Open Access. Powered by Scholars. Published by Universities.®
Science and Technology Studies Commons™
Open Access. Powered by Scholars. Published by Universities.®
- Discipline
-
- Engineering (8)
- Communication (4)
- Communication Technology and New Media (4)
- Computer Sciences (4)
- Physical Sciences and Mathematics (4)
-
- Law (3)
- Public Affairs, Public Policy and Public Administration (3)
- Administrative Law (2)
- Artificial Intelligence and Robotics (2)
- Bioinformatics (2)
- Databases and Information Systems (2)
- Life Sciences (2)
- OS and Networks (2)
- Public Administration (2)
- Science and Technology Law (2)
- Science and Technology Policy (2)
- Anthropology (1)
- Antitrust and Trade Regulation (1)
- Business (1)
- Computer Law (1)
- Courts (1)
- Economics (1)
- Entertainment, Arts, and Sports Law (1)
- Health Law and Policy (1)
- Industrial Organization (1)
- Internet Law (1)
- Judges (1)
- Jurisprudence (1)
- Institution
Articles 1 - 13 of 13
Full-Text Articles in Science and Technology Studies
Regulating Machine Learning: The Challenge Of Heterogeneity, Cary Coglianese
Regulating Machine Learning: The Challenge Of Heterogeneity, Cary Coglianese
All Faculty Scholarship
Machine learning, or artificial intelligence, refers to a vast array of different algorithms that are being put to highly varied uses, including in transportation, medicine, social media, marketing, and many other settings. Not only do machine-learning algorithms vary widely across their types and uses, but they are evolving constantly. Even the same algorithm can perform quite differently over time as it is fed new data. Due to the staggering heterogeneity of these algorithms, multiple regulatory agencies will be needed to regulate the use of machine learning, each within their own discrete area of specialization. Even these specialized expert agencies, though, …
Regulating New Tech: Problems, Pathways, And People, Cary Coglianese
Regulating New Tech: Problems, Pathways, And People, Cary Coglianese
All Faculty Scholarship
New technologies bring with them many promises, but also a series of new problems. Even though these problems are new, they are not unlike the types of problems that regulators have long addressed in other contexts. The lessons from regulation in the past can thus guide regulatory efforts today. Regulators must focus on understanding the problems they seek to address and the causal pathways that lead to these problems. Then they must undertake efforts to shape the behavior of those in industry so that private sector managers focus on their technologies’ problems and take actions to interrupt the causal pathways. …
Fair Play: Notes On The Algorithmic Soccer Referee, Michael J. Madison
Fair Play: Notes On The Algorithmic Soccer Referee, Michael J. Madison
Articles
The soccer referee stands in for a judge. Soccer’s Video Assistant Referee (“VAR”) system stands in for algorithms that augment human deciders. Fair play stands in for justice. They are combined and set in a polycentric system of governance, with implications for designing, administering, and assessing human-machine combinations.
Using Cost-Sensitive Learning And Feature Selection Algorithms To Improve The Performance Of Imbalanced Classification, Fang Feng, Kuan-Ching Li, Jun Shen, Qingguo Zhou, Xuhui Yang
Using Cost-Sensitive Learning And Feature Selection Algorithms To Improve The Performance Of Imbalanced Classification, Fang Feng, Kuan-Ching Li, Jun Shen, Qingguo Zhou, Xuhui Yang
Faculty of Engineering and Information Sciences - Papers: Part A
Imbalanced data problem is widely present in network intrusion detection, spam filtering, biomedical engineering, finance, science, being a challenge in many real-life data-intensive applications. Classifier bias occurs when traditional classification algorithms are used to deal with imbalanced data. As already known, the General Vector Machine (GVM) algorithm has good generalization ability, though it does not work well for the imbalanced classification. Additionally, the state-of-the-art Binary Ant Lion Optimizer (BALO) algorithm has high exploitability and fast convergence rate. Based on these facts, we have proposed in this paper a Cost-sensitive Feature selection General Vector Machine (CFGVM) algorithm based on GVM and …
Towards Merging Binary Integer Programming Techniques With Genetic Algorithms, Reza R. Zamani
Towards Merging Binary Integer Programming Techniques With Genetic Algorithms, Reza R. Zamani
Faculty of Engineering and Information Sciences - Papers: Part B
No abstract provided.
