Reviewerly/exHarmony huggingface dataset:
Curating Interest in Open Story Generation

Author(s): Behrooz, Morteza | Advisor(s): Jhala, Arnav | Abstract: Stories are the most valuable currency of human communication; a fact manifested in our social lives, cultural identities and prevalent forms of entertainment. Seeking the reasons behind this level of influence takes us to a journey in human cognition. Stories are also the currency of our situated understanding of events and experiences. This deep cognitive link not only speaks to the reasons behind the influence of stories, but it also outlines specific cognitive processes involved in storytelling between humans. Awareness of these cognitive processes can enable a storyteller to tell better stories, to the point that Herman’s Storytelling and the Sciences of the Mind recommends that cognitive scientists would benefit from studying narratology and narratologists would benefit from studying cognitive science. More specifically, Keith Oatley discusses how a storyteller uses a process of theory-of-mind to tell a story tailored for the perception by a listener. Thus, when evaluating generated in the field of computational story generation, we also need to focus on the cognitive processes involved in the perception of stories. Crucially, the contexts in which the generated are used, and the approaches with which they are generated, introduce a strong influence over how this evaluation can be performed. If the semantics of the domain in which the are generated are known, such as it is the case in games, then a much wider set of approaches become available to both generation and evaluation of stories. However, given the advances in story generation and potential expanded use cases of it in the future, such as interactive sociable agents, it is increasingly inefficient to assume the semantics of a domain and perform knowledge engineering before generating stories. To this end, I focus on open story generation, in which such a priori semantic models are not assumed. It is decidedly more challenging to generate through open story generation, and it is particularly more challenging to evaluate them. I believe that a focus on the perception of should be an integral part of this generation and evaluation, and I see open story generation to be the most compatible approach with future use cases. To this end, in this dissertation, I offer a consolidation of literature review and an evaluated expanded theory of perceived interestingness in stories. I then report on an evaluated approach to generating without assuming a priori semantics and using the event sequences of past interactions. Further, I will introduce an evaluation metric for the perception of that focuses on predictive inference and consequently cognitive interest, and show this measure to correlate with human judgment. Lastly, I will report on stories in the wild, the tales of two prototypes developed and evaluated in the domains of music listening and online shopping, that use story generation techniques while incorporating aspects of story interestingness theories.
A Hybrid Yoruba Noun Ontology

The primary purpose of ontological annotation in Natural Language Processing (NLP) is to make explicit the content of concepts in a domain, using a set of arbitrary tags or labels which must conform to an agreed standard. This method has contributed to the development of many European languages, but it has not been so much employed in African languages. This paper therefore develops a model to prepare the implicit knowledge of Yoruba noun as found in the literatures into their component features so as to make it both human and machine readable. The ontology development process proposed by (Schultz, 1997) which is based on the activities identified in the IEEE standard for software development is the method of ontological annotations adopted to design the hybrid model for Yoruba noun. Bamgbose (1990)’s “Fonoloji ati Girama Yoruba” , Awobuluyi (1978)’s Essentials of Yoruba Grammar and Awobuluyi (1978)’s Eko Girama Ede Yoruba  were purposively selected and the implicit knowledge of Yoruba noun in these literatures were extracted as the data for implementing the model. The informally perceived domain knowledge of Yoruba nouns were extracted randomly, using intermediate representations based on tabular and entity-relation notations. Protege 4.5, a semantic web editing tool was used to implement the hybrid model for Yoruba Nouns. The model at the final edge specifies the semantic load and properties of each of the nouns captured according to the Yoruba Language Scholars’ perspectives and classifications. The definitions in the annotation serve as backbones for machine learning, web searching and artificial intelligence agents and other (NLP) systems. The model through the annotation schema and label serves as repositories of data and make the content available for machine manipulation and semantic web reasoning. This paper recommends that more on ontological annotations for Yoruba grammar concepts are needed to foster Yoruba language engineering.Keywords: Yoruba noun, Ontological annotation, Semantic web, Natural language processing
RENCANA PENGEMBANGAN SEKOLAH

This study described the school development plan in senior high school Number 2 Kepahiang. In the study used a qualitative descriptive method. While the subjects of this study were the principal, vice principal, teachers, administrative staff, parents of students, and students. In collecting data, the method used by the researcher is interview, observation, and documentation. then, the data collected will be analyzed using qualitative descriptive techniques such as those proposed by Miles and Huberman. The results of this study indicate that in general the plans for developing schools in Kepahiang 2 Public High School have not met the standard operating procedures that have been set.
TEST WISENESS EXPLOITS BY TOEFL TEST-TAKERS: WISELY OR NAIVELY?

