Reviewerly/exHarmony huggingface dataset:
Security

Throughout history, humanity has invented valuable technologies and ways to organize society. These innovations are typically accompanied by risks. Fire cooks food, and also provides heat on cold nights. Yet, when left unchecked, fire can cause huge damage as well as loss of life. Cities enabled new forms of community and commerce. However, they brought us more thievery, and made it easier for epidemics to spread. The automobile allowed a separation of locales for work and residence; trucks allowed goods to be shipped long distances. But vehicular accidents have caused far greater injury and loss of life than did mishaps with horses and mules. Information technology, like other technologies, has potential for good and for harm. In the first six chapters, we introduced aspects of human activity, such as education, medicine, and government, in which IT has been transformative and mostly positive. The next three chapters examine areas in which the negatives of IT are dominant, in which risks seem everywhere. This chapter focuses on security. IT security flaws are exploited by outsiders for personal or political gain. In Chapter 8 we shall look at safety, where the risks are often injury or loss of life. In Chapter 9, we shall look at privacy, where the risks are exposure of private, confidential, and even sensitive information. Security is the attribute of a computer system that ensures that it can continue to function properly after an attack. Attacks against computer systems happen routinely now, are in the news almost every week, and are accelerating in numbers and in impact. Damage to both individuals and organizations—financial losses, chaos, and deteriorating morale— is severe. We shall provide a primer on the multitude of ways computer systems, from large networks to mobile phones, can be ‘hacked’ so that they no longer function properly. We shall define the most common kinds of destructive software, often called malware. We will discuss large-scale data breaches, which now happen frequently and expose the personal data of millions to billions of people. The word hackers refers to individuals who disrupt digital technologies and thereby damage the functioning of an institution or a society.
Software Architecture Challenges for ML Systems

The International Conference on Software Maintenance and Evolution is the premier international forum for researchers and practitioners from academia, industry, and government to present, discuss, and debate the most recent ideas, experiences, and challenges in software maintenance and evolution.
Installing Python

Before we start using Python, we need to install it. Some operating systems, like Mac OS X and some Linux variants, have Python preinstalled. Those versions of Python, colloquially called “system Python,” often make poor defaults for people who want to develop in Python.
Enhanced Privacy with Multiple Search Over Cloud Data using EPSS

Cloud computing is the service-oriented platform which will provide security for the various data uploaded by the users. Security is the service which can be provided by the service providers. There is a lot data that can be stored in the cloud with the help of various security algorithms. The data which can be stored in the cloud is called outsourced data. Every user wants to store the sensitive data to cloud storage. In this paper, the Enhanced Privacy and Secure Storage data (EPSS) can be searched with the multiple keywords. For the searching of multiple keywords the Enhanced Keyword Search (EKS) which retrieve the data very fast and with multiple records. Experimental results show the performance of the searching and security.
SISTEM PAKAR KERUSAKAN HARDWARE KOMPUTER DENGAN METODE BACKWARD CHAINING BERBASIS WEB

Computers are a major need to support human performance. Computers also often damage the hardware such as processor, memory, mouse, keyboard, hard disk, optical drive, monitor. Hardware damage is still rarely known by computer users. In this final project aims to build a knowledge-based system to diagnose damage to computer hardware or hardware in the form of websites using PHP using the waterfall model and the backward chaining method. Making a Computer Damage Expert System with Web-Based Backward Chaining Method is expected to be able to help computer users to solve problems on computer hardware, so users can save on technician costs and can save time.
Training in Metacognitive Perspective in Construction and Architecture at High School Stage in Bulgarian Vocational Education

To implement training in construction and architecture in a metacognitive perspective at the high school stage, it is necessary to construct a new learning environment. The model of learning environment presented in the article includes new elements. In order to effectively apply the metacognitive didactic tools, in addition to teachers and students, the learning process is also attended by prominent representatives of the construction business, university students in architecture and construction, media group specializing in construction and architecture. The described model also includes observations in the context of the topics of the curriculum, that are to be conducted during visits of construction sites and manufacturing plants, as well as many events together with students and young professionals: innovative forums, competitions. The conducted action research shows that in order to comply vocational education with the requirements and needs of the labor market, such education must create opportunities for students to perceive the future profession on a metaphysical level.
WHAT DO YOU KNOW ABOUT THE PUDRETTEITA DEPOSITS AT MARS?

