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Full-Text Articles in Computer Engineering

Camera Placement Meeting Restrictions Of Computer Vision, Sara Aghajanzadeh, Roopasree Naidu, Shuo-Han Chen, Caleb Tung, Abhinav Goel, Yung-Hsiang Lu, George K. Thiruvathukal Oct 2020

Camera Placement Meeting Restrictions Of Computer Vision, Sara Aghajanzadeh, Roopasree Naidu, Shuo-Han Chen, Caleb Tung, Abhinav Goel, Yung-Hsiang Lu, George K. Thiruvathukal

Computer Science: Faculty Publications and Other Works

In the blooming era of smart edge devices, surveillance cam- eras have been deployed in many locations. Surveillance cam- eras are most useful when they are spaced out to maximize coverage of an area. However, deciding where to place cam- eras is an NP-hard problem and researchers have proposed heuristic solutions. Existing work does not consider a signifi- cant restriction of computer vision: in order to track a moving object, the object must occupy enough pixels. The number of pixels depends on many factors (how far away is the object? What is the camera resolution? What is the focal length ...


Evaluating The Potential Of Drone Swarms In Nonverbal Hri Communication, Kasper Grispino, Damian Lyons, Truong-Huy Nguyen Sep 2020

Evaluating The Potential Of Drone Swarms In Nonverbal Hri Communication, Kasper Grispino, Damian Lyons, Truong-Huy Nguyen

Faculty Publications

Human-to-human communications are enriched with affects and emotions, conveyed, and perceived through both verbal and nonverbal communication. It is our thesis that drone swarms can be used to communicate information enriched with effects via nonverbal channels: guiding, generally interacting with, or warning a human audience via their pattern of motions or behavior. And furthermore that this approach has unique advantages such as flexibility and mobility over other forms of user interface. In this paper, we present a user study to understand how human participants perceived and interpreted swarm behaviors of micro-drone Crazyflie quadcopters flying three different flight formations to bridge ...


Temporal Heterogeneous Interaction Graph Embedding For Next-Item Recommendation, Yugang Ji, Mingyang Yin, Yuan Fang, Hongxia Yang, Xiangwei Wang, Tianrui Jia, Chuan Shi Sep 2020

Temporal Heterogeneous Interaction Graph Embedding For Next-Item Recommendation, Yugang Ji, Mingyang Yin, Yuan Fang, Hongxia Yang, Xiangwei Wang, Tianrui Jia, Chuan Shi

Research Collection School Of Information Systems

In the scenario of next-item recommendation, previous methods attempt to model user preferences by capturing the evolution of sequential interactions. However, their sequential expression is often limited, without modeling complex dynamics that short-term demands can often be influenced by long-term habits. Moreover, few of them take into account the heterogeneous types of interaction between users and items. In this paper, we model such complex data as a Temporal Heterogeneous Interaction Graph (THIG) and learn both user and item embeddings on THIGs to address next-item recommendation. The main challenges involve two aspects: the complex dynamics and rich heterogeneity of interactions. We ...


Embedding Online Runtime Verification For Fault Disambiguation On Robonaut2, Brian Kempa, Pei Zhang, Phillip H. Jones, Joseph Zambreno, Kristin Yvonne Rozier Aug 2020

Embedding Online Runtime Verification For Fault Disambiguation On Robonaut2, Brian Kempa, Pei Zhang, Phillip H. Jones, Joseph Zambreno, Kristin Yvonne Rozier

Aerospace Engineering Conference Papers, Presentations and Posters

Robonaut2 (R2) is a humanoid robot onboard the International Space Station (ISS), performing specialized tasks in collaboration with astronauts. After deployment, R2 developed an unexpected emergent behavior. R2’s inability to distinguish between knee-joint faults (e.g., due to sensor drift versus violated environmental assumptions) began triggering safety-preserving freezes-in-place in the confined space of the ISS, preventing further motion until a ground-control operator determines the root-cause and initiates proper corrective action. Runtime verification (RV) algorithms can efficiently disambiguate the temporal signatures of different faults in real-time. However, no previous RV engine can operate within the limited available resources and specialized ...


