Reviewerly/exHarmony huggingface dataset:
Medical Image Compression Techniques with Wavelet Discrete Transformation and Entropy Encoding

Medical imaging is a presentment of human organ parts. Medical imaging is saved on a film; therefore, it needs a big saving quota. Compressing is a process to remove redundancy from a piece of information without reducing its quality. This study recommended compressed medical image with DWT (Discrete Wavelet Transform) with adaptive threshold added and entropy copying with the Run Length Encoding (RLE) coding. This study is comparing several parameters, such as compressed ratio and compressed image file size, and PSNR (Peak Signal to Noise Ratio) for analyzing the quality of reconstructive image. The study showed that the comparison of rate, compressed ratio, and PSNR tracing of Haar and Daubechies doesn’t have a significant difference. Comparison of rate, compressed ratio, and PSNR tracing on the hard and soft threshold is the rate of the sold threshold is lower than the hard threshold. The optimal outcome of this study is to use a soft threshold.
"Goal Recognition Design - Artificial intelligence techniques in surveillance problems”

This thesis focuses on Goal Recognition, an innovative and still developing field of research in Artificial Intelligence, which involves determining an agent's goal by observing its behaviour. Several real-world applications can be modelled in this context, for example, surveillance problems, operations where it is necessary to preserve user privacy, chat-boxes, and human-robot interaction. In this dissertation, we consider an environment in which an intelligent agent, the target, performs actions that can be observed by another intelligent agent, the observer (or by the environment itself). We analyze an evasive or fleeing target that moves in the environment to reach its destination, while the observer tries to find it. An example of this scenario is a surveillance drone that flies over a wide geographical area to discover a criminal who is trying to reach a hideout by car as soon as possible. In this context, the observer runs Goal Recognition algorithms that aim to discover where the target is going. In particular, the observer needs to reason about the target's strategy to obscure its goals. To support this kind of reasoning, we propose a technique to calculate a new measure, the undisclosing index, that represents the maximal length of the prefix of a path that a fleeing agent may take before its goal becomes apparent to the observer. Moreover, we present methods for the observer to reason about how the target might change its behaviour based on the resources that it has available: the target will take shorter or longer paths based on his total travel budget. We modelled the environment in which the agents move by using a connected graph. For our experiments, we construct the graphs based on data from a real web map provided by OpenStreetMap (OSM). We implemented a web application designed for this purpose. Through it, the user selects and exports an area of interest on the map, identifying the target's possible goals within that area. The web-app provides a viewable version of the graph, implements the algorithms that help the observer reason about the possible paths of the target based on its budget and visualize them. The experimental evaluation shows how the solutions proposed in this thesis are useful tools for solving Goal Recognition problems.
Final year project logbook portal

Final Year Project (FYP) Logbook Portal is a Web-based application developed for Universiti Malaysia Pahang (UMP) communities which are students, supervisors, and coordinator that involved in the Final Year Project. This system is designed to replace the manual logbook of Final Year Project. Students claimed that it is difficult using the manual logbook because they did not understand their supervisor handwriting, forgot to bring the logbook during the meeting which is resulted the progress is made not meets the supervisor’s expectation. The main purpose of this project is to develop an online logbook as a replacement of the manual logbook of Final Year Project that can help the student progressing the Final Year Project become more productive. The system convenience for coordinator, supervisor and student who take the FYP. Its help the coordinator and supervisor to monitor the student progress on the Final Year Project. In order to develop the system, the Rapid Application Development (RAD) Methodology is used to manage the development process. This methodology can improve the quality of the project flow. This project incorporates some of the latest technology which using Bootstrap as graphic interface design, Visual Studio to develop the codes and PHPMyAdmin as the database storage. In conclusion, the Final Year Project (FYP) Logbook Portal connects both supervisor and student in order to make the progress of Final Year Project more efficient.
PROSPETTIVE DI RICERCA SULL’ETEROGLOSSIA A BASE ITALIANA

By referring to the contributions included in this volume and pertinent critical literature, this paper aims to deal with some relevant features of literary heteroglossia and to suggest further reflections and research perspectives.
Core Control System Of An Autonomous Electric Vehicle Sponsored by: Tata Technologies Limited, Pune

Keeping in mind the advancement of implementing the A-EVs on road, this project includes designing of a control system for a 4 wheeled autonomous electric vehicle using MATLAB/Simulink environment. The vehicle can travel to a predefined destination avoiding obstacles coming its way. The features and algorithms required to developed the robot is illustrated. MATLAB and Simulink environment is an ideal platform for developing such kind of projects. A typical scenario is shown to demonstrate the functionality of the robot. Autonomous electric vehicles come with their own procs and cons. Huge investment has been made by automobile companies to come over A-EV's limitations and make a breakthrough in the automobile industry.
AUTOMATED CONTRAST LIMITED ADAPTIVE HISTOGRAM EQUALIZTION USING INTRINSIC DECOMPOSITION AND DUAL GAMMA CORRECTION

