Reviewerly/exHarmony huggingface dataset:
OnE: An Ontology Evaluation Framework

A comprehensive set of evaluation criteria, named OnE, for evaluating ontologies has been proposed in this paper. Each criterion of OnE has been defined in a way such that together they are capable of evaluating any ontology from all aspects. The process of using OnE for evaluation has been demonstrated by evaluating chemical ontologies. Also, for this purpose, an ontology on the domain of agricultural chemicals has been constructed by following the human-centric faceted approach for ontology construction (HCFOC) and has been evaluated using OnE. The results obtained after the evaluation has provided insights about the ontologies. The constructed ontology aims to support any information system trying to support farmers in the process of decision making while selecting chemicals for use in agriculture. Also, it is envisaged that the demonstrated ontology and the set of evaluation criteria named OnE will redefine ontology evaluation and make it easy while making a strong impact on ontology developers.
Comparison of Knuth Morris Pratt and Boyer Moore algorithms for a web-based dictionary of computer terms

Computer students need a dictionary of computer terms to deepen lectures. In developing dictionary applications, the term computer will choose the fastest and most efficient memory algorithm. The comparison algorithm is Knuth Morris Pratt (KMP) and Boyer Moore (BM) algorithm. Based on previous research, the KMP algorithm has a better performance compared to other string matching algorithms. However, other studies have concluded that the BM algorithm has better performance. Besides, the Zhu-Takaoka algorithm is more efficient than the KMP algorithm in dictionary development. The BM algorithm has the same search concept as the Zhu-Takaoka algorithm. The determination of the fastest and most efficient algorithm in this study uses the Exponential Comparison Method (ECM). ECM sets criteria for when searching and using the memory in the search process. The results of the comparison of the KMP and BM algorithm are the search time for the BM algorithm is 37.9%, and the KMP algorithm is 62.1%. The results of the use of search memory for the KMP algorithm are 50.6%, and the BM algorithm is 49.4%. The total ECM score shows that the BM algorithm is 0.55% better than the KMP algorithm.
AI4D - African Language Dataset Challenge

As language and speech technologies become more advanced, the lack of fundamental digital resources for African languages, such as data, spell checkers and PoS taggers, means that the digital divide between these languages and others keeps growing. This work details the organisation of the AI4D - African Language Dataset Challenge, an effort to incentivize the creation, curation and uncovering to African language datasets through a competitive challenge, particularly datasets that are annotated or prepared for use in a downstream NLP task.
Challenges in developing an interdisciplinary teaching material on effects related to the Earth’s rotation

The increasing public attention attracted by environmental issues requires the understanding of the physics behind large scale motions of the atmosphere and the oceans. It is therefore necessary to extend the scope of secondary education to the physical principles behind these phenomena related to the Earth’s rotation. The main message to convey is the fascinating effect that the importance of the Coriolis deflection increases with extension in space. The communication of size making such a difference requires quantitative considerations, whereas high school treatment is scarce and only provides a qualitative explanation of the Coriolis deflection. To bridge this gap, we have developed secondary level teaching material on the physical background of large-scale environmental processes and made it available on the internet for interested students and teachers. Aimed at regular secondary school students, it requires no further knowledge beyond the very basics of mechanics. The material consists of a core study and several extensions. The core study only uses elementary formulae and is easily followed by as independent learner or completed in three teaching periods in class. It begins with simple hands-on experiments from which students can derive the expression of the Coriolis acceleration. Students can also use data from their own experiments or everyday life observations to obtain a numerical measure of the strength of the Coriolis effect. Through the three sections, the material proceeds from small scales, where the Coriolis effect is practically negligible, to planetary scales, where the effect inevitably becomes dominant. As an illustration of the difference between the large and small scales, it also reveals why a video pretending to demonstrate the different rotation of plughole vortices around the Equator must be faked. The material has been developed in permanent contact with students, the paper also shows steps of improvement based on the feedback received from them.
BLOCKCHAIN AND TANGLE: THE TRANSACTION SECURITY IN THE IOT ECOSYSTEM

