Reviewerly/exHarmony huggingface dataset:
A Privacy-Preserving Authentication and Key Agreement Scheme with Deniability for IoT

User authentication for the Internet of Things (IoT) is a vital measure as it consists of numerous unattended connected devices and sensors. For security, only the user authenticated by the gateway node can access the real-time data gathered by sensor nodes. We present an efficient privacy-preserving authentication and key agreement scheme for IoT, which enables the user, the gateway node and sensor nodes to authenticate with each other. Only the trusted gateway node can determine the real identity of the user; however, no other entities can get information about user’ identity by just intercepting all exchanged Cyber threats are a global risk that governments, the private sector, non-governmental organizations – and the global community as a whole – must deal with. Chatham House focuses on building cyber capacity and expertise among policymakers, investigating key issues through publishing in-depth policy research, conducting cyber simulation exercises, and convening high-level meetings with a wide group of stakeholders. messages during authentication phase. The gateway cannot prove the received messages from the sender to a third party, and thus preserving the privacy of the sender. The correctness of the proposed scheme is proved to be feasible by using BAN logic, and its security is proved under the random oracle model. The execution time of the proposed scheme is evaluated and compared with existing similar schemes, and the results demonstrate that our proposed scheme is more efficient and applicable for IoT applications. The economic and social benefits of digital technology have transformed the world as we know it, but have introduced high risks through its malicious use by both state and non-state actors. These risks affecting economies, societies and livelihoods, and are threatening international peace and security.
Australian Attitudes Towards Privacy of Information: Will COVID-19 Make a Difference?

There has always been tension between security needs (as expressed by a nation-state) and privacy needs (as expressed by the citizens of said nation-state). Achieving this balance is perhaps one of the goals of statecraft. Terrorist attacks tend to shift the balance towards security, whilst proponents of civil liberties tend to want to move the balance in the other direction. We examine Australian attitudes to privacy in the light of the COVID-19 pandemic and consider whether the effect of the pandemic is likely to change Australian’s perception of their fundamental right to privacy, as determined by law, enabled by technology and shaped by human concerns.
Essay Writing Skill of the Fourth Semester Students of STKIP PGRI Bandar Lampung

The problem raised in this study is about the ability and difficulty in writing essays.Research used a descriptive method.Data obtained from the essay writing task with the topic that has been provided, then the data are analyzed.The subject in this study were 25 students.From the results of the analysis in terms of authenticity and logic, the completeness of the essay, the contents of the essay, as well as
THE EFFECT OF LEARNING MEDIA AND INTEREST IN LEARNING ON ENGLISH LEARNING OUTCOMES

&lt;p&gt;This study aims to determine the Effect of Learning Media Influence and Interest in Learning Outcomes of English in Public Junior High School Students in Lebak Banten. Furthermore,the researcher to find out the effect of learning media interaction and learning interest on learning outcomes using the quantitative experiment method. This study used population of 583 students and sample of 70 students. The research hypotheses tested include: 1) There is a significant effect of learning media on learning outcomes. 2) There is a significant effect of interest in learning on learning outcomes. 3) There is a significant interactive influence on learning media and interest in learning about learning outcomes. Then from the results of the hypothesis test, it was found that 1) there is a significant effect of learning media on the learning outcomes of English students of Lebak region at Junior High School. This is evidenced by the acquisition of the Sig. = 0,000 &amp;lt;0,05 and F count = 16,334. 2) There is a significant effect of interest in learning on the learning outcomes of English students in Lebak region at Junior High School. This is evidenced by the acquisition of Sig. = 0,000 &amp;lt;0,05 and F count = 15,127. 3) There is a significant interaction effect of learning media and learning interest in the learning outcomes of English students of Lebak region Junior High School. This is evidenced by the acquisition of Sig. = 0,000 &amp;lt;0,05 and F count = 13,833.&lt;/p&gt;
Development Of Network Interaction Model “School-University-Factory” On Regional Level

