scholarly journals Thinking Globally, Acting Locally: Distantly Supervised Global-to-Local Knowledge Selection for Background Based Conversation

2020 ◽  
Vol 34 (05) ◽  
pp. 8697-8704
Author(s):  
Pengjie Ren ◽  
Zhumin Chen ◽  
Christof Monz ◽  
Jun Ma ◽  
Maarten De Rijke
Keyword(s):  
Local Knowledge ◽  
State Of The Art ◽  
Background Knowledge ◽  
Global Perspective ◽  
Conversational Context ◽  
Human Evaluation ◽  
Text Fragment ◽  
Selection For ◽  
High Degree ◽  
Transition Vector

Background Based Conversation (BBCs) have been introduced to help conversational systems avoid generating overly generic responses. In a BBC, the conversation is grounded in a knowledge source. A key challenge in BBCs is Knowledge Selection (KS): given a conversational context, try to find the appropriate background knowledge (a text fragment containing related facts or comments, etc.) based on which to generate the next response. Previous work addresses KS by employing attention and/or pointer mechanisms. These mechanisms use a local perspective, i.e., they select a token at a time based solely on the current decoding state. We argue for the adoption of a global perspective, i.e., pre-selecting some text fragments from the background knowledge that could help determine the topic of the next response. We enhance KS in BBCs by introducing a Global-to-Local Knowledge Selection (GLKS) mechanism. Given a conversational context and background knowledge, we first learn a topic transition vector to encode the most likely text fragments to be used in the next response, which is then used to guide the local KS at each decoding timestamp. In order to effectively learn the topic transition vector, we propose a distantly supervised learning schema. Experimental results show that the GLKS model significantly outperforms state-of-the-art methods in terms of both automatic and human evaluation. More importantly, GLKS achieves this without requiring any extra annotations, which demonstrates its high degree of scalability.

A Statistical Predictive Model to Prioritize Site Selection for Stress Corrosion Cracking Direct Assessment

2006 ◽  
Author(s):  
Anthony Merle ◽  
P. F. Ehlers
Keyword(s):  
Stress Corrosion ◽  
Stress Corrosion Cracking ◽  
Environmental Parameters ◽  
Predictive Modelling ◽  
Corrosion Cracking ◽  
Direct Assessment ◽  
Degree Of Certainty ◽  
Regression Techniques ◽  
Selection For ◽  
High Degree

Pipeline stress-corrosion cracking (SCC) is an ongoing integrity concern for pipeline operators. A number of different strategies are currently employed to locate and mitigate SCC. Ultrasonic in-line inspection tools have proven capable of locating SCC, but reliability of these tools in gas pipelines remains in question. Rotating hydrotest programs are effectively employed by some companies but may not provide useful information as to the location of SCC along the pipeline. NACE Standard RP0204-2004 (SCC Direct Assessment Methodology) outlines factors to consider and methodologies to employ to predict where SCC is likely to occur, but even this document acknowledges that there are no well-established methods for predicting the presence of SCC with a high degree of certainty. Predictive modelling attempts to date have focused on establishing quantitative relationships between environmental factors and SCC formation and growth; these models have achieved varying degrees of success. A statistical approach to SCC predictive modelling has been developed. In contrast to previous models that attempted to determine direct correlations between environmental parameters and SCC, the new model statistically analyzed data from dig sites where SCC was and was not found. Regression techniques were used to create a multi-variable logistic regression model. The model was applied to the entire pipeline and verification digs were performed. The dig results indicated that the model was able to predict locations of SCC along the pipeline.

scholarly journals Peritoneal Carcinomatosis: Current State of the Art and Schools of Thought

2021 ◽  
Vol 11 (1) ◽  
pp. 85-91
Author(s):  
Sh. Kh. Gantsev ◽  
M. V. Zabelin ◽  
K. Sh. Gantsev ◽  
A. A. Izmailov ◽  
Sh. R. Kzyrgalin
Keyword(s):  
Peritoneal Carcinomatosis ◽  
State Of The Art ◽  
Global Perspective ◽  
Basic Principles ◽  
Global Challenge ◽  
Current State ◽  
Emerging Therapies ◽  
The World ◽  
The Usa ◽  
Scientific Questions