A Review Paper: Analysis Of Weka Data Mining Techniques For Heart Disease Prediction System, Basma Jumaa Saleh, Ahmed Yousif Falih Saedi, Ali Talib Qasim Al-Aqbi, Lamees Abdalhasan Salman Aug 2020

A Review Paper: Analysis Of Weka Data Mining Techniques For Heart Disease Prediction System, Basma Jumaa Saleh, Ahmed Yousif Falih Saedi, Ali Talib Qasim Al-Aqbi, Lamees Abdalhasan Salman

Library Philosophy and Practice (e-journal)

Data mining is characterized as searching for useful information through very large data sets. Some of the key and most common techniques for data mining are association rules, classification, clustering, prediction, and sequential models. For a wide range of applications, data mining techniques are used. Data mining plays a significant role in disease detection in the health care industry. The patient should be needed to detect a number of tests for the disease. However, the number of tests should be reduced by using data mining techniques. In time and performance, this reduced test plays an important role. Heart disease is ...


Nsf Engineering Research Center For Advancing Sustainability Through Powered Infrastructure For Roadway Electrification (Aspire), Zane Regan Aug 2020

Nsf Engineering Research Center For Advancing Sustainability Through Powered Infrastructure For Roadway Electrification (Aspire), Zane Regan

Funded Research Records

No abstract provided.


Enhanced Control Algorithms In Permanent Magnet Synchronous Machines, Haibo Li Aug 2020

Enhanced Control Algorithms In Permanent Magnet Synchronous Machines, Haibo Li

Theses, Dissertations, and Student Research from Electrical & Computer Engineering

Permanent magnet synchronous machines (PMSMs) are gaining increasing popularity in various applications due to their advantages, such as high efficiency, high power density, and superior control performance. A well-designed machine control algorithm is indispensable for a PMSM system to secure its good performance.

In this work, enhanced control algorithms in PMSMs are developed. Online machine current trajectory tracking, source power management, hardware overcurrent regulation, and machine current sensor fault detection and isolation (FDI) are included in the developed algorithms. The online machine current trajectory tracking ensures the maximum torque per ampere (MTPA) or maximum torque per voltage (MTPV) control in ...


An End-To-End Trainable Method For Generating And Detecting Fiducial Markers, J Brennan Peace Aug 2020

An End-To-End Trainable Method For Generating And Detecting Fiducial Markers, J Brennan Peace

Theses, Dissertations, and Student Research from Electrical & Computer Engineering

Existing fiducial markers are designed for efficient detection and decoding. The methods are computationally efficient and capable of demonstrating impressive results, however, the markers are not explicitly designed to stand out in natural environments and their robustness is difficult to infer from relatively limited analysis. Worsening performance in challenging image capture scenarios - such as poorly exposed images, motion blur, and off-axis viewing - sheds light on their limitations. The method introduced in this work is an end-to-end trainable method for designing fiducial markers and a complimentary detector. By introducing back-propagatable marker augmentation and superimposition into training, the method learns to generate ...


Querying Recurrent Convoys Over Trajectory Data, Munkh-Erdene Yadamjav, Zhifeng Bao, Baihua Zheng, Farhana M. Choudhury, Hanan Samet Aug 2020

Querying Recurrent Convoys Over Trajectory Data, Munkh-Erdene Yadamjav, Zhifeng Bao, Baihua Zheng, Farhana M. Choudhury, Hanan Samet

Research Collection School Of Information Systems

Moving objects equipped with location-positioning devices continuously generate a large amount of spatio-temporal trajectory data. An interesting finding over a trajectory stream is a group of objects that are travelling together for a certain period of time. Existing studies on mining co-moving objects do not consider an important correlation between co-moving objects, which is the reoccurrence of the movement pattern. In this study, we define a problem of finding recurrent pattern of co-moving objects from streaming trajectories and propose an efficient solution that enables us to discover recent co-moving object patterns repeated within a given time period. Experimental results on ...


Formal Language Constraints In Deep Reinforcement Learning For Self-Driving Vehicles, Tyler Bienhoff Jul 2020

Formal Language Constraints In Deep Reinforcement Learning For Self-Driving Vehicles, Tyler Bienhoff

Computer Science and Engineering: Theses, Dissertations, and Student Research

In recent years, self-driving vehicles have become a holy grail technology that, once fully developed, could radically change the daily behaviors of people and enhance safety. The complexities of controlling a car in a constantly changing environment are too immense to directly program how the vehicle should behave in each specific scenario. Thus, a common technique when developing autonomous vehicles is to use reinforcement learning, where vehicles can be trained in simulated and real-world environments to make proper decisions in a wide variety of scenarios. Reinforcement learning models, however, have uncertainties in how the vehicle acts, especially in a previously ...


