scholarly journals Image De-Blurring Based on Constraint Conditional Model

2020 ◽  
Vol 9 (3) ◽  
pp. 995-1000
Keyword(s):  
The Other ◽  
Original Image ◽  
Conditional Model ◽  
Proposed Model ◽  
Image Capturing ◽  
Degraded Image ◽  
Physical Limitations ◽  
Blur Kernel ◽  
The Given ◽  
State Of Art

Image capturing is more vulnerable to the various physical limitations such as defocus, low lighting and camera shaking; this makes the image blurry and noisy. Moreover De-blurring is the process to recover the original image from the given degraded image. De-blurring technique uses the estimated blur kernel for achieving the optimal restored image with the sharp features, however the accuracy has been one of the major concern , hence in this paper we use Constrained Conditional model (CCM) for restoring the image. Moreover, here two different methods are integrated i.e. conditional model and convergence operator, these two combined learns the model and efficiently and provides the better results. In order to evaluate the proposed model, Levin dataset is used by considering the two eminent model metric i.e. PSNR and SSIM and CCM based model outperforms the other state-of-art technique.

scholarly journals Chatbot Using Dialogflow and Web Services

2019 ◽  
Vol 9 (1S) ◽  
pp. 253-260
Keyword(s):  
Artificial Intelligence ◽  
The Other ◽  
Great Satisfaction ◽  
User Input ◽  
User Query ◽  
Proposed Model ◽  
Human Effort ◽  
Chat Bot ◽  
The Given ◽  
Artificial Intelligence Systems

The Chatbots are helpful in making human effort minimal for less-complex tasks like answering messages and also to provide great satisfaction to the clients round the clock. This is considered a better initiative as the business organizers don't have to worry about reaching to customers. There are many proposed models to get the desired output most of these are helpful if the user input is always from the given set of words the software is designed for, but unfortunately, this is not the scenario always as the user shall have a different way to message. This and the other models are being replaced by the Artificial Intelligence systems which have the capability to identify the structure and wordsfrom a given context and use it predict the best possible outcomes. In our proposed model, we are using the same and it is handled by Dialogflow, which helps in achieving an end-to-end bot without the user being worried about the algorithm that should be used to train this bot. Using a configured server with Dialog flow helps in handling various requests. Using technologies like Dialog flow, Node.js in this proposed model, an effort is made to make better bots with better functionality and continuation in the conversation. The system here is proposed to analyse the user query and respond back to the user with an appropriate answer. Our model is developed to help user in searching restaurants around him with different cuisines, categories else to see the list of top reviews of a hotel and it’s cuisines. This chat-bot since being location dependent, it shall be using the location of the user to fetch real-time results for the queries put forward by the user.

The acquisition of Hungarian recursive PPs

2018 ◽  
Vol 4 (1) ◽  
pp. 105-123
Author(s):  
Ágnes Langó-Tóth
Keyword(s):  
Language Acquisition ◽  
Functional Element ◽  
The Other ◽  
Functional Head ◽  
Experiment Subject ◽  
The Given

Abstract In this study an experiment is presented on how Hungarian children interpret two word orders of recursive PPs (subject-PP-verb and PP-subject-verb order). According to the research of Roeper (2011) and Hollebrandse and Roeper (2014), children tend to give conjunctive interpretation to multiple embedded sentences at the beginning of language acquisition. This interpretation later turns into an adult-like, recursive interpretation. Our aim is to discover (i) whether Hungarian children start with conjunction as well, and whether (ii) the apparently more salient functional head lévő appearing in Hungarian recursive PPs can help them to acquire the correct, recursive interpretation early. We also want to find out whether (iii) the word orders in recursive PPs have an influence on the acquisition of children. In this paper two experiments are presented conducted with 6 and 8-year-olds and adults, in which the participants were asked to choose between two pictures. One of the pictures depicted recursive and the other one depicted conjunctive interpretation of the given sentence. In the first experiment subject-PP-verb order was tested, but in the second one sentences were tested with PP-subject-verb order. We will claim that lévő, which is (arguably) a more salient Hungarian functional element than -i, does not help children to acquire the embedded reading of recursive sentences, because both of them are overt functional heads. However, the two types of word orders affect the acquisition of recursive PPs. PP-subject-verb order is easier to compute because the order of the elements in the sentences and the order of the elements in the pictures matches.

