arXiv subjects

Md. Ashraful Islam

Publications and source records attributed to Md. Ashraful Islam.

12 recordsLinked to original sources

arXiv2025

Predicting Gas Well Performance with Decline Curve Analysis: A Case Study on Semutang Gas Field

Decline-curve analysis (DCA) is a widely utilized method for production forecasting and estimating remaining reserves in gas reservoir. Based on the assumptions that past production trend can be mathematically characterized and used to predict future performance. It relies on historical production data and assumes that production methods remain unchanged throughout the analysis. This method is particularly valuable due to its accuracy in forecasting and its broad acceptance within the industry. Wells in the same geographical area and producing from similar geological formations often exhibit similar decline curve parameters. This study applies DCA to forecast the future production performance and estimate the ultimate recovery for the Semutang gas field's well 5 in Bangladesh. Using historical production data, decline curves were generated based on exponential, hyperbolic, and harmonic model equations. The cumulative production estimations were 11,139.34 MMSCF for the exponential model, 11,620.26 MMSCF for the hyperbolic model, and 14,021.92 MMSCF for the harmonic model. In terms of the well's productive life, the estimates were 335.13 days, 1,152 days, and 22,611 days, respectively. Among these models, the hyperbolic decline provided the most realistic forecast, closely aligning with observed production trend. The study highlights the importance of selecting an appropriate decline model for accurate production forecasting and reserve estimation, which is essential for effective reservoir management and resource optimization.

cs.CE↗

arXiv2025

Automatic High-Level Test Case Generation using Large Language Models

We explored the challenges practitioners face in software testing and proposed automated solutions to address these obstacles. We began with a survey of local software companies and 26 practitioners, revealing that the primary challenge is not writing test scripts but aligning testing efforts with business requirements. Based on these insights, we constructed a use-case $\rightarrow$ (high-level) test-cases dataset to train/fine-tune models for generating high-level test cases. High-level test cases specify what aspects of the software's functionality need to be tested, along with the expected outcomes. We evaluated large language models, such as GPT-4o, Gemini, LLaMA 3.1 8B, and Mistral 7B, where fine-tuning (the latter two) yields improved performance. A final (human evaluation) survey confirmed the effectiveness of these generated test cases. Our proactive approach strengthens requirement-testing alignment and facilitates early test case generation to streamline development.

cs.SE↗

arXiv2025

CODESIM: Multi-Agent Code Generation and Problem Solving through Simulation-Driven Planning and Debugging

Large Language Models (LLMs) have made significant strides in code generation and problem solving. Current approaches employ external tool-based iterative debuggers that use compiler or other tool-based runtime feedback to refine coarse programs generated by various methods. However, the effectiveness of these approaches heavily relies on the quality of the initial code generation, which remains an open challenge. In this paper, we introduce CodeSim, a novel multi-agent code generation framework that comprehensively addresses the stages of program synthesis-planning, coding, and debugging-through a human-like perception approach. As human verifies their understanding of any algorithms through visual simulation, CodeSim uniquely features a method of plan verification and internal debugging through the step-by-step simulation of input/output. Extensive experiments across seven challenging competitive problem-solving and program synthesis benchmarks demonstrate CodeSim's remarkable code generation capabilities. Our framework achieves new state-of-the-art (pass@1) results-(HumanEval 95.1%, MBPP 90.7%, APPS 22%, and CodeContests 29.1%). Furthermore, our method shows potential for even greater enhancement when cascaded with external debuggers. To facilitate further research and development in this area, we have open-sourced our framework in this link (https://kagnlp.github.io/codesim.github.io/).

cs.CL↗

arXiv2024

MapCoder: Multi-Agent Code Generation for Competitive Problem Solving

Code synthesis, which requires a deep understanding of complex natural language problem descriptions, generation of code instructions for complex algorithms and data structures, and the successful execution of comprehensive unit tests, presents a significant challenge. While large language models (LLMs) demonstrate impressive proficiency in natural language processing, their performance in code generation tasks remains limited. In this paper, we introduce a new approach to code generation tasks leveraging multi-agent prompting that uniquely replicates the full cycle of program synthesis as observed in human developers. Our framework, MapCoder, consists of four LLM agents specifically designed to emulate the stages of this cycle: recalling relevant examples, planning, code generation, and debugging. After conducting thorough experiments, with multiple LLM ablations and analyses across eight challenging competitive problem-solving and program synthesis benchmarks, MapCoder showcases remarkable code generation capabilities, achieving new state-of-the-art results (pass@1) on HumanEval (93.9%), MBPP (83.1%), APPS (22.0%), CodeContests (28.5%), and xCodeEval (45.3%). Moreover, our method consistently delivers superior performance across various programming languages and varying problem difficulties. We open-source our framework at https://github.com/Md-Ashraful-Pramanik/MapCoder.