A Novel Path Loss Forecast Model To Support Digital Twins For High Frequency Communications Networks, James Marvin Taylor Jr Jul 2020

A Novel Path Loss Forecast Model To Support Digital Twins For High Frequency Communications Networks, James Marvin Taylor Jr

Theses, Dissertations, and Student Research from Electrical & Computer Engineering

The need for long-distance High Frequency (HF) communications in the 3-30 MHz frequency range seemed to diminish at the end of the 20th century with the advent of space-based communications and the spread of fiber optic-connected digital networks. Renewed interest in HF has emerged as an enabler for operations in austere locations and for its ability to serve as a redundant link when space-based and terrestrial communication channels fail. Communications system designers can create a “digital twin” system to explore the operational advantages and constraints of the new capability. Existing wireless channel models can adequately simulate communication channel conditions with ...


Research Review On Mixed-Criticality Scheduling, Hattan Althebeiti Jul 2020

Research Review On Mixed-Criticality Scheduling, Hattan Althebeiti

Recent Advances in Real-Time Systems as of 2019

No abstract provided.


Artificial Intelligence And Game Theory Controlled Autonomous Uav Swarms, Janusz Kusyk, M. Umit Uyar, Kelvin Ma, Eltan Samoylov, Ricardo Valdez, Joseph Plishka, Sagor E. Hoque, Giorgio Bertoli, Jefrey Boksiner Jul 2020

Artificial Intelligence And Game Theory Controlled Autonomous Uav Swarms, Janusz Kusyk, M. Umit Uyar, Kelvin Ma, Eltan Samoylov, Ricardo Valdez, Joseph Plishka, Sagor E. Hoque, Giorgio Bertoli, Jefrey Boksiner

Publications and Research

Autonomous unmanned aerial vehicles (UAVs) operating as a swarm can be deployed in austere environments, where cyber electromagnetic activities often require speedy and dynamic adjustments to swarm operations. Use of central controllers, UAV synchronization mechanisms or pre-planned set of actions to control a swarm in such deployments would hinder its ability to deliver expected services. We introduce artificial intelligence and game theory based flight control algorithms to be run by each autonomous UAV to determine its actions in near real-time, while relying only on local spatial, temporal and electromagnetic (EM) information. Each UAV using our flight control algorithms positions itself ...


A Real-Time Feature Indexing System On Live Video Streams, Aditya Chakraborty, Akshay Pawar, Hojoung Jang, Shunqiao Huang, Sripath Mishra, Shuo-Han Chen, Yuan-Hao Chang, George K. Thiruvathukal, Yung-Hsiang Lu Jul 2020

A Real-Time Feature Indexing System On Live Video Streams, Aditya Chakraborty, Akshay Pawar, Hojoung Jang, Shunqiao Huang, Sripath Mishra, Shuo-Han Chen, Yuan-Hao Chang, George K. Thiruvathukal, Yung-Hsiang Lu

Computer Science: Faculty Publications and Other Works

Most of the existing video storage systems rely on offline processing to support the feature-based indexing on video streams. The feature-based indexing technique provides an effec- tive way for users to search video content through visual features, such as object categories (e.g., cars and persons). However, due to the reliance on offline processing, video streams along with their captured features cannot be searchable immediately after video streams are recorded. According to our investigation, buffering and storing live video steams are more time-consuming than the YOLO v3 object detector. Such observation motivates us to propose a real-time feature indexing (RTFI ...


Transcending Lockdown: Fostering Student Imagination Through Computer-Supported Collaborative Learning And Creativity In Engineering Design Courses, Martin E. Nolan Jul 2020

Transcending Lockdown: Fostering Student Imagination Through Computer-Supported Collaborative Learning And Creativity In Engineering Design Courses, Martin E. Nolan

Creative Humanities

Engineering design and communication courses are typically dynamic, active learning spaces that bring together a complex array of knowledge and skills. Their ambiguous nature has allowed, often contentiously, subjects such as language and communication, the arts, the humanities and the social sciences to enter the discourse of engineering in a newly meaningful way. This paper considers this development in the context of the COVID-19 pandemic, and in particular how the creativity and imagination required to succeed in engineering design might be cultivated in emergency distance learning. I consider a plethora of sources for guidance, with a special interest in how ...


