Future work and practical applications of genetic programming

2004 ◽  
Author(s):  
John R Koza
Keyword(s):  
Genetic Programming ◽  
Practical Applications ◽  
Future Work

Essential Features and Critical Issues With Educational Chatbots

2021 ◽  
pp. 246-262
Author(s):  
Jeremy Riel
Keyword(s):  
Artificial Intelligence ◽  
Machine Learning ◽  
Formal Learning ◽  
Automated Systems ◽  
Conversational Agents ◽  
Teacher Instruction ◽  
Practical Applications ◽  
Significant Potential ◽  
Critical Issues ◽  
Future Work

Conversational agents, also known as chatbots, are automated systems for engaging in two-way dialogue with human users. These systems have existed in one form or another for at least 60 years but have recently demonstrated significant potential with advances in machine learning and artificial intelligence technologies. The use of conversational agents or chatbots for education can potentially reduce costs and supplement teacher instruction in transformative ways for formal learning. This chapter examines the design and status of chatbots and conversational agents for educational purposes. Common design functions and goals of educational chatbots are described, along with current practical applications of chatbots for educational purposes. Finally, this chapter considers issues about pedagogical commitments, ethics, and equity to suggest future work in the field.

Estimating Ability With the Wrong Model

1987 ◽  
Vol 12 (4) ◽  
pp. 339-368 ◽  
Author(s):  
Howard Wainer ◽  
David Thissen
Keyword(s):  
Item Response ◽  
Robust Estimator ◽  
Unexpected Finding ◽  
Robust Estimators ◽  
Practical Applications ◽  
Ability Estimates ◽  
Irt Models ◽  
Accuracy Of Measurement ◽  
Future Work ◽  
Bayesian Prior

No model is ever a perfect reflection of the data it is to summarize. There are always errors of fit. This is as true with modern item response theory (IRT) as with all other models. It is important to know to what extent the accuracy of measurement made with these models is influenced by misfit and what can be done to minimize the inaccuracy. First, a detailed general model was fit to data to provide the framework for a realistic simulation structure. Then three of the most commonly used IRT models were fit in this simulation. A variety of robust estimators of ability were used and the accuracy and efficiency of each estimator was determined. With short tests, a simple model coupled with a robust estimator seemed to be the methodology of choice for describing the data. As test length increased, so too did the benefits of utilizing a more complex parameterization. An unexpected finding was that coupling robust estimators with a Bayesian prior yielded substantial shrinkage. Future work on ability estimation, especially for practical applications of adaptive testing, is required to “unshrink” ability estimates.

ZERO-INFLATED POISSON REGRESSION MODELS: APPLICATIONS IN THE SCIENCES AND SOCIAL SCIENCES

2021 ◽  
pp. 2150006
Author(s):  
BUU-CHAU TRUONG ◽  
KIM-HUNG PHO ◽  
CONG-CHANH DINH ◽  
MICHAEL McALEER
Keyword(s):  
Estimating Equation ◽  
Regularity Conditions ◽  
Data Set ◽  
Practical Applications ◽  
Theoretical Contribution ◽  
Likelihood Functions ◽  
Actual Application ◽  
Zip Model ◽  
Excess Number ◽  
Future Work

This paper makes a theoretical contribution by presenting a detailed derivation of a zero-inflated Poisson (ZIP) model, and then deriving the parameters of the ZIP model using a fishing data set. This model has several practical applications, and is largely performed to model count data that have an excess number of zero counts. In the scope of the paper, we introduce the complete formulae, the likelihood and log-likelihood functions and the estimating equation of the ZIP model. We then investigate the theory of large sample properties of this model under some regularity conditions. A simulation study and a fishing data set are studied for the ZIP model. The results in the actual application in this work are meaningful, useful and crucial in reality. The results also provide reliable evidence for obtaining the largest number of fish while fishing. This is the contribution of this research in terms of applications. Finally, the important applications of this model in practice, some conclusions, and future work is also presented for consideration.

scholarly journals Quantitative Indicators for Country-Level Innovation Ecosystems

2018 ◽  
Author(s):  
Michael Hogan ◽  
Michael Gallaher
Keyword(s):  
Growth Potential ◽  
Middle Income ◽  
Practical Applications ◽  
Country Level ◽  
Data Limitations ◽  
Starting Point ◽  
Key Factor ◽  
Changes Over Time ◽  
Future Work ◽  
Quantitative Indicators