Nowadays the model of Russian secondary and higher education has been significantly transformed leading to the increase of interest to the formation of practical competences in students. The authors consider the fact that currently the state of pedagogical system being quite conservative is changed only as a result of qualitative shifts of its inner structure so any nonsystematic influence is absorbed and dissipated. The present article is intended to justify a complex approach to train highly-qualified specialists for Russian enterprises that implement network knowledge-competence model as an additional direction. The research made allowed the authors to formulate basic competences being the most important from the viewpoint of staff preparation in the course of innovation economy development. The model of network interaction “School – University – Factory” has been developed. The authors point out that this approach can be successful when many factors such as the level of teachers and tutors qualification, the presence of technological platforms in partnership with specialized enterprises, the creation of intellectual infrastructure. As a result the authors make the conclusion about the practice-oriented approach to teach future specialists based on three components “School – University – Factory” being the efficient one. This system of additional education can help forming innovational thinking of future specialists. The whole process here is aimed at the creating interactive educational environment that develops professional competences, viz. forming the ability to generate innovations; developing innovation culture. This aim, therefore, provides the reliable basis for creation and development of innovation-oriented human resources of Russian industry.
Non-Compliance with COVID-19 Screening in Pakistan

Objectives: To quantify the non-complaint portion of the general public – not wanting to be screened for COVID-19 and find the reason for this non-compliance, in the general public of Rawalpindi Pakistan.&#x0D; Study Design: Cross-sectional survey.&#x0D; Place and Duration of Study: General public of Rawalpindi, Pakistan. From June 19, 2020, to June 21, 2020.&#x0D; Methodology: A questionnaire was constructed based on a local study, it was injected to the accessible online population through Google Forms. Surveyors collected data from the illiterate population on printed proforma. A sample of 1108 was collected. IBM® SPSS® was used for data analysis. For categorical data, frequencies and percentages were calculated. A Chi-square test was applied for statistical significance.&#x0D; Results: 45.3% of participants were females, 54.7% were males. 37.9% of participants were married and 62.1% were unmarried. 3.8% were illiterate, 40.4% were matriculated and 47.1% had education higher than intermediate. 38.3% was non-compliant population – didn’t want to get screened for COVID-19. 30.7% were non-compliant because of ‘fear of isolation/ quarantine with other COVID-19 patients, leading to worsening of disease’ followed by 26.9% who ‘don’t trust the reliability of the test’. Gender and Education level variables were statistically significant in determining non-compliance. Marital status was found non-significant.&#x0D; Conclusion: A significant portion of the population i.e. 38.3% showed non-compliance with COVID-19 screening, which was statistically associated with gender and education level.
A Semantic Perspective on Omission Abstraction in ASP

The recently introduced notion of ASP abstraction is on reducing the vocabulary of a program while ensuring over-approximation of its answer sets, with a focus on having a syntactic operator that constructs an abstract program. It has been shown that such a notion has the potential for program analysis at the abstract level by getting rid of irrelevant details to problem solving while preserving the structure, that aids in the explanation of the solutions. We take here a further look on ASP abstraction, focusing on abstraction by omission with the aim to obtain a better understanding of the notion. We distinguish the key conditions for omission abstraction which sheds light on the differences to the well-studied notion of forgetting. We demonstrate how omission abstraction fits into the overall spectrum, by also investigating its behavior in the semantics of a program in the framework of HT logic.
M-Learning and Student Engagement in English Language Teaching: The Case of First-YearUndergraduate Students at Ecole Normal Superieur,Algeria

The aim of the current paper is to explore the attitudes of teachers, students, and institutional leaders toward m-learning and student engagement within Algerian context.Researches explain such practices bear traditional approach and overlooks modern teaching methods such as mlearning.That is why the research output of exploring student engagement in respect of mlearning was obtained from the following aims (1) To evaluate the current practice of English language teaching within Algerian higher education institutions, (2) To explore how social constructivism theory and m-learning help student engagement in the classroom and (3) To explore the feasibility and acceptability of m-learning amongst institutional leaders.The methodology underpins a case study and action research.For the case study, the researcher engaged with seven teachers, four institutional leaders, and 30 students.For the action research, the researcher applied an intervention course to investigate the possibility and implications for future implementation of m-learning in higher education institutions.The results were deployed using thematic analysis.The research outcome showed that the disengagement of students in English language learning has many aspects.As seen from the interviews from the teachers, the researcher found that they do not have enough resources except for using ppt for some teacher.According to them, the teaching method they are using is mostly based on Grammar Translation Method.Teachers informed that students are disengaged because they have psychological barriers.In classroom setting, the students are conscious about social approval from the peer, and thus if they are to face negative reinforcement which would damage their image, it is seen as a preventive mechanism to be scared of making mistakes.This was also very reflective in this finding.A lot of other arguments can be given for this claim; however, in Algerian setting, it is usual practice where teachers do not provide positive reinforcement which is open up students for possible learning.Thus, in order to overcome the psychological barriers, proper measures can be taken.Unlike institutional leaders, it was evident that teachers and students provided positive feedback for using m-learning.It is not only motivating but also engaging in learning processes.Apps such as Kahoot, Padlet and Slido were well received and thus can be taken further to examine its higher impact in Algerian context.Thus, in the future, it will be important to implement m-learning effectively in higher education to transform the current traditional practices into modern, innovative and active learning.Persuasion for this change for institutional leaders may be challenging; however, its long-term benefits can be reflective from the current research paper.
Modified error correction method using one-time pad in qkd systems

