Reviewerly/exHarmony huggingface dataset:
A Steganographic Method with an Overlapping of Three Pixel Block of Image

In this paper a new image steganographic technique has been proposed which is capable of hiding data and produces a stego image that is totally indistinguishable from the original image by the human eye. To estimate the contrast and smoothness of pixels we check the relation between neighboring pixels. Our method first arranges the pixel in ascending manner, then takes the highest pixel value common with the other two pixels and then applies the pixel value differencing (PVD) method. To hide the secret data PVD technique is used in each pixel block. The two overlapping blocks are readjusted to attain the modified three-pixel components. Then calculate the new stego pixel block. In this way, take the middle and lowest pixel as the common pixel and apply the same procedure. In comparison, we get that if the highest value pixel value takes as a common one then the data hiding capacity is increased. The embedding capacity of the cover image is increased by using the pixel block overlapping mechanism. It has been tested on a set of images and also maintains the visual quality of the image.
Awareness and Attitudes toward Eye-Tracking Technology

For decades, researchers from many fields have been utilizing eye tracking as an assessment tool. In human-computer interaction, recent technical advancements indicate eye-gazing as a new input modality. Despite all the improvements and advantages, eye tracking is still seen as challenging and it is not widely used. This research made a preliminary step towards the evaluation of people’s awareness of eye tracking and their attitudes towards it. An online questionnaire was designed, and it is comprised of three users' categories: general users, researchers and eye-tracking researchers. A total of 98 users participated in the survey. The survey indicated that approximately half of the respondents had heard about eye-tracking technology, 47% of them working in the research area. Nevertheless, the majority of them did not know the basic facts and theories about this technology. Even among researchers, only 10% of them had adopted eye tracking, and they agreed on the value eye tracking offers for different research disciplines. nevertheless, they also agreed with the perception that eye tracking is a difficult and expensive research methodology. In conclusion, the results support the usefulness of eye tracking and favorable attitudes towards it among most users, but the low response to the survey could also indicate negative attitudes toward eye tracking and a lack of awareness. Therefore, in order to take advantage of eye-tracking technology, further efforts such as training and cost reduction are recommended to the eye-tracking community and manufacturers.
Analysis of the style and language of the Milanese writer Carlo Emilio Gadda in the novel of “Quer pasticciaccio brutto de via Merulana

This article gives an overview of the style and language of the Milanese writer Carlo Emilio Gadda particularly of his masterpiece of "Quer Pasticciaccio brutto de via Merulana", invaded by an abundant pluriuism and an infinite intertextuality.In this study I tried to investigate, through a stylistic-lexical study, the pastiche and linguistic experimentalism in the work of the "Pasticciaccio" by Carlo Emilio Gadda.The word "pastiche" is used to describe a literary text that blends multiple genres of disparate provenance, through casts and imitations of styles and forms of different origins.The reason that inspired me to be interested in Carlo Emilio Gadda comes from reading his particular novel Quer Pasticciaccio brutto de via Merulana
Managing Threads

We have all experienced that moment when running some process such as copying files between directories or launching a new instance of an application causes a program to lag for just a moment and, in some cases, to freeze completely. PyQt a number of different methods for handling threads in UI applications. When you are creating GUIs, you should be aware of how to handle, or more preferably have foresight about avoiding, these situations.
The Construction of College English Teaching Model Based on Artificial Intelligence Technology

The five most representative systems, including PEG, IEA, Y, BETSY, and E-rater, have been applied abroad, while the automatic composition scoring system developed for language learners has been applied. Among them, ICALL, an intelligent computer-assisted language teaching system mainly with sentence automatic analysis technology, has entered the field of education and teaching and changed the direction of language teaching in colleges and universities. From the "deep learning" algorithm to the specific application of artificial technology, the current English teaching system has been improved.
PENGARUH KETERSEDIAAN KOLEKSI FIKSI TERHADAP MOTIVASI KUNJUNGAN MAHASISWA KE PERPUSTAKAAN UNIVERSITAS NEGERI PADANG

The purpose of this study was to describe: 1) the availability of fiction collections at the Padang State University Library, 2) the motivation for student visits to the Padang State University Library, and 3) the influence of the availability of fiction collections on the motivation of student visits to the Padang State University Library. This research uses descriptive research using quantitative methods through distributing questionnaires as a data source. The population in this study were students at the State University of Padang with a purposive sampling technique, which is a sampling technique based on certain considerations. The considerations used as a reference for determining the sample are Padang State University Students who have been to the Padang State University Library and have used fiction collections either reading or borrowing.&#x0D; The results of the research questionnaire that the author conducted lead to the following conclusions: 1) the availability of fiction collections at the Padang State University Library is high because it has a total average value of 2,865. 2) the motivation for student visits to the Padang State University Library is high because it has a total average score of 2.77. 3) there is a significant influence between the availability of fiction collections and the motivation of student visits to the Padang State University Library of 0.585 which is classified as moderate.&#x0D;
Algorithmic and advanced Programming in Python - Syllabus in Computer Science, Decision Making &amp;amp; Data - Masterclass 1

