아브둘 라히마 라히만 교수

Recently Indian Handwritten character recognition is getting much more attention and researchers are contributing a lot in this field. But Malayalam, a South Indian language has very less works in this area and needs further attention. This paper focuses on an efficient algorithm for recognizing the handwritten Malayalam characters. Malayalam OCR is a complex task owing to the various character scripts available and more importantly the difference in ways in which the characters are written. The

Recently, the use of IoT (Internet of Things) based system has been expanded with inestimable Internet resources. The system demonstrates the creation of innovative systems that facilitate control and supervision regardless of distance and time. In a poultry house, both temperature and humidity levels should be monitored regularly in ensuring the system runs smoothly. It needs to be monitored 24/7 to avoid incidents that caused the temperature rises too high. This paper highlights the IoT soluti

Abstract The applications of the Internet of Things in different areas and the resources that demand these applications are on the increase. However, the limitations of the IoT devices such as processing capability, storage, and energy are challenging. Computational offloading is introduced to ameliorate the limitations of mobile devices. Offloading heavy data size to a remote node introduces the problem of additional delay due to transmission. Therefore, in this paper, we proposed Dynamic tasks

Abstract With the increasing level of IoT applications, computation offloading is now undoubtedly vital because of the IoT devices limitation of processing capability and energy. Computation offloading involves moving data from IoT devices to another processing layer with higher processing capability. However, the size of data offloaded is directly proportional to the delay incurred by the offloading. Therefore, introducing data reduction technique to reduce the offloadable data minimizes delay

This review article provides a comprehensive analysis of the latest advancements and persistent challenges in Software-Defined Wide Area Networks (SD-WANs), with a particular emphasis on the multi-objective Controller Placeme... | Find, read and cite all the research you need on Tech Science Press

There are many scientific applications ranging from weather prediction to oil and gas exploration that requires high-performance computing. It aids industries and researchers to enrich further their advancements. With the advent of general purpose computing over GPUs, most of the applications above are shifting towards High-Performance Computing (HPC). Agent-based crowd simulation is one of the candidates that requires high-performance computing. This type of application is used to predict crowd

Tawaf ritual performed during Hajj and Umrah is one of the most unique, large-scale multi-cultural events in this modern day and age. Pilgrims from all over the world circumambulate around a stone cube structure called Ka'aba. Disasters at these types of events are inevitable due to erratic behaviours of pilgrims. This has prompted researchers to present several solutions to avoid such incidents. Agent-based simulations of a large number of pilgrims performing different the ritual can provide th

Solid state disk (SSD) is a new storage device that utilizes semiconductor memory chips (e.g. RAM, EEPROM, flash memory) to store data rather than using conventional spinning platters and moving heads found in conventional magnetic disk drive. The term of “solid state” means there are no moving parts involve in accessing, storing and retrieving required data on the drive. Several benefits offered by the SSD drives due to absent of moving mechanical components are high access speed, light weight,

Modern Software-Defined Wide Area Networks (SD-WANs) require adaptive controller placement addressing multi-objective optimization where latency minimization, load balancing, and fault tolerance must be simultaneously optimized. Traditional static approaches fail under dynamic network conditions with evolving traffic patterns and topology changes. This paper presents a novel hybrid framework integrating Gaussian Mixture Model (GMM) clustering with Multi-Agent Reinforcement Learning (MARL) for dy

Software-Defined Wide Area Networks (SD-WANs) require optimal controller placement to minimize latency, balance loads, and ensure reliability across geographically distributed infrastructures. This paper introduces NA-GMM (Network-Aware Gaussian Mixture Model), a novel multi-objective optimization framework addressing key limitations in current controller placement approaches. Three principal contributions distinguish NA-GMM: (1) a hybrid distance metric that integrates geographic distance, netw