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Sarah is a married (10 years!) 32 year old, UK ex-pat, mother of 2 boys. She is an avid runner, and Martha Stewart wanna-be and recently converted vegan.
What characteristics define the Vancouver Housewife?
It depends on the situation! For me, I would say, hardworking (you gotta be, it costs so much to live here!), outdoorsy, the willingness to done yoga pants for any given occasion, and passionate about their city
Are you a good representation of a Vancouver Housewife? Why?
I am certainly a representation of a type of Vancouver housewife, and I like to think a good one!
I have a young family, I have a more than full time job, I have a husband who has a more than full time job, I am a fiercely passionate mother, I am long distance runner (or I try to be…), and I am a total wanna-be Martha Stewart clone. If it can be made from scratch in my house it will be from baked goods to patchwork quilts, to (amazing – in my eyes) 3-D cakes – there is no crafting project that hasn't been attempted!
Do you feel that living in Vancouver in some way defines who you are? Please explain.
I feel that living in Vancouver can't help but define who you are, but not the way most people would assume. I think that living wherever you live; you can't help but be defined somewhat by the location. I have to admit, I am a North Vancouver snob. I am totally and crazily in love with my neighbourhood. I have everything I could need within walking distance, parks, playgrounds, coffee shops, restaurants and 30 minutes from downtown. It means that we compromise on space, our boys share a room, we don't have a grassy back yard… but I can't imagine ever leaving.
Have you ever had cosmetic surgery, Botox, Restalyne injections, etc.? If so, please provide details. If you haven't had any of the above procedures performed, would you consider it?
I recently entered into the cosmetic surgery with the staggeringly daring mole removal procedure. The scabbiest of all facial procedures!
I would absolutely consider it, however, it certainly isn't a must have for me, when I look at things like that I am considering them from a cost perspective as in, is a smooth forehead really worth $500 to me? The answer typically is, "hell no! Do you have any idea how many cute dresses / kids shoes / summer camp days / winter tires I can buy for $500?"
Other than your children (if applicable), what is the accomplishment of which you are most proud?
I am proud of the fact that my husband and I, as a unit, chose to carve out a life for ourselves in Vancouver. We moved in in 2005 with no family support, raised 2 amazing children, and succeeded in both of our careers. That in itself brings a lot of stress, very little downtime and we celebrated 10 years of marriage May 2012.
Has the desire for affluence/power/money been a motivator in the choices you've made for your life?
No! I mean, I like money. I would like more money. It certainly makes life easier. But, we do what we love and that doesn't necessarily bring in the big bucks.
Tell us about your stuff. What do you like to buy, collect, etc.?
Dust… no only kidding; however, I do seem to inadvertently collect dust….
Without even trying, I/we seem to collect toys. My almost 8 year old has a seriously large collection of Lego. I am a shoe kind of girl, I am also very proud of my (gifted) Louis Vuitton purse, something I would NEVER buy for myself but is now my prized possession. I have a thing for dresses. I am a big collector of photographs and then creating memory books each year which we send to our families back in the UK.
Do you have "staff" in your home? (E.g. nanny, driver, chef, etc.)
Hello, my name is Sarah. I am the cleaner, cook, laundry person, driver, first aid expert, chief baker, and reader of bedtime stories. My husband's name is Martin and he holds the glamorous title of garbage-taker-outer and head recycler, car maintenance and laundry-putter-away-er.
Do you belong to any clubs, teams, groups or social organizations?
Oh how I would love to. I run on a regular basis but don't belong to any running clubs, with a busy work/home life I have to go whenever there is a window. My husband is a video games developer and often keeps pretty unusually hours. If I were to commit to a group I am sure I would let it down more times than actually be able to attend.
Finish this sentence: "My life's motto is …."
Really to be happy, to keep the ones I love safe & secure, to experience and embrace change and to make time for the people I love – what more is there?
As a special thank you for participating, Sarah will be receiving a Sunrise gift basket worth $40 – cookbook, Sunrise premiums and coupons plus a $10 Chapters book gift card. Sunrise Soya Foods, founded in 1956, is the largest tofu manufacturer in Canada specializing in a wide range of tofu products and soy beverage. From the non-GMO soybeans to the ingredients, everything is natural and free of preservatives and trans fat. For more information, visit www.sunrise-soya.com
Interested in being profiled as one of the REAL Real Housewives of YVR? Interested in gifting one of these amazing women with something special? E-mail me!


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Skydiving.com now has a network skydiving location serving Red Creek and Wayne County in New York. Call Skydiving.com at 1-800-617-7948 for details, free information and specials on skydiving in Red Creek, NY today!
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subset: commoncrawl


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Climate graph
The driest month is February. There is 33 mm of precipitation in February. Most precipitation falls in July, with an average of 71 mm.
Temperature graph
With an average of 18.2 °C, July is the warmest month. In January, the average temperature is -1.9 °C. It is the lowest average temperature of the whole year.
Climate table
The precipitation varies 38 mm between the driest month and the wettest month. The average temperatures vary during the year by 20.1 °C.


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Meyer, Martin; Elmer, S; Ringli, M; Oechslin, M; Baumann, S; Jäncke, Lutz (2011). Long-term exposure to music enhances the sensitivity of the auditory system in children. European Journal of Neuroscience, 34(5):755-65.
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This event-related brain potential study aims to contribute to the present debate regarding the effect of musical training on the maturation of the human auditory nervous system. To address this issue, we recorded the mismatch negativity (MMN) evoked by violin and pure sine-wave tones in a group of 7.5- to 12-year-old children who had either several years of musical experience with Suzuki violin lessons, or no musical training. The strength of the MMN responses to violin tones evident in the Suzuki students clearly surpassed responses in controls; the reverse pattern was observed for sine-wave tones. Suzuki students showed significantly shorter MMN latencies to violin tones than to pure tones; the MMN latency did not differ significantly between pure tones and violin sounds in the control group. Thus, our data provide general evidence of how and to what extent extensive musical experience affects the maturation of human auditory function at multiple levels, namely, accuracy and speed of auditory discrimination processing. Our findings add to the present understanding of neuroplastic organization and function of the mammalian nervous system. Furthermore, behavioural recordings obtained from the participating children provide corroborating evidence for a relationship between the duration and intensity of training, the specific sensitivity to instrumental timbre, and pitch recognition abilities.
19 citations in Web of Science®
22 citations in Scopus®
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|Item Type:
|Journal Article, refereed, original work
|Communities & Collections:
|06 Faculty of Arts > Institute of Psychology
|Dewey Decimal Classification:
|150 Psychology
|Deposited On:
|08 Nov 2011 13:33
|Last Modified:
|05 Apr 2016 15:05
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Skydiving.com now has a network skydiving location serving Beaufort and Carteret County in North Carolina. Call Skydiving.com at 1-800-617-7948 for details, free information and specials on skydiving in Beaufort, NC today!
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New Blood (hardcover)
Lawrence R. Heibel
I'm a professional writer and photographer. I've been writing fiction since I was a kid. Spent 14 years writing and taking pictures freelance for area newspapers. I now am focused on writing fiction and photographing everything from events and weddings to portraits for home and business. I also teach photography at my studio, www.workshoots.com
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New Blood (softcover)
Publicado 26 de noviembre de 2012
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For the last 24 hours, the Drudge Report has had a photo of House Speaker John Boehner, with the obligatory; Charlie Sheen inspired headline, "Winning!"
The inside the beltway crowd is crowing, "Boehner won!" The left is laughing that Boehner won. When they are happy he won, we need to be worried. Much of the GOP establishment is saying Boehner won. Those outside of the beltway and not in the establishment have a more realistic view. When you escape DC, you realize, Boehner did not win. He and the GOP House leadership lost the opportunity of a political lifetime.
Dick Morris excoriates Boehner and the GOP for selling out. He notes that now, any chance for serious budget reduction is gone, because Boehner will not fight. Morris is an incredible political analyst, having run some amazingly successful campaigns. But even he does not get the Tea Party and the opportunity the GOP has just thrown away.
The goal of many in the Tea Party in the recent budget fight was not to shut the government down. We wanted the fight. People who are not in this movement probably won't understand that.
For the last two years, this movement has been on the defensive. Our goals have been to stop Obama, Pelosi and Reid from spending money. To stop Obamacare. To stop the radical agenda of the socialist Democrats. All of those have been defensive stands. Now the tide has changed. We had the chance to go on the offense. We had the chance to win. We had the chance to start taking ground back.
The messaging from the GOP leadership in DC was simple. We only control one half of one third of the government. There is a good expression for that kind of messaging: Bovine Scatology! (If you don't know what that means, just think BS)
No, the Supreme Court has nothing to do with the appropriations process and neither does the White House. The GOP controls half of the apparatus of spending.
The course Boehner and the GOP chose was timidity not bold and courageous. Had they been willing to be bold, with major objectives; had Boehner done what we suggested at TPN, demanding hundreds of billions in cuts by eliminating waste, he could have been hailed as a hero. Had he held firm for bold and decisive action and shut the government down, we would have had his back. Had he stood firm and called for Tea Party support, we would have flooded the Capitol to support him and the GOP.