Test-taking strategies in TOEFL are seen as test significance since the test-takers mostly make a guess when they are faced with the absence of decision in identifying the correct option. Guessing with strategy is helpful and can manifest in score achievement. This study aimed at finding the test-taking strategies utilized by TOEFL test-takers. This study employed a descriptive case study by which the researchers access in-depth information about the test-taking strategies used by TOEFL testees. There were 23 non-English department students involved as the respondents in this study. They were asked to answer three sets of questions within different times—each set consisting of 7 questions representing each test-wise strategy. The data were then analyzed using descriptive statistics to see the score variance. The result displays that only 4 out of 23 students who can employ their test strategies—are known to be test wise; meanwhile the rest cannot—known to be test naive .
Research Guides: Text Descriptions of Images in Guides: Connect to the UO Network from Off Campus Graphic Description

This guide contains a long text description of images used in guides for accessibility purposes.
UN-Substituted Video Steganography

Steganography is the art of concealing the existence of a secret data in a non-secret digital carrier called cover media.While the image of steganography methods is extensively researched, studies on other cover files remain limited.Videos are promising research items for steganography primitives.This study presents an improved approach to video steganography.The improvement is achieved by allowing senders and receivers exchanging secret data without embedding the hidden data in the cover file as in traditional steganography methods.The method is based mainly on searching for exact matches between the secret text and the video frames RGB channel pixel values.Accordingly, a random key-dependent data is generated, and Elliptic Curve Public Key Cryptography is used.The proposed method has an unlimited embedding capacity.The results show that the improved method is secure against traditional steganography attacks since the cover file has no embedded data.Compared to other existing Steganography video systems, the proposed system shows that the method proposed is unlimited in its embedding capacity, system invisibility, and robustness.The system achieves high precision for data recovery in the receiver.The performance of the proposed method is found to be acceptable across different sizes of video files.
Privacy Preservation Using Top K Multi-Keyword Synonym Fuzzy Search Scheme

Owing to the numerous advantages arising out of storing data in the cloud such as flexible costs, improved mobility, many users are outsourcing their data to the cloud. However, it poses security challenges and rigidity issues. The cloud is often honest but curious, and hence, the need to encrypt the data arises. However, it renders the basic processes like searching difficult. Hence, there is a need to implement search algorithms on encrypted data. Plaintext fuzzy search and semantic search techniques cannot be implemented on encrypted data. To save its resources, the cloud may return partially correct results, and thus, there is a need for verification of the results returned. Access control mechanisms for multiple users should be implemented ensuring the confidentiality of unauthorized data. This paper deals with the design and analysis of a privacy-preserving top k multi-keyword synonym/similarity fuzzy search.
Does this make me look arrogant? : Examining people's perceptions of humble-bragging on social media

In this project, I examine whether a man who humblebrags online about a recent achievement or his attractive is seen as less arrogant than one who brags about these topics in a straightforward manner.
Analisis Air Limbah Pada Dapur Praktek di Politeknik Pariwisata Makassar

The importance of research is to provide a description of wastewater content in Makassar polytechnics in the kitchen, through experimental research methods, by taking wastewater samples from practical kitchens, laboratory test results provide results data obtained from chemical Oxygen Demand supply, wastewater discharged directly into sewers Will not meet the requirements for wastewater quality standards. The wastewater treatment model in polytechnics is still not feasible and is not environmentally friendly, steps need to be taken to make wastewater installations.
A Model for Simulating the Robotic Pushing of Dirt

In this paper we present a model for simulating the pushing of dirt. This is a complex problem requiring the study of the action space for the robot, a deformable model for movable earth, the interaction between the robot's pushing surface and the environment, and techniques that will allow this model to simulate such a scenario. We present our novel framework for studying this problem including the grid-based model of the environment, a simplified earth pushing robot model, and action strategies to model the pushing of dirt from one area of the environment to another.
A Scene Classification Method based on Neural Network and Computational Verb

Deep learning is often used in learning tasks for complex scene classification. However, the neural network established by deep learning has a long process from initial state to convergence. It may take more time for training the neural network for a network with more complex structure and higher recognition rate. This paper chooses a neural network learning method based on computational verbs, by selecting an appropriate computational verb rules, which dynamically changes the neural network learning step size to achieve the purpose of allowing the neural network to converge quickly. The experimental results show that the convergence speed of the neural network can be accelerated under the premise of ensuring the classification accuracy by adding computational verbs in the training process.
A Survey on Objectifies of Clustering With Different Strategies