Image enhancement is a technique to bring out the detailed which is hidden in an image that is to increase the contrast of that part of the image where the information of the image lies. An image can be enhanced by using different enhancement techniques.Even though the image enhancement technique enhance the contrast of an image in an effective and efficient way, they usually have some drawbacks like loss in information, noise amplification and over enhancement. In this paper, an algorithm is proposed for image contrast enhancement using CLAHE, Intrinsic Decomposition and Dual Gamma Correction. As image decomposition is a highly critical problem, on both reflectance and illumination layers we have implemented some conditions .To avoid this problem intrinsic decomposition is used. Dual gamma correction is used to enhance the pixel intensities. There are four quantitative measuring parameters such as total variation (TV), average mean brightness error (AMBE) , enhancement measure error (EME), CQE is used to measure the quality of the enhanced image.
Uma breve viagem pela Inteligência Artificial

The present article presents a rapid journey through artificial intelligence, starting from a more generalist side and then entering generically the main tools available to humans to train artificial intelligence. Finally, half of the text will be devoted to exploring the basics of a neural network, as it is the approach that is most in vogue.
The Students' Error Analysis of Writing in Recount Text for Millineal Students

Abstract.  Nowadays, the millineal students are the largest and most diverse generation.  So, the millineal students need to increase their knowledge and new skill in learning process especially in writing skill with good grammar for holiday experience in recount text form. Writing is the act or process to express idea which support of information throught written language. Meanwhile, recount text is a text to retell the story that happened in the past.  The aim of this research is to find out kinds of errors made by the tenth grade students of SMAN 1 Petanahan in the academic year of 2016/2017 in writing recount text. This research under  descriptive qualitative method and use test as an instrument. The test is a written test about an experience. The researchers collected the data from 30 students as a subject of this research. Which is the researcher assumes one class from eight classes in eighth grade of  SMAN 1 Petanahan. While, in analyzing the data, the researchers classifies the students’ errors. There are four kinds error found: omission, addition, substitution, and permutation. The result of this research shows that the total students’ error are 248 consist of omission 102 (41.10%), errors of addition 37 (14.90%), errors of substitution 77 (31.00%), and errors of permutation 32 (13.00%). The dominant errors made by the students is omission, while the lowest one is permutation. Key Word s : Milleneal Students, Error analysis, recount text, writing
A Systematic Review on Various Reversible Data Hiding Techniques in Digital Images

: Nowadays, Internet has become essential for living and running businesses smoothly; it has made things simpler like online transaction, online shopping, sharing images, videos, audios, messages on social media, uploading some important information on Google drives, etc. So the very first requirement is to secure and protect digital contents from any unauthorized access. Reversible Data Hiding (RDH) is one of the ways to provide security in digital content, through which useful information can be embedded in the digital content, and at the receiver’s end, the complete recovery of cover media as well as the embedded message is possible. In this digital era, digital images are most rapidly used for communication purposes; therefore, the security of digital images is in high demand. RDH in digital images has gained a lot of interest during the last few decades. This paper describes and investigates a systematic review on various RDH techniques for digital images, which can be broadly classified into five categories: Lossless Compression Based, Histogram Modification Based, Difference Expansion Based, Interpolation Based and Encrypted image Based techniques.
THE INFLUENCE OF IMAGE MEDIA ON STUDENTS' SPEAKING SKILLS IN ENGLISH

The formulation of the problem in this study is whether the use of image media has an effect on learning the ability to speak English in English? In this study a total sample of 24 students was applied. The instruments in this study were Pre-Test and Post-Test. Data analysis used descriptive analysis and inferential statistical analysis with the help of computers using the Statistical Package for Social Science (SPSS) Version 25 program. The results of the study can be concluded that 1) the ability to tell students before using the media images in class X IPA 4 MA Negeri Sampang students are generally categorized as very low and unable. The average value obtained by students only touches on the number 46.33.2) the students' ability to tell stories after using the picture media in class X IPA 4 MA Negeri Sampang students are generally categorized as being moderate or capable. This is evidenced by the average value obtained by students touching the number 71.67. 3) the effect of learning the ability to tell stories in class X IPA 4 MA Negeri Sampang shows that there is a significant difference of 0,000 less than the significance of 0.05 (0,000 <0.05), then the hypothesis (Ha) in this study is accepted. This means that the variable use of image media has an effect on student learning outcomes, there is a significant effect between the students' ability to tell stories before using the media and after using the media images in class X IPA 4 MA Negeri Sampang students.
Evaluation of Narr8, an automated presentation service

