The objective of the study is to examine the impact of financial development and foreign remittances on poverty and income inequality in the context of Pakistan. The study used ARDL-Bounds testing approach for robust inferences. The results show that in the short-run, remittances increases poverty and income inequality, which further translated into its long-run impact. The result confirmed the inverted Ushaped relationship between per capita income and income inequality, while the second order coefficient of per capita income substantially decline poverty incidence in a country. In the long-run, the results disappeared and it’s turned into U-shaped relationship between income inequality and country’s per capita income. Education largely decreases income inequality both in the short and long-run, however, it increases poverty in the long-run. Unemployment rate substantially damaged the pro-poor growth scenario, as high unemployment rate increases both the poverty rates and income inequality, which suffered poor more than non-poor in a country. Financial development has a positive impact on poverty reduction and income inequality in the short-run. The impact of income inequality on poverty incidence is positive both in the short- and long-run, which need pro-poor growth policies and rationale income distribution in a country.

The auditor, an important instrument of corporate governance, ensures the transparency and accountability of the firm to the stakeholders. The objective of this paper is to explore the impact of audit characteristics on firm performance. In this study, external audit quality (BIG4), frequencies of audit committee meetings, and audit committee size are used as the proxies of audit characteristics and firm performance is measured through ROA, profit margin and EPS. A total of 503 firm years are considered as sample size from the listed manufacturing firms of Dhaka Stock Exchange (DSE) during the period of 2013 to 2017 to find out the impact of audit characteristics on firm performance. In this study, multivariate regression analysis is conducted using the pooled OLS method. Moreover, time dummy and lag model of multivariate analysis are also analyzed as robust check. The multivariate regression results find that external audit quality (BIG4) and audit committee size are significantly positively associated with firm performance. This study also finds that there is a significant negative relationship between audit committee meeting and firm performance. This study recommends that the regulatory authority and audit committee should review the frequencies of audit committee meeting to make it more effective to ensure better firm performance.

Purpose – The goal of this study is to analyze the differences in education performances between students of the government's financial support program and those who do not receive support at a local university in Korea. Research design, data, and methodology - The questionnaire used was NASEL. NASEL is considered a highly suitable survey tool for professors, courses, and performances in Korean universities. The 290 students who participated and 44 students do not participate in the financial support program were surveyed for 10 days. The characteristics of students were investigated by frequency analysis and technical statistics. The analysis of student collective characteristics used independent t and f-tests,and one-way ANOVA with IBM SPSS Statistics 22.0 for statistical purposes. Results – The p-value of the group receiving financial support and the group without financial support in active-collaborative learning is 0.167. The p-value of the economically supported group and the non-supported group of the faculty-student interaction is 0.281. The confidence coefficient of the active-collaborative learning questionnaire is 0.861. The reliability coefficient of the questionnaire for the faculty-student interaction questionnaire is 0.871. Conclusions – There are no clear differences in active-collaborative learning and faculty-student interaction between participating and non-participating students in the economic program.

Two main sources of data, meteorological data and land surface characteristics, are essential to effectively run a distributed rainfall-runoff model. The specification and averaging of the land surface characteristics in a suitable way is crucial to obtaining accurate runoff output. Recent advances in remote sensing techniques are often being used to derive better representations of these land surface characteristics. Due to the mismatch in scale between digital land cover maps and numerical grid sizes, issues related to upscaling or downscaling occur regularly. A specific method is typically selected to average and represent the land surface characteristics. This paper examines the amount of flooding by applying the FLO-2D routing model, where vegetation heterogeneity is manipulated using the Manning’s roughness coefficient. Three different upscaling methods, arithmetic, dominant, and aggregation, were tested. To investigate further, the rainfall-runoff model with FLO-2D was facilitated in Yongdam catchment and heavy rainfall events during wet season were selected. The results show aggregation method provides better results, in terms of the amount of peak flow and the relative time taken to achieve it. These rwsults suggest that the aggregation method, which is a reasonably realistic description of area-averaged vegetation nature and characteristics, is more likely to occur in reality.

