scholarly journals PewLSTM: Periodic LSTM with Weather-Aware Gating Mechanism for Parking Behavior Prediction

2020 ◽  
Author(s):  
Feng Zhang ◽  
Ningxuan Feng ◽  
Yani Liu ◽  
Cheng Yang ◽  
Jidong Zhai ◽  
...  
Keyword(s):  
New York ◽  
State Of The Art ◽  
Prediction Method ◽  
Well Being ◽  
Behavior Prediction ◽  
Parking Lots ◽  
Gating Mechanism ◽  
Smart Parking ◽  
Reservation System ◽  
Parking Place

In big cities, there are plenty of parking spaces, but we often find nowhere to park. For example, New York has 1.4 million cars and 4.4 million on-street parking spaces, but it is still not easy to find a parking place near our destination, especially during peak hours. The reason is the lack of prediction of parking behavior. If we could provide parking behavior in advance, we can ease this parking problem that affects human well-being. We observe that parking lots have periodic parking patterns, which is an important factor for parking behavior prediction. Unfortunately, existing work ignores such periodic parking patterns in parking behavior prediction, and thus incurs low accuracy. To solve this problem, we propose PewLSTM, a novel periodic weather-aware LSTM model that successfully predicts the parking behavior based on historical records, weather, environments, and weekdays. PewLSTM has been successfully integrated into a real parking space reservation system, ThsParking, which is one of the top smart parking platforms in China. Based on 452,480real parking records in 683 days from 10 parking lots, PewLSTM yields 85.3% parking prediction accuracy, which is about 20% higher than the state-of-the-art parking behavior prediction method. The code and data can be obtained fromhttps://github.com/NingxuanFeng/PewLSTM. 

scholarly journals Himalayan perceptions: Environmental change and the well-being of mountain peoples

1970 ◽  
Vol 2 (3) ◽  
pp. 17-19 ◽  
Author(s):  
Jack D Ives
Keyword(s):  
New York ◽  
Environmental Change ◽  
Environmental Degradation ◽  
Full Text ◽  
Armed Conflict ◽  
Well Being ◽  
Government Agencies ◽  
The Past ◽  
Highland Forests ◽  
Development Paradigm

Preview of Himalayan perceptions: Environmental change and the well-being of mountain peoples by JD Ives Routledge, London and New York To be published in August 2004 Himalayan Perspectives returns to the enormously popular development paradigm that Ives dubbed the ‘Theory of Himalayan Degradation’. According to this seductive construct, poverty and overpopulation in the Himalayas was leading to degradation of highland forests, erosion, and downstream flooding. In the ‘Himalayan Dilemma’, Ives and Messerli exposed this “Theory” as a dangerous collection of assumptions and misrepresentations. While most scholars in the field promptly conceded Ives and Messerli’s points, the Theory has somehow survived as the guiding myth of development planners and many government agencies. In his new book, Ives returns to drive a stake through the heart of this revenant. His book not only reviews the research that, over the past 15 years, has confirmed the arguments of the ‘Himalayan Dilemma’; it also takes a close look at all those destructive factors that were overlooked by the conveniently simplistic ‘Theory of Himalayan Environmental Degradation’: government mismanagement, oppression of mountain minorities, armed conflict, and inappropriate tourism development. Himalayan Journal of Sciences 2(3): 17-19, 2004 The full text is of this article is available at the Himalayan Journal of Sciences website

scholarly journals Plant-based fructans for increased animal welfare: provision processes and remaining challenges

2021 ◽  
Author(s):  
A. Zimmermann ◽  
C. Visscher ◽  
M. Kaltschmitt
Keyword(s):  
Animal Welfare ◽  
Dietary Fibre ◽  
Animal Feed ◽  
State Of The Art ◽  
Public Awareness ◽  
Well Being ◽  
Glycosidic Bonds ◽  
Health Promoting ◽  
Branched Structure ◽  
Stimulation Of

AbstractFructans are carbohydrates consisting of fructose monomers linked by β-2,1- and/or β-2,6-glycosidic bonds with linear or branched structure. These carbohydrates belong to the group of prebiotic dietary fibre with health-promoting potential for humans and mammals due to their indigestibility and selective stimulation of microorganisms in the gastrointestinal tract. This makes fructans interesting mainly for healthy food as well as animal feed applications. As a consequence of a growing public awareness for animal welfare, dietary fibre and thus fructans move into the focus as a fibre-rich feeding improving not only animals’ health but also their well-being. Against this background, this paper summarises the known effects of fructans focusing on pigs and highlights the state of the art in fructan production processes from plant material as well as selected current research lines. Additionally, an attempt is made to assess the potential of European fructan production for an application as animal feed. Based on this, challenges in the field of fructan production are addressed and alternative substrates for fructans are discussed and pointed out.