cs.CL↗

arXiv2020

A Survey on Deep Learning Based Point-Of-Interest (POI) Recommendations

Location-based Social Networks (LBSNs) enable users to socialize with friends and acquaintances by sharing their check-ins, opinions, photos, and reviews. Huge volume of data generated from LBSNs opens up a new avenue of research that gives birth to a new sub-field of recommendation systems, known as Point-of-Interest (POI) recommendation. A POI recommendation technique essentially exploits users' historical check-ins and other multi-modal information such as POI attributes and friendship network, to recommend the next set of POIs suitable for a user. A plethora of earlier works focused on traditional machine learning techniques by using hand-crafted features from the dataset. With the recent surge of deep learning research, we have witnessed a large variety of POI recommendation works utilizing different deep learning paradigms. These techniques largely vary in problem formulations, proposed techniques, used datasets, and features, etc. To the best of our knowledge, this work is the first comprehensive survey of all major deep learning-based POI recommendation works. Our work categorizes and critically analyzes the recent POI recommendation works based on different deep learning paradigms and other relevant features. This review can be considered a cookbook for researchers or practitioners working in the area of POI recommendation.

cs.IR↗

arXiv2018

Comprehending Real Numbers: Development of Bengali Real Number Speech Corpus

Speech recognition has received a less attention in Bengali literature due to the lack of a comprehensive dataset. In this paper, we describe the development process of the first comprehensive Bengali speech dataset on real numbers. It comprehends all the possible words that may arise in uttering any Bengali real number. The corpus has ten speakers from the different regions of Bengali native people. It comprises of more than two thousands of speech samples in a total duration of closed to four hours. We also provide a deep analysis of our corpus, highlight some of the notable features of it, and finally evaluate the performances of two of the notable Bengali speech recognizers on it.

eess.AS↗

arXiv2012

Performance Evaluation of an Orthogonal Frequency Division Multiplexing based Wireless Communication System with implementation of Least Mean Square Equalization technique

Orthogonal Frequency Division Multiplexing (OFDM) has recently been applied in wireless communication systems due to its high data rate transmission capability with high bandwidth efficiency and its robustness to multi-path delay. Fading is the one of the major aspect which is considered in the receiver. To cancel the effect of fading, channel estimation and equalization procedure must be done at the receiver before data demodulation. This paper mainly deals with pilot based channel estimation techniques for OFDM communication over frequency selective fading channels. This paper proposes a specific approach to channel equalization for Orthogonal Frequency Division Multiplex (OFDM) systems. Inserting an equalizer realized as an adaptive system before the FFT processing, the influence of variable delay and multi path could be mitigated in order to remove or reduce considerably the guard interval and to gain some spectral efficiency. The adaptive algorithm is based on adaptive filtering with averaging (AFA) for parameter update. Based on the development of a model of the OFDM system, through extensive computer simulations, we investigate the performance of the channel equalized system. The results show much higher convergence and adaptation rate compared to one of the most frequently used algorithms - Least Mean Squares (LMS).

cs.IT↗

arXiv2012

Effect of AWGN & Fading (Raleigh & Rician) channels on BER performance of a WiMAX communication System

The emergence of WIMAX has attracted significant interests from all fields of wireless communications including students, researchers, system engineers and operators. The WIMAX can also be considered to be the main technology in the implementation of other networks like wireless sensor networks. Developing an understanding of the WIMAX system can be achieved by looking at the model of the WIMAX system. This paper discusses the model building of the WIMAX physical layer using computer MATLAB 7.5 versions. This model is a useful tool for BER (Bit error rate) performance evaluation for the real data communication by the WIMAX physical layer under different communication channels AWGN and fading channel (Rayleigh and Rician), different channel encoding rates and digital modulation schemes which is described in this paper. This paper investigates the effect of communication channels of IEEE 802.16 OFDM based WIMAX Physical Layer. The performance measures we presented in this paper are: the bit error rate (BER) versus the ratio of bit energy to noise power spectral density (Eb/No). The system parameters used in this paper are based on IEEE 802.16 standards. The simulation model built for this research work, demonstrates that AWGN channel has better performance than Rayleigh and Rician fading channels. Synthetic data is used to simulate this research work.