A Numerical modeling approach is usually applied to reproduce the physical phenomena of a fill dam-break. The accuracy of the dam-break model depends on the physical structure that defines input variables such as the storage volume, breach formation and progress, and the parameters of the model, which are subjective as they are prescribed by users. In this study, a sensitivity analysis was performed for the nonlinear breach progression curve that was already developed, which includes four parameters. The study focuses on the two of the parameters which control the breach forming time and peak discharge. The model is coupled with a two-dimensional flood simulation model (FLO-2D) to examine flood coverage and depth. It is generally observed that the parameter β controls only the breach forming time, the parameter γ is particularly sensitive to the peak flow.

Education is the manifestation of culture, and is an important component part of culture. International education and international students are vital for the country’s economy. The trump administration, under the slogan "America first," overhauled the U.S. immigration policy that has been in place for nearly half a century, with the core idea of prioritizing immigrants who can succeed in the United States and stand on their own feet economically, ensuring that immigrants identify with American values. Stop immigration in areas where terrorism is rampant and background checks are difficult to carry out. Deport illegal immigrants and reduce the number of immigrants; Encourage "quality immigration", eliminate "link immigration", abolish the green card lottery system, adopt points system and so on. The new immigration policy triggered heated debate, the American higher education and strict immigration policy or a willingness to stay in the United States, will affect the students work visa or reform will lead to high quality international talent loss, cumbersome application program, or will affect the quality of education for international students, the policy of science and engineering major is preferred, or will affect balance of American colleges and universities. The implementation of the trump administration's new immigration policy will not only affect the development of education, but also change the international competition pattern of education.

본 연구에서는 기후변화에 따른 메콩강 유출변화 분석을 목적으로 하고 있다. HadGEM3-RA로 부터 생산된 동아시아 지역 RCP 4.5 및 8.5 시나 리오의 일 자료를 기반으로 편의보정을 통해 미래 기후변화 시나리오를 구축한 후, SWAT 모형을 이용하여 메콩강 주요지점인 Kratie(유역면적: 646,000 km2, 메콩강의 연평균 유량의 88%)에서의 유출변화 모의하고 유황분석을 수행하였다. 기후변화 분석 결과 Kratie 유역의 미래 강수량은 기준 년 연평균 강수량 대비 미래 년 기간의 연평균 강수량은 두 시나리오 모두 증가하는 것으로 분석되었으며 월별 강수량 변화 분석을 통해 6 월∼11월에 강수량의 증가가 비교적 크게 나타나며 특히 RCP 8.5 시나리오에서 강수량의 변동 폭 및 증가량이 크게 나타남을 확인하였다. 시나리 오별 월평균 최대 및 최소기온의 변화는 두 시나리오 모두 미래 기온의 상승을 전망하고 있으며 특히 RCP 8.5 시나리오의 온도증가 폭이 크게 나타 나는 것을 확인 하였다. 또한 하천유황변화 분석결과 유역의 유량변동성이 더욱 커질 것으로 분석되었으며 저수계수 값이 52∼57% 감소하고 갈 수계수 값이 67∼74% 감소하는 것으로 나타나 하천의 갈수상황이 지속되어 미래에 가뭄이 보다 심화될 것으로 분석되었다.

본 연구는 PVA(polyvinyl alcohol) 섬유와 VAE(vinyl acetate ethylene) 분말 폴리머를 사용한 시멘트복합체의 압축·휨강도 와 온도변화에 따른 충격파괴거동을 연구하였다. 충격시험은 -35℃, 0℃ 및 35℃의 선정된 온도조건에서 실시하였다. 본 실험에서는 시멘트 복합체와 일반 모르타르에 대한 충격파괴 에너지와 변위, 시간을 얻기 위해 낙하 충격시험기(Ceast 9350)를 사용하여 충격시험을 수행하였다. 강도 시험결과, PVA 섬유와 VAE 분말 폴리머의 휨강도는 모두 증가하였다. PVA 섬유보강 시멘트복합체의 경우 재령 28일에서의 압축강도는 약간 감소하였으나, 휨강도는 일반 모르타르 강도보다 24.4% 증가하였다. 낙하 충격시험 결과, PVA 섬유보강 시멘트복합체 시편은 섬유의 가교역할로 인한 균열발생의 억제와 에너지 분산에 의한 미세균열이 발생하였으며, 충격에 의한 배면파괴와 관통에 대하여 억제되었다. 반면 VAE 분말 폴리머 시멘트복합체와 일반 모르타르의 시편은 대부분 큰 균열이나 관통파괴 되었다. 충격하중을 받는 시멘트복합체와 일반 모르타르의 시편은 대부분 국부적인 취성파괴거동을 보이며, PVA 섬유보강에 의한 휨성능 증진으로 인해 충격에 대한 저항성능이 크게 향상되었다.