Bunching is imperative in information examination and information mining applications.There are diverse kinds of bunches: Well-isolated groups, Center-based groups, Contiguous groups, Density-based bunches, Shared Property or Conceptual Clusters.Prescient and the clear are the two primary errands of the information mining.Grouping should be possible by the diverse no. of calculations, for example, various leveled, parceling, lattice and thickness based calculations.Progressive grouping is the availability based bunching.Apportioning is the centroid-based grouping, the estimation of k-mean is set.Thickness based bunches are characterized as a territory of higher thickness than the staying of the informational index.Network-based bunching is the quickest preparing time that regularly relies upon the extent of the matrix rather than the information.The framework based techniques utilise the single uniform network work to segment the whole issue area into cells.In this overview paper, a survey of grouping and its distinctive procedures in information mining is finished.
IoT- Supply Chain Forensics and Vulnerabilities

The Supply Chain Forensics are latest revolution to save money and reduce the Risk Supply chain management has been developed over many centuries ago from ancient civilization. The review of literature reveals that the current Digital Supply Chain industry is more connected to IoT devices which is latest revolution and future development such as gathering information and tracking goods, has evolved in to smart Supply Chain with RFID based tagging and sensor based technologies connected to IoT (Internet of Things). The use of these devices gives accurate organizational and operational outcome even though there may be unidentified procedural inconsistencies that may weakens the smooth operational procedures. This paper explains about the vulnerabilities related Supply Chain industry 4.0. Even though the application of IoT today not only tracks the goods and services but also predicts helps in future analysis for Supply Chain Industry. The entire digitalized process may help in protecting and reducing losses but there may be vulnerabilities will be identified by digital forensics. The problem really comes into focus when IoT devices are connected in unsecure Supply Chain environment. That may further concern is the fractured digital supply chains that they are relying on by modern industry experts.
Decentralized Reasoning on a Network of Aligned Ontologies with Link Keys.

Link keys are recently introduced to formalize data interlinking between data sources. They are considered as a new kind of correspondences included in ontology alignments. We propose a procedure for reasoning in a decentralized manner on a network of ontologies with alignments containing link keys. In this paper, the ontologies involved in such a network are expressed in the logic \(\mathcal {ALC}\) while the alignments can contain concept, individual and link key correspondences equipped with a loose semantics. The decentralized aspect of our procedure is based on a process of knowledge propagation through the network via correspondences. This process allows to reduce polynomially global reasoning to local reasoning.
Video Stabilization

Video Stabilization is a technology used to rectify the blurry motion of camera while capturing a video. It is an optimization technology which is proposed to eliminate the video shakiness. To achieve this image motion has to be measured by multi layer gray projection method. Multi layer gray projection method is introduced to evaluate scaling motion, translation and rotation among the target image and the reference image. Differential gray projection is used to measure the relative image translation and the resulting high-grade projection will help us to find the projection centre for the round projection and ring projection. Then find the rotational values and values obtained by scaling among the target frames and the reference frames by performing ring and circular projection. Keywords— multilayer gray projection, translation, rotation, scaling
A Case of the Chicken or the Egg: Social Media, GAD, & Substance Use

Like it or not, social media has become a constant in our lives, and it is getting harder to unplug. But, is social media actually causing harm?
Modified KDF & ERLS Regressing Filter Based Satellite Image Restoration Method

Image taken by Satellite sending are much for time dependent because for station impacts or environmental situations. These impacts present different commotion examples, for example, variable Additive White Gaussian Noise, high Salt Pepper Noise and sometime Mixed Noise. On the other hand, recovered pictures at receiving station are exceedingly highly noisy debased on grounds that picture substance are progressively weakened or intensified. Reconstruction for ideal picture rearrangement pixel sifting strategy depends to known about attributes for abnormal framework highly noisy design in a received image. In this paper work a Extended Recursive Least Square (ERLS) with complex calculation & Kalman diffeomorphism filter (KDF) is merging for picture re-fabrication from exceptionally commotion available debased pictures. Implementation for proposed method is being done by analysing and evaluation existing examples for remote channel through designing System Identification with ERLS complex calculation. At that point, these evaluated highly noisy images are dispensed with by designing Signal Enhancement with ERLS calculation. Re-established pictures are worked for further de-noising & improvement strategies. Picture is re-fabricated & further handling calculations are recreated in MATLAB condition. Presentation is assessed by methods for Human Visual System, quantitative measures as far as MSE, RMSE, and SNR & PSNR &by graphical measures. Trial results exhibit that RLS versatile calculation productively wiped out high noise from twisted pictures & conveyed an upright assessment without plenteous debasement in execution.
Block-Level Cross Diagonal Texture Matrix-Based Feature Extractor for Digital Mammogram Classification

