List of Accepted papers is now available. Authors of accepted and rejected papers have been notified. click here to see the conference program and presentation schedule.





ACSE 2020 Accepted Papers

Lawrence Byson and Tiwonge Manda. Software Architecture and Software Usability: A Comparison of Data Entry Form Designing Platforms
Isaac Nyabisa Oteyo, Kennedy Kambona, Jesse Zaman, Wolfgang De Meuter and Elisa Gonzalez Boix. Developing Smart Agriculture Applications: Experience Report
Kevin Gogo, Lawrence Nderu and Makau Mutua. Context aware recommender systems and techniques in offering smart learning: A survey and future work
Leonard Peter Binamungu and Jimmy T Mbelwa. An Empirical Distribution of Code Reviews in DHIS2 Repositories and the Impact of Code Reviews on the Popularity of DHIS2 Repositories on GitHub
Leah Mutanu, Khushi Gupta, Jeet Gohil, Dharmik Karania and Abdi Ali. Integrating Non-Functional Requirements for Marginalized Users in the Design of IoT Systems
Lennah Etyang, Waweru Mwangi and Lawrence Nderu. Parameter Settings Optimization in MapReduce Big Data processing using the MOPSO Algorithm
Daniel Ogenrwot, Joyce Nakatumba-Nabende and Michel R.V. Chaudron. Comparison of Occurrence of Design Smells in Desktop and Mobile Applications
Sofie Muriithi, Geoffrey Chemwa and George Okeyo. Cloud-Based Business Continuity for Universities: Issues and Challenges
Dorcas Mwigereri, Dr. Lawrence Nderu and Dr. Tobias Mwalili. A Multi-Feature Fusion Deep Convolutional Network based on A Coarse-Fine Structure for Cloud Detection
Stephen Kiptoo, Leah Matanu and Lawrence Nderu. AUTOMATED DETECTION OF CERVICAL PRE-CANCEROUS LESIONS USING REGIONAL-BASED CONVOLUTIONAL NEURAL NETWORK
Peter Mwangi, Dr. Lawrence Nderu and Dorcas Gicuku. A Proposed Ensemble Model based on RUSBoost and a Cost-Sensitive Convolution Neural Network for Class Imbalance in Big Data Analytics
Henry Ngie, Dr. Lawrence Nderu and Dorcas Mwigereri. Tree-based Regressor Ensemble Machine Learning for Covid-19 and Viral Infectious Diseases Daily Global Spread Prediction