This paper is the first one of a series of 10 lecture notes in Algorithmic and Advanced Programming in Python that are part of the Syllabus of Dauphine PSL's Master in Computer Science, Decision Making & Data. It taught advanced data structure in python with a focus on core and practical details to learn the ins and outs of advanced data structures
Smartphone-based Virtual Reality as an Immersive Tool for Teaching Marketing Concepts

With the advent of Virtual Reality (VR) technology and the ubiquity of mobile devices, smartphone-based VR has become more affordable and accessible to business educators and millennial students. While millennials expect learning to be fun and prefer working with current technology, educators are constantly challenged to integrate new technology into the curriculum and evaluate the learning outcomes. This study examines the gain in learning effectiveness and students' intrinsic motivations that would result from the use of VR as compared to the use of traditional learning activity, namely think-pair and share. The results show that students who took part in the VR simulation demonstrated a better understanding of concepts and reported a better learning experience as compared to those who participated in the think-pair-share activity. In particular, the findings show evidence of higher intrinsic motivation and better learning outcomes.
USING DATA MINING TECHNIQUES FOR GAME RULE EXTRACTION

Tic-Tac-Toe game is an easy to play two-player game played on a three by three grid."Three in a row" is the rule to win a game.After watching a number of games, human players may be able to figure out the way to find the winner of finished games without knowing the rules.Data mining techniques have been applied to solve various problems.Machine classifiers can be used to deal with classification issues such as credit evaluation.Association rule mining is used to find significant relationships among items such as Market Basket Analysis.This study is to propose the use of both classification, specifically decision trees, and association rule techniques to find the rules of Tic-Tac-Toe games.Comparisons on results of the two different data mining techniques are made.The experimental results show that decision tree ID3 and association rule miner Predictive Apriori can identify 100% of game rules while decision tree generates more duplicating rules and it is harder to extract the rules.Although high accuracy rate was reached, Functional Tree utilizing logistic regression for nodes extracted no usable game rules.
A Cost-Effective Technology-Assisted Communication for Paralyzed People using Eye Blink – An Experimental Approach

Over decades, a number of solutions have been placed in practice to help physically challenged person to communicate with environment.The solutions refer to devices that help manage living environment such as opening a window, adjusting AC, controlling TV or turning lights off and on.One such solution is in the form of keyboard, where a care giver, for example a nurse, lets paralyzed person's eyeball scan the keyboard to select options on it to understand his/her needs.Currently, technology-assisted communication is possible, but is limited and at a higher cost.In this research, a customized soft keyboard and cost-effective eye blink communication system are presented to connect to an electric movable bed to select a comfortable bed position for the paralyzed without help of a nurse or a care-giver.An experimental setup is built and results are presented with accuracy of 95%, and with an operational time of less than a second.It is also shown that the built system can be easily modified and extended to facilitate the paralyzed person for various other movable machines, for example, wheelchair or remotely-controlled machines in home environment, or even at driving, etc.The practical constraints are also discussed.
Person Re-Identification using Reduced Dictionary Sparse Representation Based Classifier

Video surveillance has become a necessary tool for monitoring a public places. Automation of the video surveillance is the current need, as it a tough task for the humans to monitor the surveillance video continuously. Also searching a person from a bulk of videos is not an easy job. Person re-identification is a step taken towards to make the video surveillance an automated one. Person re-Identification is a task of matching the identity of a person captured by different cameras in the network at different places and times. The cameras used for surveillance are located at a much higher position than the person so that the conventional method of face recognition is not used for identification of the person. The images of the same person may differ based on the qualities of different cameras (resolution changes), or due to different lighting conditions (variation in illumination) or due to posture changes. Recently sparse based classifier is used in person re-identification and is effective in handling in illumination variation and occlusion. But sparse based decomposition method is not computational efficient. This leads to the development of the person re-identification method based on Reduced Dictionary Sparse representation based Classifier (RDSC). This is done with 2 steps: (i) Similarity score for reduction of the gallery; (ii) Sparse basis expansion of targets in terms of reduced gallery. The proposed method is both computational efficient and creates better outcomes.
Self Learning Gaming Bot using CNN.