Want to know more about the poudretteite deposits on Mars? Then you can safely pay attention to this article, and we begin our journey! Today we will be talking about minerals on Mars, but our focus is on poudretteite.
IEEE Transactions on Information Forensics and Security publication information

The Signal Processing Society is an organization, within the framework of the IEEE, of members with principal professional interest in the technology of transmission, recording, reproduction, processing, and measurement of speech; other audio-frequency waves and other signals by digital electronic, electrical, acoustic, mechanical, and optical means; the components and systems to accomplish these and related aims; and the environmental, psychological, and physiological factors of these technologies.
Correction

This article refers to:Transformative leadership for women’s rights in Africa: Learning from Oxfam’s work
A Novel Clustering-based Class-asociation Rule Mining Method for Handling Class-Imbalanced Datasets

Class-association Rules (CARs) mining is a knowledge discovery technique with many practical applications.One of the extensions of mining CARs algorithm is to combine information about data classes to derive rules between item and class.However, in the class-imbalance field, it is difficult to mine the rules related to minor classes.One of the solutions is at first to cluster with the combination with CARs mining, then the items of minor classes can be grouped to some clusters.Thus, the corresponding rules will be easier to detect.The k-means clustering method is often used due to its fast computing speed.However, the clustering results of k-means are non-deterministic, so it may affect the clustering quality.In this study, we propose a new direction for combining k-means and Hierarchical Agglomerative Clustering, and continue with class-based association rule mining.Our method has the same execution time as the k-means method but has better clustering quality, so the generated rules are also more accurate, as illustrated in the experimental results.
Improving collaborative recommendation based on item weight link prediction

There is a continuous information overload on the Web. The problem treated is how to have relevant items (documents, products, services, etc.) at time and without difficulty. Filtering system also called recommender systems are widely used to recommend items to users by similarity process such as Amazon, MovieLens, Cdnow, etc. In the literature, to predict a link in a bipartite network, most methods are based either on a binary history (like, dislike) or on the common neighbourhood of the active user. In this paper, we modelled the recommender system by a weighted bipartite network. The bipartite topology offers a bidirectional reasoning item side and user side, which preserve the information shared between the nodes. To make such a prediction, we seek to determine the shares of items shared between users. In the first step, we accumulate the shares of the users towards the items and in the second step, the shares of the items towards the users. The idea is to exploit the item-user connectivity to predict nonexistent links based on existing links. Therefore, the information is propagated linearly and without loss between nodes in the network. We focused on the item through a dual projection that combines the sharing of quotas between users and items. Empirical tests on real data sets (Amazon-Books, MovieLens 1M, Yelp2018, Yahoo! Songs) showed satisfactory results.
The suitability of similarity measures to the grading of short answers in examination

Grading of short answers in an examination is a tedious exercise that takes so much of examiners' time. Fatigue could set in leading to errors. Sometimes sentiments come into play. The attendant effect of this is variations in the marks awarded to candidates even when they express the same opinion. In this study, Jaccard, Cosine, Jaro and Dice similarity measures were used to grade the answers provided by candidates in examinations of 647 questions. The similarity measures were tested with the aim of ascertaining the measure that rank closest to the average scores provided by three human examiners with the same examinations' answers and marking guides. Results showed that Jaro similarity measure ranked closest to the mean score of the examiners with a variance absolute error of 0.62% and covaried strongly by 97% with a significant level of 0.001.
Aggregate Linear Discriminate Analyzed Feature Extraction and Ensemble of Bootstrap with Knn Classifier for Malicious Tumour Detection

Tumour detection medical applications utilize classification techniques to categorize malicious and non-malicious tumour features to provide an efficient medical diagnosis of the human individual under investigation. One way to enable efficient classification, Feature extraction methods are used to eliminate the redundant features and obtain the most relevant features. However, the challenges concerning the dimension and quantum of tumour dataset persist. Toward this goal, this paper aims to maximize the malicious tumour classification accuracy using two reliable ensemble classifiers namely Bootstrap Aggregation and k-nearest neighbour. Tumour features extracted by Aggregate Linear Discriminate Analysis (LDA) and the feature distance is calculated with iterative scattering matrix algorithm. The extracted features are further refined by aggregation to select most effective feature values. After this, an ensemble classifier technique is employed to construct malicious and non-malicious tumour classes. The tumour classification based on an ensemble of bagging and k-nearest neighbour. Simulation is carried out on Tumour Repository data set to show that proposed ensemble classifiers have considerably better tumour detection accuracy than existing conventional techniques. Numerical performance evaluations show that 8% improvement by proposed method in tumour classification accuracy for malicious tumour detection in human individuals.
Data security and privacy models for/on edge computing