Peritoneal carcinomatosis (PC) is a global challenge of modern oncology representing the most unfavourable scenario in diverse-locality tumourisation. Despite certain attention by the oncological community, the management of PC patients is currently palliative, which weakly promotes research into the basic principles of this morbidity. This literature review attempts to comprehensively cover the PC problematic from a global perspective and presents a key evidence on the world schools of thought in this area. Briefly taking, peritoneal carcinomatosis is viewed today as a local process in the conventional implantation theory, which imposes a locoregional character on all current or emerging therapies, such as cytoreductive surgery and hyperthermic intraperitoneal chemotherapy. Their inadequate efficacy is largely due to pronounced gaps in our understanding of PC logistics and signalling. PSOGI is a key organisation for centralising the specialty effort in peritoneal carcinomatosis. Despite its global geography and approach to PC discussion, a multitude of scientific questions remain unanswered impeding the establishment of novel effective therapies. The seven countries that nurtured distinguished schools of thought in PC studies are the USA, UK, Japan, China, Italy, France and Germany. Taking peritoneal carcinomatosis in a global perspective, an insufficient attention to its problematic in Russia should be addressed. The founding and fostering of national PC institutions will benefit cancer patients and progress in oncological science.

scholarly journals Reverse Logistic Strategy for the Management of Tire Waste in Mexico and Russia: Review and Conceptual Model

2018 ◽  
Vol 10 (10) ◽  
pp. 3398 ◽  
Author(s):  
Maria-Lizbeth Uriarte-Miranda ◽  
Santiago-Omar Caballero-Morales ◽  
Jose-Luis Martinez-Flores ◽  
Patricia Cano-Olivos ◽  
Anastasia-Alexandrovna Akulova
Keyword(s):  
European Union ◽  
Reverse Logistics ◽  
State Of The Art ◽  
The European Union ◽  
Public Companies ◽  
Reverse Logistic ◽  
Private And Public ◽  
Key Aspects ◽  
Social Entities ◽  
High Degree

Management of tire waste is an important aspect of sustainable development due to its environmental, economical and social impacts. Key aspects of Reverse Logistics (RL) and Green Logistics (GL), such as recycling, re-manufacturing and reusable packaging, can improve the management of tire waste and support sustainability. Although these processes have been performed with a high degree of efficiency in other countries such as Japan, Spain and Germany, the application in Mexico and Russia has faced setbacks due to the absence of guidelines regarding legislation, RL processes, and social responsibility. Within this context, the present work aims to develop an integrated RL model to improve on these processes by considering the RL models from Russia and Mexico. For this, a review focused on RL in Mexico, Russia, Japan and the European Union (EU) was performed. Hence, the integrated model considers regulations and policies performed in each country to assign responsibilities regarding RL processes for the management of tire waste. As discussed, the implementation of efficient RL processes for the management of tire waste depends of different social entities such as the user (customer), private and public companies, and manufacturing and state-of-the-art approaches to transform waste into different products (diversification) to consider the RL scheme as a total economic system.

scholarly journals The Force Is Strong with This One (but Not That One): What Makes a Successful Star Wars Video Game Adaptation?

Arts ◽  
2020 ◽  
Vol 9 (4) ◽  
pp. 131
Author(s):  
Matthew Barr
Keyword(s):  
Video Game ◽  
State Of The Art ◽  
Star Wars ◽  
George Lucas ◽  
John Williams ◽  
Potential Factors ◽  
Old Republic ◽  
Space Opera ◽  
High Degree

The Star Wars films have probably spawned more video game adaptations than any other franchise. From the 1982 release of The Empire Strikes Back on the Atari 2600 to 2019’s Jedi: Fallen Order, around one hundred officially licensed Star Wars games have been published to date. Inevitably, the quality of these adaptations has varied, ranging from timeless classics such as Star Wars: Knights of the Old Republic, to such lamentable cash grabs as the Attack of the Clones movie tie-in. But what makes certain ludic adaptations of George Lucas’ space opera more successful than others? To answer this question, the critical response to some of the best-reviewed Star Wars games is analysed here, revealing a number of potential factors to consider, including the audio-visual quality of the games, the attendant story, and aspects of the gameplay. The tension between what constitutes a good game and what makes for a good Star Wars adaptation is also discussed. It is concluded that, while many well-received adaptations share certain characteristics—such as John Williams’ iconic score, a high degree of visual fidelity, and certain mythic story elements—the very best Star Wars games are those which advance the state of the art in video games, while simultaneously evoking something of Lucas’ cinematic saga.

