ACM-SE

Recently, strategies of National Basketball Association (NBA) teams have evolved with the skillsets of players and the emergence of advanced analytics. This has led to a more free-flowing game in which traditional positions and play calls have been ...

Machine Translation is the usage of machine learning techniques in translation from one language to another. It has recently been applied to streaming translation, also known as automatic subtitling. The most common challenge in this area is the trade-...

In this research, a Principal Component Analysis (PCA) with Genetic Algorithm based Machine Learning (ML) approach is developed for the binary classification of epileptic seizures from the EEG dataset. The proposed approach utilizes PCA to reduce the ...

In today's world every system developer and administrator should be familiar with cyberattacks and possible threats to their organizations systems. Petri Nets have been used to model and simulate cyberattacks allowing for additional knowledge on the ...

Recent research points to a severe shortage of cybersecurity professionals right now and in the near future. Universities are introducing cybersecurity programs to fill the gap between cybersecurity professionals' supply and demand. Although ...

Various Learning Engagement Strategies (LESs) have been used in CS education to motivate students and facilitate learning. More recently, LESs are being used to support programming pedagogy. Therefore, investigating the influence that the multiple ...

With the introduction of the Digital Literacy and Computer Science (DLCS) education standards, there is a need for Alabama teachers at all grade levels to be equipped with software tools that can be used to bolster students' learning of content ...

Online discussion forums provide valuable information about students' learning and engagement in course activities. The hidden knowledge in the contents of these discussion posts can be examined by analyzing the social interactions between the ...

In this paper, we survey network simulators and/or emulators with support for wireless networks. We selected six tools, OMNeT++/INET, ns-3, Packet Tracer, Mininet-WiFi, CORE and Komondor, and further investigate them in regards to their potential use in ...

In this paper we describe a method for computing item based recommendations using matrix-factorization-like embeddings of the items computed using a neural network. Matrix factorizations (MF) compute near optimal item embeddings by minimizing a loss ...

Due to its deep penetration in people's daily life, smartphone has been proposed as a practical platform for indoor localization. Yet one major challenge is how to handle the non-negligible sensor errors that can become problematic when accumulated over ...

Student motivation in the Programming Fundamentals (CS1) course in our college has long been a problem. Our project utilized both peer modeling and game development to increase students' curiosity for programming and help them enjoy the learning ...

Containers, an emerging service to manage and deploy applications into isolated boxes, are quickly increasing in popularity in the cloud and edge computing. In order to provide connectivity among multiple hosts, cloud providers adopt overlay networks, ...

Monitoring and tracking inventory is one of the most important aspects of administrating any large-scale enterprise operation that involves physical goods. One of the most evident examples of such operations is automotive manufacturing, especially for ...

Fabric density and distortion offer important information on fabric attributes and quality during the manufacturing process. However, most current procedures require human effort, which is often inefficient, time-consuming, and imprecise. In this paper, ...

Recently one deep learning technique, Convolutional Neural Networks (CNN), has gained immense popularity. Their success is particularly noticeable on image data, but falls short on non-image data. New methods have been developed to transform non-image ...

Hyperspectral images (HSI) contain rich spectral information from a large portion of the electromagnetic spectrum. Using these images, it is possible to make pixel-level classification as each pixel holds hundreds of features. In this paper, we propose ...

Ambiguous requirements are problematic in requirement engineering as various stakeholders can debate on the interpretation of the requirements leading to a variety of issues in the development stages. Since requirement specifications are usually written ...

Software requirement specification (SRS) document contains faults due to the inherent ambiguous nature of natural language (NL). These faults are identified and reported (using fault logs) through inspections and are handed back to the requirements ...

Feature modeling is a process for identifying the common and variable parts of a software product line and recording them in a tree-structured feature model. However, feature models can be difficult for mainstream developers to specify and maintain ...

The Internet of Things (IoT) is the term coined to encompass the myriad of devices that have some data processing and transmitting capabilities. Due to the increasing number of IoT devices connected to the Internet, network protocols intended for IoT ...

In this research, a wavelet transform-based feature extraction approach is proposed for the detection of epileptic seizures from the EEG raw dataset. The proposed approach uses the Wavelet Transform (WT) method to divide the seizure and non-seizure ...

This article introduced the modification of an incremental learning algorithm and summarized its performance via the complexity analysis. The algorithm was originally proposed in the context of classic rough set theory, utilizing the hierarchy of ...

Cloud-edge systems are vulnerable to thermal attacks as the increased energy consumption may remain undetected, while occurring alongside normal, CPU-intensive applications. The purpose of our research is to study thermal effects on modern edge systems. ...

Network security is an important aspect for any organization to keep their information systems secure. A Network Intrusion Detection System (NIDS) is an aid to secure the network by detecting abnormal or malicious traffic. In this paper, we applied a ...

Phishing attacks are the scourge of the network security manager's job. Looking for a solution to counter this trend, this paper examines and verifies the efficacy of Phishmon, a machine learning framework for scrutinizing webpages that relies on ...

The national STEM teacher shortage in public schools is no secret. A recent expansion and adoption Computer Science (CS) Education in the K-12 curriculum exacerbates the shortage. Many states have formed CS Education committees in charge of creating ...

Problem-based instruction is an active learning instructional practice that requires students to use rational and critical thinking skills to generate reasonable solutions to problem-based scenarios. For complex medical conditions such as stroke, ...

In this paper, we use Association rule learning to analyze the relationship between students' performance in database courses and their performance of database design in the capstone projects. Students need to design and implement databases to store ...

Continuous integration and delivery (CI/CD) frameworks are a core element of DevOps-based software development. A PHP-based case study assessed the suitability of five such frameworks---JFrog Arti-factory, Bitbucket Pipelines, Jenkins, Azure DevOps, and ...