Narr8 is today a prototype that combines PowerPoint with a written script and creates a new PowerPoint-file that has a sound file added to it where the sound file is a voice that reads the script f ...
Communication Strategies Used by EFL Learners with Different English Achievements in Oral Communication

This article aims to identify the communication strategies used by the learners with low and high English achievement in classroom oral communication and to describe the difference of the frequency of using communication strategies from low and high achievement learners. This research used a descriptive research. The researcher used a case-study design because the present research concentrated on communication strategies used by the learners with low and high English achievement in a specific setting. The 30 learners of the eleventh-grade learners at SMA Negeri 1 Malang was selected as research subject. The result showed that the learners employed 14 communication strategies. The mostly used by the learners was time-gaining strategy and followed by self-repetition, self-repair, appeal for help, code-switching, circumlocution, approximation, use of all-purpose word, other-repetition, message abandonment, other correction, topic avoidance, use of non-linguistic mean, and literal translation. This research also found that the learners with low English achievement used communication strategies more frequently than the learners with high achievement.
PENGEMBANGAN MODEL KEPUTUSAN PEMILIHAN UNIVERSITAS MENGGUNAKAN PENDEKATAN BAYESIAN NETWORKS (Studi Kasus: Universitas X)

University selection has become a probabilistics study because the basis for decision making is not rational, non linear (Tyler, 1998) and is a complex relationship between the environment, personal identity, life experiences, social and learning (Bloomer and Hodkinson, 1997). Thats make high complexity relationships factors and uncertainty due to the probabilistic nature. Bayesian Networks is a directed acylic graph (DAG) with a probability table for each node. Node contained on Bayesian Networks is a variable proportional representation in a domain and the line showing the dependency relationships between variables (Jie, 2001). Based on the data processing, it can be stated that the alternative models are built have been able to model the decision with an error of 0.09%. University decision-making model is influenced by node academic skills, node information (formed by nodes registration fee, tuition, scholarships, cost of living, the good name of the university, the university facilities, the quality of graduates, ease of graduates get jobs, information from senior high school teachers, information from friends, from the media, other media), node influence of parents (father's university, mother’s university, father’s expectations, mothers expectations, parents income, expenditure parents).
Attention-aware fusion for RGB-D face recognition

A novel attention aware method is proposed to fuse two image modalities, RGBand depth, for enhanced RGB-D facial recognition. The proposed method uses twoattention layers, the first focused on the fused feature maps generated byconvolution layers, and the second focused on the spatial features of thosemaps. The training database is preprocessed and augmented through a set ofgeometric transformations, and the learning process is further aided usingtransfer learning from a pure 2D RGB image training process. Comparativeevaluations demonstrate that the proposed method outperforms otherstate-of-the-art approaches, including both traditional and deep neuralnetwork-based methods, on the challenging CurtinFaces and IIIT-D RGB-Dbenchmark databases, achieving classification accuracies over 98:2% and 99:3%respectively.
4 aana land on sale at Gothatar, Kageshwori Manohora Nagarapalika-07,

Land For sale In Gothatar, Ward No. 7, Kageshwori Manohara Municipality, Kathmandu, Pradesh 3 Nepal
Library Guides: HASS 433 -- Shakespeare and the Scientific Revolution: Find Books

This guide provides resources and search tips for students taking Dr. Pass's course on Shakespeare and the Scientific Revolution
Skydd för företagshemligheter innan angrepp? - En rättssäkerhetsanalys om vitessanktionering vid nära förestående angrepp

The Swedish Act on trade secret protects against trade secret attacks, such as unlawful acquisition, use and disclosure of trade secrets. Since the new law entered into force 2018, the protection against trade secrets has been extended to include situations where the unlawful acquisition, use or disclosure of the trade secret is not yet carried out. The purpose of this thesis is to identify the earliest stage at which a prohibition under penalty of a fine in accordance with § 12 in The Swedish Act on trade secrets can be imposed. In order to fulfil the purpose of this essay, a certain Swedish legal method has been used, which involves studying a legal problem based on relevant sources of law.The conclusion of this thesis is that prohibition under penalty of a fine can be imposed on so-called imminent attacks on trade secret. An imminent attack is defined as taking place at an earlier stage in the chain of events, as opposed to completed attacks. Chapter 23 of the Swedish Penal Code can serve as guidance for procedures that may be subject to imminent attacks according to the legislative history of the Swedish Act on trade secret. However, there are no clear answers in the legislative history of the Swedish Act on trade secret on how Chapter 23 of the Penal Code should be applied in relation to the imposition of a penalty fine. In the absence of a clear definition of the term imminent attack interpretation difficulties arise. This thesis conclusion therefore state that the current legislation does not provide thelevel of legal certainty that can be expected in the case of severely sanctioned rules, such as prohibition under penalty of a fine.
TEACHING DISCOURSE ANALYSIS BY USING SYSTEMIC FUNCTIONAL LINGUISTICS APPROACH IN ENGLISH