고속도로 통행량 및 주행속도 증가로 인해 중앙분리대 충돌사고가 빈번히 발생하고 있다. 특히 차량의 대형화와 통행 중차량의 증가로 인해 중앙분리대 충돌사고 시 중앙분리대의 방호 성능을 초과하는 사고 역시 증가하는 추세이다. 따라서 고속도로의 안전성을 높이기 위해 고성능 중앙분리대의 개발이 필요하다. 본 논문은 고성능 중앙분리대 설치 필요에 따라 성능개선수준(하중모델) 및 설치위치 제안을 목적으로 하고 있다. 이를 위해 고속도로 중앙분리대 충돌 사고 자료 분석을 통해 고성능 중앙분리대 개발을 위한 성능 개선 수준 SB6등급(충격도 = 420 kJ, 하중: 25 ton, 충돌속도: 80 km/h, 충돌각도: 15°)으로 제안하고 운전자의 운전행태 분석을 통해 개량 및 신설 고성능 중앙분리대 설치 위치를 제안하였다.

This study aimed to assess the impact of livestock excreta discharged from an Intensive Livestock Farming Area (ILFA) on river water quality during a rainfall event. The Bangcho River, which is one of the 7 tributaries in the Cheongmi River watershed, was the study site. The Cheongmi River watershed is the second largest area for livestock excreta discharge in Korea. Our results clearly showed that, during the rainfall event, the water quality of the Bangcho River was severely deteriorated due to the COD, NH4-N, T-N, PO4-P, T-P, and heavy metals (Cu, Zn, and Mn) in the run-off from nearby farmlands, where the soil comprised composted manure and unmanaged livestock excreta. In addition, stable isotope analysis revealed that most of nitrogen (NH4-N and NO3-N) in the run-off was from the ammonium and nitrate in the livestock excreta. The values of δ15NNH4 and δ15NNO3 for the Bangcho River water sample, which was obtained from the downstream of mixing zone for run-off water, were lower than those for the run-off water. This indicates that there were other nitrogen sources upstream river in the river. It was assumed from δ15NNH4 and δ15NNO3 stable isotope analyses that these other nitrogen sources were naturally occurring soil nitrogen, nitrogen from chemical fertilizers, sewage, and livestock excreta. Therefore, the use of physicochemical characteristics and nitrogen stable isotopes in the water quality impact assessment enabled more effective analysis of nitrogen pollution from an ILFA during rainfall events.

Prior literature has posited that the sport industry has been effective method to drive the economic growth. Given the rationale, this study sets China as a research object with a quarterly data from the first quarter of 2003 to the fourth quarter of 2017 to explore how the sport industry affects economic growth. This study employed Johansen cointegration test and dynamic ordinary least squares as methods for an empirical analysis. The input of sport industry, the labor input, the capital input, and the economic growth are used as research variables. The results show that there is a long-run relationship among them. Johansen cointegration test’s estimation indicated that 1% increase in the input of sport industry will lead to 0.064% increase in economic growth. Dynamic ordinary least squares’ estimation showed that whenever in the one lead, in the one lag and in the present period, the input of sport industry always poses a positive effect on economic growth. Labor input also has a positive effect on economic growth. The capital input has a negative effect on economic growth. Finally, even though the input of sport industry has a positive effect on economic growth, its impact on economic growth is relative weak.

