Enhancement of a global lake and reservoir database to aid climate studies and resource monitoring utilizing satellite radar altimetry

Here, we describe the expansion and enhancement of a large (surface area ≥100 km²) lake and reservoir database (1.GREALD). These efforts have also resulted in the spin-off of two additional databases, one containing lakes and reservoirs (2.GREALD, area 10–99 km²), and the other containing ephemeral lakes (3.GELD, area ≥100 km²). These databases are unique sources for projects that utilize satellite radar altimeter data to monitor surface water levels. While 1.GREALD aims to be a complete catalog, 2.GREALD focuses on reservoirs in response to applied sciences programs that monitor water and energy resources. The creation of 3.GELD has climate change objectives as well as water resources and ecosystem conservation applications. The recording of information pertaining to the potential overpasses (waterbody crossings) of the current and archive satellite altimeters is a primary objective as is the need to highlight any form of controlled water level variation. The permanent water databases now contain 6282 entries, half experience some form of anthropogenic influence and ～430 have been identified as potential climatically sensitive terminal lakes. The revised integral surface area distribution is a power law with exponent ?1.016. Statistics reveal that with altimetric repeat visit times of 10-day to monthly, at least 80% of the permanent water bodies (≥10 km²) have been overflown at some period since the 1990s. Current information on water use and reservoir formation date show that the primary use of the reservoir class is hydroelectric power, and that China, Brazil, India, Turkey, and Vietnam dominate the dam building in recent decades.     

Understanding the asymmetric perceptions of smartphone security from security feature perspective: A comparative study

Smartphones are being used and relied on by people more than ever before. The open connectivity brings with it great convenience and leads to a variety of risks that cannot be overlooked. Smartphone vendors, security policy designers, and security application providers have put a variety of practical efforts to secure smartphones, and researchers have conducted extensive research on threat sources, security techniques, and user security behaviors. Regrettably, smartphone users do not pay enough attention to mobile security, making many efforts futile. This study identifies this gap between technology affordance and user requirements, and attempts to investigate the asymmetric perceptions toward security features between developers and users, between users and users, as well as between different security features. These asymmetric perceptions include perceptions of quality, perceptions of importance, and perceptions of satisfaction. After scoping the range of smartphone security features, this study conducts an improved Kano-based method and exhaustively analyzes the 245 collected samples using correspondence analysis and importance satisfaction analysis. The 14 security features of the smartphone are divided into four Kano quality types and the perceived quality differences between developers and users are compared. Correspondence analysis is utilized to capture the relationship between the perceived importance of security features across different groups of respondents, and results of importance-satisfaction analysis provide the basis for the developmental path and resource reallocation strategy of security features. This article offers new insights for researchers as well as practitioners of smartphone security.     

Multiple material domain‐based computational tools for ease assessment of modal parameter in photonic crystal fibers

We report here the development of two computational tools PCFPS (Photonic Crystal Fiber Parameter Study) and PCFPA (Photonic Crystal Fiber Parameter Analysis), equipped with graphical user interface (GUI) for modeling of photonic crystal fiber. The tools are based on different structural parameters, and they provide characteristic analysis of the modal parameters from the structural parameters. The main feature of PCFPS is that it enables the user to find out the values of each defining modal parameter that has an immense contribution towards the manufacture of photonic crystal fiber. Additionally, PCFPA allows the user to observe the variation in the modal parameters with respect to the changes in structural parameters (such as d, Λ, d/Λ, and λ/>Λ). Besides their ease of use, these two schemes have high computational precision and adaptability, giving a novel platform to optical engineers to modulate the microstructured fibers according to their requirement.     

Relevance- and interface-driven clustering for visual information retrieval

Search results of spatio-temporal data are often displayed on a map, but when the number of matching search results is large, it can be time-consuming to individually examine all results, even when using methods such as filtered search to narrow the content focus. This suggests the need to aggregate results via a clustering method. However, standard unsupervised clustering algorithms like $K$-means (i) ignore relevance scores that can help with the extraction of highly relevant clusters, and (ii) do not necessarily optimize search results for purposes of visual presentation. In this article, we address both deficiencies by framing the clustering problem for search-driven user interfaces in a novel optimization framework that (i) aims to maximize the relevance of aggregated content according to cluster-based extensions of standard information retrieval metrics and (ii) defines clusters via constraints that naturally reflect interface-driven desiderata of spatial, temporal, and keyword coherence that do not require complex ad-hoc distance metric specifications as in $K$-means. After comparatively benchmarking algorithmic variants of our proposed approach – RadiCAL – in offline experiments, we undertake a user study with 24 subjects to evaluate whether RadiCAL improves human performance on visual search tasks in comparison to $K$-means clustering and a filtered search baseline. Our results show that (a) our binary partitioning search (BPS) variant of RadiCAL is fast, near-optimal, and extracts higher-relevance clusters than $K$-means, and (b) clusters optimized via RadiCAL result in faster search task completion with higher accuracy while requiring a minimum workload leading to high effectiveness, efficiency, and user satisfaction among alternatives.     