Extracting City Traffic Events From Social Streams, Pramod Anantharam, Payam Barnaghi, Krishnaprasad Thirunarayan, Amit P. Sheth
Extracting City Traffic Events From Social Streams, Pramod Anantharam, Payam Barnaghi, Krishnaprasad Thirunarayan, Amit P. Sheth
Kno.e.sis Publications
Cities are composed of complex systems with physical, cyber, and social components. Current works on extracting and understanding city events mainly rely on technology enabled infrastructure to observe and record events. In this work, we propose an approach to leverage citizen observations of various city systems and services such as traffic, public transport, water supply, weather, sewage, and public safety as a source of city events. We investigate the feasibility of using such textual streams for extracting city events from annotated text. We formalize the problem of annotating social streams such as microblogs as a sequence labeling problem. We present …
Novel Algorithms For Complete Targets Coverage In Energy Harvesting Wireless Sensor Networks, Changlin Yang, Kwan-Wu Chin
Novel Algorithms For Complete Targets Coverage In Energy Harvesting Wireless Sensor Networks, Changlin Yang, Kwan-Wu Chin
Faculty of Engineering and Information Sciences - Papers: Part A
This paper addresses the problem of maximizing the network lifetime of rechargeable Wireless Sensor Networks (WSNs) whilst ensuring all targets are monitored continuously by at least one sensor node. The objective is to determine a group of sensor nodes, and their wake-up schedule such that within a time interval, one subset of nodes are active whilst others enter the sleep state to conserve energy as well as recharge their battery. We propose a Linear Programming (LP) based solution to determine the activation schedule of sensor nodes whilst affording them recharging opportunities and at the same time ensures complete target coverage. …
Optimal Design Of Vertical Ground Heat Exchangers By Using Entropy Generation Minimization Method And Genetic Algorithms, Su Huang, Zhenjun Ma, Paul Cooper
Optimal Design Of Vertical Ground Heat Exchangers By Using Entropy Generation Minimization Method And Genetic Algorithms, Su Huang, Zhenjun Ma, Paul Cooper
Faculty of Engineering and Information Sciences - Papers: Part A
This paper presents the development and validation of an optimal design methodology for vertical U-tube ground heat exchangers (GHEs) used in HVAC systems. The dimensionless entropy generation number obtained by scaling the entropy generation due to heat transfer and pressure drop, on the ratio of the heat transfer rate to the average fluid temperature of vertical GHEs is employed as the objective function. Five design variables are first selected based on the global sensitivity analysis and then optimized by a genetic algorithm optimization technique. The entropy generation process combines the heat transfer and fluid mechanics with thermodynamic analysis. A case …
Investigating The Optimal Passive And Active Vibration Controls Of Adjacent Buildings Based On Performance Indices Using Genetic Algorithms, Muhammad N. S Hadi, Mehmet Uz
Investigating The Optimal Passive And Active Vibration Controls Of Adjacent Buildings Based On Performance Indices Using Genetic Algorithms, Muhammad N. S Hadi, Mehmet Uz
Faculty of Engineering and Information Sciences - Papers: Part A
This study proposes the optimal passive and active damper parameters for achieving the best results in seismic response mitigation of coupled buildings connected to each other by dampers. The optimisation to minimise the H2 and H- norms in the performance indices is carried out by genetic algorithms (GAs). The final passive and active damper parameters are checked for adjacent buildings connected to each other under El Centro NS 1940 and Kobe NS 1995 excitations. Using real coded GA in H- norm, the optimal controller gain is obtained by different combinations of the measurement as the feedback for designing the control …
Evaluations Of Heuristic Algorithms For Teamwork-Enhanced Task Allocation In Mobile Cloud-Based Learning, Geng Sun, Jun Shen, Junzhou Luo, Jianming Yong
Evaluations Of Heuristic Algorithms For Teamwork-Enhanced Task Allocation In Mobile Cloud-Based Learning, Geng Sun, Jun Shen, Junzhou Luo, Jianming Yong
Faculty of Engineering and Information Sciences - Papers: Part A
Enhancing teamwork performance is a significant issue in mobile cloud-based learning. We introduce a service oriented system, Teamwork as a Service (TaaS), to realize a new approach for enhancing teamwork performance in the mobile cloud environment. To coordinate most learners' talents and give them more motivation, an appropriate task allocation is necessary. Utilizing the Kolb's learning style (KLS) to refine learner's capabilities, and combining their preferences and tasks' difficulties, we formally describe this problem as a constraint optimization model. Two heuristic algorithms, namely genetic algorithm (GA) and simulated annealing (SA), are employed to tackle the teamwork-enhanced task allocation, and their …
Approximation Algorithms For Interference Aware Broadcast In Wireless Networks, Dianbo Zhao, Kwan-Wu Chin
Approximation Algorithms For Interference Aware Broadcast In Wireless Networks, Dianbo Zhao, Kwan-Wu Chin
Faculty of Engineering and Information Sciences - Papers: Part A
Broadcast is a fundamental operation in wireless networks and is well supported by the wireless channel. However, the interference resulting from a node's transmission pose a key challenge to the design of any broadcast algorithms/protocols. In particular, it is well known that a node's interference range is much larger than its transmission range and thus limits the number of transmitting and receiving nodes, which inevitably prolong broadcast. To this end, a number of past studies have designed broadcast algorithms that account for this interference range with the goal of deriving a broadcast schedule that minimizes latency. However, these works have …
Computing Inconsistency Measure Based On Paraconsistent Semantics, Pascal Hitzler, Yue Ma, Guilin Qi
Computing Inconsistency Measure Based On Paraconsistent Semantics, Pascal Hitzler, Yue Ma, Guilin Qi
Computer Science and Engineering Faculty Publications
Measuring inconsistency in knowledge bases has been recognized as an important problem in several research areas. Many methods have been proposed to solve this problem and a main class of them is based on some kind of paraconsistent semantics. However, existing methods suffer from two limitations: (i) they are mostly restricted to propositional knowledge bases; (ii) very few of them discuss computational aspects of computing inconsistency measures. In this article, we try to solve these two limitations by exploring algorithms for computing an inconsistency measure of first-order knowledge bases. After introducing a four-valued semantics for first-order logic, we define an …
Self-Shape Optimisation Of Cold-Formed Steel Closed Profiles Using Genetic Algorithms, Benoit Gilbert, Lip H. Teh, Hong Guan
Self-Shape Optimisation Of Cold-Formed Steel Closed Profiles Using Genetic Algorithms, Benoit Gilbert, Lip H. Teh, Hong Guan
Faculty of Engineering and Information Sciences - Papers: Part A
For economical benefits, optimisation of mass-produced structural steel products is widely researched. The objective is to minimise the quantity of material used without sacrificing the strength and practicality of the structural members. Current research focuses on optimising the dimensions of conventional cross-sectional shapes but rarely considers discovering new optimum shapes. This report introduces the concepts of a new optimisation method which enables the crosssection to self-shape to an optimum by using the evolution and adaptation benefits of Genetic Algorithm. The feasibility and accuracy of the method are verified by implementing it to find optimum thin-walled profiles against simple parameters for …