This article examines the level of security ensured by Blockchainand Tangle technologies when performing transactionsin the IoT ecosystem, especially considering the informationintegrity. To this end, analytical models and simulationsare employed to investigate fraud scenarios in which an attackerattempts to modify transactions already recorded inthe databases. The results suggest that Tangle technology ismuch more promising, as it proves to be more competitive inscenarios where potential attackers have outstanding computationalprocessing power. In addition, Tangle technologycan deliver scalability that is not observed in the Blockchaintechnology. In this context, the main contribution of thisarticle is to provide subsidies for the development of realapplication projects for the IoT ecosystem
SORTIS: Sharing of Resources in Cloud Framework Using CloudSim Tool

In today’s environment, many number of FOSS Cloud Computing software and Proprietary Cloud Computing tools are available for academicians and researchers for carrying out their SAAS or PAAS-oriented Programming. In current research work, Free and Open Source (FOSS) Java-based CloudSim Tool has been used to actively portray customization to the Cloud Framework for better performance, using multiple attributes/resources such as Virtual Machine (VM), MIPS Requirement (million instructions per second), RAM, Bandwidth (BW), and Number of Processors required. A user is prompted to ascertain his requirements and they are allocated depending on his day-to-day dynamic needs.
Efficient Utilization of Dependency Pattern and Sequential Covering for Aspect Extraction Rule Learning

The use of dependency rules for aspect extraction tasks in aspect-based sentiment analysis is a promising approach. One problem with this approach is incomplete rules. This paper presents an aspect extraction rule learning method that combines dependency rules with the Sequential Covering algorithm. Sequential Covering is known for its characteristics in constructing rules that increase positive examples covered and decrease negative ones. This property is vital to make sure that the rule set used has high performance, but not inevitably high coverage, which is a characteristic of the aspect extraction task. To test the new method, four datasets were used from four product domains and three baselines: Double Propagation, Aspectator, and a previous work by the authors. The results show that the proposed approach performed better than the three baseline methods for the F-measure metric, with the highest F-measure value at 0.633.
Implementation of Pharmaceutical Drug Traceability Using Blockchain Technology

The healthcare industry relies heavily on the use of pharmaceutical drugs to treat patients, and acquires said drugs using supply chain management. However, fraud and abuse cases in current healthcare industry are a major problem, costing the industry billions of dollars annually. Furthermore, counterfeit drugs also plague the healthcare industry, which is a major health concern to patients who consume said drugs. To solve these problems, a system is required to trace pharmaceutical drugs as they travel the supply chain, from the provider of the ingredients to produce pharmaceutical drugs, to its consumers. The proposed project will implement blockchain, an emerging technology that enables decentralized storage of data and immutable data. Blockchain stores data in a distributed ledger visible to all participants, which will create transparency in the supply chain, a much-needed change, which are presently very complex and opaque. Blockchain records the transaction details of relevant participants involved in the supply chain process as pharmaceutical drugs move through the supply chain.
Secure Merge with O(n log log n) Secure Operations