水位骤降对下伏隧道堤防安全影响研究

建立了考虑水位骤降条件下的下伏隧道堤防模型,依托湘江某下伏隧道堤防工程,基于堤防边坡渗流原理,结合有限元应力计算,探讨了不同水位骤降速率下的浸润线情况,计算了堤防安全系数。研究结果表明:湘江水位骤降速率越快,浸润线变化范围越大,浸润线变化范围与水位降落速率成正比;湘江水位骤降速度在3 m/d^4 m/d,水位降到28.8 m时,堤岸失去稳定;水位骤降并非整个过程中堤岸均处于失稳状态,而是水位降至某高度后堤岸失稳,骤降速率增快对堤防安全系数有一定负面作用。研究结果对隧道下穿堤防建设具有一定指导意义。     

张庄铁矿高阶段矿房切割天井施工工艺试验

张庄铁矿设计采矿方法为大直径深孔阶段空场嗣后充填法。为了最大化发挥采矿设备性能，降低采切工程量，提高回采效率，通过实施一系列技术攻关，实现了将采矿阶段高度由原来的60 m提高到90 m。而作为最初爆破回采的自由面及爆破补偿空间，切割天井施工工艺为影响高阶段矿房爆破回采效果的关键因素，施工质量的优劣，直接影响矿房爆破回采生产作业能否顺利进行，而二次处理在增加施工成本的同时将带来安全隐患。张庄铁矿在面临可参考的成熟经验较少的情况下，结合现场可用的作业条件采取了对比试验的方法，在安全、技术及经济多方面综合分析比较下，确定了最终方案，为张庄铁矿安全稳定生产奠定了基础，同时研究成果可为大型地下矿山生产实践提供一定的参考。     

库水位变动下庄屋滑坡变形与稳定性分析

库水位变动是三峡库区滑坡等地质灾害频发的重要原因之一。为研究库水位变动对库岸涉水滑坡变形和稳定性的影响,以庄屋滑坡为例,结合GPS位移监测数据和数值模拟分析,探讨了该滑坡在库水升降过程中变形和稳定性的响应规律。结果表明,庄屋滑坡受库水影响滑坡后缘变形大于前缘,为推移式滑坡。水位变动过程中,滑坡渗流和稳定性变化具有动水压力型滑坡特点,即在水位上升时滑体内地下水浸润线呈内凹趋势,水位下降时滑体内地下水浸润线呈外凸趋势,且具有一定的滞后性;库水位上升时滑坡稳定性系数增大,水位下降时减小;当库水位保持在恒定水位时,稳定性系数也逐渐趋于稳定。     

Optimal carbon reduction level and ordering quantity under financial constraints

Carbon tax policy is widely adopted by many countries to curb carbon emissions. In the context of carbon tax policy, firms have more incentive to improve carbon reduction levels by reducing their carbon tax costs. However, firms need to bear carbon reduction costs that may cause shortage of capital. Thus, firms may face problems of financial constraints, which may demotivate firms to produce greener products. To address the decision‐making challenges of firms in the contexts of carbon tax policy and financial constraints, we consider a supply chain with a manufacturer who produces green products and a retailer who sells these products. Our study develops five models to investigate the two firms’ optimal wholesale price, carbon reduction level and ordering quantity, according to the manufacturer and retailer with or without financial constraints. Our goal in this study is to explore how carbon tax policy and banks’ interest rates affect the profits of the two firms, supply chain and consumer surplus. Certain managerial insights are obtained as follows. We demonstrate that carbon tax policy and banks’ interest rates demotivate the manufacturer to produce greener products and demotivate the retailer to order more products. If the interest rate to the manufacturer (retailer) is relatively low, then the manufacturer with financial constraint benefits (harms) the consumers compared with the retailer with financial constraint. Importantly, our analysis suggests that carbon tax policy harms the firms but benefits consumers, and the government in some conditions should reduce unit carbon tax.     

气藏采收率影响因素研究与启示——以靖边气田A井区为例

以鄂尔多斯盆地靖边气田A井区为例，采用单因素相关分析和数值模拟方法，对比研究了井网控制程度、储层物性及地层废弃压力对气藏采收率影响及其主次关系。结果表明，井网控制程度是影响采收率的首要因素，井网控制程度每增加10%，采收率提高8.5%；渗透率是影响采收率的重要因素，渗透率每增加10%，采收率平均增加6%；废弃压力对采收率亦有较大影响，废弃压力每降低10%，采收率可提高1.6%。三者对采收率影响综合排序为：井网控制程度>储层物性>废弃压力。分析认为，渗透率是储层固有属性，很难从根本改变；而废弃压力受井口外输压力和增压开采成本制约，降低幅度有限。因此，优化井网及增加井网控制程度是提高气藏采收率的有效途径。研究成果具有实践意义，可为改进气田开发方式和提高气藏采收率提供参考。     

Modeling task completion time of in-vehicle information systems while driving with keystroke level modeling

The use of touchscreen-based in-vehicle information systems (IVIS) is increasing. To ensure safe driving, it is important to evaluate IVIS task performance during driving situations. Therefore, we proposed a model to assess the task completion time (TCT) of IVIS tasks while driving using a keystroke-level modeling (KLM) technique. The basic assumptions and heuristic rules of driver behaviors were considered. In addition, based on the characteristics of visual and manual IVIS interactions, we determined the basic unit operators (i.e., visual, manual, and mental operators). User experiments were conducted to determine the individual execution times of unit tasks and to measure the TCT of IVIS tasks while driving. Based on the heuristic rules for model development and individual task execution times, we derive a predictive model for the TCT of IVIS tasks. We used a regression analysis to validate the modeling procedure, showing that the observed TCT was found to have a strong positive correlation with the predicted time from the modeling process. The findings showed that the task completion time needed to perform a secondary task in a driving context can be predicted by KLM. This study provides meaningful insights into the design of touchscreen-based IVIS to enhance driving safety.