Journal of Management and Engineering Integration, v.15 no.2

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    Journal of Management & Engineering Integration, v.15, no.2 (Winter)
    (Association for Industry, Engineering and Management Systems (AIEMS), 2022-12) Association for Industry, Engineering and Management Systems (AIEMS)
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    Effects of functional nanomaterials for reduction of carbon monoxide levels in the workplace and homes
    (Association for Industry, Engineering and Management Systems (AIEMS), 2022-12) Asmatulu, Eylem; Pham, Anh
    Carbon monoxide (CO) at high concentrations is extremely poisonous to humans and other invertebrates. It is one of the leading causes of unintentional deaths in the United States. Furthermore, people with heart diseases are more vulnerable to high CO levels since they already have a reduced ability to get oxygenated blood to their hearts. Functional nanomaterials (metallic nanoparticles [NPs], carbon nanotubes [CNTs], and nanofibers [NFs]) offer a high surface area, low weight-to-volume ratio, flexibility, and high porosity, which are perfect properties for gas absorption. Many nanomaterials are currently playing an essential role in CO-capturing technologies. This paper focuses on the usage of those functional nanomaterials for CO absorption and their absorption mechanisms. Due to high surface area and porosity, these materials have been widely used to absorb pollutants, including toxic gas like CO. Fabrications, CO-absorbing mechanisms, and absorbing properties of some nanomaterials will be discussed here.
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    Computer applications: A novel architecture to improve the performance of audio visual applications
    (Association for Industry, Engineering and Management Systems (AIEMS), 2022-12) Asaduzzaman, Abu; Chidella, Kishore K.; Sibai, Fadi N.
    To attain the best audio-visual experience, the underlying computing platform should provide high performance in real time. The forthcoming computer systems consist of multicore processors to achieve a high performance-to-power ratio. The algorithms in visual computing are becoming highly complex to meet the requirements. According to the new design paradigm, a simultaneous exploration of multicore architecture and complicated algorithms is beneficial to achieve the design goals for visual systems. However, caches in multicore architecture multiply the timing unpredictability and that creates a serious challenge in running real-time audio/visual applications in multicore systems. In this work, we introduce a novel multicore architecture with miss tables inside level-1 caches to improve performance and decrease power consumption. Miss table holds block address information regarding the application being processed that causes cache misses. Miss table information is used for efficient selection of the blocks to be locked or victim blocks to be replaced. This approach improves predictability by locking important blocks inside the cache during the execution time. At the same time, this approach decreases average delay per task and total power consumption by reducing cache misses when the right cache blocks are locked and/or replaced. We simulate an 8-core architecture that has 2 levels of caches using the Moving Picture Experts Group (MPEG)-4 decoding and Fast Fourier Transform (FFT) workloads. Simulation results show that a reduction of 42% in mean delay per task and a reduction of 40% in total power consumption are achieved by locking 20% of the total level-1 instruction (I1) cache size.
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    Continuous human pose estimation by machine learning and computer vision
    (Association for Industry, Engineering and Management Systems (AIEMS), 2022-12) Huan, Xiaoli; Zhou, Hong
    Pose estimation is an important topic that has drawn significant attention from the computer vision community (Luo, Wang, Wong, & Cheng, 2020). The main task is to identify and track the pose of a person in an image or video. It can also be thought of as solving the problem of determining a set of coordinates that describe the person's pose.
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    Business analytics at Florida commuter colleges: The impact and effectiveness of implementing a business analytics program
    (Association for Industry, Engineering and Management Systems (AIEMS), 2022-12) Gooden, Joachim P.; Ford, Rakeem R.; Black, Jason T.
    Only forty of Florida's one-hundred seventy-eight colleges and universities are public, meaning the vast majority are privately run. Many of these schools provide associate degrees or certificates (Community College Review, 2021). Commuter colleges hold the distinction of providing off-campus student living, with the majority offering two-year degrees. Despite the growing need in industry for individuals who can manage large amounts of data, commuter colleges rarely offer business analytics courses, causing many students to miss out on such employment opportunities. Most businesses struggle with analytical planning and are looking for experts who can turn data into insight (Albright & Winston, 2016). The absence of data analytics capabilities causes organizations to waste data resources at a rate of approximately sixty to seventy percent (Forrester, 2017). Intrinsically, universities of all sizes, including commuter colleges, need to train and produce more data analysts. Many major universities now offer business analytics degrees, yet business analytics degrees are available at less than twenty percent of commuter colleges. The goal of this research is to investigate whether commuter colleges would indeed benefit from business analytics programs and to determine the appropriate analytics degree curricula most optimal for these types of institutions. The paper will present an exhaustive comparison of the state of Florida's colleges and universities, including commuter colleges, examining both business intelligence and business analytics degree programs. The objective is to analyze the impact and effectiveness of these programs at larger universities and present a model for developing such programs at commuter colleges.