Predicting pavement condition index based on the utilization of machine learning techniques:A case study

Pavement management systems(PMS)are used by transportation government agencies to promote sustainable development and to keep road pavement conditions above the minimum performance levels at a reasonable cost.To accomplish this objective,the pavement condition is monitored to predict deterioration and determine the need for maintenance or rehabilitation at the appropriate time.The pavement condition index(PCI)is a commonly usedmetric to evaluate the pavement's performance.This research aims to create and evaluate prediction models for PCI values using multiple linear regression(MLR),artificial neural networks(ANN),and fuzzy logic inference(FIS)models for flexible pavement sections.The authors collected field data spans for 2018 and 2021.Eight pavement distress factors were considered inputs for predicting PCI values,such as rutting,fatigue cracking,block cracking,longitudinal cracking,transverse cracking,patching,potholes,and delamination.This study evaluates the performance of the three techniques based on the coefficient of determination,root mean squared error(RMSE),and mean absolute error(MAE).The results show that the R2 values of the ANN models increased by 51.32%,2.02%,36.55%,and 3.02%compared toMLR and FIS(2018 and 2021).The error in the PCI values predicted by the ANNmodel was significantly lower than the errors in the prediction by the FIS and MLR models.

Monitoring vegetation drought in the nine major river basins of China based on a new developed Vegetation Drought Condition Index

The effect of global climate change on vegetation growth is variable.Timely and effective monitoring of vegetation drought is crucial for understanding its dynamics and mitigation,and even regional protection of ecological environments.In this study,we constructed a new drought index(i.e.,Vegetation Drought Condition Index(VDCI))based on precipitation,potential evapotranspiration,soil moisture and Normalized Difference Vegetation Index(NDVI)data,to monitor vegetation drought in the nine major river basins(including the Songhua River and Liaohe River Basin,Haihe River Basin,Yellow River Basin,Huaihe River Basin,Yangtze River Basin,Southeast River Basin,Pearl River Basin,Southwest River Basin and Continental River Basin)in China at 1-month–12-month(T1–T12)time scales.We used the Pearson's correlation coefficients to assess the relationships between the drought indices(the developed VDCI and traditional drought indices including the Standardized Precipitation Evapotranspiration Index(SPEI),Standardized Soil Moisture Index(SSMI)and Self-calibrating Palmer Drought Severity Index(scPDSI))and the NDVI at T1–T12 time scales,and to estimate and compare the lag times of vegetation response to drought among different drought indices.The results showed that precipitation and potential evapotranspiration have positive and major influences on vegetation in the nine major river basins at T1–T6 time scales.Soil moisture shows a lower degree of negative influence on vegetation in different river basins at multiple time scales.Potential evapotranspiration shows a higher degree of positive influence on vegetation,and it acts as the primary influencing factor with higher area proportion at multiple time scales in different river basins.The VDCI has a stronger relationship with the NDVI in the Songhua River and Liaohe River Basin,Haihe River Basin,Yellow River Basin,Huaihe River Basin and Yangtze River Basin at T1–T4 time scales.In general,the VDCI is more sensitive(with shorter lag time of vegetation response to drought)than the traditional drought indices(SPEI,scPDSI and SSMI)in monitoring vegetation drought,and thus it could be applied to monitor short-term vegetation drought.The VDCI developed in the study can reveal the law of unclear mechanisms between vegetation and climate,and can be applied in other fields of vegetation drought monitoring with complex mechanisms.

Population dynamics and condition index of natural stock of blood cockle,Tegillarca granosa(Mollusca,Bivalvia,Arcidae)in the Marudu Bay,Malaysia

The population parameters of blood cockles,Tegillarca granosa in the intertidal zone of Marudu Bay,Sabah,Malaysia were investigated based on monthly length-weight frequency data(July 2017 to June 2018).A total of 279 cockle individuals with shell length and weight ranging from 27.7 mm to 82.2 mm and 13.11 g to 192.7 g were subjected to analysis.T.granosa in Marudu Bay showed a consistent moderately high condition index 4.98±0.86 throughout the year.The exponent b of the length-weight relationship was 2.6 demonstrating negative allometric growth.The estimated asymptotic length(L_(∞)),growth coefficient(K)and growth performance(Ф)of the T.granosa population in Marudu Bay were estimated at 86.68 mm,0.98 a^(-1) and 3.87,respectively.The observed maximum shell length was 82.55 mm and the predicted maximum shell length was 84.44 mm with estimated maximum life span(t_(max))of 3.06 years.The estimated mean lengths at the end of 2,4,6,8,10 and 12 months of age were 21.31 mm,31.16 mm,39.53 mm,46.63 mm,52.67 mm and 57.79 mm.Total,natural,and fishing mortalities were estimated at 2.39 a^(-1),1.32 a^(-1) and 1.07 a^(-1).The exploitation level(E)was 0.45.Results of the current study also demonstrated that T.granosa in the Marudu Bay has two major recruitment peaks;one in March and another in October.The exploitation level revealed that natural stock of T.granosa in the Marudu Bay was approaching the maximum exploitation level.If such trend continues or demand for T.granosa is increasing,coupled with no effective fisheries management in place,possibility of the T.granosa population in the Marudu Bay to collapse is likely to elevate.

