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Evaluating the Knowledge of Conversational Agents
Get PDFSeveral studies have tested chatbots for their abilities to emulate human conversation, but few have evaluated the systems’ general knowledge. In this study, we asked two chatbots (Mitsuku and Tutor) and a digital assistant (Cortana) several questions and compared their answers to 67 humans’ answers. Results showed that while Tutor and Cortana performed poorly, the accuracies of Mitsuku and the humans were not significantly different. As expected, the chatbots and Cortana answered factual questions more accurately than abstract questions
The Evolution and Revolution of Financial Accounting
Get PDFAccounting services are one of the primary reasons why companies are able to serve its customers and perform at high levels. The emergence of Artificial Intelligence has become an additional resource that have revolutionized the accounting world not only in the financial services industry, but the oil and gas industry)as well. Within the oil and gas industry, fair value impairment and financial reporting methods are analyzed to elaborate on how generally accepted accounting principles impact companies\u27 assets which are vital to financial statements. However, accounting services are generally overshadowed with the technical aspects it provides. Demonstrating integrity and ethical standards are just as significant. Manual responsibilities and moral principles will always remain essential to the accounting industry which is discussed in the scandal of Satyam Computer Services
A NOx emission model incorporating temperature for heavy-duty diesel vehicles with urea-SCR systems based on field operating modes
No full textThe selective catalytic reduction (SCR) is the most commonly used technique for decreasing the emissions of nitrogen oxides (NOx) from heavy-duty diesel vehicles (HDDVs). However, the same injection strategy in the SCR system shows significant variations in NOx emissions even at the same operating mode. This kind of heterogeneity poses challenges to the development of emission inventories and to the assessment of emission reductions. Existing studies indicate that these differences are related to the exhaust temperature. In this study, an emission model is established for different source types of HDDVs based on the real-time data of operating modes. Firstly, the initial NOx emission rates (ERs) model is established using the field vehicle emission data. Secondly, a temperature model of the vehicle exhaust based on the vehicle specific power (VSP) and the heat loss coefficient is established by analyzing the influencing factors of the NOx conversion efficiency. Thirdly, the models of NOx emissions and the urea consumption are developed based on the chemical reaction in the SCR system. Finally, the NOx emissions are compared with the real-world emissions and the estimations by the proposed model and the Motor Vehicle Emission Simulator (MOVES). This indicates that the relative error by the proposed method is 12.5% lower than those calculated by MOVES. The characteristics of NOx emissions under different operating modes are analyzed through the proposed model. The results indicate that the NOx conversion rate of heavy-duty diesel trucks (HDDTs) is 39.2% higher than that of urban diesel transit buses (UDTBs)
Policing in Eastern Africa: A Focus on the National Police Service in Kenya by Jospeter Mbuba. Nairobi: LawAfrica, 2017. 205 Pages.
Get PDFDemocratization or Business As Usual? Evaluating Long Term Impact of Africa’s Watershed Elections
Get PDFIn many African countries, “watershed” elections led to political liberalization, and to democratization in a handful of cases. However, years later, many liberalized regimes backslid into authoritarianism. This paper evaluates the long-term impact of these election outcomes. Using a transitology framework, it shows that the reforms implemented at this crucial time dictated the course of liberalization well into the 2010s. Countries where a cohesive opposition managed to wrestle power from the elites have retained their liberalization gains to date. Countries where the opposition was more disorganized and where civil society was weaker remain, at best, hybrid regimes
Exploring the Link: Administrative Exclusion and Second Order Devolution
Get PDFDevolution was embedded in the 1996 welfare reform. Using the National Survey of America’s Families, this article explores the relationship between living in a Second Order Devolution (SOD) state and administrative exclusion from a welfare program. Results from the logistic model indicate that low-income clients and single mothers living in a SOD state had an increased likelihood of administrative exclusion. Administrative exclusion reflects bureaucratic choices and rules violations—implying some of these individuals and families may be leaving welfare without having achieved self-sufficiency. Results suggest that a careful evaluation of the state welfare performance measure and of the devolution of authority under block grants are needed before block granting other safety net programs
Creative Authors And Their Messages: A Collection Of Criticisms