Power-Over-Tether Uas Leveraged For Nearly-Indefinite Meteorological Data Acquisition, Daniel Rico, Carrick Detweiler, Francisco Muñoz-Arriola Jul 2020

Power-Over-Tether Uas Leveraged For Nearly-Indefinite Meteorological Data Acquisition, Daniel Rico, Carrick Detweiler, Francisco Muñoz-Arriola

Computer Science and Engineering: Theses, Dissertations, and Student Research

Use of unmanned aerial systems (UASs) in agriculture has risen in the past decade. These systems are key to modernizing agriculture. UASs collect and elucidate data previously difficult to obtain and used to help increase agricultural efficiency and production. Typical commercial off-the-shelf (COTS) UASs are limited by small payloads and short flight times. Such limits inhibit their ability to provide abundant data at multiple spatiotemporal scales. In this paper, we describe the design and construction of the tethered aircraft unmanned system (TAUS), which is a novel power-over-tether UAS leveraging the physical presence of the tether to launch multiple sensors along ...


Born-Digital Preservation: The Art Of Archiving Photos With Script And Batch Processing, Rachel S. Evans, Leslie Grove, Sharon Bradley Jul 2020

Born-Digital Preservation: The Art Of Archiving Photos With Script And Batch Processing, Rachel S. Evans, Leslie Grove, Sharon Bradley

Articles, Chapters and Online Publications

With our IT department preparing to upgrade the University of Georgia’s Alexander Campbell King Law Library (UGA Law Library) website from Drupal 7 to 8 this fall, a web developer, an archivist, and a librarian teamed up a year ago to make plans for preserving thousands of born-digital images. We wanted to harvest photographs housed only in web-based photo galleries on the law school website and import them into our repository’s collection. The problem? There were five types of online photo galleries, and our current repository did not include appropriate categories for all of the photographs. The solution ...


Vector Magneto-Optical Generalized Ellipsometry On Magnetic Slanted Columnar Heterostructured Thin Films, Chad Briley Jul 2020

Vector Magneto-Optical Generalized Ellipsometry On Magnetic Slanted Columnar Heterostructured Thin Films, Chad Briley

Theses, Dissertations, and Student Research from Electrical & Computer Engineering

Modern material growth techniques allow for nano-engineering highly complex three dimensionally nanostructured materials. These nano-engineered materials possess highly anisotropic physical properties that are significantly different from that of their bulk counterparts. The magnetization properties of nano-engineered materials can be modified through a close range interaction known as magnetic exchange. These materials are referred to as magnetic exchange-coupled materials. Exchange-coupled magnetic materials are composite magnetic materials where the magnetization of one material is influenced by the magnetization state of the neighboring materials.

The author describes the creation of a representative sample set of exchange-coupled nanoengineered magnetic materials. These materials are created ...


Adaptive Large Neighborhood Search For Vehicle Routing Problem With Cross-Docking, Aldy Gunawan, Audrey Tedja Widjaja, Pieter Vansteenwegen, Vincent F. Yu Jul 2020

Adaptive Large Neighborhood Search For Vehicle Routing Problem With Cross-Docking, Aldy Gunawan, Audrey Tedja Widjaja, Pieter Vansteenwegen, Vincent F. Yu

Research Collection School Of Information Systems

Cross-docking is considered as a method to manage and control the inventory flow, which is essential in the context of supply chain management. This paper studies the integration of the vehicle routing problem with cross-docking, namely VRPCD which has been extensively studied due to its ability to reducethe overall costs occurring in a supply chain network. Given a fleet of homogeneous vehicles for delivering a single type of product from suppliers to customers through a cross-dock facility, the objective of VRPCD is to determine the number of vehicles used and the corresponding vehicle routes, such that the vehicleoperational and transportation ...


Active Fuzzing For Testing And Securing Cyber-Physical Systems, Yuqi Chen, Bohan Xuan, Christopher M. Poskitt, Jun Sun, Fan Zhang Jul 2020

Active Fuzzing For Testing And Securing Cyber-Physical Systems, Yuqi Chen, Bohan Xuan, Christopher M. Poskitt, Jun Sun, Fan Zhang

Research Collection School Of Information Systems

Cyber-physical systems (CPSs) in critical infrastructure face a pervasive threat from attackers, motivating research into a variety of countermeasures for securing them. Assessing the effectiveness of these countermeasures is challenging, however, as realistic benchmarks of attacks are difficult to manually construct, blindly testing is ineffective due to the enormous search spaces and resource requirements, and intelligent fuzzing approaches require impractical amounts of data and network access. In this work, we propose active fuzzing, an automatic approach for finding test suites of packet-level CPS network attacks, targeting scenarios in which attackers can observe sensors and manipulate packets, but have no existing ...