기존 기후변화 영향평가에서 발생하는 불확실성에 대한 연구들은 전체과정에서 총 불확실성과 그 전파에 대한 것보다 각 단계별 불확실성에 초점을 맞추어 연구가 진행되었다. 따라서 본 연구에서는 first-order Taylor series expansion에 기반하여 전망의 분산을 이용하는 Uncertainty Delta Method (UDM)를 제안하였으며, 이 방법은 각 단계별 불확실성 정량화와 증감정도, 단계별 불확실성 비율, 총 불확실성의 전파 과정 제시가 가능 하다. 본 연구에서는 기후변화 영향평가 과정의 단계별 불확실성 정량화와 전파과정 분석을 위해 미래 2030년부터 2059년까지를 대상으로 2개 배출 시나리오, 3개 GCM, 2개 상세화기법, 2개 수문모형을 사용하였다. 결과를 분석하면, UDM을 이용한 총 불확실성은 5.45(배출시나리오: 4.45, 상세화기법: 0.45, 상세화기법: 0.27, 수문모형: 0.28)이며, 배출 시나리오의 불확실성(4.45)이 가장 크게 나타났다. 불확실성은 각 단계를 거칠수록 증가하는 것으로 나타났다. 이러한 결과는 어떠한 배출시나리오를 선정하느냐에 따라 미래 수자원전망이 매우 달라질 수 있음을 의미한다. 다음으로 Hawkins and Sutton (2009)가 제안한 Fractional Uncertainty Method (FUM)을 이용한 기후변화 영향평가 불확실성 분석에서 가장 불확 실성이 큰 요인은 배출 시나리오(FUM 불확실성: 0.52)이며, 이 결과는 UDM 결과와 동일하게 나타났다. 따라서 이 연구에서 제안한 UDM은 기후 변화 영향평가에서의 불확실성 이해와 적합한 분석 및 미래 기후변화 대비 보다 나은 수자원 전망이 가능하도록 기여할 것으로 판단된다.

Numerical experiments were carried out to investigate the effect of data assimilation of observational data on weather and PM (particulate matter) prediction. Observational data applied to numerical experiment are aircraft observation, satellite observation, upper level observation, and AWS (automatic weather system) data. In the case of grid nudging, the prediction performance of the meteorological field is largely improved compared with the case without data assimilations because the overall pressure distribution can be changed. So grid nudging effect can be significant when synoptic weather pattern strongly affects Korean Peninsula. Predictability of meteorological factors can be expected to improve through a number of observational data assimilation, but data assimilation by single data often occurred to be less predictive than without data assimilation. Variation of air pressure due to observation nudging with high prediction efficiency can improve prediction accuracy of whole model domain. However, in areas with complex terrain such as the eastern part of the Korean peninsula, the improvement due to grid nudging were only limited. In such cases, it would be more effective to aggregate assimilated data.

A Visual landscape planning and management system has been introduced and implemented by each ministry so as to solve the problems of visual landscape destruction due to recognition on the value of natural landscape of beautiful territory and various development projects. At present, this system emphasizes the importance of the visual and perceptual aspect of the landscape however, there is a lack of techniques required for comprehensively predicting, evaluating, and managing it. Furthermore, sustainable landscape management after the completion of development projects has been inadequately carried out, as the focus has been only on consultation in the planning process of the development project in institutional performance. To this end, we presented objective and standardized criteria to predict and judge the effects of development projects on landscapes before project implementation. During the implementation of the development project, the influence of the visual landscape becomes accumulated in the construction progress stage. There is a need to identify the main viewpoints and to examine the continuous changes in the landscape-influencing factors, owing to the remarkable influences on the landscape, such as the change in the topography and the change caused by the artificial structure. During the stage of managing the influence on the visual landscape after the completion of the project, the influence on landscape should be monitored by measuring the change in the continuous landscape-influencing factors and determining the extent to which the actual reduction plan has been implemented. These processes should be performed continuously to maintain the quality of the visual landscape. The change in the landscape caused by the development project is shown to cause relatively greater visual damage than other factors composing the landscape owing to the influence of the artificial factors including the structure or the building. This shows that not only detailed examination of the visual impact before the development project but also continuous management is required during and after the development project. For this purpose, we derived eight landscape-influencing factors including form/shape, line, color, texture, scale/volume, height, skyline, and landscape control point. The proposed considering to be of high utilization in that it has a clear target of the landscape influencing factors.

