International Journal of Computer Science and Technology

International Journal of Computer Science and Technology Vol. 2, No. 4, April 2000 | pp. 25–32

DOI: 10.46882/2000/IJCST/000016

Research Article

Title: An Object-Oriented Database Schema Transformation Model for Heterogeneous Data Migration

Names of Authors: Robert K. Jones¹, Amara Okafor²

Authors’ Affiliations: ¹Department of Software Engineering, Australian National University, Canberra, Australia; ²Department of Computer Science, University of Ibadan, Ibadan, Nigeria.

Abstract:
Enterprise computing centers face significant interoperability and data-loss challenges when migrating legacy legacy records into modern object-oriented database management architectures. Structural differences between traditional tabular records and hierarchical object classes often cause runtime exceptions, broken relational linkages, and slow querying speeds. This paper introduces a formal, automated schema transformation model designed to map entity-relationship structures into optimized object-oriented formats smoothly. The framework uses a structural dependency mapping engine that evaluates table constraints, foreign key mappings, and cardinality indices before constructing equivalent class inheritance trees. We tested the execution efficiency of our migration engine by transferring an enterprise resource planning database containing 50 million records and 400 interconnected tables. The system completed the complete structural transformation process without requiring human repair scripts, achieving 100% data integrity preservation. Post-migration query benchmarks show a 31.4% improvement in complex data retrieval operations, validating that our object nesting logic successfully avoids high-overhead join statements in production environments.

Keywords: Database Migration, Schema Transformation, Object-Oriented Databases, Data Integrity, Relational Mapping, Enterprise Software.

Manuscript Timeline: Received: January 08, 2000; Revised: February 18, 2000; Accepted: March 11, 2000; Published: April 22, 2000.

Citation: Jones, R. K., & Okafor, A. (2000). An Object-Oriented Database Schema Transformation Model for Heterogeneous Data Migration. International Journal of Computer Science and Technology, 2(4), 25–32.

International Journal of Computer Science and Technology Vol. 2, No. 3, March 2000 | pp. 17–24

DOI: 10.46882/2000/IJCST/000015

Research Article

Title: Dynamic Buffer Management for Enhancing Quality of Service in Packet-Switched Networks

Names of Authors: Marcus Vance¹, Nadia Al-Suwaidi²

Authors’ Affiliations: ¹School of Computer Science, McGill University, Montreal, Canada; ²Department of Computer Engineering, United Arab Emirates University, Al Ain, UAE.

Abstract:
Packet-switched communication routers encounter massive packet drop rates and elevated queuing delays during heavy network traffic bursts, severely degrading the Quality of Service (QoS) for real-time media streams. Static buffer allocation policies either fail to capture sudden transmission surges or cause excessive packet delays due to bloated queue architectures. This paper introduces an optimized, dynamic buffer management algorithm that automatically calibrates queue thresholds based on real-time packet arrival rates and port utilization metrics. The framework applies a mathematical threshold adjustments scheme that penalizes non-responsive flows while prioritizing time-critical multimedia packets. We simulated our dynamic buffer configuration using a multi-node network simulator operating under a heavy mix of TCP and UDP data packets. The experimental outcomes indicate a 26.3% reduction in overall packet drop rates and a 38-millisecond improvement in average end-to-end queuing latency compared to standard Random Early Detection and Drop-Tail routing approaches. The system maintains uniform channel utilization across heavily congested backbone switches without inducing packet reordering anomalies, proving its efficacy for high-speed network infrastructures.

Keywords: Buffer Management, Quality of Service, Network Congestion, Packet Switching, Queue Optimization, Router Performance.

Manuscript Timeline: Received: December 01, 1999; Revised: January 10, 2000; Accepted: February 02, 2000; Published: March 15, 2000.

Citation: Vance, M., & Al-Suwaidi, N. (2000). Dynamic Buffer Management for Enhancing Quality of Service in Packet-Switched Networks. International Journal of Computer Science and Technology, 2(3), 17–24.

