Reviewerly/exHarmony huggingface dataset:
Strategic Data and Cyber Security Management in the Arab World

In this chapter, the author will discuss the human life transformation during the last 100 years, moving from the transmission of a message through pigeons and going forward to living a digitalized way of life that could be described as a life where human interaction and communication is taking place predominantly through devices. The chapter will discuss technological advancements such as automation, digitalization, digital transformation, data science, data analytics, real-time data acquisition, artificial intelligence, and predictive intelligence and how all these aspects are affecting the lives of people in the Arab world. The author will discuss how today's people are living within an interconnected world where humans and devices are communicating through the world wide web (the internet). Then, the author will discuss the cyber challenges and how businesses and humans can utilize these technology advancements in a safe and secure way.
Tumbling Down the GraphBLAS Rabbit Hole with SHMEM

In this paper we present shgraph, a SHMEM implementation of the GraphBLAS standard, which enables the user to redefine complex graph algorithms in terms of simple linear algebra primitives. GraphBLAS offers many nice features such as type abstractions, the ability to perform generalized matrix/vector operations over a semiring, and executing graph operations out-of-order (non-blocking mode). shgraph seeks to efficiently manage and process billion-edge or greater sparse graphs on an HPC system. We walk through sample GraphBLAS code and discuss the shgraph development process. In particular, we explain how SHMEM was used and where it was necessary to tweak the GraphBLAS specification to be compatible with a distributed system. Additionally, we analyze some preliminary performance results, map out next steps, and suggest potential applications.
Tweets Competitive Sentimental Analysis of Android Mobile Brands to Understand Customer Experience

With the dawn of the social media era the world has connected more than ever, every opinion, news and discussion is now online. Public opinion data is freely available and accessible through the API of the provider. Data mining, text mining and sentimental analysis provide insight of data. Companies hold official pages on micro-blogging websites like Twitter. This helps them to introduce products and keep in touch with customers. We choose the three Android phone selling brands which are Samsung, Oppo &, Nokia and do our analysis on the tweets posted on official page as a response to officially posted tweets or mentioned using hashtags "#" or mentioned tag "@". We performed a competitive analysis on our finding to find similarities & differences. In the end, we provided recommendations on how to make a better competitive analysis strategy to win the market both on social media forum and in the sale market.
A Note on Optimal Double Spending Attacks

In the present note we address the important problem of stability of blockchain systems. The so-called “double-spending attacks” (attempts to spend digital funds more than once) have been analyzed by several authors. We re-state these questions under more realistic assumptions than previously discussed and show that they can be formulated as an optimal stopping problem.
A General Analytical Model for Problem Solving Teaching: BoS

In this study, a general analytical model called Bag of Solution (BOS) was developed to help students understand and solve mathematical problems.The model is based on graph theory, a topic under discrete mathematics.The types of problems to be modelled for BoS were determined by looking at densities of the problems in the central placement examinations and exam preparation books.As a result, three types of problems were selected; namely Mixture, Worker and Motion problems.In order to develop a common model for solution of the three types of problems, a total of 1509 mixture, worker and movement problems were examined.After the analysis, the problem types were taken together, and variable relations were determined, and a common graph model was created.Since it is an algorithmic model, it allows solving problems both by paper and pencil and computer.This study proves that different types of problems (with different scenarios, objects and object relations) can be solved using a single model.It is expected that the BoS developed in this study will offer two benefits.It is hoped to both provide an algorithmic basis for computer-aided instructional materials, adaptive systems and intelligent tutoring systems to be developed for problem solving and also help students to develop a new understanding of the problem-solving process.A common graph structure that can covers the entirety of a problem can allow students to construct their own learning while solving the problem step by step.
Hierarchical OCR for printed Tamil text

Optical Character Recognition (OCR) of Tamil characters is harder, due to the variety, compared to that of Latin characters. We propose a new technique to perform optical character recognition of printed Tamil characters using a hierarchical Convolutional Neural Network (CNN) which recognises the similarities between characters, while identifying the differences between the fine-grained characters. The performance of the developed system is comparable to the stateof-the-art techniques for OCR.
Image offset density distribution model and recognition of hand knuckle