Boehner was afraid the media would blame him for the shutdown. Does the man not understand messaging? The Tea Party was ready to fight with good messaging. In a battle of public opinion, when the messaging is Obama, Pelosi, Reid and the rest of the Democrats are willing to defund the military because they don't want to defund Planned Parenthood, that is one of the easiest victories that could be won.
Boehner and the House GOP leadership don't get a couple of other things either. A couple of my friends who are serious GOP insiders have emailed me saying the GOP has accomplished some good things since it took over the House. The Bush tax cut extension being one of them and some budget reductions.
The Bush tax cut extensions were a good thing. A tax increase on this fragile economy would have probably kicked us even further down the path to the Obama economic implosion. By keeping those tax cuts in place and avoiding a de facto tax increase, the GOP has done something good. $38 billion in cuts is good, though not that good when you consider that the budget deficit for this year is $1,650,000,000,000.00.
Arrogance is perhaps the best word to describe how the House GOP leadership reacts to the Tea Party. My friends complained that we were not talking about what they were doing. To be honest, unless it is in the media, we do not know a lot of what they are doing because they do not make any effort to spread the word to Tea Party groups about what they are doing. Even Republican insiders are privately complaining that the House leadership is not keeping any of them informed either.
Unfortunately, even if they did take the time to spread the word about what they are doing, they still do not understand the Tea Party movement. We are not simply going to jump because the House Leadership or Boehner snaps his fingers. We are not simply going to cheer because they do something. The Tea Party movement remains a leaderless movement. We still work from the bottom up. We don't take orders well. We do expect our elected officials to listen to us and other than the few who have made it a point of reaching out to the Tea Party movement, most are not listening.
Had Boehner shown some courage and asked the Tea Party for help, he could have won an outstanding victory for the American people. He could have rolled back spending. He could have defunded two major liberal support groups (Planned Parenthood and NPR). He could have stopped the EPA from imposing job killing carbon regulations. He could have supported talk radio, which has been the GOP's consistent ally, from Obama's FCC, which wants to shut it down. Boehner could have come to the Tea Party and we would have been there for him. We could have crippled the Obama, Pelosi, Reid axis of fiscal evil. We could have had a sea change in politics in Washington. Boehner could have brought together the alliance that would have changed politics for decades.
Next year, the Tea Party had hoped to focus on liberal Democrats exclusively. We will be hitting them hard. But this week has taught us that we are going to need to clean house in the GOP if we are ever going to accomplish anything.
For John Boehner, enjoy the accolades of the establishment this week. The Tea Party is going to remember it as an epic failure to lead.
Views: 77
Mark has been a truth teller and a hero of mine from the 90's when he would rip the libs on MSNBC and he did it again in this clip---thanks for posting it as I don't watch Cavuto, or much of anything anymore on FNC.
Maybe Trump should start a real news org instead of running for POTUS. Mark, Andrew Breitbart and Michelle Malkin should be the head execs...Yes, I am a major league dreamer.
I completely agree. We are fighting on two fronts and it is a heavy lift. In my opinion the
Republican establishment circled the wagons after the election in order to claim that
the Republican Party turned the Country around and not the Tea Party. We, the Tea Party
Movement, are now being managed and kept at arms length. At this point in time I am thinking
we may have to remove a few of them in the primaries and identify them for removal
in the near future. If the Republican Party will not take us seriously we will have to get serious with
the Republican Party.
Absolutely Jim,
The TEA Party needs to focus all its efforts of the removal of Boehner, Cantor, and McCarthy. They are the three heads in the house. Even if a Democrat wins in all three seats, it will send a clear message to the Republicant's and the next three selected for House leadership will know they are on the hot-seat. Focus on just the removal of those three. Focus TEA Party money and boots on the ground into VA 7, OH 8, and CA 22, and let them know they are targeted for defeat...and carry through with it. Primary them and if they win, support a third party or independent candidate. There must be the credible threat that the TEA Party will use its "nuclear option". Only taking out those three will most likely leave the Republican'ts with a majority and they'll have another shot at taking the bold and audacious action we expect of real leaders. I'm not thrilled with McConnell or Kyl in the Senate either, but I expect that if we take out the House leadership...they'll get the message. If not...they're the next to go. We've got nothing to lose. Both parties are marching down the same road, just at slightly different paces. It will also send the message to disenfranchised Democrats (of which there are many here in the South) and Independents, that we are not just shills for the Republican Party...that we sat what we mean and mean what we say and will hold all government officials to the same standard. The message will be just a clear to the establishment maneuverers and manipulators in the RNC, State, and local party units. This is the plan I've presented to our Tea Party Coordination Council here in South and Western VA. After this week, I do not believe we'll have any further dissension in adopting this plan.
With respects where due and apologies to none...
I couldn't agree more, D Wayne. I'm very disappointed in the House leadership, or should I say lack of same. I must admit I put more faith in Boehner than he has shown himself worthy of. I suggest we not wait for them (the leadership) to ask for our help but start right now to campaign for even larger cuts to the 2012 budget than Rep Ryan has put forth. And this CR is only for a week. How can we get to the House leadership and make them stand firm when this CR is up? Can we, shouldn't we, fight the demagoguery of the Dems now, with the next installment of this farcical exercise in political manipulation?
My biggest fear is that we are out of time.
Yes we should fight the demagoguery of the Demorats now...and the Republican'ts too. Don't kid yourself into thinking that the vast majority of elected Repubs think like you and I, especially once they are in DC. I've been a Repub my entire adult (and mid-teen) life. It wasn't until I retired from the Army a couple of years ago that I really took a good hard look at what both parties have done to eviscerate the Constitution. I am a member of our local unit and by and large they are a pretty Conservative bunch. That is until the hierarchy gets involved in the nomination process for candidates. At that point they want who they want and will get who they want...another lifetime pol, generally a lawyer, definitely a go along to get along yes man or woman. Once the real conservative is defeated in the closed nomination process it is then expected that all the good little minions will fall into line and support the party pick...because he or she is, after all, at least the lesser of evils. You see, they want your donations, your vote, and your effort...but they do not want you to be part of the process. They will handle that for you.
Republicans like big government too. They enjoy the power just the same as the Dems and are loathe to actually relinquish it. Don't believe me? Ask yourself, when was the last time the "party of smaller government" actually shrank government? They might cut taxes and even reduce spending, but do they ever actually reduce the size and scope of the "national" government? No. Not even under Reagan. What we need to do is dislodge incumbents and party leadership, defund all unconstitutional "national" (yes I know it's Federal, but in name only) programs and agencies, deregulate our industries from "national" oversight, and then dismantle the infrastructure from which they wield power. We need to restore state functions to the state. Rebublican'ts will not do this of their own volition. It will take the credible threat of their own demise (as a party that is, for all you HP et al trolls that are looking for another Tim McVeigh amongst we patriots). The question is, what are we prepared to do? I know where I stand.
With respect where due and apologies to none,
I live in Boehner's home district. The following is a copy of the message I just sent to Boehner wit Cc to: Sen. Portman, Govermonr Kasich, and various other Ohio Republican leaders.
Conressman Boehner, On Friday, 8 April 2011, you let America down. YOU were beaten. YOU did not put up a fight.
**This year's Federal spending deficit is $1.7Trillion.That deficit is a grave to danger to America. It MUST be eliminated.You let Obama blackmail you into surrender by holding US Armed forces' pay and other factors hostage for a pathetic $35Billion in cuts... barely a 2% cut.**
YOU FAILED to take THAT message to America.
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Ryder Makes a Mess
Chris Westgate
There's a big mess in the living room! But who is to blame? Find out in this book for all ages!
Authored and Illustrated by Chris Westgate
I'm an illustrator looking to make some awesome artwork! I love bringing original characters to life, and entertaining people with stories that inspire the imagination. I have more books on the way so stay tuned!
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Scott Fraser Von der Ahe
Position: LB
Height: 5-11 Weight: 242 lbs.
Born: October 12, 1975 in Lancaster, CA
High School: Mission Viejo
College: Iowa, Arizona St. (school history)
Drafted by the Indianapolis Colts in the 6th round (182nd overall) of the 1997 NFL Draft.
Weighted Career AV (100-95-...): 1 (13070th overall since 1950)
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Product Detail
Note: This belt is adorned with glass crystals. Some of these crystals may have sharp edges.
Product Reviews
02/18/2013By Pistol
Looked the belt and good quality. Good fit and a lot of people loved it also and asked where I got it.
12/27/2012By Lynn
Overall, I really like this belt! The only concern that I do have about the belt are pistols on it. They rotate, which is cool, but I'm nervous that They will come off! None of them have yet, so maybe they'll be ok! The belt, like alot of them you sell, is very eye catching. That's why I have bought four others from your company. You have alot of very nice choices! Thank you!
08/20/2012By Sillysat
Plan on wearing this fun belt when I'm Mounted Shooting, and when I'm headin' to town! :)
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08/20/2012By fierypistol
I absolutely love this belt! It is hands down, the most stylish item hanging in my closet. My nickname has always been the "fiery pistol", so this product fits me well so to say!
08/20/2012By Taylor
The first time I wore the belt was to an Eric Church concert and I received a ton of compliments on it!! I love the eye-catching bling and camo combination!