교량 내하력 추정을 위해 제안된 모델에서는 응답계수를 충격계수 응답스펙트럼을 활용하여 산정하고 있다. 이때 충격계수 응답스펙트럼은 오일러-베르누이 보 모델을 바탕으로 차량이동하중이 교량의 폭 방향으로 중앙부에 재하 된 조건으로 생성된 결과이다. 따라서 중앙부 차량재하가 아닌 편측 이동하중재하 시 충격계수와 응답계수의 변화를 분석해 볼 필요가 있다. 이를 위해 본 연구에서는 폭이 10m인 2차선 단순교를 대상으로 이동하중해석을 실시하여 최대 충격계수와 응답계수 변화를 분석하였다. 수치해석 결과, 중앙부 재하조건 대비 편측 재하 조건 적용 시 최대 정적 및 동적 변위 모두 증가하지만 동적변위 보다 정적변위의 증가량이 더 크기 때문에 충격계수는 오히려 감소하게 된다. 하지만 이러한 차이는 0.5%p 미만으로서 그 영향이 크지 않다. 그리고 응답계수의 경우, 편측 재하조건으로 인해 정적응답계수보다 동적응답계수에서 차이가 더 크게 나타나지만 편측 재하에 따른 오차율의 차이는 0.18%p 정도로 매우 작았다. 즉, 편측 이동하중재하가 응답계수에 미치는 영향은 거의 없으며, 응답계수 산정에 있어서 중앙부 이동하중재하 조건으로 생성된 충격계수 응답스펙트럼을 활용하여도 충분한 예측이 가능하다고 판단된다.

The aim of this study was to determine the appropriate stockpiling methods for revegetation by comparing the germination status of seed banks before and after preservation for 2 years. Soil temperature in stockpiled topsoil was higher in open treatment and at 1.5 m, whereas soil water content was maintained at lower levels (14.06-19.08%), than those in the control group. The seed banks in stockpiled topsoil had 48 species and 1,559 individuals, among which perennials showed the highest number in terms of life forms, whereas Compositae and Gramineae were dominant in terms of families. Based on seed bank type, persistent seed banks had the highest number of species, while transient seed banks had the highest number of individuals. By stockpiling period, the number of species in the seed bank started to increase after 24 months, while the number of individuals began increasing after 12 months and exceeded that of the control group after 24 months. Regarding the treatment of stockpiling methods, the number of species and individuals in open treatment were closer to those of the control group. When analyzed by height, the number of species and individuals were higher at 0 m, but still lower than those of the control group. A multivariate analysis of variance (MANOVA ) showed that the optimal combination was obtained in open treatment and the number of individuals increased with the lengthening of the stockpiling period.

본 연구의 목적은 금강유역(9,645.5 km2)을 대상으로 극한 기후변화 사상에 따른 수문 및 유황의 변동을 평가하는 것이다. 본 연구에서는 객관적인 극한 기후변화 사상을 평가하기 위해 강우관련 극한지수(STARDEX)를 적용하고, GCM 10개의 RCP 8.5 기후변화 시나리오에 대해 4개의 평 가기간별(Historical: 1975~2005, 2020s: 2011~2040, 2050s: 2041~2070, 2080s: 2071~2100)로 분석하였다. 분석 결과 5개의 습윤 (CESM1-BGC, HadGEM2-ES), 중간(MPI-ESM-MR) 건조(INM-CM4, FGOALS-s2) 극한 기후변화 사상 시나리오를 선정하여 SWAT 모형에 적용하였다. 2080s 기간에서 중간시나리오 대비 2080s의 증발산은 -3.2~+3.1 mm로 변화하였고, 2080s의 총 유출량은 +5.5~+128.4 m3/s 변화하였다. 건조한 시나리오의 경우 2020s 중간시나리오대비 큰 변화를 보였다. 건조한 시나리오에서의 2020s의 증발산량은 -16.8~-13.3 mm 의 변화를 보였고, 총 유출량은 -264.0~132.3 m3/s의 변화를 보였다. 유황 변동의 경우, 2080s 기간의 습윤한 시나리오에서 CFR은 +4.2~+10.5, 2020s 기간의 건조한 시나리오에서는 +1.7~2.6으로 변화 하였다. 극한 기후변화 시나리오를 적용한 금강유역의 수문인자의 변화에 따라 유황분 석을 실시한 결과, INM-CM4는 극한 건조상태를 나타내기에 적절한 시나리오로 나타났고 FGOALS-s2는 유황변동이 큰 가뭄 상태 분석에 적절한 시나리오로 나타났다. HadGEM2-ES는 유황변동이 작게 나타났기 때문에 최대유량 분석 시 활용 가능한 시나리오로 평가되었고, CESM1-BGC 의 경우 유황변동이 큰 것으로 나타나 극한 홍수 분석 시 적용할 수 있는 시나리오로 평가되었다.