As a new computing paradigm, edge computing (EC) has gained much popularity in various delay-sensitive application scenarios (like vehicular networks and autonomous driving). With the prevalence of EC, its security and privacy issues become more and more significant for its further development. When referring to the security and privacy issues in EC, its meaning is twofold: the first is the inherent security issues of EC architectures and the other is how we can strengthen the security of current systems by introducing the paradigm of EC. Thus in this chapter, after analyzing the unique properties of EC, intrusion, lightweight authentication, access control and private information leakage are chosen to be four typical threats and challenges for the security or privacy issues of EC. Then, some practical security and privacy solutions prompted by EC in existing research works are present. After that, several open research issues are given to draw more attentions from academia and industry to guarantee the security of this new paradigm.
Towards a Librarian of the Web

Centroid terms are single, descriptive words that semantically and topically characterise text documents and thus can act as their very compact representation in automated text processing tasks that strongly rely on the semantic similarity of texts. Algorithms to classify and cluster them make use of this information. In this book, the novel, brain- and physicsinspired concept of centroid terms is introduced and deeply discussed. Furthermore, their unique properties and practical usage in major natural language processing and text mining tasks are covered. In this regard, a new graph-based method for their fast calculation is presented as well. In contrast to methods relying on the bag-of-words model, the derived centroid distance measure can uncover
Unharmed Data Deduplication with Potent Claim Upstairs in Nebula Argosy

In cloud storage solutions, deduplication era is often accustomed reduce down the location and facts motion goals of offerings with the beneficial resource of the use of casting off repetitive records and moreover storing truly one replica of them. Deduplication is only even as severa clients' supply non-forestall information to the cloud storage; no matter the truth that, it's going to growth issues regarding safety and protection and assets. Evidence of- assets plans allow any form of owner of non-save you information to steer the cloud garage vicinity internet server that he possesses the records ultimately of a sturdy technique. However, severa purchaser's area tool probably to inscribe their facts preceding to outsourcing them to the cloud storage to preserve non-public privateness, however this obstructs deduplication due to the randomisation assets of coding. Recently, numerous deduplication plans are alleged to solve this disadvantage with the resource of the use of permitting every proprietor to percent ordinary coding trick for normal data. However, quite a few the structures be suffering from way of protection problems, at the same time as you take into account that they may be doing no longer take into account the colourful adjustments in the possession of outsourced information that take region ofttimes within the route of an much less expensive cloud storage issuer. For the length of this paper, we have a propensity to advocate a very one-of-a-kind server-trouble deduplication motif for encrypted facts. It lets in the cloud server to govern accessibility to reduced in size out data at the identical time as soon due to the fact the ownership changes dynamically through using exploiting uneven centered coding similarly to relaxed assets cluster important movement. This prevents information discharge not in reality torevokedusers albeit they antecedently had that facts, but in addition to Connect in Nursing honesthowever-curious cloud storage location internet server. Furthermore, the organized trouble count number warranties information honesty in opposition to any shape of tag incongruity assault. Therefore, protection and protection is advanced in the organized motif. The overall performance evaluation effects show display display that the scheduled style is shape of as low-price due to the reality the preceding systems, while the brought remedy fees is minimal.
Innovative Region Based Steganographic Technique to Provide Security and Authentication to Digital Image

In this advanced world with the growing technology, the demand for security of information is needed in any communication streams of data which is being conveyance from host to intended host over the internet. Obviously, a huge &amp; numerous amount of the data or the information are transferred in our everyday. So, the demand for securing information has become the main concern. Image Steganography is one of the important areas in the field of Steganography. The main purpose of steganography is to protect the surreptitious information from others except from intended receiver &amp; by increasing the security of the covert data in the significant way that information can’t be revealed although the intruder knows the methodology of the embedding process. In this paper, The aim is to propose a different yet, an innovative steganographical technique which provides the security on our digital image, and by using a quality measuring technique like Mean Square Error(MSE), Peak Signal Noise Ratio (PSNR) which assure the quality of image has been not degraded even after infusing the covert data inside the image. So to overcome these issues, this paper, suggests a new method to maintain the quality of the image. After embedding the authenticated information in the cover image using Region-Based Least Significant Bit (LSB) technique that provides security of digital image
An image fusion dehazing algorithm based on dark channel prior and Retinex