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Mar 16, 2011 10:14 AM
The Toto Pine Tree Pedestal Sink ($2820) would be pretty without hand painted art on it, but you know us, we like added bonuses. Probably our favorite piece from the Waza Miyabi Collection, this delicate basin pictures pine trees reaching across the bowl and blossoming plum branches climbing up the stand. These plants symbolize resilience and perseverance, so hopefully that will rub off on us (Our lives are hard).
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Instructors must complete this online form for every course.
Online non-attendance notices are available via CabriniOne—http://one.cabrini.edu—for one week, following the Add/Drop period.
After the end of the Add/Drop period, if a student stops attending class, then the instructor should complete either a First-Year Student Evaluation (for first-year students only) or a Warning Notice.
Academic Affairs will email specific instructions for non-attendance notices to all faculty at the beginning of each semester.
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International Journal of Distributed Sensor Networks
Volume 2014 (2014), Article ID 148234, 12 pages
Model Selection Approach for Distributed Fault Detection in Wireless Sensor Networks
1Department of Statistics, West Bengal State University, Barasat, India
2ASD, Indian Statistical Institute, 203 B. T. Road, Kolkata 700 108, India
3Chennai Mathematical Institute, Chennai, India
Received 2 April 2013; Revised 13 November 2013; Accepted 14 November 2013; Published 20 January 2014
Academic Editor: Shuai Li
Copyright © 2014 Mrinal Nandi et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Sensor networks aim at monitoring their surroundings for event detection and object tracking. But, due to failure or death of sensors, false signal can be transmitted. In this paper, we consider the problems of distributed fault detection in wireless sensor network (WSN). In particular, we consider how to take decision regarding fault detection in a noisy environment as a result of false detection or false response of event by some sensors, where the sensors are placed at the center of regular hexagons and the event can occur at only one hexagon. We propose fault detection schemes that explicitly introduce the error probabilities into the optimal event detection process. We introduce two types of detection probabilities, one for the center node, where the event occurs, and the other one for the adjacent nodes. This second type of detection probability is new in sensor network literature. We develop schemes under the model selection procedure and multiple model selection procedure and use the concept of Bayesian model averaging to identify a set of likely fault sensors and obtain an average predictive error.
1. Introduction
Traditional and existing sensor-actuator networks use wired communication, whereas wireless sensor networks (WSN) provide radically new communication and networking paradigms and myriad new applications. The wireless sensors have small size, low battery capacity, nonrenewable power supply, small processing power, limited buffer capacity, and low-power radio. They may measure distance, direction, speed, humidity, wind speed, soil makeup, temperature, chemicals, light, and various other parameters.
Recent advancements in wireless communications and electronics have enabled the development of low-cost WSN. A WSN usually consists of a large number of small sensor nodes, which are equipped with one or more sensors, some processing circuit, and a wireless transceiver. One of the unique features of a WSN is random deployment in inaccessible terrains and cooperative effort that offers unprecedented opportunities for a broad spectrum of civilian and military applications, such as industrial automation, military surveillance, national security, and emergency health care [1–3]. Sensor networks are also useful in detecting topological events such as forest fires [4].
Sensor networks aim at monitoring their surroundings for event detection and object tracking [1, 5]. Because of this surveillance goal, coverage is the functional basis of any sensor network. In order to fulfill its designated tasks, a sensor network must fully cover the Region of Interest (ROI) without leaving any internal sensing hole [6–9]. So far, a number of movement-assisted sensor placement algorithms have been proposed. An exclusive survey on these topics is presented by Li et al. [10]. On the other hand sensor could die or fail at runtime for various reasons such as power depletion and hardware defects. So, even after the ROI is fully covered by the sensors, wrong information can be communicated by some sensors or sensors may fail to detect the event due to noise or obstructions. Chen et al. [11] have proposed a distributed localized fault detection algorithm for WSN, where each sensor identifies its own status to be either good or faulty and the claim is then supported or reverted by its neighbors. The proposed algorithm is analyzed using a probabilistic approach. Sharma et al. [12] have characterized the different types of fault and proposed a different algorithm for fault detection considering different types of fault. Some of the methods are statistical, like using histogram and so forth. Both works can only detect the faulty sensors, but not the event.
One of the important sensor network applications is monitoring inaccessible environments. Sensor networks are used to determine event regions and boundaries in the environment with a distinguishable characteristic [13–15]. The basic idea of distributed detection [16] is to have each of the independent sensors make a local decision (typically, a binary one; i.e., an event occurs or not) and then combine these decisions at a fusion sensor (the sensor which collects the local information and takes the decision) or at a base station to generate a global decision.
A closely related area is neural network. Several works are there in the literature on this area. Li and Qin [17] find a feasible solution to a class of nonlinear inequalities defined on a graph proposing a recurrent neural network. The convergence of the neural network and the solution feasibility to the defined problem are both theoretically proven. They proposed neural network features as a parallel computing mechanism and a distributed topology isomorphic to the corresponding graph which is suitable for distributed real-time computation. The proposed neural network is applied to range-free localization of WSNs. Li et al. [18] show that feasible solution set to the same problem is often infinity and Laplacian eigenmap is used as heuristic information to gain better performance in the solution. A continuous-time projected neural network and the corresponding discrete-time projected neural network are both given to tackle this problem iteratively. The effectiveness of the proposed neural networks is tested and compared with others via its applications in the range-free localization of WSNs. Location information is useful for mobile phones. There exists a dilemma between the relatively high price of GPS devices and the dependence of location information acquisition on GPS for most phones in current stage. Li et al. [19] formulate the problem as an optimization problem defined on the Bluetooth network. The solution to this optimization problem is not unique. Heuristic information is employed to improve the performance of the result in the feasible set. They used recurrent neural networks to solve the problem distributively in real time. The convergence of the neural network and the solution feasibility to the defined problem are both theoretically proven. The hardware implementation of the proposed neural network is also explored in this paper.
Distributed algorithms are also used for a network dynamic system. Li et al. [20, 21] studied the decentralized control and kinematic control of multiple redundant manipulators for the cooperative task execution problem. The problem is formulated as a constrained quadratic programming problem, and then a recurrent neural network with independent modules is proposed to solve the problem in a distributed manner. They proposed a novel strategy capable of solving the problem, even though there exist some manipulators unable to access the command signal directly.
Another related area is the winner-take-all (WTA) competition, which is widely observed in both inanimate and biological media and society. Many mathematical models are proposed to describe the phenomena discovered in different fields. These models are capable of demonstrating the WTA competition. Li et al. [22, 23] make steps in that direction and present a simple model, which produces the WTA competition by taking advantage of selective positive-negative feedback through the interaction of neurons via -norm. They also present a class of recurrent neural networks to solve quadratic programming problems. Different from most existing recurrent neural networks for solving quadratic programming problems, the proposed neural network model converges in finite time and the activation function is not required to be a hard-limiting function for finite convergence time. The stability, finite-time convergence property, and the optimality of the proposed neural network for solving the original quadratic programming problem are proven in theory. Extensive simulations are performed to evaluate the performance of the neural network with different parameters. In addition, the proposed neural network is applied to solving the k-winner-take-all (k-WTA) problem.
1.1. Our Motivation
In this paper, we are interested in one particular query: determining event in the environment (i.e., ROI) with a distinguishable characteristic. We assume the ROI to be partitioned into suitable number of congruent regular hexagonal cells (i.e., we can think of ROI as a regular hexagonal grid). This physical structure of ROI is not a requirement for the theoretical analysis, and we can do the similar analysis with another structure also. Suppose that sensors are placed a priori at the center (which are known as nodes) of every hexagon of the grid. We assume that the sensors are connected to its adjacent sensor nodes in the sense that a hexagon will be strongly covered by its center node and weakly covered by the adjacent nodes. If event occurs in the hexagon where a particular sensor lies, then that particular sensor can detect the event with a greater probability, whereas if event occurs in any adjacent hexagon, then the particular sensor can detect the event with a lesser probability. Hence, only one node (center node of the event hexagon) can detect the event hexagon with greater probability, say , and adjacent nodes (six for interior nodes and less for boundary nodes) can detect the event hexagon with lesser probability, say , with . We assume that no other sensor can detect the event hexagon. In this paper, unlike the previous works, we assume that if the event occurs, then it occurs at only one hexagon of the grid which will be known as event hexagon, and there is no fusion sensor. All sensors can communicate with the base station and the base station takes the decision about the query. As an example, consider a network of devices that are capable of sensing mines or bombs, if we assume that a few mines or bombs may be placed on a particular area of ROI. Information from these devices can be sent to a nearby police station or a central facility. Then, an important query in this situation could be whether a particular hexagon is the event hexagon or not (i.e., mines or bombs are placed or not).
One fundamental challenge in the event detection problem for a sensor network is the detection accuracy which is disturbed by the noise associated with the detection and the reliability of sensor nodes. A sensor may fail to detect the event due to natural obstruction or any other causes. After detecting the event, a sensor can send false message to the base station due to some technical reasons. The sensors are usually low-end inexpensive devices and sometimes exhibit unreliable behavior. For example, a faulty sensor node may issue an alarm, even though it has not received any signal for event or it cannot detect any event and vice versa. Moreover, a sensor may be dead, in which case the sensor cannot send any alarm.
