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Impact of Artificial Intelligence on Corporate Leadership

Journal of Computer and Communications 2024年第4期12卷 40-48页

作者： daniel schilling weiss nguyen Mudassir Mohiddin Shaik School of Business and Technology (SBT) Aspen University Phoenix Arizona USA Information Technology Indiana Wesleyan University Indianapolis Indiana USA

Artificial Intelligence (AI) is transforming organizational dynamics, and revolutionizing corporate leadership practices. This research paper delves into the question of how AI influences corporate leadership, examining both its advantages and disadvantages. Positive impacts of AI are evident in communication, feedback systems, tracking mechanisms, and decision-making processes within organizations. AI-powered communication tools, as exemplified by Slack, facilitate seamless collaboration, transcending geographical barriers. Feedback systems, like Adobe’s Performance Management System, employ AI algorithms to provide personalized development opportunities, enhancing employee growth. AI-based tracking systems optimize resource allocation, as exemplified by studies like “AI-Based Tracking Systems: Enhancing Efficiency and Accountability.” Additionally, AI-powered decision support, demonstrated during the COVID-19 pandemic, showcases the capability to navigate complex challenges and maintain resilience. However, AI adoption poses challenges in human resources, potentially leading to job displacement and necessitating upskilling efforts. Managing AI errors becomes crucial, as illustrated by instances like Amazon’s biased recruiting tool. Data privacy concerns also arise, emphasizing the need for robust security measures. The proposed solution suggests leveraging Local Machine Learning Models (LLMs) to address data privacy issues. Approaches such as federated learning, on-device learning, differential privacy, and homomorphic encryption offer promising strategies. By exploring the evolving dynamics of AI and leadership, this research advocates for responsible AI adoption and proposes LLMs as a potential solution, fostering a balanced integration of AI benefits while mitigating associated risks in corporate settings.

关键词： Artificial Intelligence (AI) Corporate Leadership Communication Feedback Systems Tracking Mechanisms Decision-Making Local Machine Learning Models (LLMs) Federated Learning On-Device Learning Differential Privacy Homomorphic Encryption

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Toward Artificial General Intelligence: Deep Reinforcement Learning Method to AI in Medicine

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Journal of Computer and Communications 2023年第9期11卷 84-120页

作者： daniel schilling weiss nguyen Richard Odigie Aspen University Phoenix AZ USA

Artificial general intelligence (AGI) is the ability of an artificial intelligence (AI) agent to solve somewhat-arbitrary tasks in somewhat-arbitrary environments. Despite being a long-standing goal in the field of AI, achieving AGI remains elusive. In this study, we empirically assessed the generalizability of AI agents by applying a deep reinforcement learning (DRL) approach to the medical domain. Our investigation involved examining how modifying the agent’s structure, task, and environment impacts its generality. Sample: An NIH chest X-ray dataset with 112,120 images and 15 medical conditions. We evaluated the agent’s performance on binary and multiclass classification tasks through a baseline model, a convolutional neural network model, a deep Q network model, and a proximal policy optimization model. Results: Our results suggest that DRL agents with the algorithmic flexibility to autonomously vary their macro/microstructures can generalize better across given tasks and environments.

关键词： Artificial Intelligence Deep Learning General-Purpose Learning Agent Generalizability Algorithmic Flexibility Internal Autonomy

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Deepfake Video Detection Employing Human Facial Features

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Journal of Computer and Communications 2023年第12期11卷 1-13页

作者： daniel schilling weiss nguyen Desmond T. Ademiluyi Computer Science (DSCS) Aspen University Phoenix USA

Deepfake technology can be used to replace people’s faces in videos or pictures to show them saying or doing things they never said or did. Deepfake media are often used to extort, defame, and manipulate public opinion. However, despite deepfake technology’s risks, current deepfake detection methods lack generalization and are inconsistent when applied to unknown videos, i.e., videos on which they have not been trained. The purpose of this study is to develop a generalizable deepfake detection model by training convoluted neural networks (CNNs) to classify human facial features in videos. The study formulated the research questions: “How effectively does the developed model provide reliable generalizations?” A CNN model was trained to distinguish between real and fake videos using the facial features of human subjects in videos. The model was trained, validated, and tested using the FaceForensiq++ dataset, which contains more than 500,000 frames and subsets of the DFDC dataset, totaling more than 22,000 videos. The study demonstrated high generalizability, as the accuracy of the unknown dataset was only marginally (about 1%) lower than that of the known dataset. The findings of this study indicate that detection systems can be more generalizable, lighter, and faster by focusing on just a small region (the human face) of an entire video.