Data-oblivious algorithms are a key component of many secure computation protocols.In this work, we show that advances in secure multiparty shuffling algorithms can be used to increase the efficiency of several key cryptographic tools.The key observation is that many secure computation protocols rely heavily on secure shuffles. The best data-oblivious shuffling algorithms require O(n log n), operations, but in the two-party or multiparty setting, secure shuffling can be achieved with only O(n) communication.Leveraging the efficiency of secure multiparty shuffling, we give novel, information-theoretic algorithms that improve the efficiency of securely sorting sparse lists, secure stable compaction, and securely merging two sorted lists.Securely sorting private lists is a key component of many larger secure computation protocols. The best data-oblivious sorting algorithms for sorting a list of n elements require O(n log n) comparisons. Using black-box access to a linear-communication secure shuffle, we give a secure algorithm for sorting a list of length n with t ≪ n nonzero elements with communication O(t log² n + n), which beats the best oblivious algorithms when the number of nonzero elements, t, satisfies t < n/log² n.Secure compaction is the problem of removing dummy elements from a list, and is essentially equivalent to sorting on 1-bit keys. The best oblivious compaction algorithms run in O(n)-time, but they are unstable, i.e., the order of the remaining elements is not preserved. Using black-box access to a linear-communication secure shuffle, we give an information-theoretic stable compaction algorithm with only O(n) communication.Our main result is a novel secure merge protocol. The best previous algorithms for securely merging two sorted lists into a sorted whole required O(n log n) secure operations. Using black-box access to an O(n)-communication secure shuffle, we give the first multi-party secure merge algorithm that requires only O(n log log n) communication. Our algorithm takes as input n secret-shared values, and outputs a secret-sharing of the sorted list. All our algorithms are generic, i.e., they can be implemented using generic secure computations techniques and make black-box access to a secure shuffle. Our techniques extend naturally to the multiparty situation (with a constant number of parties) as well as to handle malicious adversaries without changing the asymptotic efficiency.These algorithm have applications to securely computing database joins and order statistics on private data as well as multiparty Oblivious RAM protocols.
Exclusion and Inclusion: A Model Agnostic Approach to Feature Importance in DNNs

Deep Neural Networks in NLP have enabled systems to learn complex non-linear relationships amongst words and phrases. Yet, one of the major bottlenecks for leveraging DNNs for real world applications is their characterization as black boxes. To solve this problem, we introduce a novel model agnostic algorithm which calculates phrase-wise importance of input features. We showcase generalizability of our method to a diverse set of tasks, by carrying out experiments for both Regression and Classification. We also observe that our approach works for short and long texts and is robust to outliers, implying that it captures the essential aspects of the input.
Robust Image Encryption in Transform Domain Using Duo Chaotic Maps—A Secure Communication

The increase of cyberattacks in the field of information security leads to high attention in the digitalized environment. There is a demand for well-organised methods to transmit data securely over the Internet. In the proposed algorithm, a greyscale image is secured by an encryption technique by two stages, i.e. confusion and diffusion. Digital images can be expressed in terms of numeric values called pixels. The images are converted by the integer wavelet transform-domain technique, where the images are separated by approximation and detailed sub-bands. The proposed encryption algorithm is implemented for the approximated sub-bands which contain significant information of the digital image. 1D logistic and 2D tent maps generate chaotic random keys. By various statistical and differential analyses, the robustness of the proposed algorithm is examined by achieving a maximum entropy of 7.997, near-zero correlation and larger keyspace of 1080. With the results, it has confirmed that the enhanced chaos-based Integer Wavelet Transform (IWT) encryption has succeeded to resist any cyberattacks.
DyEnTRAM- Dynamically Enhanced Metadata based Approach for Bug Assignment

Background: In open source repositories, daily numerous bugs are reported and making manual triaging difficult as well as time consuming. Aim: In this paper, we proposed a Dynamically Enhanced Metadata based approach for bug assignment (DyEnTRAM). Unlike TRAM, that worked on additional metadata features which are selected by Feature Selection (FS) algorithms that empirically analyzed the feature value and top value features are selected for triaging. Methods: The work is focused to enhance the bug features as well as rational choice of FS algorithm to improve the accuracy of developer prediction. Approach validation is done on four open- source projects and three machine learning based classifiers namely: Naive-Bayes (NB), SVM and Decision-Tree (C4.5). This approach is only worked with highly ranked meta-data fields which are selected by FS algorithms.Result: This approach has shown better prediction accuracy over the Baseline, X2 and TRAM. Findings have shown F-Score improvements in DyEnTRAM over TRAM approach as much as 24.6%, 10.9%, 16.4%, and 18.2% for Eclipse, Netbean, Firefox and Freedesktop projects respectively. Conclusion: DyEn-TRAM approach effectively improved bug prediction accuracy on the chosen datasets as compared to TRAM, X2, and baseline.
Implementation of a Cryptograpgy Algorithm for Image Transmission