Innovation has been shown to be a key factor in determining a country’s competitiveness and economic growth potential. Through investments in education and research and development, many developing countries have tried to avoid the “middle income trap” of stagnation by working to create high-value employment opportunities. To better understand country-level readiness to innovate, we have compiled a set of publicly available data indicators and created a data tool to illustrate innovation capabilities and infrastructure by country. Our approach builds on and advances existing national innovation metrics by constructing transparent, publicly sourced indicators that emphasize changes over time and interrelationships between different indicators, as opposed to creating simple indices across groups of indicators. This occasional paper is targeted to an applied audience, explaining the methods used to assemble the data, an overview of the indicators, practical applications of the data, summary statistics, and data limitations. The data are not intended to be a tool for providing answers about innovation, but rather a starting point for future work including market landscaping, country-level diagnostics, and qualitative protocols for research.

scholarly journals A Randomised Experiment Evaluating the Mindful Raisin Practice as a Method of Reducing Chocolate Consumption During and After a Mindless Activity

2019 ◽  
Vol 4 (3) ◽  
pp. 250-257 ◽  
Author(s):  
Michail Mantzios ◽  
Helen Egan ◽  
Tayaba Asif
Keyword(s):  
Food Consumption ◽  
The State ◽  
Control Group ◽  
Weight Regulation ◽  
Mindfulness Intervention ◽  
Practical Applications ◽  
State Mindfulness ◽  
Future Work ◽  
The Impact

AbstractThe present study investigated the impact of the mindful raisin exercise on overeating during and after the experiment while controlling for wellbeing. One-hundred and twenty-eight participants were recruited and completed a questionnaire on wellbeing (i.e. depression, anxiety and stress) and state mindfulness. Participants were randomly allocated to either the mindful raisin exercise or a newspaper reading control condition. The State Mindfulness Scale was then completed again, and participants watched a neutral video while exposed to chocolate for 10 min. For those 10 min, results showed that the mindfulness condition translated into lower food consumption during the mindless activity when compared to the control condition. Post experiment, participants were asked to wait for 5 min, and any extra chocolate consumption during this time was recorded. Post-consumption was non-significantly different between the two groups, with those in the mindfulness condition consuming 1.3 g less than those in the control group. Controlling for wellbeing did not alter the impact of the mindfulness intervention on consumption. Implications for future work and practical applications for weight regulation are discussed.

scholarly journals Accelerating Neural Network Inference on FPGA-Based Platforms—A Survey

Electronics ◽  
2021 ◽  
Vol 10 (9) ◽  
pp. 1025
Author(s):  
Ran Wu ◽  
Xinmin Guo ◽  
Jian Du ◽  
Junbao Li
Keyword(s):  
Neural Network ◽  
Deep Learning ◽  
Network Inference ◽  
Semantic Segmentation ◽  
Object Identification ◽  
Data Reuse ◽  
Practical Applications ◽  
Resource Limited ◽  
Video Recognition ◽  
Future Work

The breakthrough of deep learning has started a technological revolution in various areas such as object identification, image/video recognition and semantic segmentation. Neural network, which is one of representative applications of deep learning, has been widely used and developed many efficient models. However, the edge implementation of neural network inference is restricted because of conflicts between the high computation and storage complexity and resource-limited hardware platforms in applications scenarios. In this paper, we research neural networks which are involved in the acceleration on FPGA-based platforms. The architecture of networks and characteristics of FPGA are analyzed, compared and summarized, as well as their influence on acceleration tasks. Based on the analysis, we generalize the acceleration strategies into five aspects—computing complexity, computing parallelism, data reuse, pruning and quantization. Then previous works on neural network acceleration are introduced following these topics. We summarize how to design a technical route for practical applications based on these strategies. Challenges in the path are discussed to provide guidance for future work.

scholarly journals Novel Ways of Discovering, Capturing and Experiencing Cultural Heritage: A Review of Current State-of-the-Art, Challenges and Future Directions

2021 ◽  
Author(s):  
Dimitra Pappa ◽  
Constantin Makropoulos
Keyword(s):  
Cultural Heritage ◽  
Information Technologies ◽  
Current Knowledge ◽  
Future Research ◽  
Practical Applications ◽  
Current State ◽  
Digital Scanning ◽  
Future Research Directions ◽  
New Applications ◽  
Future Work

The present chapter investigates the emerging paradigm of cultural heritage experience, as shaped by the continuous advances in information technologies. Recent years have seen the growing digitisation of cultural heritage, leveraged by innovative information technologies (imaging technologies, multimedia, virtual reality etc.). Advanced digitisation, and digital preservation and accessibility have been instrumental in transforming conservation and scientific research methods in the field of cultural heritage, as well as people’s experience of cultural heritage assets, relics, and monuments. Digitisation and immersion technologies are already in use in the context of cultural tourism in museums and on location. At the same time, a manifold of new applications and services can be generated from the adoption and adaptation of relevant technologies already applied in other sectors (e.g. 2D/3D digital scanning technologies applied in the construction industry). The present chapter will provide a thorough review of relevant digital technologies and existing work in the field, highlighting important research efforts and achievements; and will discuss the current challenges and promising avenues for future work. Following a literature review methodology, our research will provide a critical appraisal of carefully selected work from recent scientific literature and contribute to the systematisation of the current knowledge in the field towards the identification of key challenges and the extraction of new insights in terms of potential for practical applications and future research directions in the area.

