Matt Treger

Bio: Matt Treger is an academic researcher. The author has contributed to research in topics: Nonverbal communication & Quality (business). The author has an hindex of 7, co-authored 35 publications receiving 484 citations.

Law of Diminishing Returns

Abstract: At some point, increased effort put into a task or operation will not result in an equal increase in output. Let's look at a production line as an example. Suppose five workers are able to produce 100 items each hour, or 20 items per person. Six workers are able to produce 132 each hour, or 22 items per person. The additional worker has increased overall productivity from 20 to 22 units per person per hour. But in this case, it turns out that adding one more worker to the line, for a total of seven, results in 147 units produced each hour, or 21 units per person.

Using Artificial Intelligence

Abstract: Computers that can see, feel, and act like people? While it may sound like science fiction, artificial intelligence (AI) simulates such processes of the human brain as reasoning, learning, and problem solving More and more, computers are developing the ability to “think,” although there is still a long way to go before they reach the complexity of a human brain

Maslow's Hierarchy of Needs

Abstract: Managers can better motivate their staffs by understanding Abraham Maslow's concepts of human motivation. Maslow described a pyramid of human needs; each need must be satisfied before the next can be addressed.

Using Financial Ratios

Abstract: 1) RMA Annual Statement Studies (Risk Management Associates) Call Number: HF 5681 .B2 R6 (latest 10 years on Reserve) The best known ratio tool, RMA gives you more ratios on more industries than any other source. RMA derives its data from annual statements. Know your company’s NAICS code before using this (get that code from Mergent). The library has RMA from 1973 to date; ask for the latest 10 years at the Access Services Desk on the 2nd (Main) floor.

From Neurons to Neighborhoods: The Science of Early Childhood Development

Abstract: How we raise young children is one of today's most highly personalized and sharply politicized issues, in part because each of us can claim some level of "expertise." The debate has intensified as discoveries about our development-in the womb and in the first months and years-have reached the popular media. How can we use our burgeoning knowledge to assure the well-being of all young children, for their own sake as well as for the sake of our nation? Drawing from new findings, this book presents important conclusions about nature-versus-nurture, the impact of being born into a working family, the effect of politics on programs for children, the costs and benefits of intervention, and other issues. The committee issues a series of challenges to decision makers regarding the quality of child care, issues of racial and ethnic diversity, the integration of children's cognitive and emotional development, and more. Authoritative yet accessible, From Neurons to Neighborhoods presents the evidence about "brain wiring" and how kids learn to speak, think, and regulate their behavior. It examines the effect of the climate-family, child care, community-within which the child grows.

Automatic Detection of Coronavirus Disease (COVID-19) Using X-ray Images and Deep Convolutional Neural Networks

Abstract: The 2019 novel coronavirus disease (COVID-19), with a starting point in China, has spread rapidly among people living in other countries, and is approaching approximately 34,986,502 cases worldwide according to the statistics of European Centre for Disease Prevention and Control. There are a limited number of COVID-19 test kits available in hospitals due to the increasing cases daily. Therefore, it is necessary to implement an automatic detection system as a quick alternative diagnosis option to prevent COVID-19 spreading among people. In this study, five pre-trained convolutional neural network based models (ResNet50, ResNet101, ResNet152, InceptionV3 and Inception-ResNetV2) have been proposed for the detection of coronavirus pneumonia infected patient using chest X-ray radiographs. We have implemented three different binary classifications with four classes (COVID-19, normal (healthy), viral pneumonia and bacterial pneumonia) by using 5-fold cross validation. Considering the performance results obtained, it has seen that the pre-trained ResNet50 model provides the highest classification performance (96.1% accuracy for Dataset-1, 99.5% accuracy for Dataset-2 and 99.7% accuracy for Dataset-3) among other four used models.

GENDERED PATHWAYS A Quantitative Investigation of Women Probationers' Paths to Incarceration

Abstract: Although qualitative research in the area of gender-responsive offending pathways has grown extensively, little quantitative work has been conducted. This study utilizes interview and survey data t...