본 연구에서는 SWAT 모형과 random forest를 이용하여 미래 기후변화에 따른 한강유역(34,148 km2)의 수생태계 건강성을 평가하였다. 국립 환경과학원에서 8년간(2008~2015년) 봄철(4~6월)에 모니터링한 부착돌말류 지수(TDI), 저서형 대형무척추동물지수(BMI), 어류평가지수(FAI)는 0~100점, A~E등급으로 평가되며, 이를 본 연구에서 사용하였다. 수생태 건강성에 영향을 미치는 변수로는 수질(T-N, NH4, NO3, T-P, PO4)과 수온을 선정하였으며, 수질 오염도가 낮은 경우에는 수생태계 건강성 점수가 광범위하게 분포되지만 수질 오염도가 높은 경우 수생태계 건강성 점수가 낮아지는 역상관관계를 확인하였다. 기계학습의 분류 분석 기법 중 하나인 random forest 모델을 이용한 세 개의 수생태 건강성 지수 등급 분류 결과 정밀도, 재현율, f1-score 모두 0.81 이상의 예측 정확도를 나타내었다. 기상청의 HadGEM3-RA RCP 4.5와 8.5 시나리오를 적용한 미래 SWAT 수문, 수질 결과 기저유출의 증가로 인해 질소 계열 수질 농도는 기준년도 대비 최대 43.2% 증가하였고, 지표유출 감소로 인해 인 계열 수질 오염도는 최대 18.9% 감소하는 것으로 분석되었다. 미래 FAI, BMI의 등급은 개선되는 경향을 보이지만 TDI는 등급이 악화되는 것으로 나타 났다. 이를 통해 TDI는 질소 계열 수질에 민감하고 FAI, BMI는 인 계열 수질에 더 민감하다고 판단하였다.

Purpose – Unstable vegetable prices have been one of the major concerns in Korean agricultural and food marketing system. The Korean government has implemented a number of policy instruments, including government purchasing programs in order to alleviate fluctuations in vegetable prices. The economic impact of policy instruments has been assessed based on the average monthly price change rate before and after the implementation of the policy. However, this approach failed to provide a net impact of policy measures on price stabilization in the vegetable markets, as policy impacts could not be successfully distinguished from other effects on price changes in the vegetable market. The purpose of this study is to evaluate the net impact of the government purchasing program on the price volatility of dried red pepper which is considered one of the major vegetables in Korea. Research design, data, and methodology – This study develops a monthly dynamic partial equilibrium model of Korean dried red pepper market. Behavioral equations in the model were estimated by OLS and synthetic method based on the annual and monthly time series data from 1993 to 2015. The model is first simulated to yield actual dried red pepper market conditions in 2015 as a baseline and then compared it to the scenario assuming that there were no government purchases of dried red pepper in 2015. Results - According to the ex-post scenario analysis using the developed model, without the government procurements in 2015, the average monthly price change rate and the value of coefficient of variation of dried red pepper in 2015 would be respectably 7.9 percent and 0.10. It is relatively higher than the actual average monthly price change rate and the value of coefficient of variation of dried red pepper in 2015 which were respectively 1.7 percent and 0.06. Conclusions - The ex-post simulation results in this study shows that if there were no government purchases of dried red pepper in 2015, the dried red pepper market would have had much higher volatile price movements. The results of this study would provide useful information for future price stabilization policy of vegetable markets in Korea.

Purpose - The artificial intelligence industry plays an increasingly significant role in stimulating the development of United States of America’s economy. On account of this background, this paper attempts to explore the impact of artificial intelligence industry on United States of America’s macroeconomy. Research design, data, and methodology - This paper mainly focuses on the impact of artificial intelligence industry on GDP, employment, real income, import, export and foreign direct investment. Furthermore, the Phillips-Perron test and Canonical cointegrating regression will be employed to examine the impact of artificial intelligence industry on United States of America’s macroeconomy with a sample form 2010-Q1 to 2017-Q4. Results - Via the empirical analysis, the results reveal that the artificial intelligence industry has a positive effect on United States of America’s GDP, employment, real income, export and foreign direct investment. Conversely, the artificial intelligence industry has a negative effect on United States of America’s import. Conclusions - In summary, the impact of artificial intelligence industry on United States of America’s macroeconomy is positive and significant in statistics. Therefore, the government of United States of America should put more input into artificial intelligence industry.