1.2. Previous Work and Our Contribution
Lou et al. [24] consider two important problems for distributed fault detection in WSN: how to address both the noise-related measurement error and sensor fault simultaneously in fault detection and how to choose a proper neighborhood size for a sensor node in fault correction such that the energy could be conserved. They propose a fault detection scheme that explicitly introduces the sensor fault probability into the optimal event detection process. They show that the optimal detection error decreases exponentially with the increase of the neighborhood size.
Krishnamachari and Iyengar [13] propose a distributed solution for canonical task in WSN (i.e., the binary detection of interesting environmental events). They explicitly take into account the possibility of sensor measurement faults and develop a distributed Bayesian algorithm for detecting and correcting such faults.
Nandi et al. [25] consider the problem of distributed fault detection in wireless sensor network (WSN), where the sensors are placed at the center of a particular square (or hexagon) of the grid covering the ROI. They proposed fault detection schemes that explicitly introduce the error probabilities into the optimal event detection process. They developed the schemes under the consideration of Neyman-Pearson hypothesis test and Bayes test. They also calculate type I and type II errors for different values of the parameters.
In almost all the previous works, except [25], authors assume that event occurs over a region and there are fusion sensors that collect the information locally and take a decision. Since they do not introduce the concept of base station, there is no concept of response probability. Also, they assume that information is spatially correlated. Unlike the previous work, in this paper, we assume that if event occurs, then it occurs at only one cell of the ROI and there is no fusion sensor. All the sensors send information to the base station. We introduce the probability model in two different stages: firstly, when a sensor detects the event and, secondly, when a sensor sends the message to the base station. In the previous works, only one type of detection probability has been introduced to simulate the different error probabilities for some specific values of the parameters. In this paper, we introduce two different detection probabilities and obtain analytically the exact test and estimate the error probabilities by simulation. In almost all the previous works, authors assume the ROI to be a square grid. The hexagonal grid is better in the sense that a minimum number of sensors are required to cover the entire ROI [26].
In our theoretical analysis, the sensor fault probabilities are introduced into the optimal event detection process. We apply model selection approach, multiple model selection approach, and Bayesian model averaging methods [27, 28] to find a solution of the problem. We develop the schemes using the model selection technique. We calculate different error probabilities and find some theoretical results.
In all previous works, the authors assume only one detection probability. We introduce two detection probabilities, and , one for the center node and other for the adjacent nodes. Even if the center node may fail to detect the event, the adjacent nodes may detect the event, and vice versa. We consider these probabilities and show that, in various situations, the adjacent nodes play key role to detect the event. One can introduce more detection probabilities and analyze the situation in similar manner.
The parameters and , the detection probabilities of a sensor, and error probabilities (see Section 3) cannot be estimated from the real life situations but need to be estimated beforehand by some experimentation. The prior probabilities of various events also cannot be estimated but may be known in some cases. Finally, we calculate the error probabilities numerically for some values of the parameters of our model and make some concluding remarks analyzing the results.
2. Statement of the Problem and Assumptions
In this section, we describe the problem in more specific terms and state the assumptions that we make.
Sensors are deployed or manually placed over ROI to perform event detection (i.e., to detect whether an event of interest has happened or not) in ROI. If sensors are deployed from air then, using actuator-assisted sensor placement or by movement-assisted sensor placement, sensors are so placed that sensor network covers the entire ROI. This ROI is partitioned into suitable number of regular hexagons (i.e., we can think of the ROI as a regular hexagonal grid), as shown in Figure 1. Sensors are placed a priori at every center (which are known as nodes) of the regular hexagons. Sensors have two detection probabilities. The sensor network covers the entire ROI and there is only one event hexagon, as discussed before.
Each sensor node determines its location through beacon positioning mechanisms [29] or by exploiting the Global Positioning System (GPS). Through a broadcast or acknowledge protocol, each sensor node is also able to locate the neighbors within its communication radius. Sensors are also able to communicate with the base station. Base station will take the decision. In this paper, we assume that event occurs at one particular hexagon of the grid which will be known as event hexagon or event does not occur (in that case we say that ROI is normal). All sensors can communicate with the base station and base station takes the decision by combining the information received from all the sensors.
There are two phases in the whole process. The first one is detection phase, when the sensor at the center of a regular hexagon tries to detect the event. The sensor at the center of the event hexagon can detect the event hexagon with greater probability and the sensors at the adjacent nodes (see Figure 1) can detect the event hexagon with lesser probability . We also assume that there is a prior probability that a particular hexagon is an event hexagon. The next phase is response phase, in which sensors send message to the base station. Even if the event hexagon is detected by a sensor, it may not respond (i.e., send message to the base station that no event occurred in that cell and the neighboring cells due to some technical fault) with some probability; then we say that the sensor is a faulty sensor. Conversely, if event hexagon is not detected or there is no event hexagon at all (i.e., ROI is normal), then also a faulty sensor can send the wrong information to the base station with some probability. A sensor is said to be a dead sensor if the sensor does not work. A dead sensor sends no response in either cases.
Each sensor sends information to the base station. As the sensors may send wrong information, the base station takes the important role in identifying the event hexagon. Base station will collect all information and take a decision about the event hexagon according to a rule which we have to find out. Our job is to find a rule for the base station such that base station works most efficiently.
2.1. Notations and Assumption
Our problem is to develop a strategy for the base station to take decision about event hexagon (i.e., which hexagon of the ROI is the event hexagon, if at all). Let be the set of all nodes. For , define as the set of adjacent node(s) of , and let be the number of adjacent node(s) of . Hence, . Call a node interior if . Let be the sensor which is placed at the node , and let be the hexagon where the node is placed (i.e., is the center of ). For , let denote the true status of the node . That is, if event occurs at , and otherwise. Also define if detects no event, and if detects the event in or , for . Finally define if does not respond; that is, the sensor informs the base station that event does not occur at or for , and if responds; that is, the sensor informs the base station that the event has occurred in or , for .
Now we make one natural assumption that once detection phase is completed, response of a sensor depends only on what it detects but not on whether the event has actually occurred or not; that is, . We also assume that the sensors work independently and identically.
Since we assume that there is at most one event hexagon, or .
The possible true scenarios are, therefore, represented by the following different models: : ( for all ), and, for each , : ( and for all ).
and, for all , .
In particular, we may assume 's to be the same for all . We denote any probability under the model as and under the model as .
We also make the followings assumptions.(i)For all , and .(ii)For all , and .(iii)For all and .(iv) and are independent for .(v)The responses from different nodes are independent under a particular model; that is, 's are independent under for a fixed .
3. Theoretical Analysis of Fault Detection
In this section we discuss some theoretical results. In real situations, may be very large. Given the network of the sensor nodes and some prior knowledge about the nature of event, one may have fairly good idea about the set of feasible regions for the event. Formally, instead of all possible models, one may be able to restrict to a set containing all the feasible models. For example, if the event is known to take place in a particular region, we can restrict our models accordingly.
3.1. Model Selection Approach
Consider Hence, under the model follows , for all , and the likelihood of the data , under the model , is So . Hence, for all , under follows . Similarly, for all , under follows , where and, under follows for all . Note that since . Hence the likelihood for the model , given , is Let , so that with the corresponding observed values denoted by Therefore, where are independent of .
In model selection approach, the model resulting in the maximum value of the likelihood is selected. Note that, since there is no parameter being estimated, this is equivalent to the well-known Akaike Information Criterion (AIC) [30]. Therefore, the base station will accept the model if Otherwise, as is positive, accept the model for which is maximum among all . If values of are equal for more than one , then we can select one of the corresponding models with equal probability. If we want to maximize the likelihood for the models corresponding to the interior nodes only, so that is fixed, then we need to maximize among all .
3.2. Multiple Model Selection
Instead of selecting one particular model, one may want to select more than one model with approximately similar log likelihood values to the maximum one. We can consider the set of models where is a suitable constant close to . This is usually chosen according to the resource available. This is similar to the idea of Occam's window in the context of Bayesian model selection [27]. This may be interpreted as the interval estimation for the true model.
Note that is an increasing function of , as is positive. We consider only the following set of models where , for all , with . In particular, if we consider the interior nodes only, then we consider the set of models given by We can select multiple models using some other criteria. One such may be to select all the models (one or more) for which the maximum value of the likelihood is attained. Let be the set of nodes corresponding to all these models, including "" corresponding to if it has the maximum value of the likelihood. Then this method selects all the models with . By another criterion, one may select the models , for ; that is, is a node in or any of the neighboring nodes of a node in . Note that for is the empty set. One can combine these two types of criteria and come up with many others.
3.3. Bayesian Model Averaging
Bayesian model averaging is an effective method to solve a decision problem when there are many alternative hypotheses or models, which are complicated [27]. Suppose that are the models considered and denotes the given data. The posterior probability for model is given by where denotes the probability of observing data under the model (which is essentially the likelihood under ) and is the prior probability that is the true model (assuming that one of the models is true).
In this work, the data is and the models are as defined in Section 3.2. Hence, the posterior probability for model is
We select the model if is greater than , for all ; otherwise, select for which is maximum among all . Hence, if 's are all equal, then Bayesian approach is the same as the likelihood approach.