The accurate description of hand posture plays an important role in the man-machine interaction involved in coordinated assembly. Knuckle image extraction and recognition are of great significance to refine and enrich hand-pose information. These are based on nonparametric density kernel estimation observation sets corresponding to unilateral and bilateral excursion of the hand knuckle gray image. In this paper, sets of pixel positions belonging to the upper- and middle-density intervals are used as two types of image targets. Random clustering and random field multi-classification target modeling are used to learn and estimate the two target distributions of the image. The discriminant field classification learning method is used to fuse the two kinds of target models. A comprehensive representation of the image offset features is obtained. Finally, the knuckle image sample set is used to train the model, and the adaptive threshold is used to identify the hand knuckle image. The results show that the proposed method is feasible.
Object Detection and Tracking in Real Time Videos

Object and human tracking in streaming videos are one of the most challenging problems in vision computing. In this article, we review some relevant machine learning algorithms and techniques for human identification and tracking in videos. We provide details on metrics and methods used in the computer vision literature for monitoring and propose a state-space representation of the object tracking problem. A proof of concept implementation of the state-space based object tracking using particle filters is presented as well. The proposed approach enables tracking objects/humans in a video, including foreground/background separation for object movement detection.
Building Hierarchical Component Directories.

Component-based development is the software paradigm focused on building applications using reusable software components.Applications are built by assembling components, where the required interfaces of a component are connected to compatible provided interfaces of other components.In order to have an effective building process, software architects need adequate component directories that both index available components and ease their search.So far, existing approaches provide only a limited structure and indexation to store/register components and, as a consequence, they propose an inadequate searching process.Even when the indexes are built as flat or hierarchical structures, the indexed elements are not the components themselves, but part of them, such as services or functions, making the search of the needed compatible components imprecise.To cope with searching and compatibility problems, the contribution of this paper is twofold: it is composed of both a refined methodology (improving a previous approach) and a tool to build a hierarchically structured component directory.The component directory solves the identified problems letting an architect find components that are compatible with a given specification (to be assembled) or components that can substitute to a given one.This directory uses Formal Concept Analysis to build component type hierarchies thanks to a three step classification process that successively classifies functionality signatures, interfaces and, at last, component types.The refinement of the methodology is based on a substitutability relationship between components, where the notion of not having a parameter or an interface of some type makes our methodology more robust when considering required interfaces.The tool made possible
Vulnerability Research of Confidential Information Transmitted Over Quantum Channels in Bank Infrastructure

Banking structures have begun to use quantum channels to guarantee the security of the exchange of confidential information. The fundamental laws of quantum physics ensure the safety of such a transfer. This paper presents the results of a theoretical research of the effect of the real parameters of the used fiber optic channels on the security of transmitted data taking into account the spontaneous emission of photons, scattering and attenuation of signals. The possibility of detecting unauthorized access is estimated, as well as the amount of information intercepted by the intruder. The results of the work can be used during the audit of information security in the bank infrastructure.
Route Planning for Teams of Unmanned Aerial Vehicles Using Dubins Vehicle Model with Budget Constraint

In this paper, we propose Greedy Randomized Adaptive Search Procedure (GRASP) with Path Relinking extension for a solution of a novel problem formulation, the Dubins Team Orienteering Problem with Neighborhoods (DTOPN). The DTOPN is a variant of the Orienteering Problem (OP). The goal is to maximize collected reward from a close vicinity of given target locations, each with predefined reward, using multiple curvature-constrained vehicles, such as fixed-wing aircraft or VTOL UAVs with constant forward speed, each limited by route length. This makes it a very useful routing problem for scenarios using multiple UAVs for data collection, mapping, surveillance, and reconnaissance. The proposed method is verified on existing benchmark instances and by real experiments with a group of three fully-autonomous hexarotor UAVs that were used to compare the DTOPN with similar problem formulations and show the benefit of the introduced DTOPN.
Review on Safe Reversible Image Data Hiding

To keep the privacy confidential now a day; two techniques are used to encrypt the image the 1st one is that encrypts the image through cryptography algorithms key. The other one involves the concealing algorithm program to keep the pictures confidential. The owner of the picture performs the cryptography key on the original picture and then use the data hider key to further encrypt the image. The owner doesn't recognize the content because the image contains more information. With the help of a cryptography key, the receiver 1st decipher it then use the data hiding key to completely decipher the image and see the result. Cover images are used which helps the data to further decrypt it. The original image is encrypted by the cover image that will cover the original image. It will further decrypt it. Two encryption techniques are used in this system one is cryptography and the other is knowledge concealing. Cryptography is the technique which is used to cypher the image. It encodes the image in this way that it is not easy to recognize. Cowl images are used which combine with the original image by make a cover around it. This will then encrypt by the specific key. Knowledge concealing is a method through which the data is embedded in the image a specific encrypted key is used that will encrypt the knowledge concealing and then it will combine with the cryptography and make it more secure. Two different keys are used differently in these two methods that more secure the data.
Improved CSO to Solve the TSP