Breast cancer holds the second rank for causing high mortality and morbidity among women and still continues to be one of the major health challenges. Early detection and diagnosis are considered to be an effective way to control this death rate. Therefore, the radiologists need a computer-aided diagnosis (CAD) system as a second opinion to reach a decision for the cancer patients. The present paper deals with a CAD system which can effectively diagnose the digital mammograms as normal, benign, and malignant. Here, a block-based cross diagonal texture matrix (CDTM) is utilized for extracting the texture features from the mammograms. Further, principal component analysis (PCA) is employed to select the most relevant features which in turn are fed to the extreme learning machine (ELM) classifier to classify the mammograms. The experimental evaluations are made on two datasets, namely, MIAS and DDSM in terms of different performance measures like accuracy, sensitivity, specificity.
Development of Learning Media “Wie spät ist es?” for German Speaking Skill of Language Class at SMAN 9 Malang

This research aimed to develop a game media called Wie spat ist es?for the students from X grade language class at SMAN 9 Malang, especially in time (Uhrzeit) material. The method used in this research were the research and development method by adapting the 4D research model. The data obtained from this research are in the form of the results of filling out an open questionnaire by media experts and material experts, as well as observations from product trials. The data were analyzed qualitatively and then explained in the form of a description. Based on data analysis, it can be concluded that the game media Wie spat ist es?is feasible to be used as a support for German course for class X students.
A reversible data hiding scheme in JPEG bitstreams using DCT coefficients truncation

A reversible data hiding scheme in JPEG compressed bitstreams is proposed, which could avoid decoding failure and file expansion by means of removing of bitstreams corresponding to high frequency coefficients and embedding of secret data in file header as comment part.We decode original JPEG images to quantified 8×8 DCT blocks, and search for a high frequency as an optimal termination point, beyond which the coefficients are set to zero.These blocks are separated into two parts so that termination point in the latter part is slightly smaller to make the whole blocks available in substitution.Then spare space is reserved to insert secret data after comment marker so that data extraction is independent of recovery in receiver.Marked images can be displayed normally such that it is difficult to distinguish deviation by human eyes.Termination point is adaptive for variation in secret size.A secret size below 500 bits produces a negligible distortion and a PSNR of approximately 50 dB, while PSNR is also mostly larger than 30 dB for a secret size up to 25000 bits.The experimental results show that the proposed technique exhibits significant advantages in computational complexity and preservation of file size for small hiding capacity, compared to previous methods. .
An Efficient and Smart Control of Solar Panel Orientation using Machine Learning

Solar panel efficiency depends on the amount of solar energy that gets converted to usable electric form when received by a solar panel. It is an important factor that decides the performance of the solar cell and is affected by the incident sunlight intensity and the temperature of the solar cell. Maximum output can be obtained from the solar panel or solar array, by directing it towards the sun’s radiation. Hence the panel orientation and the amount of light falling on it are both important factors that will maximize efficiency. Also, shadowing effect due to buildings, trees or clouds reduces the solar power efficiency. This paper presents an efficient and smart control of a solar panel, by uing machine learning to give the best tilt angle and orientation so as to obtain maximum solar power output. The simulation of solar panel model is done using Simulink and extreme machine learning algorithm is implemented in MATLAB, to obtain the optimum angles for the panel. Implementation results show that this approach of varying the panel orientation, provides an average increase of 3.98% in solar power output compared to a fixed panel.
Rocker Bogie System using RF Communication

Abstract The rocker-bogie system is a robot that can travel in rough terrain. Its mechanism helps in maintaining stability. It is a multispecialty robot that can be used for various applications. The use of Rocker-Bogie mechanism helps in maintaining the balance of the robot which is used to travel on an uneven surface, usually called as an All-Terrain Vehicular Robot. The conditions preferably needed for the robot to work are in rough conditions, surfaces such as obstacles and surfaces with uneven travel conditions. The robot consists of an RF module of 2.4 GHz frequency to communicate between the user and the robot, a mobile camera acts as a video transmission device to the user during long-distance operations. The multi-specialty system of an all-terrain vehicle is a prototype which can be implemented easily at a low cost, making it efficient to implement. The major challenge in the working of the robot is its stabilization and balance. The rocker-bogie mechanism makes the robot an All-Terrain Vehicle and a multispecialty robot which can be used for various applications. A camera is also installed on it for video surveillance. This helps the user to visualize the surroundings and operate easily from anywhere. Keywords: Actuator, frequency, robot, Rocker bogie, RF module Cite this Article N. Dinesh Kumar, A.V. Karthik Prasad, A. Harini Reddy, C. Harika. Rocker Bogie System using RF Communication. Journal of Electronic Design Technology . 2019; 10(2): 22–29p.