Moving Targets: Addressing Concept Drift In Supervised Models For Hacker Communication Detection, Susan Mckeever, Brian Keegan, Andrei Quieroz Jun 2020

Moving Targets: Addressing Concept Drift In Supervised Models For Hacker Communication Detection, Susan Mckeever, Brian Keegan, Andrei Quieroz

Conference papers

Abstract—In this paper, we are investigating the presence of concept drift in machine learning models for detection of hacker communications posted in social media and hacker forums. The supervised models in this experiment are analysed in terms of performance over time by different sources of data (Surface web and Deep web). Additionally, to simulate real-world situations, these models are evaluated using time-stamped messages from our datasets, posted over time on social media platforms. We have found that models applied to hacker forums (deep web) presents an accuracy deterioration in less than a 1-year period, whereas models applied to Twitter ...


Intelligent Sdn Traffic Classification Using Deep Learning: Deep-Sdn, Ali Malik, Ruairí De Fréin, Mohammed Al-Zeyadi, Javier Andreu-Perez Jun 2020

Intelligent Sdn Traffic Classification Using Deep Learning: Deep-Sdn, Ali Malik, Ruairí De Fréin, Mohammed Al-Zeyadi, Javier Andreu-Perez

Conference papers

Accurate traffic classification is fundamentally important for various network activities such as fine-grained network management and resource utilisation. Port-based approaches, deep packet inspection and machine learning are widely used techniques to classify and analyze network traffic flows. However, over the past several years, the growth of Internet traffic has been explosive due to the greatly increased number of Internet users. Therefore, both port-based and deep packet inspection approaches have become inefficient due to the exponential growth of the Internet applications that incurs high computational cost. The emerging paradigm of software-defined networking has reshaped the network architecture by detaching the control ...


A Proactive-Restoration Technique For Sdns, Ali Malik, Ruairí De Fréin Jun 2020

A Proactive-Restoration Technique For Sdns, Ali Malik, Ruairí De Fréin

Conference papers

Failure incidents result in temporarily preventing the network from delivering services properly. Such a deterioration in services called service unavailability. The traditional fault management techniques, i.e. protection and restoration, are inevitably concerned with service unavailability due to the convergence time that is required to achieve the recovery when a failure occurs. However, with the global view feature of software-defined networking a failure prediction is becoming attainable, which in turn reduces the service interruptions that originated by failures. In this paper, we propose a proactive restoration technique that reconfigure the vulnerable routes which are likely to be affected if the ...


A Fully Lexicographic Extension Of Min Or Max Operation Cannot Be Associative, Olga Kosheleva, Vladik Kreinovich Jun 2020

A Fully Lexicographic Extension Of Min Or Max Operation Cannot Be Associative, Olga Kosheleva, Vladik Kreinovich

Departmental Technical Reports (CS)

In many applications of fuzzy logic, to estimate the degree of confidence in a statement A&B, we take the minimum min(a,b) of the expert's degrees of confidence in the two statements A and B. When a < b, then an increase in b does not change this estimate, while from the commonsense viewpoint, our degree of confidence in A&B should increase. To take this commonsense idea into account, Ildar Batyrshin and colleagues proposed to extend the original order in the interval [0,1] to a lexicographic order on a larger set. This idea works for expressions of the type A&B, so maybe we can extend it to more general expressions? In this paper, we show that such an extension, while theoretically possible, would violate another commonsense requirement -- associativity of the "and"-operation. A similar negative result is proven for lexicographic extensions of the maximum operation -- that estimates the expert's degree of confidence in a statement A\/B.


What Is The Optimal Annealing Schedule In Quantum Annealing, Oscar Galindo, Vladik Kreinovich Jun 2020

What Is The Optimal Annealing Schedule In Quantum Annealing, Oscar Galindo, Vladik Kreinovich

Departmental Technical Reports (CS)

In many real-life situations in engineering (and in other disciplines), we need to solve an optimization problem: we want an optimal design, we want an optimal control, etc. One of the main problems in optimization is avoiding local maxima (or minima). One of the techniques that helps with solving this problem is annealing: whenever we find ourselves in a possibly local maximum, we jump out with some probability and continue search for the true optimum. A natural way to organize such a probabilistic perturbation of the deterministic optimization is to use quantum effects. It turns out that often, quantum annealing ...