We will present an RSA algorithm designed for remote visualization of medical images with data security transfer. This interface is implemented under MATLAB environment. The implementation of the image cryptography system uses the RSA algorithm with 64 bits private key length. The transfer of images in a secure way for medical diagnosis is insured by generating a watermarked key to encrypt the original image. More, we introduced a comparison study between the obtained performances and those computed with other algorithms such as AES, DES and IDEA.
The Virtual Office of the Future: Are Centralized Workplaces Obsolete?

ABSTRACT The worldwide spread of coronavirus is vigorously affecting our everyday life and many industries. Unforeseen, a significant number of workforces are required to work from home, impacting creativity, work performance, and social interaction. Video conferencing is consequently substituting in-person meetings, and new workplaces are arranged in domestic environments, causing a fundamental shift in how employees work and interact. To lower the unfavorable impact of continuous telecommuting, we highlight virtual reality technology as a potential solution to enhance domestic workplaces. In this position paper, we discuss the opportunities and current challenges for working in virtual reality. We focus on two application scenarios and present recent solutions to enable knowledge workers to work and interact in virtual reality and trends on how virtual reality services could substitute video conferencing. As a result, we envision a virtual office of the future, making centralized workplaces obsolete and highlight open research questions to realize productive and pleasant work in virtual reality. Keywords mixed reality, virtual reality, workplaces, virtual office, collaboration, COVID-19, SARS-CoV-2 ABOUT THE AUTHOR/S PASCAL KNIERIM LMU Munich pascal.knierim@lmu.de Pascal Knierim is a researcher in the Human-Centered Ubiquitous Media group at the LMU Munich, Germany. Prior, he was at the Human-Computer Interaction and Cognitive Systems group at the University of Stuttgart. His research focus includes augmented and virtual reality as ubiquitous computing technology. He is investigating the lifecycle of mixed reality applications and how they will influence our everyday life. Knierim has worked for Nokia and Microsoft Research in Cambridge. ALBRECHT SCHMIDT LMU Munich albrecht.schmidt@ifi.lmu.de New Future of Work 2020, August 3–5, 2020 © 2020 Copyright held by the owner/author(s).
Potential relationship between self-efficacy beliefs and proficiency in grammar among tertiary EFL learners

A multitude of studies on self-efficacy beliefs have been undertaken to date, especially in language learning. However, little evidence is given on looking into the relationship between self-efficacy and English grammar. To this end, the present study goes about identifying to what extent the correlation between learners’ self-efficacy and their achievements in the grammar test is. Drawing on the correlational design, an English grammar test was administered to the learners to know the learners’ acquaintance with the English grammar. Meanwhile, a self-efficacy questionnaire was performed by the researcher to the learners to figure out to what extent their efficaciousness is. A Pearson-product moment correlation was performed to analyze the relationship between such variables. The result demonstrates that there is a high positive significant correlation between learners’ self-efficacy and their attainments in the grammar test, displayed by r Correlation = +1. This finding brings a recent insight in the field of language learning.
Survey on Object Tracking using Deep Learning Paradigms

The field of object tracking extends across different domains. It is a major key player in the field of image processing and pattern recognition. Object tracking is the process of tracking an object over a continuous sequence of image frames to determine over time the relative movements or changes. With the massive advancements in the field of deep learning, the use of deep neural networks has risen due to their impressive accomplishments in object detection and tracking. In this Survey, the objective is to give a comprehensive overview of the recent attempts in the field of object tracking with a focus on the use of deep learning techniques and algorithms. The paper is divided into four sections; at first, we will give an overview of the recent work to highlight the techniques and methods which have been used in object tracking using deep learning. The second section focus is on the object tracking that uses convolutional networks techniques. The third section focuses on some of the recurrent neural networks to tack objects. The final section is concentrated on auto-encoders object tracking.
E-195 A mixed reality spatial computing framework for preprocedural evaluation of cerebral aneurysms: approach and preliminary results

