Soil and Water Conservation Planning: Policy Issues and Recommendations

This article is prepared for the Upland Policy Conference on March 14, 1988. It discusses the degree of soil erosion in various watersheds based on classified descriptive parameters. It also proposes land use planning and allocation scheme.land management, watershed, soil erosion, soil conservation

Soil and Water Conservation Planning: Policy Issues and Recommendations

This article is prepared for the Upland Policy Conference on March 14, 1988. It discusses the degree of soil erosion in various watersheds based on classified descriptive parameters. It also proposes land use planning and allocation scheme.land management, watershed, soil erosion, soil conservation

ORGANIZED SYMPOSIA, ANNUAL MEETINGS, SAEA, BIRMINGHAM, ALABAMA, FEBRUARY 1997

"Strengthening the Applied Research Base for Rural Development Action Programs," by Greg Taylor, Colien Hefferan, and John E. Lee; "Relevance of SAEA to Extension: Is the SAEA Any Longer Relevant to the South?" by Harold M. Harris, Gary F. Fairchild, Tom Johnson, Eduardo Segarra, and Josef M. Broder; "Analyzing Supply Response Under the 1996 Farm Act," by Gary Adams, Andrew Washington, William Lin, Mike Dicks, Mack Leath, and Linwood Hoffman; "Sustaining Rural Communities," by William Amponsah, William Edmondson, John Ikerd, and Surendra Singh; "Using IMPLAN to Measure the Impact of Agriculture on a State's Economy," by David Hughes, Mark Henry, and Gerald Schluter; "USDA National Research Initiative (NRI) Competitive Grants Workshop on Markets, Trade, and Rural Development," Session I by Mark Bailey and David Holder, Session II by James Seale, Patricia Duffy, Mary Marchant, Gail Cramer, Won Koo, Kim Jensen, and Dale Colyer; "Implications of Federal Milk Marketing Order Reform for the South," by Ronald D. Knutson, Albert Ortega, Harold M. Harris, and Frank Johns; "Measuring Consumers' Judgment: A Pragmatic Approach Involving Ecotourism Analysis," by Evan Mercer, Alton Thompson, Donald McDowell, George Flemming, Adesoji Adelaja, Antohny Yeboah, and Edumnd Tavernier.

Multispectral Deep Neural Networks for Pedestrian Detection

Multispectral pedestrian detection is essential for around-the-clock applications, e.g., surveillance and autonomous driving. We deeply analyze Faster R-CNN for multispectral pedestrian detection task and then model it into a convolutional network (ConvNet) fusion problem. Further, we discover that ConvNet-based pedestrian detectors trained by color or thermal images separately provide complementary information in discriminating human instances. Thus there is a large potential to improve pedestrian detection by using color and thermal images in DNNs simultaneously. We carefully design four ConvNet fusion architectures that integrate two-branch ConvNets on different DNNs stages, all of which yield better performance compared with the baseline detector. Our experimental results on KAIST pedestrian benchmark show that the Halfway Fusion model that performs fusion on the middle-level convolutional features outperforms the baseline method by 11% and yields a missing rate 3.5% lower than the other proposed architectures.Comment: 13 pages, 8 figures, BMVC 2016 ora

Approximately Minwise Independence with Twisted Tabulation

A random hash function $h$ is $\varepsilon$-minwise if for any set $S$, $|S|=n$, and element $x\in S$, $\Pr[h(x)=\min h(S)]=(1\pm\varepsilon)/n$. Minwise hash functions with low bias $\varepsilon$ have widespread applications within similarity estimation. Hashing from a universe $[u]$, the twisted tabulation hashing of P\v{a}tra\c{s}cu and Thorup [SODA'13] makes $c=O(1)$ lookups in tables of size $u^{1/c}$. Twisted tabulation was invented to get good concentration for hashing based sampling. Here we show that twisted tabulation yields $\tilde O(1/u^{1/c})$-minwise hashing. In the classic independence paradigm of Wegman and Carter [FOCS'79] $\tilde O(1/u^{1/c})$-minwise hashing requires $\Omega(\log u)$-independence [Indyk SODA'99]. P\v{a}tra\c{s}cu and Thorup [STOC'11] had shown that simple tabulation, using same space and lookups yields $\tilde O(1/n^{1/c})$-minwise independence, which is good for large sets, but useless for small sets. Our analysis uses some of the same methods, but is much cleaner bypassing a complicated induction argument.Comment: To appear in Proceedings of SWAT 201