This paper analyzes and adapts the known method of error correction of CV-QKD systems, proposed by Mario Milicevic, which modulates a code word with a correlated Gaussian sequence in amplitude and phase quadratures of coherent states, for use in DV-QKD systems, in which information is encoded by single-photon polarization states, by using a sieved key in the form of classical bits, from which the codeword is created, and also a one-time pad (Vernam cipher), which uses a fairly easy to implement classic Boolean “exclusive OR” operation (XOR). The main task of error correction is to correct errors in order to share the same secure key between the two parties (usually called Alice and Bob). Various factors can cause errors. The unreliability of the quantum channel is due to the fact that photons can cause noise when changing the polarization vector of the photon. In the proposed solution, the quantum component of the protocol occurs only in the first stage of transmission of the protected key, where the exchange of photons. The quantum key distribution system has inevitable errors in the sieved key, which must be corrected by the error correction algorithm to create a secure key. Unlike other known QKD systems, where at the stage of error correction the sifted keys are corrected and passed to the next stage of increasing confidentiality, in the modified method it is proposed to use sifted keys as keys in disposable Vernam ciphers, and the vector that will go to the next stage way and combine with the sifted key. The difference in the sieved keys between the two parties is corrected by means of low-density parity check matrices (LDPC), which are known to both of them in advance. Parity check matrices are created by an algorithm proposed by David MacKay and Radford Neal. Radford Neal open-source program code, is used to create final work program to checking proposed algorithm.
PEMBENAHAN WEB PROFIL SINODE GEREJA KRISTEN JAWA

The GKJ Synod Web had undergone several modifications independently. It led to a vulnerability condition that cost system breaches. Building the web application independently in limited security resource was the main problem for GKJ Synod. In order to resolve the problem, the GKJ Synod collaborated with FTI UKDW. Wordpress was implemented to restore the the GKJ Synod web. The restoration process, requirement and content analysis, and information architecture design. Based on the information architecture design, the website had been setup and then the team empowered the Data and Multimedia Information Service Center of GKJ Synod to maintain the web application and the contents. The installed WordPress utilised the VPS service with an additional SSL security protocol that provides development support and security. Thie web application project will continue to the next stage which is online document management services.
Reasoning with Contextual Knowledge and Influence Diagrams

Influence diagrams (IDs) are well-known formalisms, which extend Bayesian networks to model decision situations under uncertainty. Although they are convenient as a decision theoretic tool, their knowledge representation ability is limited in capturing other crucial notions such as logical consistency. In this article, we complement IDs with the light-weight description logic (DL) EL to overcome such limitations. We consider a setup where DL axioms hold in some contexts, yet the actual context is uncertain. The framework benefits from the convenience of using DL as a domain knowledge representation language and the modelling strength of IDs to deal with decisions over contexts in the presence of contextual uncertainty. We define related reasoning problems and study their computational complexity.
Bleeding-Edge Techniques

This chapter will focus on theory behind some bleeding-edge techniques and will prepare you to solve problems in univarient and multivarient data for time-series models using deep learning (covered in Chapters 6 and 7). In this chapter, we’ll start with an introduction to neural networks by reviewing perceptrons, activation functions, backpropagation, types of gradient descent, recurrent neural networks, long short-term memory, gated recurrent units, convolutional neural networks, and auto-encoders.
Secure and Verifiable Multi-Party Computation Using Indistinguishability Obfuscation