Get PDFOppression is evident m every society: from the beginning of time, First in England and then America, the defilement of people based on race, gender, and birthplace found its way from the streets of the country to the pages of many works of literature. These core issues in the plot of narrative gave rise to literary criticism. The fragile psyche of immigrants is outlined in Charles Brockden Browns Edgar Huntly, the defilement of women is greatly shown through the writing of Edna\u27s search for identity in Kate Chopin\u27s The Awakening, and the lingering effects of slavery are recorded in the pages of Richard Wrights Native Son, among other intermixed issues in various British works. For the books discussed, psychological criticism, New Historicism, ethnic study, Marxism and a few other types of criticism are touched on
Changes in human foetal osteoblasts exposed to the random positioning machine and bone construct tissue engineering
Get PDFHuman cells, when exposed to both real and simulated microgravity (s-µg), form 3D tissue constructs mirroring in vivo architectures (e.g., cartilage, intima constructs, cancer spheroids and others). In this study, we exposed human foetal osteoblast (hFOB 1.19) cells to a Random Positioning Machine (RPM) for 7 days and 14 days, with the purpose of investigating the effects of s-µg on biological processes and to engineer 3D bone constructs. RPM exposure of the hFOB 1.19 cells induces alterations in the cytoskeleton, cell adhesion, extra cellular matrix (ECM) and the 3D multicellular spheroid (MCS) formation. In addition, after 7 days, it influences the morphological appearance of these cells, as it forces adherent cells to detach from the surface and assemble into 3D structures. The RPM-exposed hFOB 1.19 cells exhibited a differential gene expression of the following genes: transforming growth factor beta 1 (TGFB1, bone morphogenic protein 2 (BMP2), SRY-Box 9 (SOX9), actin beta (ACTB), beta tubulin (TUBB), vimentin (VIM), laminin subunit alpha 1 (LAMA1), collagen type 1 alpha 1 (COL1A1), phosphoprotein 1 (SPP1) and fibronectin 1 (FN1). RPM exposure also induced a significantly altered release of the cytokines and bone biomarkers sclerostin (SOST), osteocalcin (OC), osteoprotegerin (OPG), osteopontin (OPN), interleukin 1 beta (IL-1β) and tumour necrosis factor 1 alpha (TNF-1α). After the two-week RPM exposure, the spheroids presented a bone-specific morphology. In conclusion, culturing cells in s-µg under gravitational unloading represents a novel technology for tissue-engineering of bone constructs and it can be used for investigating the mechanisms behind spaceflight-related bone loss as well as bone diseases such as osteonecrosis or bone injuries
Temporal trends and black-white disparity in mortality among hospitalized persons living with HIV in the United States
Get PDFWe sought to determine whether black-white gap in mortality exists among hospitalized HIV-positive patients in the United States (US). We hypothesized that in-hospital mortality (IHM) would be similar between black and white HIV-positive patients due to the nationwide availability of HIV services.Our analysis was restricted to hospitalized HIV-positive patients (15-49 years). We used the National Inpatient Sample (NIS) that covered the period from January 1, 2002 to December 31, 2014. We employed joinpoint regression to construct temporal trends in IHM overall and within subgroups over the study period. We applied multivariable survey logistic regression to generate adjusted odds ratios (OR) and 95% confidence intervals (CI).The total number of HIV-related hospitalizations and IHM decreased over time, with 6914 (3.9%) HIV-related in-hospital deaths in 2002 versus 2070 HIV-related in-hospital deaths (1.9%) in 2014, (relative reduction: 51.2%). HIV-related IHM among blacks declined at a slightly faster rate than in the general population (by 56.8%, from 4.4% to 1.9%). Among whites, the drop was similar to that of the general population (51.2%, from 3.9% to 1.9%). Although IHM rates did not differ between blacks and whites, being black with HIV was independently associated with a 17% elevated odds for IHM (OR = 1.17; 95% CI = 1.11-1.25).In-hospital HIV-related deaths continue to decline among both blacks and whites in the US. Among hospitalized HIV-positive patients black-white disparity still persists, but to a lesser extent than in the general HIV population. Improved access to HIV care is a key to eliminating black-white disparity in HIV-related mortality
A deep spatio-temporal fuzzy neural network for passenger demand prediction
Get PDFIn spite of its importance, passenger demand prediction is a highly challenging problem, because the demand is simultaneously influenced by the complex interactions among many spatial and temporal factors and other external factors such as weather. To address this problem, we propose a Spatio-TEmporal Fuzzy neural Network (STEF-Net) to accurately predict passenger demands incorporating the complex interactions of all known important factors. We design an end-to-end learning framework with different neural networks modeling different factors. Specifically, we propose to capture spatio-temporal feature interactions via a convolutional long short-term memory network and model external factors via a fuzzy neural network that handles data uncertainty significantly better than deterministic methods. To keep the temporal relations when fusing two networks and emphasize discriminative spatio-temporal feature interactions, we employ a novel feature fusion method with a convolution operation and an attention layer. As far as we know, our work is the first to fuse a deep recurrent neural network and a fuzzy neural network to model complex spatial-temporal feature interactions with additional uncertain input features for predictive learning. Experiments on a large-scale real-world dataset show that our model achieves more than 10% improvement over the state-of-the-art approaches