4. Some Important Considerations and Error Probabilities
In this section, we consider some important issues related to the problem of fault detection and the proposed methodology including calculation of errors (e.g., false detection, etc.) and detection probabilities.
The following probabilities give some idea about the role of neighboring nodes, along with the center node, in detection or false detection, of event. For example, gives the probability of a false detection by the th node and not by the neighboring nodes, while gives the probability of a false negative by the th node, with all the neighboring nodes detecting the event. Since, given a particular model, and are independent, calculation of such probabilities is simple as given in the following. For any and ,(1), (2), (3), (4). which can be numerically obtained using the joint distribution of and under the model . The maximum of these probabilities over all gives a lower bound for the probability that a node is considered to be an event node when the ROI is normal. On the other hand, the sum over all gives an upper bound for the same. Similarly, for , which can be again numerically obtained using the joint distribution of and under the model . This probability gives some idea about the error that when th node is the event node and it is not detected.
As noted in Section 3.1, we select the model for which is the maximum, for . The random variable is, therefore, of some interest, the distribution of which under different models is useful in calculating many error probabilities. We first find the distribution of under the model . Note that takes values , corresponding to and , for , and . Assume that, for convenience, the values of for different and are all distinct. Therefore, for and , For or , one can find in similar manner, although the calculation is very tedious as there are many subcases. Ideally, one is interested in probability of errors occurring at the level of base station. For example, the two important errors are not selecting when is true (false positive) and selecting when is true for some (false negative). Theoretical calculation of these error probabilities is complicated. We, therefore, use simulation technique to estimate these and similar error probabilities.
5. Simulation Study
We consider a hexagonal grid and we run the programme 10000 times. The simulation is performed using the -code, and required random numbers are generated using the standard -library.
In our simulation study, we consider different criteria, as discussed in Sections 3.1 and 3.2, for estimating the error probabilities or, equivalently, the success rate. First consider the probability of selecting , when it is true. Let denote the proportion of correct detection of normal situation, when model is true, using the model selection method of Section 3.1. That is, gives an estimate of . Then gives an estimate of the false positive rate.
When is true for some , let denote the proportion of correct decision for the event node using the model selection method of Section 3.1, so that it estimates . Note that, for each simulation run, the event hexagon is chosen randomly, so that gives an average value over all . In this context, this probability is the same for all the interior nodes. Then, gives an estimate of the corresponding error probability of not selecting , when it is true.
Note that, in this problem of fault detection with a single event node, the likelihood value, for a given observed data configuration, may be equal for more than one models. Therefore, quite often, the maximum value of the likelihood may be attained by more than one model. The model selection method of Section 3.1, which selects one of these models randomly in such cases, may often not select the correct model. Therefore, the method of Section 3.2, which selects more than one model having similar likelihood value, may be preferred and will have better chance of selecting the correct model. We now consider some of those methods in the following.
Let us first consider the method in which all the models corresponding to the maximum value of the likelihood are selected. Let denote the proportion of correct selection of the model , when it is true, by this method. Then estimates the probability , which is always more than or equal to the quantity estimated by , as remarked before. We also consider the method in which all the models having maximum likelihood along with their neighborhood models are selected. A model is a neighborhood model of the model if is a neighboring node of . If denotes the proportion of correct selection of the model , when it is true, by this method, then estimates . Clearly, . Similarly, if denotes the proportion of correct selection of the model , when it is true, by selecting all those models with likelihood value being more than of the maximum likelihood (i.e., the method of Section 3.2 with ), then estimates the probability with denoting the maximum value of the likelihood.
Suppose that denotes the average number of selected nodes to be searched corresponding to . Clearly, because we need no search when is selected. When event occurs and we consider only one from , we need at most one search (since no search is needed if is selected) and we have . In our simulation, we find in all the cases; which means that, in simulation, has not been selected when event occurred. Note that since we consider all 's in for searching. Again, as before, . Also, by definition, . Table 1 presents the different 's and 's based on simulation for different values of , and with and taking values 0.9 and 0.99, taking values 0.01 and 0.001, and taking values 0.0, 0.3, 0.4, 0.5, and 0.6. The choice of and reflects the corresponding high probability, whereas that of reflects small probability, which is desirable in a good sensor. Since the primary interest is to study the effect of detection by neighboring nodes, we consider as 0 (which means that there is no effect of neighboring nodes) and some positive values less than .
Note that the probability of correct detection under depends only on . This is also evident in Table 1. Intuitively, if is high, then the proportion of correct detection in normal situation is low. In Table 1, we see that is 0 for , varies from 0.35 to 0.37 for , and varies from 0.90 to 0.91 for (not shown in Table 1). If we consider smaller value of , then the success probability will be higher. Hence must be low as the number of hexagons is high to get better results in normal situation.
We see that the estimated false negative rate, that is, an estimate of , is often in our simulation (not shown in Table 1). This is because, if the event occurs at , then detection of the event by at least one of the nodes belonging to is highly probable. Furthermore, since the grid size is large, one of the nodes belonging to may respond wrongly, though it cannot detect the event. So, under , there is a small probability to select ROI as normal. If we take and the detection probabilities and to be very small, then we may get some positive false negative rate, but this is not a desired condition for a good sensor.
From simulation, we see that, as increases (for positive ), values increase, whereas decrease. As increases, it helps to differentiate between the likelihood values resulting in lower cardinality of the set and lower values of 's. However, since the neighboring nodes help to detect the event, the success probability increases. From simulation, we find that, as increases, success probabilities also increase, but the effect of is more prominent than that of . On the other hand, success probabilities also change with and . Since means , so there is little variability in the likelihood values leading to larger size of .
When , effect of on , and and , and seems to be significant, whereas the same cannot be said for . There is sudden change in 's and 's, when we shift from to , for , but not . So, when is small, the effect of the neighborhood seems to be less.
The values of and are very similar for different values of the parameters, but larger increment in than suggests that the idea of neighboring search is not effective. But is much higher than , so the method of searching all the nodes in is a better idea than that of searching a random node from .
We estimate the success probability by simulation for different values of the threshold ranging from 0.5 to 0.9 (see Table 2). Note that corresponds to the threshold value . We consider , and four values of . From Table 2, we see that the success probability increases as the threshold value decreases and increases. Similarly, the number of search decreases with both and .
6. Discussion
One prime object of this paper is to show the effect of the neighboring nodes in detection of an event. In this section, we discuss the role of the neighboring nodes and some other related issues and make remarks.
6.1. Role of the Neighboring Nodes
Since , where , and are as defined in Section 3.1, denotes the weight of the central node compared to the neighboring nodes in the corresponding likelihood. Note that, since , we have , and if is close to 1, then the six neighboring nodes are as important as the event node. So, as the value of increases, the importance of the neighboring nodes decreases. Also, gives some idea about the role of the number of adjacent nodes, that is, . Recall that and are the probabilities of responding (i.e., reporting the node as the event hexagon) by the sensors and , respectively, when is the event hexagon and is a neighboring node of . So, we numerically calculate the quantities , and for some values of the parameters (see Table 3).
From the theoretical results in Section 3.1, we see that and increase as increases, while and do not depend on . On the other hand, while increases with , and decrease and is independent of . Therefore, the importance of the neighboring nodes decreases with and increases with , as expected and observed in Table 3.
6.2. Estimation of the Parameters
In practice, the parameters , and may be unknown. We can, however, estimate the parameters by some experimentation.
Note that, under follows for all . Hence, is the expected value of given . So we perform the experiment by keeping the ROI normal. The proportion of 's having value gives an estimate of . Repeat this experiment several times, so that the average of the proportions over the repeated experiments can be taken as an estimate of .
Note that is the expected value of under . So, we perform the experiment by keeping an event in some node of the ROI. The proportion of 's having value gives an estimate of . Repeat this experiment for several times, so that the average of the proportions over the repeated experiments can be taken as an estimate of . Similar experiments will give estimates of and as well.
6.3. Incorporation of Heterogeneity and Uncertainty in Parameters
Let denote the set of parameters, which has been assumed to be the same for all the nodes. While, in practice there is no reason why the parameters should be same for all the nodes, it is also not clear how these would be different across . This unexplained heterogeneity can be incorporated by assuming the 's, for different , to be independent realizations from a common distribution.
Let denote the set of parameters for node . We assume that , are i.i.d. from some distribution, say . Also assume that, given 's are independent. Note that denotes the joint distribution of the four parameters. For simplicity, we may assume them to be independent, so that can be written as . In this situation, the likelihood for the model is where the integration is over the range of . Similarly, the likelihood for the model can be written as where the integral is over the four-dimensional space given by the range of and is the contribution of the th node to the likelihood , given the value , as described in Section 3.1.
Similar technique can also be used to incorporate parameter uncertainty. Even though the parameters can be assumed to be same for all the nodes, there may be reasonable uncertainty about the constancy of the parameter values. As in the Bayesian paradigm, the set of parameters may be assumed to be a realization from a distribution, say . Then, the likelihoods for the models and are The choice of may be a difficult one. However, sometimes there may be specific information available regarding the distribution of , which can be incorporated in the model.