NOTES AND NEWS

GREAT PLAINS STUDIES SYMPOSIA FREDERICK C. LUEBKE AWARD (David Murphy; Don D. Walker; Doreen Barrie; Howard R. Lamar; David Wishart) CALLS FOR PAPERS JOINT CONFERENC

Multiple Instance Curriculum Learning for Weakly Supervised Object Detection

When supervising an object detector with weakly labeled data, most existing approaches are prone to trapping in the discriminative object parts, e.g., finding the face of a cat instead of the full body, due to lacking the supervision on the extent of full objects. To address this challenge, we incorporate object segmentation into the detector training, which guides the model to correctly localize the full objects. We propose the multiple instance curriculum learning (MICL) method, which injects curriculum learning (CL) into the multiple instance learning (MIL) framework. The MICL method starts by automatically picking the easy training examples, where the extent of the segmentation masks agree with detection bounding boxes. The training set is gradually expanded to include harder examples to train strong detectors that handle complex images. The proposed MICL method with segmentation in the loop outperforms the state-of-the-art weakly supervised object detectors by a substantial margin on the PASCAL VOC datasets.Comment: Published in BMVC 201

Critically Examining the "Neural Hype": Weak Baselines and the Additivity of Effectiveness Gains from Neural Ranking Models

Is neural IR mostly hype? In a recent SIGIR Forum article, Lin expressed skepticism that neural ranking models were actually improving ad hoc retrieval effectiveness in limited data scenarios. He provided anecdotal evidence that authors of neural IR papers demonstrate "wins" by comparing against weak baselines. This paper provides a rigorous evaluation of those claims in two ways: First, we conducted a meta-analysis of papers that have reported experimental results on the TREC Robust04 test collection. We do not find evidence of an upward trend in effectiveness over time. In fact, the best reported results are from a decade ago and no recent neural approach comes close. Second, we applied five recent neural models to rerank the strong baselines that Lin used to make his arguments. A significant improvement was observed for one of the models, demonstrating additivity in gains. While there appears to be merit to neural IR approaches, at least some of the gains reported in the literature appear illusory.Comment: Published in the Proceedings of the 42nd Annual International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR 2019

A critical review of Japanese scholarship on modern Chinese fiction and translation studies

This paper introduces Western readers to Japanese scholarship on late Qing and early Republican fiction and translation. It begins with a historical background on the development of modern Chinese literature studies in Japan, covering research societies, publications, and scholars in the field. Next, it discusses questions related to new directions in the study of the May Fourth Movement. Then, it addresses groundbreaking studies on writers and translators outside the main stream of research, covering Lin Shu, Liu Tieyun, and Li Boyuan. Further discussion examines thematic studies, including detective novels and Japanese political fiction

A hedonic model of lamb carcass attributes

Lamb carcass value is widely reported to be a function of lean meat yield, which is the relationship between muscle, fat and bone. Five retailers and five wholesalers assessed 47 lamb carcasses from diverse genotypes and scored seven attributes. A hedonic model reveals that conformation attributes were more highly valued (16 c/kg) relative to yield characteristics (4 c/kg). Meat colour and fat distribution were significant for retailers, but less important for wholesalers. Genotype was not a strong indicator of conformation. Eye muscle area and depth were correlated with Fat C; however, these were not significant. These results indicate that carcass conformation, meat colour and fat distribution should be incorporated into carcass grading models.Hedonic, lamb, conformation and meat value, attributes, Livestock Production/Industries,