scholarly journals Effect of Annealing on the Thermoelectricity Properties of the WRe26-In2O3 Thin Film Thermocouples

Micromachines ◽  
2020 ◽  
Vol 11 (7) ◽  
pp. 664
Author(s):  
Bian Tian ◽  
Yan Liu ◽  
Zhongkai Zhang ◽  
Zhaojun Liu ◽  
Libo Zhao ◽  
...  
Keyword(s):  
Thin Film ◽  
Magnetron Sputtering ◽  
Rf Magnetron Sputtering ◽  
Annealing Process ◽  
Practical Applications ◽  
Thermoelectric Voltage ◽  
Voltage Output ◽  
Thin Film Thermocouples ◽  
Future Work ◽  
Thermoelectric Stability

WRe26-In2O3 (WRe26 (tungsten-26% rhenium) and In2O3 thermoelectric materials) thin film thermocouples (TFTCs) have been fabricated based on magnetron sputtering technology, which can be used in temperature measurement. Many annealing processes were studied to promote the sensitivity of WRe26-In2O3 TFTCs. The optimal annealing process of the thermocouple under this kind of RF magnetron sputtering method was proposed after analyzing the properties of In2O3 films and the thermoelectric voltage of TFTCs at different annealing processes. The calibration results showed that the WRe26-In2O3 TFTCs achieved a thermoelectric voltage of 123.6 mV at a temperature difference of 612.9 K, with a sensitivity of up to 201.6 µV/K. Also, TFTC kept a stable thermoelectric voltage output at 973 K for 20 min and at 773 K for two hours. In general, the WRe26-In2O3 TFTCs developed in this work have great potential for practical applications. In future work, we will focus on the thermoelectric stability of TFTCs at higher temperatures.

scholarly journals Study of Retail Applications with Virtual and Augmented Reality Technologies

2021 ◽  
Vol 3 (2) ◽  
pp. 144-156
Author(s):  
Senthil T. Kumar
Keyword(s):  
Virtual Reality ◽  
Augmented Reality ◽  
Academic Research ◽  
Consumer Acceptance ◽  
Practical Applications ◽  
Shopping Experience ◽  
Virtual And Augmented Reality ◽  
Future Work

The rapidly emerging virtual reality (VR) and augmented reality (AR) technologies have greatly improved the digital shopping experience and retail selling environment. In terms of practical applications and academic research, fragmentation in VR and AR contributes to the technology's multidisciplinary roots in terms of applications. In this paper, the retail applications and research works that make use of VR and AR technology are compared and analyzed. The implementation, consumer acceptance, applications, issues and other related terms are compared. This study establishes a foundation for future work in the retail applications field.

scholarly journals Fault and calibration shift detection in a robust MEMS accelerometer array

2021 ◽  
Vol 13 (1) ◽  
Author(s):  
Daniel Watson ◽  
Karl Reichard
Keyword(s):  
Sensor Array ◽  
Health Management ◽  
Low Cost ◽  
Micro Electro Mechanical System ◽  
Mems Accelerometer ◽  
Practical Applications ◽  
Mems Sensor ◽  
Decision Logic ◽  
High Bandwidth ◽  
Future Work

The latest generation micro-electro-mechanical system(MEMS) accelerometers offer high bandwidth and low noisefloors previously limited to piezoelectric (PZT) based sensors.These relatively low cost MEMS sensors drastically expandthe financially practical applications for high frequency,vibration based, prognostics health management (PHM).This paper examines a robust array of MEMS accelerometersfor applications where sensor access after deploymentis difficult or infeasible. Three identical single axis MEMSaccelerometers were place in an array for testing. Insteadof a typical tri-axial configuration, the three sensors werealigned on a common axis. An auto-correlation algorithmwas used to detect gross system faults of individual sensorsin the array. A separate algorithm was developed to detectabnormal sensor sensitivity drift. The 3 sensor array wastested under a variety of conditions to test the developedalgorithms; power supply voltages were systematically variedaffecting the ratio-metric accelerometer sensitivity andindividual sensor mounts were purposely compromised tosimulate common fault symptoms. A decision logic treewas then implemented to respond to both types of faults.Results show the feasibility of implementing robust MEMSaccelerometer arrays using the latest generation of high bandwidthMEMS accelerometers. Planned future work includesdeploying the sensor array on tribology test equipment tovalidate MEMS sensor effectiveness compared to traditionalPZT based accelerometers.

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