The Travelling Salesman Problem (TSP) is a known optimization problem by the important number of its applications and its complexity (classified as NP-hard combinatorial optimization). That explains the important to propose some novel methods to solve it. The Cat Swarm Optimization (CSO). metaheuristic is a nature-inspired behavior of real life of the cats that was adapted in 2013 to solve the TSP, to improve its efficiency, this paper aims propose a novel improved CSO characterized by a dynamic Mixture Ratio used to exchange the mode of the cat (Seeking or tracing mode), add a novel parameter that consider the best position the selected cat and other improvement. The results by the application of the proposed methods to solve some benchmark instances of TSPLIB; show that the novel proposal method is more efficient.
Development of m-learning vertebrate determination program to improve student’ classification and reasoning skills

This study aim to development of M-Learning Vertebrata determination program as media for learning to improve students classification skill and inductive-deductive of reasoning skill. This study used 4-D (define, design, development, and deployment) development method. Results generally show that M-learning Vertebrata determination program for learning have a synergetic effect resulting in enhanced learning. The research findings imply that using mobile learning for study Vertebrate classification had a statistically significant effect on pre-test and post-test achievement scores for increase students classification and reasoning skills. User give the positive response, it means student can operate and simulate M-Learning Vertebrate determination program. Based on validation result from validator expert and trial results, M-Learning Vertebrata determination program has legibility to be used as learning media.
Efficient Frequent Pattern Mining in Data Streams

In this paper, we present a new frequent pattern mining mechanism for data streams to enhance the performance of existing mechanisms, particularly to reduce the needed processing time and uplift the mining accuracy. Our new mechanism performs data mining by the Trie data structure (instead of the entry table in previous mechanisms) to access patterns at reduced processing steps and run time. To attain desirable mining accuracy, it adopts a Length Skip practice to skip less frequently used long patterns from the summary and preserve the space for more frequently used short patterns. Simulation results show that, when incorporated into existing frequent pattern mining algorithms, our new mechanism will effectively increase the mining accuracy at notably reduced run time.
StockSense

This paper presents StockSense, a prototype of a haptic wristband for tracking volatile markets. StockSense informs the user about current price changes via structured vibrotactile feedback. This system can be used for any volatile market: cryptocurrency market, stock market, etc. A preliminary study was carried out with 5 participants to investigate whether vibrotactile displays of smartphones could be integrated into the system for additional information transmission. Afterwards the system was evaluated in a study with 20 participants. The participants became familiar with the system within a short period of time and were able to recognize the displayed information on the vibrotactile display reliably. The participants rated the system as positive. Overall, the participants appreciated the functionality of the system and considered it to be suitable for this field of application.
Born digital preservation of e-lit: a live internet traversal of Sarah Smith’s King of Space

Sarah Smith’s King of Space, published in 1991, is the first work of science fiction produced as electronic literature. Released on a 3.5-in. floppy disk and requiring a Macintosh computer running System Software 7.0-MacOS 9x, it is now inaccessible to scholars interested in early digital literary forms, particularly of science fiction by women authors. Because this work is interactive and involves animations, images, sound, and words, preserving it requires an approach that retains as much of these experiences as possible for future audiences. To accomplish this task, our lab––the Electronic Literature Lab at Washington State University, Vancouver––used the Pathfinders methodology developed by Grigar and Stuart Moulthrop, adding to it Live Stream play-throughs on YouTube promoted through social media channels. This essay outlines our process and discusses the potential of this methodology for preserving other kinds of multimedia and interactive work.
Towards Generating Policy-Compliant Datasets

The development of intelligent (e.g., AI-based) applications increasingly requires governance models and processes, as financial legal sanctions are more and more being associated with violation of policies. We propose an ontology representing the informed consent that was collected by an organization and argue how it can be used to assess a dataset prior its use in any type of data processing activities. We demonstrate the utility of our ontology using a particular scenario, where datasets are generated “just in time” for a particular purpose such as sending newsletters. This scenario shows how data processing activities can be managed to in such a way as to support compliance verification. This paper furthermore compares the contributions to related work and positions it into prior work concerned with the broader problem of prescribing and analyzing compliance.
Investigating Result Presentation in Conversational IR

