When searching for travel opportunities to include more than visiting museums, many people think about educating themselves through more practical experiences. The option to learn at the feet of a premier wine expert/travel guide is very appealing.

With the inundation of big data, enterprises are constantly on the prowl for advanced solutions such as AI-based cognitive search platforms that significantly help cut down on time and cost

As we approach a new year?and a new decade?executives from multiple industry sectors offer predictions on the intertwined areas of CX, information governance and compliance, and automation and AI

By making the most relevant information shareable and reusable across the organization, AI-infused KM tools can bring an organization closer to the holy grail of frictionless service

Womble Bond Dickinson leverages AI-powered search to unlock knowledge and relationships to help streamline financial operations

Text analytics and natural language processing are not new concepts. Most knowledge management professionals have been grappling with these technologies for years. From the KM perspective, these technologies share the same fundamental purpose: They help get the right information to employees at the right time.

For decades, organizations have tried to unlock the collective knowledge contained within their people and systems. And the challenge is getting harder, since every year, massive amounts of additional information are created for people to share. We've reached a point at which individuals are unable consume, understand, or even find half the information that is available to them.

The consumer has spoken. Forrester Research asked 5,000 of them, "What created the biggest pain when you contacted a business for customer service?" They answered lack and consistency of agent knowledge, followed by the difficulty of finding relevant answers on company websites. So, what is driving this dissatisfaction?

James Carroll, partner and director at TetraVX, ?and Kevin Beasley, CIO at VAI, explain the importance of security and privacy safeguards in the new COVID-19 WFH world

World Bank Director, KM, Margot Brown discusses four common organizational culture challenges to knowledge sharing and how World Bank has addressed them in this clip from her presentation at KMWorld 2019.

Margaret Parker, MD, MCCM, speaks with Traci A. Wolbrink, MD, MPH

The COVID-19 pandemic has left a hole in the Gophers' budget, and AD Mark Coyle said, 'Everything is on the table.' Minnesota has the eighth biggest budget in the Big Ten, yet supports the fourth most sports.

Kevin Lewis pointed me to this article. It seemed kinda familiar, I took a look at the abstract, and I realized . . . I reviewed this article for the journal! Here was my referee report: The paper seems fine to me. I have only two minor comments, both relating to the abstract. 1. I […]

The importance to society of environmental services, provided by forest ecosystems, has significantly increased during the last few decades. A growing global concern with the deterioration of forests, beginning perhaps most noticeably in the 1980s, has led to an increasing public awareness of the environmental, cultural, economic, and social values that forests provide. Around the world, ideas of sustainable, close-to-nature, and multi-functional forestry have progressively replaced the older perception of forests as only a source for timber. The international impetus to protect and sustainably manage forests has come from global initiatives at management, conservation, and sustainable development related to all types of forests and forestry. A few of the more notable initiatives include: the 1992 Earth Summit in Rio de Janeiro, Brazil (United Nations Conference on Environment and Development, UNCED); regional follow-ups to the Earth Summit such as the Montreal Process and Helsinki Accords; the forest elements of the Convention on Biological Diversity (CBD); and the Framework Convention on Climate Change (FCCC).

This proceedings compiles papers presented by extensionists, natural resource specialists, scientists, technology transfer specialists, and others at an international conference that examined knowledge and technology transfer theories, methods, and case studies. Theory topics included adult education, applied science, extension, diffusion of innovations, social marketing, technology transfer, and others. Descriptions of methods and case studies collectively covered a wide range of current approaches that include combined digital media, engagement of users and communication specialists in the full cycle of research, integrated forestry applications, Internet-based systems, science writing, training, video conferencing, Web-based encyclopedias, and others. Innovations transferred were best management practices for water quality, forest reforestation practices, a land management system, portable timber bridges, reducedimpact logging, silvicultural practices, urban forestry, and many others. Innovation users included forest-land owners; land managers; logging industry; natural resource professionals; policymakers; public; rural and urban communities-and those in the interface between these two; and others. Technology transfer and related efforts took place in countries throughout the world.