6.4. When More Sensors Can Detect the Event Square
We may consider the situation when sensing radii are larger and more sensors can detect the event hexagon but with different probabilities. With respect to a particular node, classify the remaining nodes with respect to the probability of detecting the event at that node, which may as well depend on the distance from the particular node. Suppose that the sensors in the th class detect the event hexagon with probability . The theoretical analysis is similar to that of Section 3, but having more probability terms.
6.5. Concluding Remarks
In this paper, we consider the problem of fault detection in wireless sensor network (WSN). We discuss how to address both the noise-related measurement errors ( and ) and sensor fault ( and ) simultaneously in fault detection, where the ROI is partitioned into regular hexagons with the event occurring at only one hexagon. We propose fault detection schemes that explicitly introduce the error probabilities into the optimal event detection process. We develop the schemes under the consideration of model selection technique, multiple model selection technique, and Bayesian model averaging method. The different error probabilities are calculated by means of simulation. Note that the same analysis can be carried out when ROI is partitioned into squares and sensors are placed at the centers.
Nandi et al. [25] consider similar problem in wireless sensor network (WSN), in which the event can take place at the center of one particular square (or hexagon) of the grid covering the ROI. In our paper, we allow the event square to be any one in the grid. Our approach can also be used for the problem of [25] with only two models to be considered for selection. In [25], the authors develop the scheme under the consideration of Neyman-Pearson hypothesis test, where the null and alternative hypotheses correspond to the two models. In model selection approach, we select the model with higher likelihood. In classical Neyman-Pearson hypothesis test, a model is selected if its likelihood is greater than some constant times the likelihood of the other. This constant is fixed before the test depending on the size of the test. In model selection approach, the constant is , leaving no choice for the size of the test. On the other hand, we cannot apply the classical Neyman-Pearson test with more than two models to be considered for selection.
The principle of hypothesis testing places a large confidence in the null hypothesis and does not reject it unless there is strong evidence against it. This safeguard of null hypothesis cannot be ensured in the model selection approach of Section 3.1. However, the multiple model selection approach of Section 3.2 provides some safeguard in this regard.
This principle of model selection can be extended to the situation when there are more than one event hexagon and the objective is to detect the event hexagons. We may also assume that the sensors can detect different types of events. That is, response of sensors may not be only binary; sensors can measure distance, direction, speed, humidity, wind speed, soil makeup, temperature, and so forth and send the measurement of continuous type variables to the base station. One needs a different formulation of the problem in such case which will be taken up in future.
Conflict of Interests
The authors declare that there is no conflict of interests regarding the publication of this paper.
The authors are sincerely thankful to the anonymous reviewers for their detailed comments that helped improve the overall quality of this paper. The authors are also thankful to Sourav Sengupta, Indian Statistical Institute, Kolkata, for his valuable suggestions.
- I. F. Akyildiz, W. Su, Y. Sankarasubramaniam, and E. Cayirci, "Wireless sensor networks: a survey," Computer Networks, vol. 38, no. 4, pp. 393–422, 2002. View at Publisher · View at Google Scholar · View at Scopus
- G. J. Pottie and W. J. Kaiser, "Wireless integrated network sensors," Communications of the ACM, vol. 43, no. 5, pp. 51–58, 2000. View at Google Scholar · View at Scopus
- D. P. Agrawal, M. Lu, T. C. Keener, M. Dong, and V. Kumar, "Exploiting the use of WSNs for environmental monitoring," EM Magazine, pp. 27–33, 2004. View at Google Scholar · View at Scopus
- C. Farah, F. Schwaner, A. Abedi, and M. Worboys, "A distributed homology algorithm to detect topological events via wireless sensor networks," ACM Transaction on Sensor Networks, vol. 10, no. 10, 2010. View at Google Scholar
- F. Martincic and L. Schwiebert, "Introduction to wireless sensor networking," in Handbook of Sensor Networks: Algorithms and Architectures, I. Stojmenovic, Ed., chapter 1, John Wiley & Sons, 2005. View at Google Scholar
- X. Bai, S. Kumar, D. Xuan, Z. Yun, and T. H. Lai, "Deploying wireless sensors to achieve both coverage and connectivity," in Proceedings of the 7th ACM International Symposium on Mobile Ad Hoc Networking and Computing (MOBIHOC '06), pp. 131–142, Florence, Italy, May 2006. View at Scopus
- M. A. Batalin and G. S. Sukhatme, "The analysis of an efficient algorithm for robot coverage and exploration based on sensor network deployment," in Proceedings of the IEEE International Conference on Robotics and Automation, pp. 3478–3485, Barcelona, Spain, April 2005. View at Publisher · View at Google Scholar · View at Scopus
- J. Cortés, S. Martínez, T. Karataş, and F. Bullo, "Coverage control for mobile sensing networks," IEEE Transactions on Robotics and Automation, vol. 20, no. 2, pp. 243–255, 2004. View at Publisher · View at Google Scholar · View at Scopus
- A. Filippou, D. A. Karras, and R. C. Papademetriou, "Coverage problem for sensor networks: an overview of solution strategies," in Proceedings of the 17th Telecommunication Forum (TELFOR '09), 2009.
- X. Li, A. Nayak, D. Simplot-Ryl, and I. Stojmenovic, "Sensor placement in sensor and actuator networks," in Wireless Sensor and Actuator Networks: Algorithms and Protocols for Scalable Coordination and Data Communication, John Wiley & Sons, 2010. View at Google Scholar
- J. Chen, S. Kher, and A. Somani, "Distributed fault detection of wireless sensor networks," in Proceedings of the Workshop on Dependability Issues in Wireless Ad Hoc Networks and Sensor Networks (DIWANS '06), pp. 65–71, ACM, New York, NY, USA, September 2006. View at Publisher · View at Google Scholar · View at Scopus
- A. B. Sharma, L. Golubchik, and R. Govindan, "Sensor faults: detection methods and prevalence in real-world datasets," ACM Transactions on Sensor Networks, vol. 6, no. 3, article 23, 2010. View at Publisher · View at Google Scholar · View at Scopus
- B. Krishnamachari and S. Iyengar, "Distributed Bayesian algorithms for fault-tolerant event region detection in wireless sensor networks," IEEE Transactions on Computers, vol. 53, no. 3, pp. 241–250, 2004. View at Publisher · View at Google Scholar · View at Scopus
- K. Chintalapudi and R. Govidan, "Localized edge detection in sensor fields," in Proceedings of the 1st IEEE International Workshop on Sensor Network Protocols and Applications, pp. 59–70, 2003. View at Publisher · View at Google Scholar
- R. Nowak and U. Mitra, "Boundary estimation in sensor networks: theory and methods," in Proceedings of the 1st IEEE International Workshop Sensor Network Protocols and Applications, 2003.
- J. N. Tsitsiklis, "Decentralized detection," Advances in Statistical Signal Processing, vol. 2, pp. 297–344, 1993. View at Google Scholar
- S. Li and F. Qin, "A dynamic neural network approach for solving nonlinear inequalities defined on a graph and its application to distributed, routing-free, range-free localization of WSNs," Neurocomputing, vol. 117, pp. 72–80, 2013. View at Google Scholar
- S. Li, Z. Wang, and Y. Li, "Using laplacian eigenmap as heuristic information to solve nonlinear constraints defined on a graph and its application in distributed range-free localization of wireless sensor networks," Neural Process Letters, vol. 37, pp. 411–424, 2013. View at Google Scholar
- S. Li, B. Liu, B. Chen, and Y. Lou, "Neural network based mobile phone localization using bluetooth connectivity," Neural Computing and Applications, vol. 23, no. 3-4, pp. 667–675, 2013. View at Publisher · View at Google Scholar · View at Scopus
- S. Li, S. Chen, B. Liu, Y. Li, and Y. Liang, "Decentralized kinematic control of a class of collaborative redundant manipulators via recurrent neural networks," Neurocomputing, vol. 91, pp. 1–10, 2012. View at Publisher · View at Google Scholar · View at Scopus
- S. Li, H. Cui, Y. Li, B. Li, and Y. Lou, "Decentralized control of collaborative redundant manipulators with partial command coverage via locally connected recurrent neural networks," Neural Computing and Applications, vol. 23, pp. 1051–1060, 2012. View at Google Scholar
- S. Li, B. Liu, and Y. Li, "Selective positive—negative feedback produces the winner-take-all competition in recurrent neural networks," IEEE Transactions on Neural Networks and Learning Systems, vol. 24, no. 2, pp. 301–309, 2013. View at Google Scholar
- S. Li, Y. Li, and Z. Wang, "A class of finite-time dual neural networks for solving quadratic programming problems and its k-winners-take-all application," Neural Networks, vol. 39, pp. 27–39, 2013. View at Publisher · View at Google Scholar
- X. Luo, M. Dong, and Y. Huang, "On distributed fault-tolerant detection in wireless sensor networks," IEEE Transactions on Computers, vol. 55, no. 1, pp. 58–70, 2006. View at Publisher · View at Google Scholar · View at Scopus
- M. Nandi, A. Nayak, B. Roy, and S. Sarkar, "Hypothesis testing and decision theoretic approach for fault detection in wireless sensor networks," The International Journal of Parallel, Emergent and Distributed Systems. In press.