Recent researches in conversational IR have explored problems related to context enhancement, question-answering, and query reformulations. However, very few researches have focused on result presentation over audio channels. The linear and transient nature of speech makes it cognitively challenging for the user to process a large amount of information. Presenting the search results (from SERP) is equally challenging as it is not feasible to read out the list of results. In this paper, we propose a study to evaluate the users' preference of modalities when using conversational search systems. The study will help us to understand how results should be presented in a conversational search system. As we observe how users search using audio queries, interact with the intermediary, and process the results presented, we aim to develop an insight on how to present results more efficiently in a conversational search setting. We also plan on exploring the effectiveness and consistency of different media in a conversational search setting. Our observations will inform future designs and help to create a better understanding of such systems.
The Case Study of Software Build-in Design Based on Quality Factors and FMEA

In order to improve the quality and stability of software, software quality factors must be considered in the early stages of system development as in [1]. Moreover, in the design stage, we use Failure modes and effects analysis (FMEA) to analyze the abnormal situation. Different to traditional exception handling, FMEA is a systematic way of identifying failure modes of a system, and take actions to eliminate or reduce failures before the failures occur as in [2]. Consequently, the cost and rework of software development could be reduced, and the defect removal efficiency (DRE) could be increased. Based on McCall’s software quality factors and FMEA, we derive the quality problems that may be encountered in the software development stage and the failure scenarios that may be confronted during the operation phase. Furthermore, we analyze the failure mode and calculate their risk priority number (RPN). Following the systematic engineering thinking as in [3], we conclude the early design issues, and propose the built-in features which are worth to be designed in the early stage. Finally, we illustrate the multiple effects after its implementation.
A new non-contact coordinate measuring machine equipped with light-duty optical probe based on fringe projection profilometry

In the modern industrial manufacturing, how to effectively obtain the three-dimensional data of the parts profile is the key component for precision test and subsequent analysis. A light-duty design scheme for optical vision probe, which can be installed with a PH10T motorized probe head in CMM, is discussed in this paper. The optical probe can overcome several defects of the traditional measurement mode of CMM, such as poor efficiency and sparse point cloud. Therefore, the problem of 3D measurement and quality analysis for complicated parts can be solved. To splice data in different fields of view, a registration method using a new designed artifact is proposed. Experiments demonstrated the feasibility of the designed non-contact CMM integrated with optical 3D probe for precise 3D shape measurement. The measurement uncertainty of the optical probe can reach 0.012mm within the measuring volume width 200mm and the measurement uncertainty of the global 3D measurement is less than 0.03mm in 1500mm.
Steganography in beautified mages

Existing distortion functions in steganography which achieved high undetectability are designed for unprocessed natural image. Nowadays, a large number of images are filtered before transmitting for the sake of beautification. In this situation, existing distortion functions should be improved to fit the properties of these beautified images. This paper proposes a distortion function optimization method for steganography on beautified images. Given an unprocessed image, a popular image beautification software is employed to produce two similar beautified images. One of them is used for embedding and the other one is employed as reference. Guided by the reference, existing distortion functions are improved by distinguishing the embedding costs for ±1 embedding. After embedding, the stego image is closer to the reference, which results in a higher undetectability against steganalysis. Experimental results also proved the increasing of undetectability when examined by modern steganalytic tools.
Swarm Assistant: an intelligent personal assistant for the Swarm

Billions of devices belonging to different manufacturers and domains are connected to the Internet of Things. The amount of consumer equipment that a single person can manage, however, is limited. Additionally, personal information is spread across several sources, which prevents a seamless integration. Intelligent personal assistants are a solution to facilitate the integration of online services and data sources. However, the management of IoT equipment is still challenging due to difficulty of interaction, security information integration, among other problems. This paper proposes the architecture and implementation of a intelligent personal assistant based on the Swarm, a decentralized IoT platform for heterogeneous smart devices. Our proposal focus on ease of interaction and semantic data integration.
Size-optimal top dag compression

It is shown that for a given ordered node-labelled tree of size n and with s different node labels, one can construct in linear time a top dag of height O(log⁡n) and size bounded by O(n/logσ⁡n) and O(d⋅log⁡n), where σ=max⁡{2,s} and d is the size of the minimal dag. The size bound O(n/logσ⁡n) is optimal and improves on previous bounds.