Growth Characteristics of Activated Sludges Acclimated to para-Nitrophenol in Batch and Continuous Modes

1994 ◽  
Vol 29 (7) ◽  
pp. 327-333
Author(s):  
Y. Matsui ◽  
F. Yamaguchi ◽  
Y. Suwa ◽  
Y. Urushigawa
Keyword(s):  
Growth Characteristics ◽  
The Other ◽  
Operational Mode ◽  
Continuous Mode ◽  
Relative Resistance ◽  
Batch Mode ◽  
The Given ◽  
Operational Modes ◽  
Very High ◽  
Sensitive Group

Activated sludges were acclimated to p-nitrophenol (PNP) in two operational modes, a batch and a continuous. The operational mode of the PNP acclimation of activated sludges strongly affected the physiological characteristics of predominant microorganisms responsible for PNP degradation. Predominant PNP degraders in the sludge in batch mode (Sludge B) had lower PNP affinity and were relatively insensitive to PNP concentration. Those of the sludge in continuous mode (Sludge C), on the other hand, had very high PNP affinity and were sensitive to PNP. MPN enumeration of PNP degraders in sludge B and C using media with different PNP concentrations (0.05, 0.2,0.5 and 2.0 mM) supported the above results. Medium with 0.2 mM of PNP did not recover PNP degraders in sludge C well, while it recovered PNP degraders in sludge B as well as the medium with 0.05 mM did. When switching from one operational mode to the other, the predominant population in sludge B shifted to the sensitive group, but that of sludge C did not shift at the given loading of PNP, showing relative resistance to inhibitive concentration.

Giving and Promising

2018 ◽  
Author(s):  
Jean-Yves Lacoste ◽  
Oliver O’Donovan
Keyword(s):  
The Other ◽  
Face To Face ◽  
Present Experience ◽  
The World ◽  
The Given

Giving and promise must be thought together. Being-in-the world entails being-with the other, who is both “given” and bearer of a gift promised. But any disclosure may be understood as a gift; it is not anthropomorphic to speak of “self-giving” with a wider reference than person-to-person disclosure. Which implies that no act of giving can exhaust itself in its gift. Present experience never brings closure to self-revealing. Yet giving is crystallized into “the given,” the closure of gift. “The given” is what it is, needing no gift-event to reveal it. But the given, too, is precarious, and can be destabilized when giving brings us face to face with something unfamiliar. Nothing appears without a promise of further appearances, and God himself can never be “given.”

A Hindi Image Caption Generation Framework Using Deep Learning

2021 ◽  
Vol 20 (2) ◽  
pp. 1-19
Author(s):  
Santosh Kumar Mishra ◽  
Rijul Dhir ◽  
Sriparna Saha ◽  
Pushpak Bhattacharyya
Keyword(s):  
Computer Vision ◽  
Natural Language Processing ◽  
Natural Language ◽  
Language Processing ◽  
English Language ◽  
Image Captioning ◽  
Textual Description ◽  
Proposed Model ◽  
Hindi Language ◽  
The Given

Image captioning is the process of generating a textual description of an image that aims to describe the salient parts of the given image. It is an important problem, as it involves computer vision and natural language processing, where computer vision is used for understanding images, and natural language processing is used for language modeling. A lot of works have been done for image captioning for the English language. In this article, we have developed a model for image captioning in the Hindi language. Hindi is the official language of India, and it is the fourth most spoken language in the world, spoken in India and South Asia. To the best of our knowledge, this is the first attempt to generate image captions in the Hindi language. A dataset is manually created by translating well known MSCOCO dataset from English to Hindi. Finally, different types of attention-based architectures are developed for image captioning in the Hindi language. These attention mechanisms are new for the Hindi language, as those have never been used for the Hindi language. The obtained results of the proposed model are compared with several baselines in terms of BLEU scores, and the results show that our model performs better than others. Manual evaluation of the obtained captions in terms of adequacy and fluency also reveals the effectiveness of our proposed approach. Availability of resources : The codes of the article are available at https://github.com/santosh1821cs03/Image_Captioning_Hindi_Language ; The dataset will be made available: http://www.iitp.ac.in/∼ai-nlp-ml/resources.html .