Lexicographic-Type Extension Of Min-Max Logic Is Not Uniquely Determined, Olga Kosheleva, Vladik Kreinovich Jun 2020

Lexicographic-Type Extension Of Min-Max Logic Is Not Uniquely Determined, Olga Kosheleva, Vladik Kreinovich

Departmental Technical Reports (CS)

Since in a computer, "true" is usually represented as 1 and ``false'' as 0, it is natural to represent intermediate degrees of confidence by numbers intermediate between 0 and 1; this is one of the main ideas behind fuzzy logic -- a technique that has led to many useful applications. In many such applications, the degree of confidence in A & B is estimated as the minimum of the degrees of confidence corresponding to A and B, and the degree of confidence in A \/ B is estimated as the maximum; for example, 0.5 \/ 0.3 = 0.5. It is intuitively OK that, e.g., 0.5 \/ 0.3 < 0.51 and, more generally, that 0.5 \/ 0.3 < 0.5 + ε for all ε > 0. However, intuitively, an additional argument in favor of the statement should increase our degree of confidence, i.e., we should have ...


How To Train A-To-B And B-To-A Neural Networks So That The Resulting Transformations Are (Almost) Exact Inverses, Paravee Maneejuk, Torben Peters, Claus Brenner, Vladik Kreinovich Jun 2020

How To Train A-To-B And B-To-A Neural Networks So That The Resulting Transformations Are (Almost) Exact Inverses, Paravee Maneejuk, Torben Peters, Claus Brenner, Vladik Kreinovich

Departmental Technical Reports (CS)

In many practical situations, there exist several representations, each of which is convenient for some operations, and many data processing algorithms involve transforming back and forth between these representations. Many such transformations are computationally time-consuming when performed exactly. So, taking into account that input data is usually only 1-10% accurate anyway, it makes sense to replace time-consuming exact transformations with faster approximate ones. One of the natural ways to get a fast-computing approximation to a transformation is to train the corresponding neural network. The problem is that if we train A-to-B and B-to-A networks separately, the resulting approximate transformations are ...


Why Lasso, Ridge Regression, And En: Explanation Based On Soft Computing, Woraphon Yamaka, Hamza Alkhatib, Ingo Neumann, Vladik Kreinovich Jun 2020

Why Lasso, Ridge Regression, And En: Explanation Based On Soft Computing, Woraphon Yamaka, Hamza Alkhatib, Ingo Neumann, Vladik Kreinovich

Departmental Technical Reports (CS)

In many practical situations, observations and measurement results are consistent with many different models -- i.e., the corresponding problem is ill-posed. In such situations, a reasonable idea is to take into account that the values of the corresponding parameters should not be too large; this idea is known as {\it regularization}. Several different regularization techniques have been proposed; empirically the most successful are LASSO method, when we bound the sum of absolute values of the parameters, ridge regression method, when we bound the sum of the squares, and a EN method in which these two approaches are combined. In this ...


When Can We Be Sure That Measurement Results Are Consistent: 1-D Interval Case And Beyond, Hani Dbouk, Steffen Schön, Ingo Neumann, Vladik Kreinovich Jun 2020

When Can We Be Sure That Measurement Results Are Consistent: 1-D Interval Case And Beyond, Hani Dbouk, Steffen Schön, Ingo Neumann, Vladik Kreinovich

Departmental Technical Reports (CS)

In many practical situations, measurements are characterized by interval uncertainty -- namely, based on each measurement result, the only information that we have about the actual value of the measured quantity is that this value belongs to some interval. If several such intervals -- corresponding to measuring the same quantity -- have an empty intersection, this means that at least one of the corresponding measurement results is an outlier, caused by a malfunction of the measuring instrument. From the purely mathematical viewpoint, if the intersection is non-empty, there is no reason to be suspicious, but from the practical viewpoint, if the intersection is ...


Closing The Data-Decisions Loop: Deploying Artificial Intelligence For Dynamic Resource Management, Pradeep Varakantham Jun 2020

Closing The Data-Decisions Loop: Deploying Artificial Intelligence For Dynamic Resource Management, Pradeep Varakantham

Asian Management Insights

Improving predictions and allocations to determine the optimal matching of demand and supply in a dynamic, uncertain future.