<h3>Introduction/Purpose</h3> Mixed Reality (MxR) is an emerging technology that makes seamless connections between virtual space and the real world by superimposing computer-generated information onto the real-world environment. MxR can provide additional information in a more intuitive and natural way than alternative information-delivery methods such as traditional angiographic monitors, holograms, virtual or augmented reality models or 3D printed models. Users are able to experience realistic 3D virtual elements with augmented depth perception and binocular field of view. Newer technology has now allowed for interaction with 3D objects within these virtual environments through the use of hand gestures or hand controllers. The authors describe our preliminary experience with MxR as an adjunct tool to traditional angiographic imaging in the preprocedural workup of patients with complex aneurysms using a novel spatial computer, the Magic Leap One device (Magic Leap, Inc <i>Plantation, Florida</i>) which uses a virtual retinal display, which superimposes 3D computer-generated imagery over real world objects, by projecting a digital light field into the user’s eye. <h3>Materials and Methods</h3> Tomographic Angiographic (DynaCT) data was imported and segmented to create 3D meshes of the intracranial vasculature. The 3D meshes were then projected into MxR space, allowing the operator to inspect the vasculature using a MxR headset (Magic Leap) as well as interact with the aneurysm and adjacent vessels (handling, rotation, magnification, and sectioning) using hand gestures or hand controllers. <h3>Results</h3> 3D segmentation of a complex aneurysms was successfully performed and projected into MxR. Conventional and MxR visualization modes were equally effective in identifying and classifying the pathology. MxR visualization allowed the operators to manipulate the dataset to achieve a greater understanding of the anatomy of the parent vessel, the angioarchitecture of the aneurysm, and the surface contours of all visualized structures. <h3>Conclusion</h3> This preliminary study demonstrates the feasibility of utilizing MxR for preprocedural evaluation in patients with anatomically complex neurovascular disorders. This novel visualization approach may serve as a valuable adjunct tool in deciding patient-specific management, including decisions on prognostication and open surgical and endovascular treatment options. <h3>Disclosures</h3> <b>G. Deib:</b> None. <b>D. Smith:</b> None. <b>B. Chaudhary:</b> None. <b>S. Boo:</b> None. <b>A. Tarabishy:</b> None. <b>J. Carpenter:</b> None. <b>A. Rai:</b> None.
Perturbative complexity of an interacting theory

We present a systematic method to expand the quantum complexity of interacting theory in series of coupling constant. The complexity is evaluated by the operator approach in which the transformation matrix between the second quantization operators of reference state and the target state defines the quantum gate. We start with two coupled oscillators and perturbatively evaluate the geodesic length of the associated group manifold of gate matrix. Next, we generalize the analysis to $N$ coupled oscillators which describes the lattice $\lambda\phi^4$ theory. Especially, we introduce simple diagrams to represent the perturbative series and construct simple rules to efficiently calculate the complexity. General formulae are obtained for the higher-order complexity of excited states. We present several diagrams to illuminate the properties of complexity and show that the interaction correction to complexity may be positive or negative depending on the magnitude of reference-state frequency.
Secure Mobile-Server Communications Using Vector Decomposition Problem

Rapid advancement in the communication sector through mobile networks has made handheld devices such as smartphones and tabs as a medium for most of their private transactions and communications. This necessitates the speed and efficiency of communication at a lower cost, without compromising the security. The proposed scheme is an authenticated key agreement protocol for the communication between the user and the service provider. This scheme supports batch verification and reduces the number of verification steps required and is based on the hardness of the vector decomposition problem (VDP).