关键词： Artificial Intelligence Convoluted Neural Networks Deepfake GANs Generalization Deep Learning Facial Features Video Frames

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Effectiveness of Wastewater-Based Epidemiology as an Early Warning Tool to Detect SARS-CoV-2 (COVID-19)

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Health 2024年第7期16卷 635-656页

作者： Rakib Ahmed Chowdhury daniel E. Meeroff Sumaiya Sharmin Alamgir Kabir Sara Hollenbeck Valerie Dalencourt Thu nguyen Zack Farmer Frederick Bloetscher Waseem Asghar Stacey Volnick College of Engineering and Computer Science Florida Atlantic University Boca Raton FL USA

Medical diagnostic tests to detect Severe Acute Respiratory Syndrome Coronavirus-2 (SARS-CoV-2) for individuals in the United States were initially limited to people who were traveling or symptomatic to track disease incidence due to the cost of providing testing for all people in a community on a routine basis. As an alternative to randomly sampling large groups of people to track disease incidence at significant cost, wastewater-based epidemiology (WBE) is a well-established and cost-effective technique to passively measure the prevalence of disease in communities without requiring invasive testing. WBE can also be used as a forecasting tool since the virus is shed in individuals prior to developing symptoms that might otherwise prompt testing. This study applied the WBE approach to understand its effectiveness as a possible forecasting tool by monitoring the SARS-CoV-2 levels in raw wastewater sampled from sewer lift stations at a large public university campus setting including dormitories, academic buildings, and athletic facilities. The WBE analysis was conducted by sampling from building-specific lift stations and enumerating target viral copies using RT-qPCR analysis. The WBE results were compared with the 7-day rolling averages of confirmed infected individuals for the following week after the wastewater sample analysis. In most cases, changes in the WBE outcomes were followed by similar trends in the clinical data. The positive predictive value of the applied WBE approach was 86% for the following week of the sample collection. In contrast, positive correlations between the two data with Spearmen correlation (rs) ranged from 0.16 to 0.36. A stronger correlation (rs = 0.18 to 0.51) was observed when WBE results were compared with COVID-19 cases identified on the next day of the sampling events. The P value of 0.007 for Dorm A suggests high significance, while moderate significance was observed for the other dormitories (B, C, and D). The outcomes of this in

关键词： SARS-CoV-2 Wastewater Detection Wastewater-Based Epidemiology (WBE)

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Resilience and Stability in Organizations Employing Cloud Computing in the Financial Services Industry

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Journal of Computer and Communications 2023年第4期11卷 103-148页

作者： daniel schilling nguyen Juliette Sondano Aspen University Phoenix AZ USA

The services and solutions offered by cloud computing continue to grow, just as the number of organizations relying on the service. Cloud computing has become prevalent in the financial services industry, where 83% of financial services institutions identified cloud computing as a primary element of their infrastructure. Although there are specific benefits of cloud computing that organizations rely on such as access to critical services and lower costs, there is the possibility that cloud computing will create costs for organizations. The purpose of the study was to present an intensive review of the benefits and threats by investigating resilience and stability of the organizations in financial services industry that use cloud computing as their primary element of infrastructure. Data collected from the interview was used to answer original research questions, which are: How are organizations in the financial services industry resilient when faced with threats or losses associated with the use of cloud computing in their organization? How do organizations in the financial services industry maintain stability when faced with threats or losses associated with the use of cloud computing in their organization? The study supports the advancement of knowledge by identifying the threats and losses that occur due to the use of cloud computing, and organizations understand common threats and thus implement proper mitigation.