International Journal of Computer Science and Technology Vol. 2, No. 2, February 2000 | pp. 9–16

DOI: 10.46882/2000/IJCST/000014

Review Article

Title: A Methodological Survey of Fuzzy Expert Systems in Industrial Process Control

Names of Authors: Jean-Pierre Dubois¹, Sanjay Mehta²

Authors’ Affiliations: ¹Institute of Automation, École Polytechnique Fédérale de Lausanne, Switzerland; ²Department of Electrical Engineering, Indian Institute of Technology, Bombay, India.

Abstract:
The application of classical linear control theory to complex industrial production systems often yields poor performance due to non-linearities, unmodeled dynamics, and unpredictable load disturbances. Fuzzy logic controllers have emerged as a resilient alternative, bridging human expert heuristic rules with computational execution loops. This paper presents a comprehensive methodological survey analyzing the design, implementation, and long-term stability parameters of fuzzy expert systems across diverse manufacturing plants. We synthesize empirical data from 92 foundational studies published across the past decade, contrasting Mamdani and Takagi-Sugeno inference models applied to chemical, metallurgical, and automotive assembly pipelines. The survey assesses criteria such as rule-base optimization, membership function tuning, computational runtime overhead, and fault tolerance boundaries under extreme environmental noise. The review reveals that while Takagi-Sugeno configurations consistently deliver superior mathematical precision in tracking high-speed mechanical trajectories, Mamdani architectures offer unmatched transparency and simpler debugging workflows for human operators. We summarize current barriers including rule-base explosion in multi-variable configurations and lack of formal mathematical proof structures for absolute stability, concluding with a standardized design template for hybrid fuzzy-proportional-integral-derivative (Fuzzy-PID) control systems.

Keywords: Fuzzy Logic Controllers, Industrial Automation, Process Engineering, Expert Systems, Rule Optimization, Comparative Review.

Manuscript Timeline: Received: November 12, 1999; Revised: December 20, 1999; Accepted: January 14, 2000; Published: February 25, 2000.

Citation: Dubois, J. P., & Mehta, S. (2000). A Methodological Survey of Fuzzy Expert Systems in Industrial Process Control. International Journal of Computer Science and Technology, 2(2), 9–16.

International Journal of Computer Science and Technology Vol. 2, No. 1, January 2000 | pp. 1–8

DOI: 10.46882/2000/IJCST/000013

Research Article

Title: An Evolutionary Feature-Selection Algorithm for High-Dimensional Document Mining

Names of Authors: Hiroshi Tanaka¹, Elena Petrova²

Authors’ Affiliations: ¹Graduate School of Information Sciences, Tohoku University, Sendai, Japan; ²Department of Computational Linguistics, Sofia University, Sofia, Bulgaria.

Abstract:
High-dimensional text repositories present significant computational challenges for automated document classification due to the presence of irrelevant, redundant, and noisy linguistic features. Traditional vector space representations result in massive, sparse matrices that drastically degrade classifier accuracy and inflate training time. This paper introduces an optimized, evolutionary feature-selection algorithm designed to extract highly informative text tokens from massive corpus architectures. The proposed framework modifies standard genetic operators by incorporating an information-theoretic gain filter that accelerates population convergence. We tested the performance of the algorithm across a standardized dataset consisting of 100,000 multi-topic documents with an initial vocabulary space exceeding 50,000 distinct terms. The empirical results demonstrate that our evolutionary algorithm reduces the active feature space by 84.3% while simultaneously boosting classification accuracy by 6.5% when integrated with conventional Support Vector Machines and Naive Bayes classifiers. The processing speed during the feature extraction stage was reduced by a factor of 4, ensuring rapid throughput for text mining models. This architecture offers a scalable methodology for enterprise content search tools requiring immediate structural indexing.

Keywords: Text Mining, Feature Selection, Genetic Algorithms, High-Dimensional Data, Information Theory, Document Classification.

Manuscript Timeline: Received: October 10, 1999; Revised: November 15, 1999; Accepted: December 04, 1999; Published: January 20, 2000.

Citation: Tanaka, H., & Petrova, E. (2000). An Evolutionary Feature-Selection Algorithm for High-Dimensional Document Mining. International Journal of Computer Science and Technology, 2(1), 1–8.