In the present universe of current gaming condition bots are the intelligent agent that assumes a prominent job in the popularity of a game in the market. As these bots have gotten very unsurprising to the games. So here we are proposed an AI model for playing games with high level inputs using reinforcement learning. Algorithm works in the Atari Environment i.e. we are using 2D game. This model consists of the CNN (convolution neural network) for the inputs which is fully connected layers and find out the actions according to the inputs. In this learning -based approach, bots learned how to attack and ignore opponents so that bot can get maximum score. In this learning -based approach, bots learned how to attack and ignore opponents so that bot can get maximum score Then we tried the combine the input method which results maximum score of the bot in the environment for the better performance.
A new upper bound of the completion time of the background task in a foreground-background system

A foreground-background scheduling system is a simple real-time pre-emptive scheduler, which is commonly used in uniprocessor embedded systems. In this system, there is a single background task of the lowest priority and multiple foreground tasks have higher priorities. Foreground tasks may have different levels of priorities. Foreground tasks are allowed to pre-empt the background task. The background task takes a longer time to complete its execution because of the frequent interruptions caused by the foreground tasks. The completion time of the background task is calculated using the utilisation of the processor by the foreground tasks. In this paper, a new upper bound formula of the completion time of the background task is derived. The proposed formula gives a closer upper bound to the exact completion time compared to the existing bounds in the case of few foreground tasks and even it gives the exact time in certain cases for the heavily utilised systems. In addition, the proposed upper bound is not a recursive formula like that of the existing response time analysis.
Full Issue

Africa Research Bulletin: Economic, Financial and Technical SeriesVolume 56, Issue 9 p. I-I Full Issue Full Issue First published: 06 November 2019 https://doi.org/10.1111/j.1467-6346.2019.09132.xAboutPDF ToolsRequest permissionExport citationAdd to favoritesTrack citation ShareShare Give accessShare full text accessShare full-text accessPlease review our Terms and Conditions of Use and check box below to share full-text version of article.I have read and accept the Wiley Online Library Terms and Conditions of UseShareable LinkUse the link below to share a full-text version of this article with your friends and colleagues. Learn more.Copy URL Share a linkShare onFacebookTwitterLinkedInRedditWechat Volume56, Issue9November 2019Pages I-I RelatedInformation
An Efficient Machine Learning Method for Facial Expression Recognition

Emotions play important role in human sentiments so broad studies are carried out to explore the relation between human sentiments and machine interactions. This paper deals with an automatic system which spontaneously identifies the facial emotion. Gradient filtering and component analysis is used to extract feature vector and feature optimization is taken place using swarm intelligence approach. Thus emotion recognition with optimized feature extraction process is carried out with high accuracy rate and less error probabilities. Finally the testing process is obtained for the classification of emotions and then performance is measured in terms of false acceptance rate, false rejection rate, and accuracy.
Cryptography and Steganography Techniques in Video

Secure data transmission over the unsecured internet is an important aspect in communication. In recent times, data piracy, unauthorized access, loss of crucial information has been one of the important concern in secure communication of data. To provide security over data transmission, multiple techniques are provided each having its own benefits such as cryptography, steganography and watermarking. Cryptography is the technique for modification of data for secured transmission in an unreadable format. Steganography is the process of hiding the cover file with another file and transmitting the cover file without knowing the existence of hidden message. Watermarking is protection technique used to shield the information from intruders. Various combinations of cryptography and steganography is used to make data more secure. Such techniques differ in various aspects which are load capacity, security, efficiency, simplicity, and much more. Watermarking is the most used technique used for copyright protection in media files in recent times while cryptography and steganography are used to protect the data during communication so that the original data cannot be altered. In this paper, various techniques of cryptography and steganography are discussed which are used in the project.
A morphologically driven gradient and marker controlled distance regularised level sets for nuclear segmentation in histopathological images

The extraction of suitable biomarkers over a tissue image plays a vital role in the diagnosis and prognosis of cancer disease. Nuclear pleomorphism is one such trait, which serves as an important shape-based biomarker. An effective segmentation of the nuclei objects leads to an accurate diagnosis by an expert pathologist, which otherwise would be erroneous due to inter and intra-observer variability. In this research, a novel approach for segmenting the nuclei objects, using distance regularised level sets (DRLS), has been presented. It is shown that the shape prior based morphological transformation of the image achieves: a) centroid detection for accurate contour initialisation; b) gradient computation for an effective contour evolution. Experiments have been conducted on benign and malignant tissue images followed by a performance study using the object detection and the overlap resolution accuracy. Segmentation accuracy is assessed in comparison with the geodesic active contours, based on the ground truth.
Classification of Lexile Level Reading Load Using the K-Means Clustering and Random Forest Method

