Software Engineering Commons^™

Automatically Defined Templates For Improved Prediction Of Non-Stationary, Nonlinear Time Series In Genetic Programming, David Moskowitz

CCAC Theses and Dissertations

Soft methods of artificial intelligence are often used in the prediction of non-deterministic time series that cannot be modeled using standard econometric methods. These series, such as occur in finance, often undergo changes to their underlying data generation process resulting in inaccurate approximations or requiring additional human judgment and input in the process, hindering the potential for automated solutions.

Genetic programming (GP) is a class of nature-inspired algorithms that aims to evolve a population of computer programs to solve a target problem. GP has been applied to time series prediction in finance and other domains. However, most GP-based approaches to …

Predicting Energy Demand Peak Using M5 Model Trees, Sara S. Abdelkader, Katarina Grolinger, Miriam Am Capretz

Electrical and Computer Engineering Publications

Predicting energy demand peak is a key factor for reducing energy demand and electricity bills for commercial customers. Features influencing energy demand are many and complex, such as occupant behaviours and temperature. Feature selection can decrease prediction model complexity without sacrificing performance. In this paper, features were selected based on their multiple linear regression correlation coefficients. This paper discusses the capabilities of M5 model trees in energy demand prediction for commercial buildings. M5 model trees are similar to regression trees; however they are more suitable for continuous prediction problems. The M5 model tree prediction was developed based on a selected …

Battle Bot Ai – Patriot Bot, James Johnston

Computer Engineering

An entry in the the 'Battle Block AI' competition hosted by 'The AI Games'.

Energy Forecasting For Event Venues: Big Data And Prediction Accuracy, Katarina Grolinger, Alexandra L'Heureux, Miriam Am Capretz, Luke Seewald

Electrical and Computer Engineering Publications

Advances in sensor technologies and the proliferation of smart meters have resulted in an explosion of energy-related data sets. These Big Data have created opportunities for development of new energy services and a promise of better energy management and conservation. Sensor-based energy forecasting has been researched in the context of office buildings, schools, and residential buildings. This paper investigates sensor-based forecasting in the context of event-organizing venues, which present an especially difficult scenario due to large variations in consumption caused by the hosted events. Moreover, the significance of the data set size, specifically the impact of temporal granularity, on energy …

Mlaas: Machine Learning As A Service, Mauro Ribeiro, Katarina Grolinger, Miriam Am Capretz

Electrical and Computer Engineering Publications

The demand for knowledge extraction has been increasing. With the growing amount of data being generated by global data sources (e.g., social media and mobile apps) and the popularization of context-specific data (e.g., the Internet of Things), companies and researchers need to connect all these data and extract valuable information. Machine learning has been gaining much attention in data mining, leveraging the birth of new solutions. This paper proposes an architecture to create a flexible and scalable machine learning as a service. An open source solution was implemented and presented. As a case study, a forecast of electricity demand was …

An Adaptive Markov Strategy For Effective Network Intrusion Detection, Jianye Hao, Yinxing Xue, Mahinthan Chandramohan, Yang Liu, Jun Sun

Research Collection School Of Computing and Information Systems

Network monitoring is an important way to ensure the security of hosts from being attacked by malicious attackers. One challenging problem for network operators is how to distribute the limited monitoring resources (e.g., intrusion detectors) among the network to detect attacks effectively, especially when the attacking strategies can be changing dynamically and unpredictable. To this end, we adopt Markov game to model the interactions between the network operator and the attacker and propose an adaptive Markov strategy (AMS) to determine how the detectors should be placed on the network against possible attacks to minimize the network’s accumulated cost over time. …

Using Infrastructure-Provided Context Filters For Efficient Fine-Grained Activity Sensing, Vigneshwaran Subbaraju, Sougata Sen, Archan Misra, Satyadip Chakraborty, Rajesh Krishna Balan

Research Collection School Of Computing and Information Systems

While mobile and wearable sensing can capture unique insights into fine-grained activities (such as gestures and limb-based actions) at an individual level, their energy overheads are still prohibitive enough to prevent them from being executed continuously. In this paper, we explore practical alternatives to addressing this challenge-by exploring how cheap infrastructure sensors or information sources (e.g., BLE beacons) can be harnessed with such mobile/wearable sensors to provide an effective solution that reduces energy consumption without sacrificing accuracy. The key idea is that many fine-grained activities that we desire to capture are specific to certain location, movement or background context: infrastructure …