scholarly journals Context-Aware Neural Machine Translation for Korean Honorific Expressions

Electronics ◽  
2021 ◽  
Vol 10 (13) ◽  
pp. 1589
Author(s):  
Yongkeun Hwang ◽  
Yanghoon Kim ◽  
Kyomin Jung
Keyword(s):  
Machine Translation ◽  
Deep Neural Networks ◽  
Contextual Information ◽  
Context Aware ◽  
Neural Machine Translation ◽  
Translation Quality ◽  
Sentence Level ◽  
Proposed Model ◽  
The Given ◽  
The Relationship

Neural machine translation (NMT) is one of the text generation tasks which has achieved significant improvement with the rise of deep neural networks. However, language-specific problems such as handling the translation of honorifics received little attention. In this paper, we propose a context-aware NMT to promote translation improvements of Korean honorifics. By exploiting the information such as the relationship between speakers from the surrounding sentences, our proposed model effectively manages the use of honorific expressions. Specifically, we utilize a novel encoder architecture that can represent the contextual information of the given input sentences. Furthermore, a context-aware post-editing (CAPE) technique is adopted to refine a set of inconsistent sentence-level honorific translations. To demonstrate the efficacy of the proposed method, honorific-labeled test data is required. Thus, we also design a heuristic that labels Korean sentences to distinguish between honorific and non-honorific styles. Experimental results show that our proposed method outperforms sentence-level NMT baselines both in overall translation quality and honorific translations.

Development of Advanced CNC Interpolation Algorithm With Consideration of Command and Dynamic Errors

2015 ◽  
Author(s):  
Meng-Shiun Tsai ◽  
Ying-Che Huang
Keyword(s):  
The Other ◽  
Contour Error ◽  
Interpolation Algorithm ◽  
Interpolation Scheme ◽  
Error Equation ◽  
The Past ◽  
Cnc Interpolation ◽  
Dynamic Errors ◽  
Simulation Results ◽  
The Given

In this paper, an integrated acceleration/deceleration with dynamics interpolation scheme is proposed to confine the maximum contour error at the junction of linear junction. The dynamic contour error equation is derived analytically and then it is utilized for the interpolation design. Based on the derived formulations which could predict the command and dynamic errors, the advanced interpolation design could adjust the connecting velocity of the two blocks to confine the overall contour errors under the given tolerance. Simulation results validate the proposed algorithm can achieve higher accurate trajectory as compared to the other interpolation algorithm proposed in the past.

scholarly journals Deep spatio-temporal emotion analysis of geo-tagged tweets for predicting location based communal emotion during COVID-19 Lock-down

2021 ◽  
pp. 1-14
Author(s):  
M. Amsaprabhaa ◽  
Y. Nancy Jane ◽  
H. Khanna Nehemiah
Keyword(s):  
Latent Dirichlet Allocation ◽  
Temporal Analysis ◽  
The Other ◽  
Classification Model ◽  
Grid Search ◽  
Analysis Framework ◽  
Emotion Classification ◽  
Spatio Temporal ◽  
Improved Accuracy ◽  
State Of Art

Due to the COVID-19 pandemic, countries across the globe has enforced lockdown restrictions that influence the people’s socio-economic lifecycle. The objective of this paper is to predict the communal emotion of people from different locations during the COVID-19 lockdown. The proposed work aims in developing a deep spatio-temporal analysis framework of geo-tagged tweets to predict the emotions of different topics based on location. An optimized Latent Dirichlet Allocation (LDA) approach is presented for finding the optimal hyper-parameters using grid search. A multi-class emotion classification model is then built via a Recurrent Neural Network (RNN) to predict emotions for each topic based on locations. The proposed work is experimented with the twitter streaming API dataset. The experimental results prove that the presented LDA model-using grid search along with the RNN model for emotion classification outperforms the other state of art methods with an improved accuracy of 94.6%.