cs.NI↗

arXiv2010

A System for Smart Home Control of Appliances based on Timer and Speech Interaction

The main objective of this work is to design and construct a microcomputer based system: to control electric appliances such as light, fan, heater, washing machine, motor, TV, etc. The paper discusses two major approaches to control home appliances. The first involves controlling home appliances using timer option. The second approach is to control home appliances using voice command. Moreover, it is also possible to control appliances using Graphical User Interface. The parallel port is used to transfer data from computer to the particular device to be controlled. An interface box is designed to connect the high power loads to the parallel port. This system will play an important role for the elderly and physically disable people to control their home appliances in intuitive and flexible way. We have developed a system, which is able to control eight electric appliances properly in these three modes.

cs.HC↗

arXiv2009

Comparative Study of Different Guard Time Intervals to Improve the BER Performance of Wimax Systems to Minimize the Effects of ISI and ICI under Adaptive Modulation Techniques over SUI1 and AWGN Communication Channels

The WIMAX technology based on air interface standard 802.16 wireless MAN is configured in the same way as a traditional cellular network with base stations using point to multipoint architecture to drive a service over a radius up to several kilometers. The range and the Non Line of Sight (NLOS) ability of WIMAX make the system very attractive for users, but there will be slightly higher BER at low SNR. The aim of this paper is the comparative study of different guard time intervals effect for improving BER at different SNR under digital modulation (QPSK, 16QAM and 64QAM) techniques and different communication channels AWGN and fading channels Stanford University Interim (SUI 1) of an WIMAX system. The comparison between these effects with Reed-Solomon (RS) encoder with Convolutional encoder (half) rated codes in FEC channel coding will be investigated. The simulation results of estimated Bit Error Rate (BER) displays that the implementation of interleaved RS code (255,239,8) with (half) rated Convolutional code of 0.25 guard time intervals under QPSK modulation technique over AWGN channel is highly effective to combat in the Wimax communication system. To complete this performance analysis in Wimax based systems, a segment of audio signal is used for analysis. The transmitted audio message is found to have retrieved effectively under noisy situation.

cs.NI↗

arXiv2009

Performance Evaluation of Wimax Physical Layer under Adaptive Modulation Techniques and Communication Channels

Wimax (Worldwide Interoperability for Microwave Access) is a promising technology which can offer high speed voice, video and data service up to the customer end. The aim of this paper is the performance evaluation of an Wimax system under different combinations of digital modulation (BPSK, QPSK, 4 QAM and 16 QAM) and different communication channels AWGN and fading channels (Rayleigh and Rician). And the Wimax system incorporates Reed Solomon (RS) encoder with Convolutional encoder with half and two third rated codes in FEC channel coding. The simulation results of estimated Bit Error Rate (BER) displays that the implementation of interleaved RS code (255, 239, 8) with two third rated Convolutional code under BPSK modulation technique is highly effective to combat in the Wimax communication system. To complete this performance analysis in Wimax based systems, a segment of audio signal is used for analysis. The transmitted audio message is found to have retrieved effectively under noisy situation.

cs.PF↗

arXiv2009

Hardware Virtualization Support In INTEL, AMD And IBM Power Processors

At present, the mostly used and developed mechanism is hardware virtualization which provides a common platform to run multiple operating systems and applications in independent partitions. More precisely, it is all about resource virtualization as the term hardware virtualization is emphasized. In this paper, the aim is to find out the advantages and limitations of current virtualization techniques, analyze their cost and performance and also depict which forthcoming hardware virtualization techniques will able to provide efficient solutions for multiprocessor operating systems. This is done by making a methodical literature survey and statistical analysis of the benchmark reports provided by SPEC (Standard Performance Evaluation Corporation) and TPC (Transaction processing Performance Council). Finally, this paper presents the current aspects of hardware virtualization which will help the IT managers of the large organizations to take effective decision while choosing server with virtualization support. Again, the future works described in section 4 of this paper focuses on some real world challenges such as abstraction of multiple servers, language level virtualization, pre-virtualization etc. which may be point of great interest for the researchers.

cs.AR↗