Energy Cost Forecasting For Event Venues, Katarina Grolinger, Andrea Zagar, Miriam Am Capretz, Luke Seewald

Electrical and Computer Engineering Publications

Electricity price, consumption, and demand forecasting has been a topic of research interest for a long time. The proliferation of smart meters has created new opportunities in energy prediction. This paper investigates energy cost forecasting in the context of entertainment event-organizing venues, which poses significant difficulty due to fluctuations in energy demand and wholesale electricity prices. The objective is to predict the overall cost of energy consumed during an entertainment event. Predictions are carried out separately for each event category and feature selection is used to select the most effective combination of event attributes for each category. Three machine learning …

Research Agenda Into Human-Intelligence/Machine-Intelligence Governance, Teddy Steven Cotter

Engineering Management & Systems Engineering Faculty Publications

Since the birth of modern artificial intelligence (AI) at the 1956 Dartmouth Conference, the AI community has pursued modeling and coding of human intelligence into AI reasoning processes (HI Þ MI). The Dartmouth Conference's fundamental assertion was that every aspect of human learning and intelligence could be so precisely described that it could be simulated in AI. With the exception of knowledge specific areas (such as IBM's Big Blue and a few others), sixty years later the AI community is not close to coding global human intelligence into AI. In parallel, the knowledge management (KM) community has pursued understanding of …

Consistency Checking Of Natural Language Temporal Requirements Using Answer-Set Programming, Wenbin Li

Theses and Dissertations--Computer Science

Successful software engineering practice requires high quality requirements. Inconsistency is one of the main requirement issues that may prevent software projects from being success. This is particularly onerous when the requirements concern temporal constraints. Manual checking whether temporal requirements are consistent is tedious and error prone when the number of requirements is large. This dissertation addresses the problem of identifying inconsistencies in temporal requirements expressed as natural language text. The goal of this research is to create an efficient, partially automated, approach for checking temporal consistency of natural language requirements and to minimize analysts' workload.

The key contributions of this …

Traccs: Trajectory-Aware Coordinated Urban Crowd-Sourcing, Cen Chen, Shih-Fen Cheng, Aldy Gunawan, Archan Misra, Koustuv Dasgupta, Deepthi Chander

Research Collection School Of Computing and Information Systems

We investigate the problem of large-scale mobile crowd-tasking, where a large pool of citizen crowd-workers are used to perform a variety of location-specific urban logistics tasks. Current approaches to such mobile crowd-tasking are very decentralized: a crowd-tasking platform usually provides each worker a set of available tasks close to the worker's current location; each worker then independently chooses which tasks she wants to accept and perform. In contrast, we propose TRACCS, a more coordinated task assignment approach, where the crowd-tasking platform assigns a sequence of tasks to each worker, taking into account their expected location trajectory over a wider time …

Hippi Care Hospital: Towards Proactive Business Processes In Emergency Room Services, Kar Way Tan, Venky Shankaraman

Research Collection School Of Computing and Information Systems

It was 2.35 am on a Saturday morning. Wiki Lim, process specialist from the Process Innovation Centre (PIC) of Hippi Care Hospital (HCH), desperately doodling on her notepad for ideas to improve service delivery at HCH’s Emergency Department (ED). HCH has committed to the public that its ED would meet the service quality criterion of serving 90% of A3 and A4 patients, non-emergency patients with moderate to mild symptoms, within 90 minutes of their arrival at the ED. The ED was not able to meet this performance goal and Dr. Edward Kim, the head of the ED at HCH, had …

Improved Microrobotic Control Through Image Processing And Automated Hardware Interfacing, Archit R. Aggarwal, Wuming Jing, David J. Cappelleri

The Summer Undergraduate Research Fellowship (SURF) Symposium

Untethered submilliliter-sized robots (microrobots) are showing potential use in different industrial, manufacturing and medical applications. A particular type of these microrobots, magnetic robots, have shown improved performance in power and control capabilities compared to the other thermal and electrostatic based robots. However, the magnetic robot designs have not been assessed in a robust manner to understand the degree of control in different environments and their application feasibility. This research project seeks to develop a custom control software interface to provide a holistic tool for researchers to evaluate the microrobotic performance through advance control features. The software deliverable involved two main …