关键词： Resilience Cloud Computing Financial Services Industry

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CAD-VR geometry and meta data synchronization for design review applications

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Journal of Zhejiang University-Science A(Applied Physics & Engineering) 2006年第9期7卷 1482-1491页

作者： schilling Arne KIM Seokryul weissMANN daniel TANG Ziying CHOI Sangsu Fraunhofer Institute for Computer Graphics （IGD） Darmstadt 64283 Germany Institute for Graphic Interfaces （IGI） Seou1120-750 Korea Computer Graphics Center （ZGD V） Rostock 18059 Germany

In this paper we present the MEMPHIS middleware framework for the integration of CAD geometries and assemblies with derived Virtual Reality (VR) models and its specific meta data and attributes. The goal of this work is to connect real time VR applications, especially for the Design Review, with enterprise software storing and managing CAD models (Product Data Man- agement—PDM). The preparation of VR models requires expert knowledge, is time consuming, and includes selection of required CAD data, tessellation, healing of unwanted gaps, applying materials and textures, and special surface and light effects. During the Design Review process, decisions are made concerning the choice of materials and surface forms. While materials can be switched directly on the VR model, the modification of part geometries must be made on the CAD model. Our system synchronizes modi- fications of the original CAD geometries and of attributes that are relevant for the realistic rendering using the PLM Services standard. Thus, repeated work for the VR preparation can be avoided.

关键词：虚拟现实 CAD PDM 几何变换产品数据管理

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Characteristics associated with falls among the elderly within aged care wards in a tertiary hospital： a retrospective case-control study

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Chinese Medical Journal 2010年第13期123卷 1668-1672页

作者： CHEN Xue-li LIU Yun-hu daniel KY Chan SHEN Qing Huong Van nguyen Department of Rehabilitation Beijing Geriatric Hospital Beijing 100095 China Aged Care Bankstown-Lidcombe Hospital Sydney New South Wales Australia Faculty of Medicine University of New South Wales Sydney Anetralia

Background Falls are the most frequently reported adverse events in inpatient settings. We conducted a retrospective case-control study of inpatient falls within aged care wards in a tertiary hospital to investigate the associated characteristics of elderly patients suffering from falls and fall-related characteristics. Methods Consecutive retrospective cross-sectional design spanned July 2006 to December 2008. Patient group： Information on all aged care inpatients who suffered from 1 or more falls was extracted from Incident Information Management System （IIMS）. Further details about the particular admission（s） were obtained from patients＇ medical records, e.g., patients＇ characteristics and circumstances surrounding the falls. Randomly selected aged care patients who did not suffer from a fall and who were discharged from the hospital in the same period served control group. Characteristics among patients with single fall and recurrent falls, as well as non-railers were compared. Results Of the 438 falls evaluated, 71.9% occurred in patients＇ room and 18.9% in patients＇ bathroom/toilet. The common activities were moving/transferring and taking shower/toileting, respectively, 70.3%, 12.1% while occurring falls; and time of falls had a high peak during 9：00-11：00 a.m. Many were unassisted while falling. The common contributing factors for fall were intrinsic factors. Patients with recurrent falls were more likely to have lower Mini-Mental State Examination （MMSE） score. Logistic regression analysis showed length of stay longer than five weeks, dementia and stroke were independent risk factors for recurrent falls; and living in hostel/nursing home preadmission, needing assistance with mobility, cognitive impairment, stroke, incontinence and arthritis/osteoporosis were independent risk factors for fall. Conclusions In an aged care ward, falls are independently associated with recurrent factors. Cognitive impairment/dementia was a strong risk factor for falls, and main

关键词： falls recurrent falls inpatients the elderly

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High human disturbance decreases individual variability in skink escape behavior

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Current Zoology 2020年第1期66卷 63-70页

作者： Dana M.WILLIAMS Phat-Tan nguyen Kemal CHAN Madeleine KROHN daniel T.BLUMSTEIN Department of Ecology&Evolutionary Biology University of California621 Young Drive SouthLos AngelesCA90095-1606USA

Animals living around people may modify their antipredator behavior as a function of proximity to humans,and this response has profound implications for whether or not a population can coexist with *** asked whether inland blue-tailed skinks Emoia impar modified their individual antipredator behavior as a function of differential exposure to *** conducted multiple consecutive flushes and recorded 2 measures of antipredator response:flight initiation distance(FID),the distance from a threatening stimulus at which an individual flees,and distance fled,the distance an individual fled after a *** used a multiple model comparison approach to quantify variation in individual escape behavior across multiple approaches and to test for differences in between-individual variation among *** found that individuals tolerated closer approach and fled shorter distances at locations with relatively less human disturbance than at locations with medium and high human disturbance,*** addition,skinks living at high human disturbance sites had less variable FIDs than at low human disturbance *** theories may explain these *** against less favorable phenotypes has reduced behavioral variation in urban habitats and behavioral plasticity allows individuals to flexibly adjust their behavioral patterns in response to human *** results highlight the importance of studying variation within populations,at the individual level,which may better elucidate the impact that human disturbance has on the behavioral composition of populations.