Seasonal variation in the biochemical composition,condition index,and meat yield of the non-indigenous pearl oyster Pinctada imbricata radiata(Leach,1814)from the West of the Aegean Sea,Greece

The average values of the seasonal flesh biochemical composition(%)of the pearl oyster Pinctada imbricata radiata originated form 2 sampling sites,the gulfs of Evoikos(E)and Saronikos(S)in the Western Aegean Sea,showed that is rich in proteins(64.00±1.86-(E),64.67±2.95-(S))with low fat content(10.96±1.04-(E),11.86±1.13-(S))and carbohydrates(13.29±2.48-(E),9.94±4.32(S)).The condition index ranged from 26.16%±5.04 in the autumn in(E),to 44.73%±7.50 in the summer in(S).The meat yield varied from 20.49%±3.20%in the summer in(E)to 30.73%±3.47%in the summer in(S).Both results demonstrate the high nutritional profile of the pearl oyster,supporting its suitability as a potential new Mediterranean seafood source for human consumption.

Do U.S.economic conditions at the state level predict the realized volatility of oil‑price returns?A quantile machine‑learning approach

Because the U.S.is a major player in the international oil market,it is interesting to study whether aggregate and state-level economic conditions can predict the subse-quent realized volatility of oil price returns.To address this research question,we frame our analysis in terms of variants of the popular heterogeneous autoregressive realized volatility(HAR-RV)model.To estimate the models,we use quantile-regression and quantile machine learning(Lasso)estimators.Our estimation results highlights the dif-ferential effects of economic conditions on the quantiles of the conditional distribution of realized volatility.Using weekly data for the period April 1987 to December 2021,we document evidence of predictability at a biweekly and monthly horizon.

数据中心用单元式空气调节机能效评价指标研究

针对现有的机房空调性能评价指标AEER对于新开发机房空调类型考虑的不足,提出一种新的性能评价指标AEER^(*),并给出其推导过程。针对性地选取已完成测试的机房空调的EER数据,分别计算AEER值和AEER^(*)值,得出以下结论:对于压缩机单循环的机房空调,其AEER值和AEER^(*)值较为接近;现行的AEER指标,对于制冷剂泵-压缩机双循环机房空调或其他类型利用自然冷源的机房空调,弱化EER_(a)和EER_(b)这2项评价指标;使用AEER^(*)作为机房空调性能评价指标,更为科学并且贴合实际。

Distributed Air-Conditioning Energy Management System within the Smart Grid Context

-Air-conditioning （AC） systems are the major energy consumption units in residential and commercial buildings. In the context of smart grid, optimizing AC operations leads to substantial saving in energy consumption, reducing the consumer＇s bill and contributing to the environment by minimizing carbon emissions from generating stations. This paper presents a distributed AC energy management system for buildings by using networked master-slaves controller architecture. The proposed system was designed, simulated, and experimentally tested by using real AC units in a students＇ residence hall. Based on the students＇ class schedules, several operational scenarios were implemented and tested. The proposed system implementation leads to a 40% to 60% saving of the consumed energy by the tested units. The same energy management scheme can be applied and implemented in other commercial and residential buildings.

Sliding Mode Control of Coupled Tank Systems Using Conditional Integrators

For the problem of set point regulation of the liquid level in coupled tank systems, we present a continuous sliding mode control(SMC) with a "conditional integrator", which only provides integral action inside the boundary layer. For a special choice of the controller parameters, our design can be viewed as a PID controller with anti-windup and achieves robust regulation.The proposed controller recovers the transient response performance without control chattering. Both full-state feedback as well as output-feedback designs are presented in this work. Our output-feedback design uses a high-gain observer(HGO) which recovers the performance of a state-feedback design where plant parameters are assumed to be known. We consider both interacting as well as non-interacting tanks and analytical results for stability and transient performance are presented in both the cases. The proposed controller continuous SMC with conditional integrators(CSMCCI) provides superior results in terms of the performance measures as well as performance indices than ideal SMC, continuous SMC(CSMC) and continuous SMC with conventional integrator(CSMCI). Experimental results demonstrate good tracking performance in spite of unmodeled dynamics and disturbances.