The aim of this research were; to validate materials for teaching discourse analysis by using systemic functional linguistic approach and to describe  practicality of  materials for teaching discourse analysis by using systemic functional linguistic approach in English education department of IAIN Padangsidimpuan. This research was Research and Development which aimed to create a material design of Discourse Analysis based on Systemic Functional Linguistics. This research used 4D Model with the process define, design, develops and dissemination. The sample of this research was 20 students of English Education Department of State Institute for Islamic Studies Padangsidimpuan on eighth semester. The technique for collecting the data was observation, questionnaire, interview and test. The result showed that the research of material design development categorized into valid according to validators and students’ questionnaire. The content of textbook had been appropriate with the competencies on the syllabus, and the component had been appropriate with the elements that had been determined. The materials for teaching Discourse Analysis had been practical. It could be seen from the learning process, the content, time allocation and student’s needs. The Discourse Analysis materials based on Systemic Functional Linguistic was been effective.
Embedding of Signed Networks Focusing on Both Structure and Relation

Network embedding is a method for learning representation of nodes in given networks as low-dimensional vectors which preserves the proximity in the networks. Most of the research on network embedding are for simple networks without edge signs. However, relations among users in real social media are often represented as signed networks composed of positive and negative relationships. In this paper, we propose a new method for embedding signed networks focusing on both network structure and node relation (sign of connecting edges). Experimental results show that our method outperforms previous methods for the tasks of relation prediction and link prediction.
LibGuides: Virginia Beach Public Library Visits University Library: Home

Virginia Beach Public Library (VBPL) will be on campus at the Regent University Library Tues Jan 28 from 2:00 - 4:00 pm.
Study I: Events

Random events depicted by various instruments with a slight Dadaistic ending. The first of four philosophical studies in sound related to architecture. An experimental envisioning of events in and around a building
Gradient Cryptanalysis of Block Cipher CHAM 64/128

We1 provide the results of cryptanalysis of the lightweight block cipher CHAM 64/128 carried out by means of a so-called gradient statistical attack. The experiments show that after 23 rounds the secret key can be determined with probability 0.01 under the length of the input sample 231 bytes and complexity 237 round function evaluations. Theoretical extrapolation of the suggested attack shows that the key can be completely determined with probability 0.01 after 57 rounds. The recommended number of rounds for CHAM 64/128 is 80. According to the cipher designers, the most successful attack has been a related-key boomerang attack which is effective on 56 rounds.
Directly Optimizing IoU for Bounding Box Localization

Object detection has seen remarkable progress in recent years with the introduction of Convolutional Neural Networks (CNN). Object detection is a multi-task learning problem where both the position of the objects in the images as well as their classes needs to be correctly identified. The idea here is to maximize the overlap between the ground-truth bounding boxes and the predictions i.e. the Intersection over Union (IoU). In the scope of work seen currently in this domain, IoU is approximated by using the Huber loss as a proxy but this indirect method does not leverage the IoU information and treats the bounding box as four independent, unrelated terms of regression. This is not true for a bounding box where the four coordinates are highly correlated and hold a semantic meaning when taken together. The direct optimization of the IoU is not possible due to its non-convex and non-differentiable nature. In this paper, we have formulated a novel loss namely, the Smooth IoU, which directly optimizes the IoUs for the bounding boxes. This loss has been evaluated on the Oxford IIIT Pets, Udacity self-driving car, PASCAL VOC, and VWFS Car Damage datasets and has shown performance gains over the standard Huber loss.
CoRP: A Pattern-Based Anomaly Detection in Time-Series

Monitoring and analyzing sensor networks is essential for exploring energy consumption in smart buildings or cities. However, the data generated by sensors are affected by various types of anomalies and this makes the analysis tasks more complex. Anomaly detection has been used to find anomalous observations from data. In this paper, we propose a Pattern-based method, for anomaly detection in sensor networks, entitled CoRP “Composition of Remarkable Point” to simultaneously detect different types of anomalies. Our method detects remarkable points in time series based on patterns. Then, it detects anomalies through pattern compositions. We compare our approach to the methods of literature and evaluate them through a series of experiments based on real data and data from a benchmark.
LibGuides: Web of Science Core Collection: Introduction

Web of Science Core Collection is a painstakingly selected, actively curated database of the journals that researchers themselves have judged to be the most important and useful in their fields.