- R. Williams, The Geometrical Foundation of Natural Structure: A Source Book of Design, Dover, New York, NY, USA, 1979.
- J. A. Hoeting, D. Madigan, A. E. Raftery, and C. T. Volinsky, "Bayesian model averaging: a tutorial," Statistical Science, vol. 14, no. 4, pp. 382–417, 1999. View at Google Scholar · View at Scopus
- D. Madigan and J. York, "Bayesian graphical models for discrete data," International Statistical Review, vol. 63, pp. 215–232, 1995. View at Google Scholar
- N. Bulusu, J. Heidemann, and D. Estrin, "GPS-less low-cost outdoor localization for very small devices," IEEE Personal Communications, vol. 7, no. 5, pp. 28–34, 2000. View at Publisher · View at Google Scholar · View at Scopus
- J. K. Ghosh, M. Delampady, and T. Samanta, An Introduction to Bayesian Analysis, Theory and Methods, Springer, New York, NY, USA, 2011.


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Playwright of a new musical JUDY GARLAND - World's Greatest Entertainer. This show is a takeoff of the '70's tv show THIS IS YOUR LIFE. But Judy's guests are Liza, Frank and Dean. The 4 of them sing their signature tunes. Opening in April 2015
CANDLELIGHT THEATRE: April 24,25,26 & May 1,2,3 302.475.2313
baby grand Mother's Day May 10 matinee and evening performance (Mom loved Judy, Frank & Dean) 800.37.Grand
The Milton (DE) Theatre May 16 302.684.3038
Interviewer Greer Firestone and Videographer Chris Senge have launched The Heirloom Video. Generally, the clients are grandparents who wish to provide a legacy for their family. Generally, the sons and daughters support our cost. In the finished product are family photos and film telling the chronology of the family. It becomes a personal family mission statement similar to ones made by companies to express their core values.
by Bruce Feiler, columnist from the NYT and author of "The Secrets of Happy Families"
Do you know where your grandparents grew up? Do you know where your mom and dad went to high school? Do you know where your parents met? Do you know an illness or something really terrible that happened in your family? Do you know the story of your birth?
Family psychologists Dr. Marshall Duke and Dr. Sara Fivush of Emory University asked those questions of four dozen families in the summer of 2001, and taped several of their dinner table conversations. They then compared the children's results to a battery of psychological tests the children had taken, and reached an overwhelming conclusion. The more children knew about their family's history, the stronger their sense of control over their lives, the higher their self-esteem and the more successfully they believed their families functioned. The "Do You Know?" scale turned out to be the best single predictor of children's emotional health and happiness.
The bottom line: if you want a happier family, create, refine and retell the story of your family's positive moments and your ability to bounce back from the difficult ones. That act alone may increase the odds that your family will thrive for many generations to come.
YouTube trailer with our latest client Jack Carney, father of DE US Congressman, John http://www.youtube.com/watch?v=3rBEO2GXvwc&feature=youtu.be
Greer Firestone
Facebook.com/The Heirloom Video


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A lot.
Especially those thin shoestring ones. Oh man, I could eat a whole basket myself!!! While squealing in happiness and licking grease from my fingers. And I would be in total heaven.
Unfortuntely, breading and frying slices of onion aren't so good for you. Or your heart.
Fortunately, I found a great recipe that is the best "diet" version of onion rings I have ever found, or would happily eat again. And don't think you're going to get skimped here. No, no my friends, I would never do that to you! For a grand total of 153 calories and 1 gram of fat (yeah, you read that right!) you get the whole onion. That's a lot of rings! Especially if you slice them thin!!!!
Make them. Devour them. Love them.
Per Serving:
1 large onion
1/2 cup Fiber One Bran Cereal (Original Flavor)
1/4 cup egg whites
dash of salt
Optional: add a dash of peppers, oregano, garlic powder, onion, powder, etc. if you want!
Preheat oven to 375 Degrees.
Cut the ends off the onion, remove the outer layer, and cut onion into 1/2 inch wide slices.
Seperate rings.
Crush the cereal into breadcrumb like consistency (use a food processor, or smash the heck out of it in a ziplock bag).
Pour the crumbs into a small dish and add any seasoning you choose.
Pour the egg whites into a second bowl.
Dip the onion slices into the egg whites, then the crumbs, shake off any cling-ons, and then place onto a baking sheet. Don't crowd them!
Make for 20-25 minutes, flipping halfway through.
153 Calories, 1g fat, 379mg Sodium, 41g carbs, 16g fiber, 7g sugars, 9g protein, 4 Weight Watchers Plus Points
Recipe from Hungry Girl, page 104


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From the Sandlot Brewery at the appropriately-named Coors Field, to a team called the Milwaukee Brewers; beer has become a more integral part of the baseball experience than the infield fly rule could ever dream of.
Now, a partnership between Delaware North Sportservice and Anheuser-Busch will put that beauty completely in the eyes of the beer holder.
According to the Twin Cities Pioneer Press on Monday, patrons at Target Field (home of the Minnesota Twins) will now be able to pour themselves a cold one at self-service beer stations (assuming they are of proper age).
"It's a fun, cool new gadget," said Twins spokesman Chris Isles. "We've been all about embracing technology, so we jumped at the opportunity that nobody has done before."
The technology will make its debut next week at the festivities surrounding the MLB All-Star game. Fans who are over 21 will be able to go to a cash register and buy a preloaded card to use at the machines. They then will be able to control how much is poured, only paying for the exact amount of beer they want.
"There's obviously some novelty value to this, but it also allows people to pour what they want," said Delaware North principal Jerry Jacobs Jr. "If they want half of a cup, that's all they will pay for."
The station will allow each card to be used to pour up to 48 ounces of beer every 15 minutes. They will serve four beers; with Budweiser and Bud Light costing 38 cents an ounce, and Shock Top Lemon Shandy and Goose Island 312 Urban Pale Ale each costing 40 cents per ounce.
The stations will not be completely automated however, as an employee will at each to check IDs and cut off those who may have had one too many.
Not everybody is thrilled with this development, which may have an impact on vendor sales.
"You'll never be able to compete with seat vendors because I'd rather sit and watch the game and have a beer brought to me, but I'd say from an employment standpoint, it's just another attack on workers being replaced by machines," said Nancy Goldman, president of the Local 17 Twin Cities Hospitality Union.
The 85th MLB All-Star Game will take place at Target Field on July 15.
Suggested Links
- Sleeping New York Yankees' fan suing ESPN, MLB for $10 million
- A's and Giants send a total of nine players to All-Star Game
- Death of Tony Gwynn gives new meaning to AleSmith beer
- Colorado Rockies outfielder Carlos Gonzalez has tumor removed from finger
- Derek Jeter ready to go for 2014, but will Tulowitzki take his spot next season?


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Organization Details:
ESL & Immigrant Ministries - VA - Arlington
We believe that a way in which we can practically serve our neighbors in a community where one in four homes speaks a language other than English is to teach English. We believe that by teaching English as a second language we are offering "new Americans" a practical skill that will empower them to be full participants in their communities and in society.
Contact person: Dorothy Hettmann, Program Coordinator, (703) 841-0292, (email)
Main office number: (703) 841-0292
Web Site: http://www.eslim.org
Be the first person to offer feedback on this organization!
Post a volunteer reflection to share your experiences with other volunteers!
The inclusion of any organization or person in this database does not constitute a representation, warranty, or endorsement with respect to the competence, suitability, or reliability of such organization or person by Volunteer Arlington; nor does Volunteer Arlington sponsor or endorse any third-party web site. Legal Notices
2100 Washington Blvd
3rd Floor
Arlington, Virginia 22204
Tel: 703-228-1760
Fax: 703-228-1013
Email: email@example.com
An affiliate of


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New subscription
Renew my subscription
Give a gift
Pay my bill
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Active within 559 Days
Hi! My name is Buffy
I am Domestic Longhair from Charlotte, MI
Nicknames: Drama Queen, Buffroo
Age: 15 years old
Gender: F
Coat: long haired
Education: Not necessarily proud or spectacular, but they always remember my "faceplant" on the edge of the mattress while trying to run and jump up on the bed!
My favorite tricks and treats are: When you're beautiful you don't have to do tricks! and Tuna juice!
Where I hang out: The end of our bed, all day.
My favorite grubs: Meow Mix!
My pet peeves: My feline housemate, Danny! He's mean!
What I love about my owners: "She gives great Massages!"
My cat hobbies: Playing with my "little pink mouse".
Pet motto: "You can never be too cute or fluffy!"
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Fate! Mom adopted me and my brother when we were only four weeks old. They told her we were nine weeks, but she knew better. She had to make an unplanned excersise stop at a store where they had us in a cage. She had no intentions of getting kittens, since she was alone at the time and couldn't manage two kittens by herself, she waited for her husband to return from an all day trip(fretting the whole time someone wrong would get us,or worse just one!). They drove 80 miles round trip to bring us to our forever home. It was just four months later that their eight year old cat, Jordy, unexpectedly succumbed to kidney disease. Fate brought her to me and Jesse so she wouldn't be without a cat when she needed one most.
I've had 4669 friends visit me.
I'm the 32,130th member on CatChannel.com.