“There Was No ‘That’s Not My Job’”: New York Area Agencies on Aging Approaches to Supporting Older Adults During the COVID-19 Pandemic

2021 ◽  
pp. 073346482199102
Author(s):  
Claire Pendergrast
Keyword(s):  
Older Adults ◽  
New York ◽  
New York State ◽  
Well Being ◽  
Contextual Influences ◽  
Structured Interviews ◽  
Response And Recovery ◽  
Pandemic Response ◽  
Increasing Demand ◽  
Priority Needs

The COVID-19 pandemic has disrupted many older adults’ traditional sources of formal and informal supports, increasing demand for Area Agency on Aging services (AAAs). This study examines strategies used by AAAs to support older adults’ health and well-being during COVID-19 and identifies contextual influences on AAA pandemic response activities. Semi-structured interviews were conducted with representatives of 20 AAAs in New York State. A combined inductive and deductive approach was used to code and thematically analyze the data. AAAs rapidly expanded capacity and dramatically modified program offerings, communications activities, and service delivery protocols to address emergent needs and minimize COVID-19 exposure risk for clients. AAAs’ trusted relationships with older adults and community partners improved their capacity to identify priority needs and coordinate appropriate supports. Policymakers should ensure that AAAs receive sustained financial and technical support to ensure critical community-based services are available for older adults throughout pandemic response and recovery.

The Impact of Stationarity, Regularity, and Context on the Predictability of Individual Human Mobility

2021 ◽  
Vol 7 (4) ◽  
pp. 1-24
Author(s):  
Douglas Do Couto Teixeira ◽  
Aline Carneiro Viana ◽  
Jussara M. Almeida ◽  
Mrio S. Alvim
Keyword(s):  
State Of The Art ◽  
Human Mobility ◽  
Contextual Information ◽  
Prediction Method ◽  
Mobility Prediction ◽  
Mobility Patterns ◽  
Distinct Cell ◽  
Inherent Nature ◽  
The One ◽  
The Impact

Predicting mobility-related behavior is an important yet challenging task. On the one hand, factors such as one’s routine or preferences for a few favorite locations may help in predicting their mobility. On the other hand, several contextual factors, such as variations in individual preferences, weather, traffic, or even a person’s social contacts, can affect mobility patterns and make its modeling significantly more challenging. A fundamental approach to study mobility-related behavior is to assess how predictable such behavior is, deriving theoretical limits on the accuracy that a prediction model can achieve given a specific dataset. This approach focuses on the inherent nature and fundamental patterns of human behavior captured in that dataset, filtering out factors that depend on the specificities of the prediction method adopted. However, the current state-of-the-art method to estimate predictability in human mobility suffers from two major limitations: low interpretability and hardness to incorporate external factors that are known to help mobility prediction (i.e., contextual information). In this article, we revisit this state-of-the-art method, aiming at tackling these limitations. Specifically, we conduct a thorough analysis of how this widely used method works by looking into two different metrics that are easier to understand and, at the same time, capture reasonably well the effects of the original technique. We evaluate these metrics in the context of two different mobility prediction tasks, notably, next cell and next distinct cell prediction, which have different degrees of difficulty. Additionally, we propose alternative strategies to incorporate different types of contextual information into the existing technique. Our evaluation of these strategies offer quantitative measures of the impact of adding context to the predictability estimate, revealing the challenges associated with doing so in practical scenarios.

scholarly journals A Combined Approach to Predicting Rest in Dogs Using Accelerometers

Sensors ◽  
2018 ◽  
Vol 18 (8) ◽  
pp. 2649 ◽  
Author(s):  
Cassim Ladha ◽  
Christy Hoffman
Keyword(s):  
Resting State ◽  
State Of The Art ◽  
Hybrid Approach ◽  
Well Being ◽  
Housing Conditions ◽  
Combined Approach ◽  
Current State ◽  
Healthy Dogs ◽  
State Of Rest ◽  
Health And Well Being

The ability to objectively measure episodes of rest has clear application for assessing health and well-being. Accelerometers afford a sensitive platform for doing so and have demonstrated their use in many human-based trials and interventions. Current state of the art methods for predicting sleep from accelerometer signals are either based on posture or low movement. While both have proven to be sensitive in humans, the methods do not directly transfer well to dogs, possibly because dogs are commonly alert but physically inactive when recumbent. In this paper, we combine a previously validated low-movement algorithm developed for humans and a posture-based algorithm developed for dogs. The hybrid approach was tested on 12 healthy dogs of varying breeds and sizes in their homes. The approach predicted state of rest with a mean accuracy of 0.86 (SD = 0.08). Furthermore, when a dog was in a resting state, the method was able to distinguish between head up and head down posture with a mean accuracy of 0.90 (SD = 0.08). This approach can be applied in a variety of contexts to assess how factors, such as changes in housing conditions or medication, may influence a dog’s resting patterns.

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