AKADEMSKI VOKABULAR: DA LI SU STUDENTI (U)OPŠTE OBRAZOVANI? O POTREBI ZA UKLjUČIVANjEM AKADEMSKOG VOKABULARA U KURIKULUME ZA SRPSKI JEZIK U SREDNjOJ ŠKOLI I NA UNIVERZITETU

Lipar ◽  
2020 ◽  
Vol XXI (73) ◽  
pp. 203-216
Author(s):  
Jovana Milovanović ◽  
Keyword(s):  
Academic Language ◽  
School Curriculum ◽  
The Other ◽  
Academic Vocabulary ◽  
High School Curriculum ◽  
Language Competence ◽  
Entrance Exams ◽  
University Level ◽  
Comparison Of The Results ◽  
The Given

This article discusses reception and production of academic vocabulary among native speakers of Serbian language. Academic vocabulary is one of the key elements of academic language competence, and a modest lexicon and underdeveloped academic language competence can cause problems in both comprehension and production. In this research, we used a vocabulary test consisting of 12 items taken from general culture entrance exams used at the Faculty of Philosophy, University of Belgrade. The participants are BA students of French language at the Faculty of Philology, University of Belgrade, years 1-4. The participants were instructed to provide a synonym or a definition for each item, as well as a sentence containing the given word. The aim of this research is to highlight issues in comprehension of academic vocabulary and establish the influence of factors such as word etymology or university level on the success of the participants. We analysed the results and classified them in three categories: correct, incorrect and unanswered. The majority of participants successfully identified just half of the given words (in order of success: poliglota 95,76%, bestseler 92,37%, pacifista 66,10%, suveren 58,47%, prototip 57,63%, elokventan 56,78%). The success level for the other half of the items from the test was below 50% (in order of success: erudita 49,15%, hipokrizija 39,83%, nepotizam 22,03%, skrupulozan 18,64%, šprahfeler 10,17%, eksproprijacija 8,47%). The influence of etymology was analysed through a comparison of the results for six items of French/Latin origin with the results for the other six items which did not originate from Romance languages. This analysis shows that the participants had similar results in both groups of items, with three words from each group having above 50% of correct answers (suveren, elokventan, pacifista; poliglota, bestseler, prototip). Lastly, we examined success levels from year 1, year 2, year 3 and year 4 students and determined that the median of correct answers for each year does vary, but that there is no strong linear progression (median year 1=5, year 2=6, year 3=7, year 4=6). The results indicate a lack of knowledge of academic vocabulary and difficulties in identifying and manipulating this type of lexis. We believe it is necessary to integrate academic language skills, including academic vocabulary, in high school curriculum and introduce Serbian language as a subject at university level.

A Model of Secure Functioning of Computer Systems

2021 ◽  
Vol 12 (3) ◽  
pp. 150-156
Author(s):  
A. V. Galatenko ◽  
◽  
V. A. Kuzovikhina ◽  
Keyword(s):  
Lower Bound ◽  
Computer System ◽  
Finite Automaton ◽  
Nonnegative Integer ◽  
The Other ◽  
Shannon Function ◽  
Security Breaches ◽  
System Functioning ◽  
The Cost ◽  
The Given

We propose an automata model of computer system security. A system is represented by a finite automaton with states partitioned into two subsets: "secure" and "insecure". System functioning is secure if the number of consecutive insecure states is not greater than some nonnegative integer k. This definition allows one to formally reflect responsiveness to security breaches. The number of all input sequences that preserve security for the given value of k is referred to as a k-secure language. We prove that if a language is k-secure for some natural and automaton V, then it is also k-secure for any 0 < k < k and some automaton V = V (k). Reduction of the value of k is performed at the cost of amplification of the number of states. On the other hand, for any non-negative integer k there exists a k-secure language that is not k"-secure for any natural k" > k. The problem of reconstruction of a k-secure language using a conditional experiment is split into two subcases. If the cardinality of an input alphabet is bound by some constant, then the order of Shannon function of experiment complexity is the same for al k; otherwise there emerges a lower bound of the order nk.

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