749 friends have voted for me since I joined Club Cat!
Come visit me, ana bonana and haley & april and the 5 angels.
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San Antonio Office Contact Information
615 E. Houston Street, Suite 207
San Antonio Staff
Daniel Rodriguez
Aerospace & Defense, Automotive & Ground Transportation, Education, Energy Services, Industrial Equipment & Supplies, Manufacturing Industries and Marine Technology.
Michael Rosales
Environmental Technologies, General Services, Health Technologies, Textiles, Apparel & Sporting Goods, Travel & Tourism.
Oscar Magaña
Agribusiness, Consumer Goods & Home Furnishings, Food Processing & Packaging, Information Technology & Communication, Architecture & Engineering, Construction, Building, & Heavy Equipment, Publishing, Franchising, Media & Entertainment, Safety & Security, Used & Reconditioned Equipment.
Trade Information Center
1-800-USA-TRADE (1-800-872-8723). The Trade Information Center works in conjunction with your local office. For immediate export assistance or for answers to your technical questions on exporting, call M-F 8:30am - 6:00 pm Eastern time.


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A meat recall announced on Feb. 8, 2014 affects an entire year's worth of beef produced by Rancho Feeding Corporation. The meat was processed at the company's slaughterhouse between Jan. 1, 2013 and Jan. 7, 2014. It was distributed to retail establishments and distribution centers in California, Florida, Illinois and Texas.
The company is based out of Petaluma in Northern California. It is recalling a whopping 8.7 million pounds of beef products because some of the cattle were not properly inspected. This is a mandatory recall.
According to a report by the United States Department of Agriculture (USDA) Food Safety and Inspection Service (FSIS), which has classified the situation as a high health risk:
Rancho Feeding Corporation, a Petaluma, Calif. establishment, is recalling approximately 8,742,700 pounds, because it processed diseased and unsound animals and carried out these activities without the benefit or full benefit of federal inspection.
Thus, the products are adulterated, because they are unsound, unwholesome or otherwise are unfit for human food and must be removed from commerce, the U.S. Department of Agriculture's Food Safety and Inspection Service (FSIS) announced today.
The FSIS further stated that they have received no complaints of illness related to the beef included in the massive meat recall. However, this is classified as a Class I Recall.
According to the USDA, a Class I Recall meets the following qualification:
This is a health hazard situation where there is a reasonable probability that the use of the product will cause serious, adverse health consequences or death." Those concerned about illness from eating tainted product from the meat recall were advised to consult a health care provider.
The list of impacted meat products involved in the recall, as posted on the USDA website, includes the following items:
- Beef Carcasses" (wholesale and custom sales only)
- 2 per box "Beef (Market) Heads" (retail only)
- 4-gallons per box "Beef Blood" (wholesale only)
- 20-lb. boxes of "Beef Oxtail"
- 30-lb. boxes of "Beef Cheeks"
- 30-lb. boxes of " Beef Lips"
- 30-lb. boxes of "Beef Omasum"
- 30-lb. boxes of "Beef Tripas"
- 30-lb. boxes of "Mountain Oysters"
- 30-lb. boxes of "Sweet Breads"
- 30- and 60-lb. boxes of "Beef Liver"
- 30- and 60-lb. boxes of "Beef Tripe"
- 30- and 60-lb. boxes of "Beef Tongue"
- 30- and 60-lb. boxes of "Veal Cuts"
- 40-lb. boxes of "Veal Bones"
- 50-lb. boxes of "Beef Feet"
- 50-lb. boxes of "Beef Hearts"
- 60-lb. boxes of "Veal Trim"


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Nov 5, 2012 8:30 AM
You thought you were prepared for the new arrival and honestly believed you had it all figured out. You were going to deliver naturally, breastfeed, and ban all pacifiers from ever entering the house. You were doing so well until you brought the bundle home... [More]
Nov 4, 2012 10:22 AM
Face it: one of the perks of having kids is being able to subject them to looking ridiculous pretty much any time you need a laugh - especially in that magical window of time when they can't walk away or talk back. The Mustachifier ($12)... [More]
Nov 1, 2012 10:30 AM
Teddy bears and lambkins are so predictable! Gift the little one in your life a Snuggly Rosita Monster ($45). This cuddly toy is the perfect size for young hands and stitched together from re-purposed cashmere sweaters. It's soft, eco-friendly, and destined to become a best... [More]
Nov 1, 2012 9:51 AM
We like the fact that designer Iris Savir created the Organic Felt Animals ($80-96) to be played with. A novel idea these days. The bunny, giraffe, elephant, rhino, and zebra aren't for shelf-sitting. Gift one to a kid who will drag it along everywhere, "feed"... [More]
Nov 1, 2012 8:55 AM
The adorable Animal Crayons ($8, set of 6) elicit an "aww!" all by themselves, but add in the fact that they're packaged in a little school bus, and they're easily the sweetest crayons in the art box. The thick bodies are just the right size... [More]
If you've got a product or service that you'd like to promote on Outblush, click here to find out about our advertising opportunities.
Oct 31, 2012 8:15 AM
You're not a fan of hipsters, skinny jeans on men, ironic facial hair, or baristas on a mission to save the community. But you're not about to pass up the opportunity to dress your kiddo like one of the above, especially considering how sweet these... [More]
Oct 30, 2012 10:45 AM
The amount of charm packed into the Wooden Gumball Machine ($59) probably surpasses the number of little wooden beads. We love back-to-basics toys. Kids get to use their imaginations when they play, and parents don't have to stare at garish plastic monstrosities all day long!... [More]
Oct 28, 2012 9:51 AM
French designer Marie de Crecy teamed up with writer Sandra Lanilis to create Books to Illustrate, a set of simply bound books with quirky stories ready for imaginative illustrations. We're currently coveting Where Do Monsters and Spiders Hide When They're Afraid? ($14), and though we'd... [More]
Oct 26, 2012 9:10 AM
We love our children more than life itself, but each and every child should come with an instruction manual and a Time Out Bench ($30).... [More]
Oct 25, 2012 9:45 AM
When a kid is learning to use utensils to eat soft foods like yogurt, mild salsa, and hummus, the whole hand-eye-spoon-coordination thing can be hard. That's why we're in capital-L Love with these Benders Utensils ($6). The sturdy BPA-, PVC-, and phthalate-free spoon and spork... [More]
Oct 25, 2012 8:45 AM
You're usually not the kind of person to spend so much money on a pair of shoes that will get worn, at best, for six months. But you are all for spending the money if it helps your kid complete a tedious task solo. These... [More]
Oct 23, 2012 8:45 AM
We all know what it's like to get into a car after it's been baking in the sun for even just thirty minutes. As soon as you sit in that seat, your ass burns faster than it would if you had just swandived straight into... [More]
Oct 22, 2012 10:16 AM
There are plenty of natural hair care products out there aimed at parents who want the best for their kiddos. But we're going to go out on a limb and say none of them are as hip as Hip Peas! The earth-friendly company creates awesome... [More]
Oct 18, 2012 10:45 AM
He drools, he farts, he poops when he pleases, he chases wild animals (read: the family cat) instinctively, and babbles incoherently as if you are somehow supposed to understand him. Might as well take Halloween as an opportunity to dress him like the caveman he... [More]
Oct 18, 2012 10:35 AM
We're frankly jealous of this Design Your Own Superhero Cape ($40) kit. Someone bought it for one of our nephews, and we probably would have stolen it, except that it's sized for eight-year-olds. What's the kid going to do with it anyway? Run around pretending... [More]
Oct 17, 2012 10:35 AM
Sure, all the latest plastic baby toys are laden with annoying sounds and lights bells and whistles, but if there's anything a mom values above everything else, it's the sweet sound of quiet. We love pursing Hape's line of brightly colored, wood-based toys for baby... [More]
Oct 17, 2012 10:20 AM
You don't have to use Halloween as an excuse to dress up your kiddo. The Superhero in Disguise onesie ($46) by Mini Shatsu will make her look like she has a secret superidentity any day of the year. The utility belt, mask, and faux costume... [More]
Oct 17, 2012 8:05 AM
Junior a little messy during mealtime? Give him something else to focus on (besides flinging his grilled cheese!) with the Pop Art Placemat ($10) from Psychobaby. Easily personalized, these would make awesome gifts for the toddler superheroes in your life.... [More]
Oct 16, 2012 10:07 AM
Pregnancy is hard. Your body aches all the time, you have to pee every 7 minutes, and you've got a little soccer player booting you in the ribs like he's the next Pelé. The Sleep Softly Maternity Tee ($24) by discobelly ought to help you... [More]
Oct 16, 2012 8:50 AM
Forget music lessons and watercolors. We don't want our kids to grow up dreaming of being artists. If we want them to move out of the house before they're thirty, we know where their real future lies: with the Teamsters. That's why we're starting them... [More]
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Each April since 1981, OVC has helped lead communities throughout the country in their observances of National Crime Victims' Rights Week (NCVRW). Rallies, candlelight vigils, and a host of commemorative activities are held each year to promote victims' rights and to honor crime victims and those who advocate on their behalf.
Links:[1] http://www.ovc.gov/ncvrw/welcome.html
[2] http://www.nsvrc.org/states-territories/national