In most practical cloud computing applications such as e-voting, auctions, health, and financial applications or cloud services in common, to prove the exactness of outsourced data is one of the major needs today.Most of the time, third party auditing is employed for this task.This auditing work is controlled by assigning the secret inputs to an entity trusted third party, or worker, who is liable for performing computations and hand over the result of the computation to the cloud users or clients.To verify the integrity of computations using traditional cryptographic techniques, the time required to generate and validate the proof is a major computation issue.This paper proposes an improved public auditing technique for multi-party computation to check the integrity of outsourced data using a cryptographic solution.Many researchers have given auditing protocols that generate and verify proof using a cryptographic solution.Most of these scheme uses Non-Interactive Zero-Knowledge Proof (NIZK) which are basically built on bilinear map technology.The verification time using these existing technique is computationally expensive which affect the performance of the auditing system.We propose an efficient protocol that verifies the result correctness using modern cryptographic technique Indistinguishability Obfuscation.The proposed system works in two phases, (i) auction and (ii) audit.During the auction phase, multiple clients share their encrypted bid value to the worker.The worker generates auction result and proof using Pedersen Commitment Scheme.The audit phase starts only after the completion of the auction phase which results in reduced verification time.During the Audit phase, clients can verify the integrity of results using NIZK with the IO technique.The results for reduced verification time in auction system have been presented.It is found that the performance of the proposed system has improved compared to the pertinent NIZK Proof technique.In our setting, we assumed that a worker is one of the trusted entity.By this notion, our protocol also guarantees privacy to the clients during the audit phase.
Maturity Model for Successful Cost Transformation in ETO Companies

Companies are more and more required nowadays to monitor and to improve their cost structure. Hereby, ETO enterprises experience particular difficulties, due to the high complexity and dynamics as well as less opportunities for standardization which are an intrinsic part of their products and processes. Therefore, a systematic and holistic approach for cost management is needed, considering hard factors as well as soft factors, like organizational and behavioral aspects. In this paper, we introduce a product cost maturity model, which integrates a multitude of success factors for cost transformation from different categories in an ETO environment. Hereby companies will be enabled to determine and evaluate their current state as well as a future state to derive a roadmap for necessary actions. The maturity model is based on a thorough literature research and on practical experiences in ETO companies. It is complemented with a systematic procedure for cost transformation projects. We describe the maturity model and its application as far as possible in detail, hereby also justifying every design decision we made.
The Needs of Functional Academic Teaching Materials for Special Education Teachers With Visual Impairment

Functional academic learning is crucial for students with visual impairment, since it is a basis for problem solving in life.This learning aims to increase students' independence in daily life.The purpose of this study was to determine the needs of functional academic teaching materials for special teachers of students with visual impairment.The research implemented descriptive qualitative method.The subjects of this study were teachers at one of SLB for the students with visual impairment in Yogyakarta.Data collection was conducted in this study by using observation, interview, and documentation techniques.The data was analyzed by using qualitative descriptive analysis techniques.The results of the study showed that the special teachers of students with visual impairment require functional academic teaching materials that are more organized and systematic based on the learning stages with the syntax of contextual learning models.Good teaching materials should have brief, communicative, solid, and systematic language use.The scope of the content contained in teaching material should be suitable with the students' conditions as the learning subjects.
Deteksi Dini Status Keanggotaan Industri Kebugaran Menggunakan Pendekatan Supervised Learning

In the fitness industry, the number of members is a major factor for the sustainability of its business. The ability of managers and trainers to detect members who represent traits to quit membership is critical. Four supervised learning classification methods like Support Vector Machine, Random Forest, K-Nearest Neighbor, and Artificial Neural Network were used to generate early detection using two variants of datasets that have different amounts of data. Classification results are separated into three different zones, which are Green Zone, Yellow Zone, and Red Zone. Artificial Neural Network methods using backpropagation training give 99.90% of accuracy on a dataset which has more amount of data. The evaluation has been done using the confusion matrix and AUC-ROC curves.
KTRICT A KAZE Feature Extraction

To improve the retrieval accuracy in CBIR system means reducing this semantic gap. Reducing semantic is a necessity to build a better, trusted system, since CBIR systems are applied to a lot of fields that require utmost accuracy. Time constraint is also a very important factor since a fast CBIR system leads to a fast completion of different tasks. The aim of the paper is to build a CBIR system that provides high accuracy in lower time complexity and work towards bridging the aforementioned semantic gap. CBIR systems retrieve images that are related to query image (QI) from huge datasets. The traditional CBIR systems include two phases: feature extraction and similarity matching. Here, a technique called KTRICT, a KAZE-feature extraction, tree and random-projection indexing-based CBIR technique, is introduced which incorporates indexing after feature extraction. This reduces the retrieval time by a great extent and also saves memory. Indexing divides a search space into subspaces containing similar images together, thereby decreasing the overall retrieval time.