Games People Play: Exploring Depaul's Top-Rated Computer Game Development Program

DePaul Magazine

In March 2014, the Princeton Review, in conjunction with PC Gamer magazine, named the top 25 schools to study game design in the United States and Canada. DePaul's undergraduate program ranked 20th, a considerable leap from 2013’s honorable mention. The graduate program came in at 12th. DePaul's strong ranking reflects the game development program's extension of its basic game development, software engineering and programming to include art, design and storytelling, as well as computer graphics technology, networking, artificial intelligence and human-computer interaction. Examples of the award-winning games developed by students and now marketed by such going concerns as Sony PlayStation …

Opportunistic Service Differentiation And Cloud Resource Management In Support Of Enhanced Vehicular Applications, Mohammad Ali Salahuddin

Dissertations

An integral part of Intelligent Transportation Systems (ITS) are Vehicular Ad hoc Networks (VANETs), which consist of vehicles with on-board units (OBUs) and fixed road-side units (RSUs). Wireless Access in Vehicular Environment (WAVE) offers QoS via service differentiation by using application defined priorities. However, WAVE has unbounded delay and is oblivious to network load and severity of vehicles with respect to their environment. Our context severity metric innovatively enhances WAVE to be sensitive to vehicle and environment interactions. Our novel Opportunistic Service Differentiation (OSD) technique, dynamically readjusts the WAVE packet priorities to improve utilization of lower latency queues, prioritizing packets …

Scalable Collaborative Filtering Recommendation Algorithms On Apache Spark, Walker Evan Casey

CMC Senior Theses

Collaborative filtering based recommender systems use information about a user's preferences to make personalized predictions about content, such as topics, people, or products, that they might find relevant. As the volume of accessible information and active users on the Internet continues to grow, it becomes increasingly difficult to compute recommendations quickly and accurately over a large dataset. In this study, we will introduce an algorithmic framework built on top of Apache Spark for parallel computation of the neighborhood-based collaborative filtering problem, which allows the algorithm to scale linearly with a growing number of users. We also investigate several different variants …

Hybrid Intelligent Model For Software Maintenance Prediction, Abdulrahman Ahmed Bobakr Baqais, Mohammad Alshayeb, Zubair A. Baig

Research outputs 2014 to 2021

Maintenance is an important activity in the software life cycle. No software product can do without undergoing the process of maintenance. Estimating a software’s maintainability effort and cost is not an easy task considering the various factors that influence the proposed measurement. Hence, Artificial Intelligence (AI) techniques have been used extensively to find optimized and more accurate maintenance estimations. In this paper, we propose an Evolutionary Neural Network (NN) model to predict software maintainability. The proposed model is based on a hybrid intelligent technique wherein a neural network is trained for prediction and a genetic algorithm (GA) implementation is used …

Misheard Me Oronyminator: Using Oronyms To Validate The Correctness Of Frequency Dictionaries, Jennifer G. Hughes

Master's Theses

In the field of speech recognition, an algorithm must learn to tell the difference between "a nice rock" and "a gneiss rock". These identical-sounding phrases are called oronyms. Word frequency dictionaries are often used by speech recognition systems to help resolve phonetic sequences with more than one possible orthographic phrase interpretation, by looking up which oronym of the root phonetic sequence contains the most-common words.

Our paper demonstrates a technique used to validate word frequency dictionary values. We chose to use frequency values from the UNISYN dictionary, which tallies each word on a per-occurance basis, using a proprietary text corpus, …

Clustering Of Search Trajectory And Its Application To Parameter Tuning, Linda Lindawati, Hoong Chuin Lau, David Lo

Research Collection School Of Computing and Information Systems

This paper is concerned with automated classification of Combinatorial Optimization Problem instances for instance-specific parameter tuning purpose. We propose the CluPaTra Framework, a generic approach to CLUster instances based on similar PAtterns according to search TRAjectories and apply it on parameter tuning. The key idea is to use the search trajectory as a generic feature for clustering problem instances. The advantage of using search trajectory is that it can be obtained from any local-search based algorithm with small additional computation time. We explore and compare two different search trajectory representations, two sequence alignment techniques (to calculate similarities) as well as …

Intelligent Systems Development In A Non Engineering Curriculum, Emily A. Brand, William L. Honig, Matthew Wojtowicz

Computer Science: Faculty Publications and Other Works

Much of computer system development today is programming in the large - systems of millions of lines of code distributed across servers and the web. At the same time, microcontrollers have also become pervasive in everyday products, economical to manufacture, and represent a different level of learning about system development. Real world systems at this level require integrated development of custom hardware and software.