调理剂对多环芳烃污染黏性土壤热脱附的影响

黏性土壤具有颗粒细小和通透性弱等特点,会影响受多环芳烃(PAHs)污染的黏性土壤的热脱附效率,因此本研究选择6种调理剂(CaO、MgO、Al2O3、Fe2O3、K2CO3和沸石)来改良黏性土壤,考察调理剂对PAHs污染黏性土壤热脱附的影响,分析了调理剂对黏性土壤塑性指数、pH、阳离子交换量、粒径的影响,探讨了调理剂对PAHs污染黏性土壤热脱附的影响机制.结果表明:(1)添加6种调理剂均提高了PAHs污染黏性土壤的热脱附效率,可有效去除总PAHs,并显著降低超标物质苯并[a]蒽(Baa)和苯并[a]芘(Bap)的残留浓度,其中在添加10%CaO条件下,总PAHs去除率最高,达97.48%.(2)分别添加6%的CaO、MgO、K2CO3调理剂后,黏性土壤塑性指数由18.55%分别降至14.38%、13.58%和15.25%,但添加Al2O3、Fe2O3和沸石均增加了黏性土壤的塑性指数.(3)综合分析,调理剂改良黏性土壤主要通过阳离子交换作用和絮凝作用.研究显示,调理剂改变了黏性土壤的细粒含量和阳离子交换量,进而影响其塑性指数,提升了PAHs热脱附去除效率,CaO、MgO、K2CO3可作为调理剂的合适选择.

Condition indices for rigid pavements: A comparative analysis of state DOTs using Michigan PMS data

Pavement infrastructure is vital in providing services and links between various sectors of society. Therefore, thepreservation and maintenance of these roads are critical to attaining a pavement network in good conditionthroughout its service life. Various performance indicators like the international roughness index (IRI), pavementcondition index (PCI), and present serviceability rating (PSR) have been used by the state department of transportation (DOT) and highway agencies for evaluating pavement surface conditions and planning future maintenance strategies. Limited data availability, multiple distresses depending on region, lack of correlation of thesecondition indices to maintenance strategies, and data collection limitations pose a challenge for applying theseindices to local conditions. This paper compares condition indices of different states for rigid pavements. Further,using a specific condition index for local conditions is also highlighted. For this purpose, five states and theircorresponding condition indices were evaluated and compared to the Michigan DOT distress index (DI). Thesestates include Virginia, Minnesota, North Dakota, Louisiana, and Oregon. The corresponding distresses of eachcondition index were converted to make them compatible with the MDOT DI. This study used the MDOT'spavement management system (PMS) database to evaluate each condition index for 433 rigid pavement sections.Each distress index was plotted against MDOT DI and compared using a paired t-test. Results show that thecondition indices of Virginia and Minnesota are comparable to DI in terms of the Spearman correlation value. Thet-test results show that except for Virgina, condition indices from other states statistically differ from DI.Therefore, one can't use those directly for local conditions in Michigan. This paper presents the evaluation anddata requirements for each condition index and its impact on selecting a maintenance treatment.

中缅树形态性状的遗传制约性初步研究

树是一种在医学和生物学上用途广泛的实验动物遗传资源。主要以上海市肿瘤研究所购自云南昆明地区的35只中缅树及其实验室条件下繁殖的G1代为试验素材,对涉及形态性状遗传制约性的一些指标进行分析,应用Rife Buranamanas定律分析中缅树涉及毛色等诸多具有遗传制约性的外貌特征的显隐性关系,得出中缅树典型的外貌特征为野生型毛色有季节性红斑、白腹、没有白眼圈、掌底肤色为肉色、耳朵不竖、圆形的尾尖、两侧乳房每对之间的连线分别与体轴线垂直。

