine learning models. Such models require frequent retraining and are not very sensitive ...
By Ashraf Thaker Mahmood, Qais Rashid Ibrahim
HYBRID HYDROGEN ELECTRIC POWERTRAIN OPTIMIZATION FOR CONNECTED AUTONOMOUS VEHICLES IN URBAN TRAFFIC
The transition to low-carbon urban transport has catalyzed interest in hybrid hydrogen-electric powertrains for connected autonomous vehicles (CAVs), which offer zero tailpipe emissions, long driving range, and the potential to refuel quickly. The paper proposes a system-level optimization model for hybrid hydrogen-electric powertrains in urban tra...
By Anjali Goswami, Anjali Krushna Kadao
METARFM: A META-LEARNING FRAMEWORK FOR THE ADAPTIVE SELECTION OF RFM MODEL ARIANTS IN CUSTOMER SEGMENTATION
The Recency-Frequency-Monetary (RFM) model is a widely used method for customer segmentation, but its effectiveness depends on selecting the appropriate variant (e.g., weighted or entropy-based) for a given dataset. This selection process is typically manual and task-specific, leading to inconsistent results and limited generalizability. To address...
By F. Mary Magdalene Jane, V. Pream Sudha, S. Saranya, P. Usha, V. Santhana Lakshmi, S.R. Kalaiselvi
NEUROMORPHIC-INSPIRED HYBRID COGNITIVE MODEL FOR SELF-OPTIMIZING RESOURCE MANAGEMENT IN 6G EDGE NETWORKS
Introduction: The 6G world requires connected intelligence, but there is a crucial paradox between the standards of Large Language Model (LLM) and edge constraints. The premium devices have up to 6-12GB of DRAM, whereas the typical 175B models need 350GB of storage, which is 30 times that of the premium version. Literature Survey: It has been...
By Reji K Kollinal, Mariya T Cheeran
A TWO – ECHELON INVENTORY MODEL FOR DETERIORATING ITEMS WITH RAMP – TYPE DEMANDS AND VARIABLE HOLDING COSTS
It presents a dynamic model of inventory management of the deteriorating items with time-sensitive demand and variable holding costs. The model is used to solve the problem in industries where demand is seasonal or because of other external conditions, like weather or market conditions. A two-tier inventory model is implemented as a way of minimizi...
By Prashant Sharma, Birendra Kumar Chauhan, Gajraj Singh