Channel Selection for Optimal EEG Measurement in Motor Imagery-Based Brain-Computer Interfaces

2020 ◽  
pp. 2150003
Author(s):  
Pasquale Arpaia ◽  
Francesco Donnarumma ◽  
Antonio Esposito ◽  
Marco Parvis
Keyword(s):  
Motor Imagery ◽  
Classification Accuracy ◽  
State Of The Art ◽  
Binary Classification ◽  
Brain Computer Interfaces ◽  
Eeg Signals ◽  
Non Invasive ◽  
Computer Interfaces ◽  
Selection For ◽  
A Performance

A method for selecting electroencephalographic (EEG) signals in motor imagery-based brain-computer interfaces (MI-BCI) is proposed for enhancing the online interoperability and portability of BCI systems, as well as user comfort. The attempt is also to reduce variability and noise of MI-BCI, which could be affected by a large number of EEG channels. The relation between selected channels and MI-BCI performance is therefore analyzed. The proposed method is able to select acquisition channels common to all subjects, while achieving a performance compatible with the use of all the channels. Results are reported with reference to a standard benchmark dataset, the BCI competition IV dataset 2a. They prove that a performance compatible with the best state-of-the-art approaches can be achieved, while adopting a significantly smaller number of channels, both in two and in four tasks classification. In particular, classification accuracy is about 77–83% in binary classification with down to 6 EEG channels, and above 60% for the four-classes case when 10 channels are employed. This gives a contribution in optimizing the EEG measurement while developing non-invasive and wearable MI-based brain-computer interfaces.

scholarly journals Automated Multi-Sensor 3D Reconstruction for the Web

2019 ◽  
Vol 8 (5) ◽  
pp. 221 ◽  
Author(s):  
Arttu Julin ◽  
Kaisa Jaalama ◽  
Juho-Pekka Virtanen ◽  
Mikko Maksimainen ◽  
Matti Kurkela ◽  
...  
Keyword(s):  
Laser Scanning ◽  
Production Efficiency ◽  
State Of The Art ◽  
Real Life ◽  
3D Models ◽  
Life Project ◽  
Close Range ◽  
High Degree ◽  
The Web ◽  
3D Content

The Internet has become a major dissemination and sharing platform for 3D content. The utilization of 3D measurement methods can drastically increase the production efficiency of 3D content in an increasing number of use cases where 3D documentation of real-life objects or environments is required. We demonstrated a developed, highly automated and integrated content creation process of providing reality-based photorealistic 3D models for the web. Close-range photogrammetry, terrestrial laser scanning (TLS) and their combination are compared using available state-of-the-art tools in a real-life project setting with real-life limitations. Integrating photogrammetry and TLS is a good compromise for both geometric and texture quality. Compared to approaches using only photogrammetry or TLS, it is slower and more resource-heavy but combines complementary advantages of each method, such as direct scale determination from TLS or superior image quality typically used in photogrammetry. The integration is not only beneficial, but clearly productionally possible using available state-of-the-art tools that have become increasingly available also for non-expert users. Despite the high degree of automation, some manual editing steps are still required in practice to achieve satisfactory results in terms of adequate visual quality. This is mainly due to the current limitations of WebGL technology.

scholarly journals Improving Semantic Similarity with Cross-Lingual Resources: A Study in Bangla—A Low Resourced Language

Informatics ◽  
2019 ◽  
Vol 6 (2) ◽  
pp. 19 ◽  
Author(s):  
Rajat Pandit ◽  
Saptarshi Sengupta ◽  
Sudip Kumar Naskar ◽  
Niladri Sekhar Dash ◽  
Mohini Mohan Sardar
Keyword(s):  
Semantic Similarity ◽  
Language Processing ◽  
State Of The Art ◽  
Human Beings ◽  
Human Evaluation ◽  
Evaluation Scores ◽  
Similarity Calculation ◽  
Marked Enhancement ◽  
Cross Lingual ◽  
Standing Problem

Semantic similarity is a long-standing problem in natural language processing (NLP). It is a topic of great interest as its understanding can provide a look into how human beings comprehend meaning and make associations between words. However, when this problem is looked at from the viewpoint of machine understanding, particularly for under resourced languages, it poses a different problem altogether. In this paper, semantic similarity is explored in Bangla, a less resourced language. For ameliorating the situation in such languages, the most rudimentary method (path-based) and the latest state-of-the-art method (Word2Vec) for semantic similarity calculation were augmented using cross-lingual resources in English and the results obtained are truly astonishing. In the presented paper, two semantic similarity approaches have been explored in Bangla, namely the path-based and distributional model and their cross-lingual counterparts were synthesized in light of the English WordNet and Corpora. The proposed methods were evaluated on a dataset comprising of 162 Bangla word pairs, which were annotated by five expert raters. The correlation scores obtained between the four metrics and human evaluation scores demonstrate a marked enhancement that the cross-lingual approach brings into the process of semantic similarity calculation for Bangla.