How can academic institutions give students a view of this other extreme - programming on small microcontrollers with specialized hardware? Full scale system development including custom hardware and software is expensive, beyond the range of any …

Instance-Based Parameter Tuning Via Search Trajectory Similarity Clustering, Linda Lindawati, Hoong Chuin Lau, David Lo

Research Collection School Of Computing and Information Systems

This paper is concerned with automated tuning of parameters in local-search based meta-heuristics. Several generic approaches have been introduced in the literature that returns a ”one-size-fits-all” parameter configuration for all instances. This is unsatisfactory since different instances may require the algorithm to use very different parameter configurations in order to find good solutions. There have been approaches that perform instance-based automated tuning, but they are usually problem-specific. In this paper, we propose CluPaTra, a generic (problem-independent) approach to perform parameter tuning, based on CLUstering instances with similar PAtterns according to their search TRAjectories. We propose representing a search trajectory as …

Fine-Tuning Algorithm Parameters Using The Design Of Experiments Approach, Aldy Gunawan, Hoong Chuin Lau, Linda Lindawati

Research Collection School Of Computing and Information Systems

Optimizing parameter settings is an important task in algorithm design. Several automated parameter tuning procedures/configurators have been proposed in the literature, most of which work effectively when given a good initial range for the parameter values. In the Design of Experiments (DOE), a good initial range is known to lead to an optimum parameter setting. In this paper, we present a framework based on DOE to find a good initial range of parameter values for automated tuning. We use a factorial experiment design to first screen and rank all the parameters thereby allowing us to then focus on the parameter …

On Machine Learning Methods For Chinese Document Classification, Ji He, Ah-Hwee Tan, Chew-Lim Tan

Research Collection School Of Computing and Information Systems

This paper reports our comparative evaluation of three machine learning methods, namely k Nearest Neighbor (kNN), Support Vector Machines (SVM), and Adaptive Resonance Associative Map (ARAM) for Chinese document categorization. Based on two Chinese corpora, a series of controlled experiments evaluated their learning capabilities and efficiency in mining text classification knowledge. Benchmark experiments showed that their predictive performance were roughly comparable, especially on clean and well organized data sets. While kNN and ARAM yield better performances than SVM on small and clean data sets, SVM and ARAM significantly outperformed kNN on noisy data. Comparing efficiency, kNN was notably more costly …

Sistem Jadual Waktu Elektronik (Sjwe), Mohd Noh Mohd Nizam

Student Works (2000-2009)

Projek llmiah Tahap Akhir IT (WXES3182) ini merupakan salah satu keperluan kursus yang perlu diambil sebelum seseorang pelajar Ijazah Srujana Muda Sains Komputer itu bergelar graduan unversiti. Bagi tujuan itu saya telah membuat keputusan membina suatu sistem pentadbiran jadual waktu untuk FakuJti Sains Komputer & Teknologi Maklumat dan sistem ini saya namakan sebagai Sistem Jadual Waktu Elektronik (SJWE). SJWE ini dibangunkan oleh dua orang dan setiap orang membuat domain yang berlainan. Rakan saya Mohd. Sirhan Shabrani Bin Mt. Salleh membuat bahagian pentadbiran jadual waktu (Administration) di mana bahagian ini meliputi kerja-kerja yang perlu mempertimbangkan proses-proses yang perlu dijalankan sebelum suatu …

Online Counseling Assistant Ii (Oca Ii), Abdul Satar Roliana

Student Works (2000-2009)