This paper synthesizes the existing literature about traditional and local ecological knowledge relating to biodiversity in Pacific Northwest forests in order to assess what is needed to apply this knowledge to forest biodiversity conservation efforts. We address four topics: (1) views and values people have relating to biodiversity, (2) the resource use and management practices of local forest users and their effects on biodiversity, (3) methods and models for integrating traditional and local ecological knowledge into biodiversity conservation on public and private lands, and (4) challenges to applying traditional and local ecological knowledge for biodiversity conservation. We focus on the ecological knowledge of three groups who inhabit the region: American Indians, family forest owners, and commercial nontimber forest product (NTFP) harvesters.

Indigenous populations are projected to face disproportionate impacts as a result of climate change in comparison to nonindigenous populations. For this reason, many American Indian and Alaska Native tribes are identifying and implementing culturally appropriate strategies to assess climate impacts and adapt to projected changes. Traditional ecological knowledge (TEK), as the indigenous knowledge system is called, has the potential to play a central role in both indigenous and nonindigenous climate change initiatives. The detection of environmental changes, the development of strategies to adapt to these changes, and the implementation of sustainable land-management principles are all important climate action items that can be informed by TEK. Although there is a significant body of literature on traditional knowledge, this synthesis examines literature that specifically explores the relationship between TEK and climate change. The synthesis describes the potential role of TEK in climate change assessment and adaptation efforts. It also identifies some of the challenges and benefits associated with merging TEK with Western science, and reviews the way in which federal policies and administrative practices facilitate or challenge the incorporation of TEK in climate change initiatives. The synthesis highlights examples of how tribes and others are including TEK into climate research, education, and resource planning and explores strategies to incorporate TEK into climate change policy, assessments, and adaptation efforts at national, regional, and local levels.​

Sustaining the health, diversity, and productivity of national forests and grasslands is the mission of the U.S. Department of Agriculture (USDA) Forest Service.

In March 23-25, 2005, an international symposium on red alder was held at the University of Washington Center for Urban Horticulture in Seattle, WA. The symposium was entitled “Red Alder: A State of Knowledge” and brought together regional experts to critically examine the economic, ecological and social values of red alder. The primary goal of the symposium was to discuss new advances in the understanding of red alder biology and silviculture, changing market and nonmarket values, and the current regulatory climate for management of alder. This proceedings includes 14 papers based on oral presentations given at the symposium. These papers highlight some of the key findings from the history, ecology, biology, silviculture and economics sessions presented at the red alder symposium.

In March 23-25, 2005, an international symposium on red alder was held at the University of Washington Center for Urban Horticulture in Seattle, WA. The symposium was entitled “Red Alder: A State of Knowledge” and brought together regional experts to critically examine the economic, ecological and social values of red alder. The primary goal of the symposium was to discuss new advances in the understanding of red alder biology and silviculture, changing market and nonmarket values, and the current regulatory climate for management of alder. This proceedings includes 14 papers based on oral presentations given at the symposium. These papers highlight some of the key findings from the history, ecology, biology, silviculture and economics sessions presented at the red alder symposium.

Existing patient data analytics platforms fail to incorporate information that has context, is personal, and topical to patients. For a recommendation system to give a suitable response to a query or to derive meaningful insights from patient data, it should consider personal information about the patient's health history, including but not limited to their preferences, locations, and life choices that are currently applicable to them. In this review paper, we critique existing literature in this space and also discuss the various research challenges that come with designing, building, and operationalizing a personal health knowledge graph (PHKG) for patients.

It has recently been shown that word embeddings encode social biases, with a harmful impact on downstream tasks. However, to this point there has been no similar work done in the field of graph embeddings. We present the first study on social bias in knowledge graph embeddings, and propose a new metric suitable for measuring such bias. We conduct experiments on Wikidata and Freebase, and show that, as with word embeddings, harmful social biases related to professions are encoded in the embeddings with respect to gender, religion, ethnicity and nationality. For example, graph embeddings encode the information that men are more likely to be bankers, and women more likely to be homekeepers. As graph embeddings become increasingly utilized, we suggest that it is important the existence of such biases are understood and steps taken to mitigate their impact.

We design and implement the first private and anonymous decentralized crowdsourcing system ZebraLancer, and overcome two fundamental challenges of decentralizing crowdsourcing, i.e., data leakage and identity breach.