There are various ways to improve the quality of someone's education, one of them is reading. By reading, insight and knowledge of various kinds of things can increase. But, the ability and someone's understanding of reading is different. This can be a problem for readers if the reading material exceeds his comprehension ability. Therefore, it is necessary to determine the load of reading material using Lexile Levels. Lexile Levels are a value that gives a size the complexity of reading material and someone's reading ability. Thus, the reading material will be classified based a value on the Lexile Levels. Lexile Levels will cluster the reading material into 2 clusters which is easy, and difficult. The clustering process will use the k-means method. After the clustering process, reading material will be classified using the reading load Random Forest method. The k-means method was chosen because of the method has a simple computing process and fast also. Random Forest algorithm is a method that can build decision tree and it’s able to build several decision trees then choose the best tree. The results of this experiment indicate that the experiment scenario uses 2 cluster and SMOTE and GIFS preprocessing are carried out shows good results with an accuracy of 76.03%, precision of 81.85% and recall of 76.05%.
The pseudo metadata concept for the chain of custody of digital evidence

The handling of the chain of custody for digital evidence is a complex issue and more difficult than physical evidence. The main problem in the chain of custody of digital evidence is related to how to record and what should be documented the information of evidence in an investigative process. This paper provides a mechanism for recording and documentation of digital evidence as well as mapping information that must exist for a chain of custody of digital evidence. The recording mechanism is performed after the acquisition and disk imaging of electronic evidence while mapping the information is done into two parts, static and dynamic information. This concept is expected to be an alternative solution for digital evidence handling and to provide solutions for information standards for a chain of custody of digital evidence.
Mining Closed Item sets using Partition Based Single Scan Algorithm

Closed item sets are frequent itemsets that uniquely determines the exact frequency of frequent item sets. Closed Item sets reduces the massive output to a smaller magnitude without redundancy. In this paper, we present PSS-MCI, an efficient candidate generate based approach for mining all closed itemsets. It enumerates closed item sets using hash tree, candidate generation, super-set and sub-set checking. It uses partitioned based strategy to avoid unnecessary computation for the itemsets which are not useful. Using an efficient algorithm, it determines all closed item sets from a single scan over the database. However, several unnecessary item sets are being hashed in the buckets. To overcome the limitations, heuristics are enclosed with algorithm PSS-MCI. Empirical evaluation and results show that the PSS-MCI outperforms all candidate generate and other approaches. Further, PSS-MCI explores all closed item sets
Nighttime Vehicle Detection on Roads by Combining Image Processing and CNN

We propose a convolutional neural network (CNN)-based approach to detect vehicles in front of an ego-vehicle for road traffic scenes at night and compare it with our AdaBoost-based approaches. The new approach enhances the previous approaches [5] in terms of vehicle detection performance. We also produce negative learning data by exploiting a vehicle candidate-generation scheme that further improves classifier performance. The experimental results for real-world road images illustrate the effectiveness of the proposed algorithm.
Detection of Syntax Similarity of Source Code using a Graph based Hybrid Technique

Software evolves inherently due to change requirement. The change request applied with intent to achieve the appropriate functionality of the software. This change inside the code makes some differences in previous code. Changes in somewhere in existing code may also affect some other part of the code. Our focus is on finding similarity of two codes to draw static call graph and program dependency graph which shows the dependencies and data flow among various part of the code then apply a distance metrics to find the percentage of similarity between two codes. This paper presents a dependency graph based hybrid technique (DGHT) for detection of similarity of two variations of python code. This method also includes a Machine learning technique which analyzes syntactic structure of object oriented software system. The objective is to apply the outcomes of this work on change impact analysis. The results of the framework will help to estimate actual impact set to optimize testing efforts.
Insights on Schemes towards Image Counterfeit Attacks &amp; Their Effectiveness

This paper reviews significant schemas pertaining to image forensics where the prime emphasize has been laid towards exploring the mechanisms which identify image counterfeit with higher accuracy. The study reviewed the prime contribution published in the last four years and also addressed the unsolved research problems which are needed to be objectified. The extraction of the research gap further extensively elaborated, which identify the gap needed to be filled up. The extensive review of literature also provides better insight into the design aspects associated with the conventional techniques which are defensive against counterfeit image attacks. The future direction of this investigational study aims to come up with a solution model which can address the accuracy and complexity problems which exist in the conventional system.