Laporan projek latihan ilmiah tahap akhir ini mencadangkan tentang pembangunan sebuah sistem yang mampu membantu pelajar di dalam proses pembelajaran. Sistem yang akan dibangunkan ialah Online Counseling Assistant II (OCA II) di mana ia tertumpu kepada 3 bahagian paling utama iaitu temujanji, perbincangan dan pengumuman dalam talian. Sasaran utama pengguna sistem OCA II ini adalah terdiri daripada pelajar-pelajar di mana ia dapat mermbantu mereka meningkatkan kualiti dan prestasi pembelajaran. Pembangunan sistem ini adalah berdasarkan kepada matlamat untuk mengeksploitasikan teknologi maklumat di dalam pendidikan serta memberi kemudahan elektronik kepada masyarakat. Beberapa kajian dan penyelidikan telah dibuat menghasilkan satu analisis dan rekabentuk …

Knowledge Management Portal (Ai Department), Rahmat Nazariah

Student Works (2000-2009)

Portal pengurusan maklumat adalah satu sistem yang mana berfungsi sebagai tempat untuk mengumpul dan mencapai maklumat. Maklumat yang terdapat di dalam portal ini adalah maklumat yang terperinci tentang Jabatan Kepintaran Buatan, FSKTM, Universiti Malaya. Semua maklumat ini akan di olah kembali untuk mendapatkan sesuatu output yang berguna kepada pengguna sistem ini. Sistem portal pengurusan maklumat ini mengandungi dua modul utama iaitu Modul Pengguna Awam dan Modul Pentadbir. Modul pengguna awam membenarkan pengguna mencari informasi dan mencapai maklumat yang dipaparkan di dalam portal ini. Akan tetapi, capaian sebagai pengguna awam adalah agak terhad. Modul pihak pentadbir pula terdiri daripada 4 peringkat …

To Explore Agent Technology In E-Commerce Mighty House Agent, Thirumalai Phiyadharshini

Student Works (2000-2009)

Agent technology is becoming more popular among system designers who want their system to be more personalized, continuously running and semi-autonomous. These properties make agents useful for a wide variety of information and process management tasks. It should come as no surprise that these same qualities are particularly useful for the information-rich and process-rich environment of electronic commerce. As such agent technology in electronic commerce (e-commerce) would be essential to improve on-line shopping which is becoming more and more popular these days. It is in these roles that agent system designers have the challenge to accurately identify and the opportunity …

Applications Of Fuzzy Logic To Software Model, Yahaya Yuhanim Hani

Student Works (2000-2009)

This thesis investigates the use of fuzzy logic approach in software metrics application. Software metrics defines a standard way of measuring the properties of software products, development processes and resources. The most common application of software metrics is the software cost estimation where it predicts the effort required for completing certain stages of a software development life cycle. The ability to obtain an accurate effort prediction is essential for the cost estimation process, as it helps a project manager to specify the efforts needed for project development. In relation to this, cost estimation models such as COCOMO (Constructive Cost Model), …

Sistem Pakar Bermultimedia Untuk Pengenalpastian Serangga, Osman Aizul Hussin

Student Works (2000-2009)

Sistem Pakar Bermultimedia untuk domain pengenalpastian serangga ,Insect Identification Expert System,(IIES ) merupakan sistem pakar untuk membantu proses pengenalpastian pangkat serangga dalam Hierarki Linnean. Sistem ini menggunakan pendekatan berorientasikan objek di mana konsep kelas dan objek akan digunakan untuk merekodkan pengetahuan ke bentuk yang akan difahami oleh sistem pakar. Strategi inferens yang digunakan ialah teknik rantaian ke hadapan di mana sistem pakar akan menghasilkan konklusi berdasarkan data-data yang diberi. Sistem pakar mempunyai ciri-ciri multimedia untuk membantu memberi panduan bagi pengguna untuk mengenal pasti ciri-ciri kunci serangga dan memberi penjelasan tentang domain di samping memberi pendekatan yang berlainan dari sistem pakar …

Intelligent Agent For E-Commerce Using Genetic Algorithm, Sun Sun Kok

Student Works (2000-2009)

This project report outlines the introduction, literature study and methodology, system analysis and design, system implementation, system testing and summary of the whole project. The major objective of this system is to develop an intelligent agent that can gather. analyze and categorize information from the Web on the printers that complying the parameters specified /identified by the web users, and to provide recommendations for online purchases for all types of printers. The recommended web sites are restricted to web pages that provide online purchase facilities and deliveries in Malaysia. The system is able to update the information from the database …