First, our outsource-then-prove methodology resolves the tension between the blockchain transparency and the data confidentiality to guarantee the basic utilities/fairness requirements of data crowdsourcing, thus ensuring: (i) a requester will not pay more than what data deserve, according to a policy announced when her task is published via the blockchain; (ii) each worker indeed gets a payment based on the policy, if he submits data to the blockchain; (iii) the above properties are realized not only without a central arbiter, but also without leaking the data to the open blockchain. Second, the transparency of blockchain allows one to infer private information about workers and requesters through their participation history. Simply enabling anonymity is seemingly attempting but will allow malicious workers to submit multiple times to reap rewards. ZebraLancer also overcomes this problem by allowing anonymous requests/submissions without sacrificing accountability. The idea behind is a subtle linkability: if a worker submits twice to a task, anyone can link the submissions, or else he stays anonymous and unlinkable across tasks. To realize this delicate linkability, we put forward a novel cryptographic concept, i.e., the common-prefix-linkable anonymous authentication. We remark the new anonymous authentication scheme might be of independent interest. Finally, we implement our protocol for a common image annotation task and deploy it in a test net of Ethereum. The experiment results show the applicability of our protocol atop the existing real-world blockchain.

Predicate constraints of general-purpose knowledge bases (KBs) like Wikidata, DBpedia and Freebase are often limited to subproperty, domain and range constraints. In this demo we showcase CounQER, a system that illustrates the alignment of counting predicates, like staffSize, and enumerating predicates, like workInstitution^{-1} . In the demonstration session, attendees can inspect these alignments, and will learn about the importance of these alignments for KB question answering and curation. CounQER is available at https://counqer.mpi-inf.mpg.de/spo.

Fashion trend forecasting is a crucial task for both academia and industry. Although some efforts have been devoted to tackling this challenging task, they only studied limited fashion elements with highly seasonal or simple patterns, which could hardly reveal the real fashion trends. Towards insightful fashion trend forecasting, this work focuses on investigating fine-grained fashion element trends for specific user groups. We first contribute a large-scale fashion trend dataset (FIT) collected from Instagram with extracted time series fashion element records and user information. Further-more, to effectively model the time series data of fashion elements with rather complex patterns, we propose a Knowledge EnhancedRecurrent Network model (KERN) which takes advantage of the capability of deep recurrent neural networks in modeling time-series data. Moreover, it leverages internal and external knowledge in fashion domain that affects the time-series patterns of fashion element trends. Such incorporation of domain knowledge further enhances the deep learning model in capturing the patterns of specific fashion elements and predicting the future trends. Extensive experiments demonstrate that the proposed KERN model can effectively capture the complicated patterns of objective fashion elements, therefore making preferable fashion trend forecast.

Making changes to a program to optimize its performance is an unscalable task that relies entirely upon human intuition and experience. In addition, companies operating at large scale are at a stage where no single individual understands the code controlling its systems, and for this reason, making changes to improve performance can become intractably difficult. In this paper, a learning system is introduced that provides AI assistance for finding recommended changes to a program. Specifically, it is shown how the evaluative feedback, delayed-reward performance programming domain can be effectively formulated via the Monte Carlo tree search (MCTS) framework. It is then shown that established methods from computational games for using learning to expedite tree-search computation can be adapted to speed up computing recommended program alterations. Estimates of expected utility from MCTS trees built for previous problems are used to learn a sampling policy that remains effective across new problems, thus demonstrating transferability of optimization knowledge. This formulation is applied to the Apache Spark distributed computing environment, and a preliminary result is observed that the time required to build a search tree for finding recommendations is reduced by up to a factor of 10x.

A method for performing relational analysis of parsed input is employed to create a visual map of knowledge information. A title, header or subject line for an input item of information is parsed into syntactical components of at least a subject component and any predicate component(s) relationally linked as topic and subtopics. A search of topics and subtopics is carried out for each parsed component. If a match is found, then the parsed component is taken as a chosen topic/subtopic label. If no match is found, then the parsed component is formatted as a new entry in the knowledge map. A translation function for translating topics and subtopics from an original language into one or more target languages is enabled by user request or indicated user preference for display on a generated visual map of knowledge information.