International Journal of Computer Science and Technology Vol. 1, No. 12, December 1999 | pp. 95–102

DOI: 10.46882/1999/IJCST/000012

Research Article

Title: An Asymmetric Cryptographic Authentication Layer for Low-Power Wireless Telemetry

Names of Authors: Alistair Vance¹, Fatima Al-Hassan²

Authors’ Affiliations: ¹Department of Electrical and Electronic Engineering, University of Manchester, UK; ²Department of Computer Science, Kuwait University, Kuwait City, Kuwait.

Abstract:
Remote telemetry systems are increasingly utilized in critical infrastructure monitoring, yet their long-range wireless links remain highly vulnerable to malicious command injection and unauthorized eavesdropping. Implementing heavy public-key cryptographic structures directly onto telemetry endpoints typically drains operational batteries rapidly due to hardware constraints. This paper introduces a lightweight, hardware-optimized asymmetric authentication protocol specifically tailored for resource-constrained 8-bit telemetry devices. By re-engineering the modular exponentiation routines and using an optimized binary sliding-window multiplier array, the encryption core significantly reduces arithmetic latency and memory utilization. The proposed authentication engine was benchmarked on physical microcontrollers to track real-time current drainage and processing cycles. The experimental results show a 29.6% drop in energy consumption per transaction phase and a 14.2% acceleration in total execution runtime compared to basic RSA implementations. Security audits confirm that our modified mathematical structure preserves full cryptographic strength against standard side-channel attacks and differential cryptanalysis. The data packet structure introduces only a 6-byte overhead, preserving valuable telemetry channel bandwidth for industrial and environmental tracking networks.

Keywords: Wireless Telemetry, Asymmetric Cryptography, Authentication Protocols, Low-Power Design, Embedded Infrastructure, Cyber Security.

Manuscript Timeline: Received: September 05, 1999; Revised: October 18, 1999; Accepted: November 09, 1999; Published: December 18, 1999.

Citation: Vance, A., & Al-Hassan, F. (1999). An Asymmetric Cryptographic Authentication Layer for Low-Power Wireless Telemetry. International Journal of Computer Science and Technology, 1(12), 95–102.

International Journal of Computer Science and Technology Vol. 1, No. 11, November 1999 | pp. 87–94

DOI: 10.46882/1999/IJCST/000011

Research Article

Title: A Scalable Multi-Agent Routing Paradigm for Adaptive Traffic Control Networks

Names of Authors: Li Wei-Min¹, Carlos Silva²

Authors’ Affiliations: ¹School of Information Engineering, Zhejiang University, Hangzhou, China; ²Department of Systems Engineering, University of Lisbon, Lisbon, Portugal.

Abstract:
Urban traffic congestion presents severe economic and logistical bottlenecks, demanding intelligent systems capable of adapting to real-time flow variations. Traditional static signal timers fail to mitigate congestion during random peak bursts or sudden lane obstructions. This paper presents an optimized, decentralized multi-agent routing paradigm developed for adaptive signal control across dense metropolitan grids. The framework treats each intersection as an autonomous agent that communicates queue lengths and velocity profiles with adjacent nodes using a localized consensus protocol. We simulated the multi-agent framework across an artificial network modeling 200 highly active transit intersections under fluctuating vehicular stress. The experimental metrics reveal a 22.4% reduction in average vehicle wait time and an 18.5% improvement in peak throughput efficiency compared to conventional fixed-time and actuated signal algorithms. Furthermore, the communication overhead between adjacent intersections remained low, scaling linearly with the grid size without oversaturating the local network channels. The system demonstrates excellent fault tolerance, isolating individual node dropouts without destabilizing the broader regional synchronization matrix. This approach provides a practical framework for municipal traffic management systems seeking to enforce stringent efficiency protocols.

Keywords: Intelligent Transportation, Multi-Agent Systems, Decentralized Control, Traffic Signal Optimization, Network Scaling, Flow Simulation.

Manuscript Timeline: Received: August 14, 1999; Revised: September 21, 1999; Accepted: October 10, 1999; Published: November 24, 1999.

Citation: Li, W. M., & Silva, C. (1999). A Scalable Multi-Agent Routing Paradigm for Adaptive Traffic Control Networks. International Journal of Computer Science and Technology, 1(11), 87–94.