不同调理剂对酸性土壤降酸效果及大麦幼苗生长的影响

采用土壤培养及盆栽试验研究5种调理剂(生石灰、油菜秸秆、有机肥、钾硅肥、土壤改良剂,用量均为1.8 g/kg)对酸性土壤(pH值3.9)酸度指标和大麦幼苗生长的影响。土壤培养试验结果表明,施用生石灰、有机肥和钾硅肥均能明显提高土壤pH值,降低土壤交换性酸总量、交换性H+和交换性铝含量。其中以生石灰降酸效果最好,到培养第90 d,相比于对照处理提高了0.66个单位,土壤交换性铝含量减少了2.01 cmol/kg;其次是有机肥和钾硅肥处理,pH值较对照处理分别提高了0.14和0.15,土壤交换性铝含量分别降低了0.23和0.19cmol/kg;油菜秸秆和土壤改良剂处理从酸度指标来看,与对照并没有显著差异。大麦幼苗盆栽试验结果表明,与对照相比,生石灰、油菜秸秆、有机肥、钾硅肥和土壤改良剂处理的大麦幼苗地上部生物量分别增加71.5%、24.1%、27.6%、28.2%、24.7%,大麦株高、根长、根系总表面积和根系活力均显著高于对照处理,根系平均直径减少,有利于养分和水分的吸收。综合结果表明,不同类型的调理剂对酸性土壤的降酸效果不尽相同,其中以生石灰效果最好,秸秆处理尽管没有有效降低土壤酸度但仍可明显促进作物生长,因此也可用作酸性土壤的改良物质,在实际生产中应因地制宜应用各种调节物质来促进作物生长。

变频空调器基于系统的变工况模糊控制仿真研究

提出了一种基于压缩机、蒸发器和房间对象的空调系统控制仿真方法 ,以克服传递函数法的缺点。应用此方法对变频空调器采用模糊控制与常规PI控制的ITAE、COP、控温精度等指标进行对比研究 ,揭示了模糊控制适应负荷变化能力强、节能的机理。

Detecting Agro-Droughts in Southwest of China Using MODIS Satellite Data

The normalized difference vegetation index （NDVI） has proven to be typically employed to assess terrestrial vegetation conditions. However, one limitation of NDVI for drought monitoring is the apparent time lag between rainfall deficit and NDVI response. To better understand this relationship, time series NDVI （2000-2010） during the growing season in Sichuan Province and Chongqing City were analyzed. The vegetation condition index （VCI） was used to construct a new drought index, time-integrated vegetation condition index （TIVCI）, and was then compared with meteorological drought indices-standardized precipitation index （SPI）, a multiple-time scale meteorological-drought index based on precipitation, to examine the sensitivity on droughts. Our research findings indicate the followings： （1） farmland NDVI sensitivity to precipitation in study area has a time lag of 16-24 d, and it maximally responds to the temperature with a lag of about 16 d. （2） We applied the approach to Sichuan Province and Chongqing City for extreme drought monitoring in 2006 and 2003, and the results show that the monitoring results from TIVCI are closer to the published China agricultural statistical data than VCI. Compared to VCI, the best results from TIVCI3 were found with the relative errors of -4.5 and 6.36% in 2006 for drought affected area and drought disaster area respectively, and 5.11 and -5.95% in 2003. （3） Compared to VCI, TIVCI has better correlation with the SPI, which indicates the lag and cumulative effects of precipitation on vegetation. Our finding proved that TIVCI is an effective indicator of drought detection when the time lag effects between NDVI and climate factors are taken into consideration.

Feedback Stabilization over Wireless Network Using Adaptive Coded Modulation

In this paper,we apply adaptive coded modulation (ACM) schemes to a wireless networked control system (WNCS) to improve the energy efficiency and increase the data rate over a fading channel.To capture the characteristics of varying rate, interference,and routing in wireless transmission channels,the concepts of equivalent delay (ED) and networked condition index (NCI) are introduced.Also,the analytic lower and upper bounds of EDs are obtained.Furthermore,we model the WNCS as a multicontroller switched system (MSS) under consideration of EDs and loss index in the wireless transmission.Sufficient stability condition of the closed-loop WNCS and corresponding dynamic state feedback controllers are derived in terms of linear matrix inequality (LMI). Numerical results show the validity and advantage of our proposed control strategies.