In general, to provide acknowledgment information by a first wireless device, the first wireless device sends repeated instances of acknowledgment information in respective first and second frame structures, in response to receipt of first information from a second wireless device. In addition, the first wireless device also sends further acknowledgment information in the second frame structure that is responsive to second information received from the second wireless device.

Administering message acknowledgements in a parallel computer that includes compute nodes, with each compute node including a processor and a messaging accelerator, includes: storing in a list, by a processor of a compute node, a message descriptor describing a message and an acknowledgement request descriptor describing a request for an acknowledgement of receipt of the message; processing, by a messaging accelerator of the compute node, the list, including transmitting, to a target compute node, the message described by the message descriptor and transmitting, to the target compute node, the request described by the acknowledgement request descriptor; receiving, by the messaging accelerator from the target compute node, an acknowledgement of receipt of the message, including notifying the processor of receipt of the acknowledgement; and removing, by the processor from the list, the message descriptor and the acknowledgment request descriptor.

Described herein are methods and systems for providing corrective maintenance using global knowledge sharing. A method to provide corrective maintenance with a CM system includes performing a query to generate a ranking of fixable causes based on factors (e.g., symptoms, configuration, test). The ranking may be determined based on a fixable cause percent match with the factors. The ranking of fixable causes may be associated with one or more solutions for each fixable cause. The ranking can be updated based on performing tests or solutions.

A system provides search results in response to a search query. The system includes a query understanding module configured to receive the search query and output a processed search query based on the search query. The search query includes one or more words and the processed search query selectively includes tags assigned to the one or more words. The system includes a fuzzy knowledge module configured to receive the processed search query, generate a set of candidate tags for selected ones of the words in the search query, and selectively validate the candidate tags. The system is configured to provide the search results to a user device based in part on the candidate tags generated and validated by the fuzzy knowledge module.

http://www.musicxray.com/xrays/1319864 Visual Shaman - Basis of Knowledge (Mastered Version)

http://www.musicxray.com/xrays/1319865 Visual Shaman - Basis of Knowledge

Because we know “how” things work sometimes we think we understand “why” these things work as they do, and that can be a problem. In this edition of Two Guys on Your Head, Dr. Art Markman and Dr. Bob Duke talk about the difference between “how” vs. “why” knowledge, and why it’s important to recognize...

Students have a lot of tugging at their energy and attention including classes, homework, jobs and activities. In this episode of KUT’s podcast “Higher Ed,” Southwestern University President Dr. Ed Burger and KUT’s Jennifer Stayton strategize on how to keep exhausted students engaged in the classroom. Ed received an email from a “Higher Ed” podcast...

Interviewing for the 2004 exit polls was the most inaccurate of any in the past five presidential elections as procedural problems compounded by the refusal of large numbers of Republican voters to be surveyed led to inflated estimates of support for John F. Kerry, according to a report released Wednesday by the research firms responsible for the flawed surveys.

Trace the path from raw data to stored knowledge. Identify various data sources and the differences between structured and unstructured data. Learn what makes data valuable before applying the DIKW model to data science.

Individuals and organizations store all kinds of data. What do we do with it all? Can we call it up as we need it? Can all that data be analyzed quickly and efficiently? Or, does it tie up storage resources and languish for years because the cost of going through it and discarding what's obsolete is too high? Discover the utility and wisdom of storing dark data.

Cardinal George Pell was aware of abuse being committed by clergy as early as the 1970s, and failed on two occasions to take action to remove paedophile priests, the Royal Commission into Institutional Responses to Child Sexual Abuse has found. Cardinal Pell said he was surprised by some of the views of the Royal Commission about his actions, and he said these views are not supported by evidence.

A small rural shire in northern Victoria that missed out on a Federal Government drought grant is rejoicing after the decision was reversed.

The ACT's top law officer says federal police should not waste their time chasing Canberrans who use small amounts of cannabis as he urges Christian Porter not to interfere with new laws.

The makers of Rexona, the deodorant identified by retailers and police as the product most misused by Queensland children, acknowledges its product was implicated in five deaths across two states through misuse but says there is "nothing that currently exists" to fix the problem.

To celebrate 40th anniversary of "Friday the 13th," take this quiz to test your knowledge of the iconic horror series.

Kevin Hart gets some sultry knowledge.

She's come a long way since "Bug-a-Boo."