scholarly journals Learning Personalized End-to-End Goal-Oriented Dialog

2019 ◽  
Vol 33 ◽  
pp. 6794-6801 ◽  
Author(s):  
Liangchen Luo ◽  
Wenhao Huang ◽  
Qi Zeng ◽  
Zaiqing Nie ◽  
Xu Sun
Keyword(s):  
User Satisfaction ◽  
State Of The Art ◽  
User Preferences ◽  
Task Completion ◽  
Dialog Systems ◽  
Performance Improvements ◽  
Human Evaluation ◽  
Proposed Model ◽  
End To End ◽  
Qualitative Performance

Most existing works on dialog systems only consider conversation content while neglecting the personality of the user the bot is interacting with, which begets several unsolved issues. In this paper, we present a personalized end-to-end model in an attempt to leverage personalization in goal-oriented dialogs. We first introduce a PROFILE MODEL which encodes user profiles into distributed embeddings and refers to conversation history from other similar users. Then a PREFERENCE MODEL captures user preferences over knowledge base entities to handle the ambiguity in user requests. The two models are combined into the PERSONALIZED MEMN2N. Experiments show that the proposed model achieves qualitative performance improvements over state-of-the-art methods. As for human evaluation, it also outperforms other approaches in terms of task completion rate and user satisfaction.

scholarly journals Enhanced Knowledge Graph Embedding by Jointly Learning Soft Rules and Facts

Algorithms ◽  
2019 ◽  
Vol 12 (12) ◽  
pp. 265 ◽  
Author(s):  
Jindou Zhang ◽  
Jing Li
Keyword(s):  
Link Prediction ◽  
State Of The Art ◽  
Background Knowledge ◽  
Background Information ◽  
Knowledge Graph ◽  
Logical Inference ◽  
Training Algorithm ◽  
First Order ◽  
Forward Chaining ◽  
Logical Rules

Combining first order logic rules with a Knowledge Graph (KG) embedding model has recently gained increasing attention, as rules introduce rich background information. Among such studies, models equipped with soft rules, which are extracted with certain confidences, achieve state-of-the-art performance. However, the existing methods either cannot support the transitivity and composition rules or take soft rules as regularization terms to constrain derived facts, which is incapable of encoding the logical background knowledge about facts contained in soft rules. In addition, previous works performed one time logical inference over rules to generate valid groundings for modeling rules, ignoring forward chaining inference, which can further generate more valid groundings to better model rules. To these ends, this paper proposes Soft Logical rules enhanced Embedding (SoLE), a novel KG embedding model equipped with a joint training algorithm over soft rules and KG facts to inject the logical background knowledge of rules into embeddings, as well as forward chaining inference over rules. Evaluations on Freebase and DBpedia show that SoLE not only achieves improvements of 11.6%/5.9% in Mean Reciprocal Rank (MRR) and 18.4%/15.9% in HITS@1 compared to the model on which SoLE is based, but also significantly and consistently outperforms the state-of-the-art baselines in the link prediction task.

scholarly journals Reaction of Spanish-Type Peanut Genotypes to Cylindrocladium Black Rot1

1980 ◽  
Vol 7 (2) ◽  
pp. 91-94 ◽  
Author(s):  
T. A. Coffelt
Keyword(s):  
The United States ◽  
Root Damage ◽  
Field Interaction ◽  
Arachis Hypogaea L ◽  
History Of ◽  
Genetic Mechanisms ◽  
Selection For ◽  
Successive Generations ◽  
High Degree ◽  
Root Resistance

Abstract Twelve peanut (Arachis hypogaea L.) genotypes of the Spanish botanical type and two of the Valencia botanical type were compared for reaction to the soil-borne pathogen, Cylindrocladium crotalariae (Loos) Bell & Sobers, that causes Cylindrocladium black rot (CBR) in peanuts. In Virginia, experiments were conducted in three fields (two in 1974 and one in 1975) with a history of severe CBR in previous peanut crops. The Spanish genotypes included all current cultivars grown commercially in the United States. Valencia genotypes (PI 355982 and 355987) were included as reference standards because of their known susceptibility to CBR. Differences among genotypes were significant on the bases of percent diseased plants and visual scores of root and pod damage at each field and combined across fields. Differences also were significant among fields for percent diseased plants and pod damage score and for the genotype by field interaction for percent diseased plants. All Spanish genotypes were significantly lower in percent diseased plants than the Valencia checks. Pod and root damage scores indicated that different genetic mechanisms might control pod and root resistance to CBR. A high degree of resistance is available in Spanish genotypes, but critical progeny selection for both pod and root resistance might be necessary for transfer of resistance in successive generations of a breeding program.

Sign in / Sign up

Export Citation Format

Share Document