Urban development broadly impacts the hydrological cycle, leading to increased peak flow and flooding. Surface water detention ponds are among most efficient measures for attenuating returning it from pre-development conditions. However, major challenge is identifying optimal locations cost-effective designs these ponds. This paper presents a new framework best strategies using control floods i...

Abstract This paper presents an application of the L-moments and L-moment ratio diagrams (LMRD) to analysis hydrological data at regional (country) scale. Existing research focuses on two main areas analysis: statistical using LMRD regression analysis. Further mixes both approaches applying L-moments. Another direction is clustering climatic physiographic catchment properties its validation LMR...

This paper looks at the present standing of ecommerce in Saudi Arabia, as well as the challenges and strengths of Business to Customers (B2C) electronic commerce. Many studies have been conducted around the world in order to gain a better understanding of the demands, needs and effectiveness of online commerce. A study was undertaken to review the literature identifying the factors influencing ...

Vision based bin picking is increasingly more di cult as the complexity of target objects increases We propose an e cient solution where complex objects are su ciently represented by simple features cues thus invariance to object complexity is established The re gion extraction algorithm utilized in our approach is capable of providing the focus of attention to the simple cues as a trigger towa...

We present preliminary work on automatically scoring constructed responses elicited as part of a certification test designed to measure the effectiveness of the test-taker as a K-12 music teacher. This content scoring differs from most previous work in that the responses are relatively long and are written by an adult population of generally proficient English writers. We obtain reasonably good...

We show that people’s travel destinations are predictable based on simple features of their home and destination. Using geotagged Twitter data from over 200,000 people in the U.S., with a median of 10 visits per user, we use machine learning to classify whether or not a person will visit a given location. We find that travel distance is the most important predictive feature. Ignoring distance, ...

Coastal polynyas are key formation regions for dense shelf water (DSW) that ultimately contributes to the ventilation of ocean abyss. However, not all form DSW. We examine how physiographic setting, water-mass distribution and transformation, column stratification, sea-ice production regulate DSW in four East Antarctic coastal polynyas. use a salt budget estimate relative contribution lateral a...

Maximum precipitation, which varies among locations and annually at a location of interest, is the base for sizing hydraulic structures. Understanding such spatiotemporal variations necessary accurate rainfall prediction but remains incomplete in most regions, including state Virginia. The objective this study was to fill information gap Virginia using 15-min precipitation data collected 57 gau...

BACKGROUND Understanding the drivers of large-scale vegetation change is critical to managing landscapes and key to predicting how projected climate and land use changes will affect regional vegetation patterns. This study aimed to improve our understanding of the role, magnitude and spatial distribution of the key environmental factors driving vegetation change in southern African savanna, and...

Monthly night averaged land surface temperature (LST) MODIS imagery was analyzed throughout a year-period (2006), in an attempt to segment the terrain of Egypt into regions with different LST seasonal variability, and represent them parametrically. Regions with distinct spatial and temporal LST patterns were outlined using several clustering techniques capturing aspects of spatial, temporal and...