The dehazing algorithm for image processing is widely used to improve image quality, which aims to reduce the impact of hazy weather. The typical dehazing algorithm using dark channel prior (DCP) can carry out image dehazing efficiently. However, the processed image only by using DCP will lead to the low lightness and the weak colour of the image, which cannot meet the visual characteristics of the human eye in some extent. To solve this problem, this paper proposes an image fusion dehazing algorithm based on DCP and retinex. First, the original image is processed by the DCP dehazing algorithm to get the dehazed image. Then, the dehazed image is processed by using the retinex algorithm to get the enhanced image. Finally, the dehazed image and the enhanced image are fused using a linear fusion method, which is expected to improve the lightness and colour of the image after dehazing. Experimental results show that the algorithm proposed in this paper not only achieves good results for image dehazing, but also enhances its lightness and colour.
Image Processing Techniques for Acute Leukaemia Detection

Every year a lot of people are diagnosed with blood cancer.This disease has a high mortality rate due to late and incorrect diagnoses.Acute leukaemia diagnosis requires an automated solution to facilitate early detection.This is one of the challenging problems and several machine learning techniques are proposed in recent years, however, image analysis using blood smear images remains the easiest and efficient technique to detect acute leukaemia.This study provides a literature review of the research work corresponding to the detection and classification of Acute lymphoblastic leukaemia (ALL) using digital image processing.The paper presents the analysis of various methods and techniques of image processing to detect leukaemia and highlights some of the research pros and cons.This literature review also introduces some of the research issues and challenges involved in this field of study
Shipwreck—invitation

Shipwreck—invitation Leslie Harrison (bio) Come be with me we have tickets for the endof the world we have a litany of years markedby fire by others years marked on our bodiesmarked in geographies of skin and isotopescome now as the snow arrives accumulateslet us be mice let us be mice crawling in throughthe gaps in a house this house made for strangerslet us curl inside their spun glass their sunrise wallsstealing food from the sloppy birds carrying it backin pieces to our quiet our stolen space heatedby breath which is to say the living body curled intothe living body curled into hidden cavity this secretbetween walls between each other come and tell methe story the one about how you'll find me outsidein the snow pulling answers down from the cloudspulling breath in past the ice the raptors past the driftshow you'll find me invisible and twilit tell me you'llfollow the footprints I leave outside your door howyou'll find them find them please before the wind risesbefore the wind comes and takes them back [End Page 52] Leslie Harrison Leslie Harrison's second book, The Book of Endings (Akron Series in Poetry, 2017), was a finalist for the National Book Award. Her first book, Displacement (Mariner Books, 2009), won the Bakeless Prize in poetry from the Bread Loaf Writers' Conference. Recent poems have appeared or are forthcoming from West Branch, Kenyon Review, Literary Matters, and elsewhere. She lives and teaches in Baltimore. Copyright © 2019 Middlebury College Publications
Binary Search In Linked List

This paper is based on an approach to implement Binary Search in Linked List. Binary Search is divide and conquer approach to search an element from the list of sorted element. In Linked List we can do binary search but it has time complexity O(n) that is same as what we have for linear search which makes Binary Search inefficient to use in Linked List. The main problem that binary search takes O(n) time in Linked List due to fact that in linked list we are not able to do indexing which led traversing of each element in Linked list take O(n) time.In this paper a method is implemented through which binary search can be done with time complexity of O(log2n). This is done with the help of auxiliary array. Auxiliary array helps in indexing of linked list through which one can traverse a node in O(1) complexity hence reducing the complexity of binary search to O(log2n) hence increasing efficiency of binary search in linked List.
Knight Tour for Image Steganography Technique

The growth rate of the Internet is exceeding that of any previous technology. As the Internet has become the major medium for transferring sensitive information, the security of the transferred message has now become the utmost priority. To ensure the security of the transmitted data, Image steganography has emerged out as an eminent tool of information hiding. The frequency of availability of image file is high and provides high capacity. In this paper, a method of secure data hiding in image is proposed that uses knight tour positions and further 8-queen positions in 8*8 pixel blocks.The cover image is divided into 8*8 pixel blocks and pixels are selected from each block corresponding to the positions of Knight in 8*8 chessboard starting from different pixel positions. 8-pixel values are selected from alternate knight position. Selected pixels values converted to 8-bit ASCII code and result in 8* 8 bit matrix. 8-Queen’s solution on 8*8 chessboard is applied on 8*8 bit matrix. The bits selected from 8-Queens positions and compared with 8-bit ASCII code of message characters. The proposed algorithm changes the LSB of only some of the pixels based on the above comparison. Based on parameters like PSNR and MSE the efficiency of the method is checked after implementation. Then the comparison done with some already proposed techniques. This is how, image steganography showed interesting and promising results when compared with other techniques.