关键词： distance fled Emoia impar flight initiation distance habitat sorting habituation urbanization

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Impact of bolus volume on small intestinal intra-luminal impedance in healthy subjects

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World Journal of Gastroenterology 2010年第17期16卷 2151-2157页

作者： Nam Q nguyen Laura K Bryant Carly M Burgstad Robert J Fraser daniel Sifrim Richard H Holloway Department of Gastroenterology & Hepatology Royal Adelaide HospitalAdelaide 5000Australia Investigation and Procedures Unit Repatriation General HospitalDaw Park 5041Australia Department of Medicine Centre for Gastroen-terological ResearchK.U.LeuvenLeuven 3000Belgium

AIM: To assess the impact of bolus volume on the characteristics of small intestinal (SI) impedance ***: Concurrent SI manometry-impedance measurements were performed on 12 healthy volunteers to assess the pattern of proximal jejunal fluid bolus movement over a 14 *** subject was given 34 boluses of normal saline (volume from 1 to 30 mL) via the feeding tube placed immediately above the proximal margin of the studied segment.A bolus-induced impedance event occurred if there was > 12% impedance drop from baseline,over ≥ 3 consecutive segments within 10 s of bolus injection.A minor or major imped-ance event was defined as a duration of impedance drop < 60 s or ≥ 60 s,***: The minimum volume required for a detectable SI impedance event was 2 mL.A direct linear relationship between the SI bolus volume and the occurrence of impedance events was noted until SI bolus volume reached 10 mL,a volume which always produced an impedance flow *** was a moderate correlation between the bolus volume and the duration of impedance drop (r = 0.63,P < 0.0001) and the number of propagated channels (r = 0.50,P < 0.0001).High volume boluses were associated with more major impedance events (≥ 10 mL boluses = 63%,3 mL boluses = 17%,and < 3 mL boluses = 0%,P = 0.02).CONCLUSION: Bolus volume had an impact on the type and length of propagation of SI impedance events and a threshold of 2 mL is required to produce an event.

关键词： Bolus volume Health Impedance Luminal flow Small intestine

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Inhibition of tumor suppressor p73 by nerve growth factor receptor via chaperone-mediated autophagy

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Journal of Molecular Cell Biology 2020年第9期12卷 700-712页

作者： daniel nguyen Kun Yang Lucia Chiao Yun Deng Xiang Zhou Zhen Zhang Shelya X.Zeng Hua Lu Department of Biochemistry and Molecular Biology Tulane Cancer CenterTulane University School of MedicineNew OrleansLA 70112USA Department of Radiation Oncology Shanghai Cancer CenterDepartment of OncologyShanghai Medical SchoolFudan UniversityShanghai 200032China Present address:Verna and Marrs McLean Department of Biochemistry and Molecular Biology Baylor College of MedicineHoustonTX 77030USA Present address:Department of Radiation Oncology Shanghai Cancer CenterFudan UniversityShanghai 200032China Present address:Institute of Biomedical Sciences Shanghai Cancer CenterFudan UniversityShanghai 200032China

The tumor suppressr p73 is a homolog of p53 and is capable of inducing cell cycle arrest and ***,we identify nerve growth factor receptor(NGFR,p75NTR,or CD271)as a novel negative p73 regulator.p73 activates NGFR transcription,which,in turn,promotes p73 degradation in a negative feedback *** directly binds to p73 central DNA-binding domain and suppresses p73 transcriptional activity as well as p73-mediated apoptosis in cancer ***,we uncover a previously unknown mechanism of NGFR-facilitated p73 degradation through the chaperone-mediated autophagy(CMA)***,our studies demonstrate a new oncogenic function for NGFR in inactivating p73 activity by promoting its degradation through the CMA.

关键词： p73 NGFR chaperone-mediated autophagy Lamp2a HSPA8

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