论变频空调器性能评价体系

以制冷运行为例 ,分析变频空调器运行性能和匹配特性。在此基础上 ,分别从行业、企业和消费者三个角度出发 ,分析建立变频空调器性能评价体系应包含的要素 ,提出以额定工况性能、高频额定比和低频额定比作为企业保证产品质量的强制性指标 ,以季节能效比作为行业向用户表明节能产品的推荐性指标 。

基于灰色-模糊理论的房间空调器评价方法研究

分析了目前有关综合评价方法中的缺陷和不足 ,从能效性、经济性、安全可靠性和外观使用性等方面确定了房间空调器的评价指标体系 ,结合灰色理论和模糊数学理论的相关知识 ,建立了综合评判的层次结构模型 ,并对五种房间空调器的性能进行了综合评价 。

Effect of Salinity on Growth of Mussels,Mytilus edulis,with Special Reference to Great Belt(Denmark)

The effects of salinities between 10 and 30 psu on the growth of blue mussels, Mytilus edulis, were studied in laboratory feeding experiments and compared to the growth of mussels suspended in net-bags in the brackish water Great Belt, Denmark. In the laboratory, 3 series of growth experiments were conducted: in Series #1, groups of mussels were exposed to 10, 15, 25 and 30 psu, in Series #2, two groups of mussels were exposed to 10 and 30 psu, respectively, for 15 days (first period) where upon the mussels were exposed to the reversed salinities for another 15 days (second period). In Series #3, two groups of mussels were initially exposed to 15 and 25 psu for 22 days whereupon the mussel groups were exposed to the reversed salinities for another 17 days. In the laboratory experiments there was a tendency towards reduced growth with decreasing salinity, reflected as reduced shell growth rate and decreasing weight specific growth rate with falling salinity. The shell growth rate was relatively low in the first feeding period compared to the second period, and mussels that were initially exposed to 10 psu, where the growth was low, exhibited fast growth when subsequently exposed to 30 psu, and reversed when 30 psu mussels were exposed to 10 psu. The study showed that mussels are able to adjust growth at changing salinities, and the observed effect of salinity could partly be explained by a temporary shell valve closure after a sudden change in salinity. The specific growth rate of mussels measured in laboratory experiments at salinities between 15 to 25 psu (4.2% to 4.8% d–1) were comparable to the growth of mussels in the field experiment (3.2% to 4.0% d–1) where the salinity varied between 24 and 13 psu during the growth period.

等室内舒适指数比调整的空调群负荷响应方法

随着智能用电的发展,采用智能调控方式,调整居民小区内大规模空调用电方式,对改善电网负荷特性和实现电网安全、稳定、经济运行具有重要意义。提出室内舒适指数,并根据用户对空调设定温度和湿度的偏好形成的室内舒适指数大小对用户空调进行了分类,形成依据室内舒适指数分类的多个空调子群,建立了空调群负荷响应数学模型;提出等室内舒适指数调整比的空调群负荷响应方法,该方法充分考虑了不同用户群体的喜好程度分类调整空调运行方式;通过算例对比分析,验证了所提等室内舒适指数比调整空调负荷方法的正确性和有效性。

施用餐厨垃圾调理剂对果园土壤有机碳组分的影响

为研究施用餐厨垃圾调理剂对土壤有机碳组分的影响,以果园土壤为研究对象,从时间、空间维度解析长期施用餐厨垃圾调理剂对土壤有机碳积累、组成及其分布规律的影响,结合CPMI(碳库管理指数)和相关性分析,揭示施用餐厨垃圾调理剂对土壤碳汇的影响机制.结果表明,施用餐厨垃圾调理剂可显著提高土壤中w(TOC)(TOC为总有机碳),并随施用时间的增加逐渐向深层土壤迁移,改善TOC分布状况.随着施用餐厨垃圾调理剂时间的增加,0～20 cm土壤层中w(NOC)(NOC为非活性有机碳)和30～40 cm土壤层中w(AOC)(AOC为活性有机碳)呈增加趋势,AOC分配比例低于NOC分配比例.随着施用时间的增长,0～30 cm土壤层中w(POC)(POC为颗粒有机碳)显著提高,最大值为42. 94 mg/g,MOC(矿质结合态有机碳)分配比例与POC分配比例呈相反变化趋势,有利于提高土壤碳稳定性.各土壤层中CPMI均大于空白对照组,最大值为154. 437,表明施用餐厨垃圾调理剂有利于提升土壤肥力.相关性分析表明,w(POC)与p H呈负相关,与含水率、EC(电导率)、w(OM)(OM为有机质)呈正相关,其中与含水率相关性最高(R=0. 91).可见,长期施用餐厨垃圾调理剂对提高果园土壤碳汇、改善土壤肥力具有重要意义,研究结果有助于进一步提升土壤碳汇的新型土壤调理剂的研发与应用.