Reviewerly/exHarmony huggingface dataset:
COMPUTATIONALLY EFFICIENT PATH PLANNING ALGORITHM FOR AUTONOMOUS VEHICLE

This paper analyses an experimental path planning performance between the Iterative Equilateral Space Oriented Visibility Graph (IESOVG) and conventional Visibility Graph (VG) algorithms in terms of computation time and path length for an autonomous vehicle. IESOVG is a path planning algorithm that was proposed to overcome the limitations of VG which is slow in obstacle-rich environment. The performance assessment was done in several identical scenarios through simulation. The results showed that the proposed IESOVG algorithm was much faster in comparison to VG. In terms of path length, IESOVG was found to have almost similar performance with VG. It was also found that IESOVG was complete as it could find a collision-free path in all scenarios.
HRCenterNet: An Anchorless Approach to Chinese Character Segmentation in Historical Documents

The information provided by historical documents has always been indispensable in the transmission of human civilization, but it has also made these books susceptible to damage due to various factors.Thanks to recent technology, the automatic digitization of these documents are one of the quickest and most effective means of preservation.The main steps of automatic text digitization can be divided into two stages, mainly: character segmentation and character recognition, where the recognition results depend largely on the accuracy of segmentation.Therefore, in this study, we will only focus on the character segmentation of historical Chinese documents.In this research, we propose a model named HRCenterNet, which is combined with an anchorless object detection method and parallelized architecture.The MTHv2 dataset consists of over 3000 Chinese historical document images and over 1 million individual Chinese characters; with these enormous data, the segmentation capability of our model achieves IoU 0.81 on average with the best speedaccuracy trade-off compared to the others.Our source code is available at https://github.com/Tverous/HRCenterNet.
Active-Standby for High-Availability in FaaS

Serverless computing is becoming more and more attractive for cloud solution architects and developers. This new computing paradigm relies on Function-as-a-Service (FaaS) platforms that enable deploying functions without being concerned with the underlying infrastructure. An important challenge in designing FaaS platforms is ensuring the availability of deployed functions. Existing FaaS platforms address this challenge principally through retrying function executions. In this paper, we propose and implement an alternative fault-tolerance approach based on active-standby failover. Results from an experimental evaluation show that our approach increases availability and performance compared to the retry-based approach.
Blockchain and Smart Contract Application for Zakat Institution

Blockchain is an open distributed database that carries out transactions on an open decentralized ledger. It is a technology that will probably be the source of a huge digital change especially in the financial sector. The application of this technology has started to take its first steps recently and its importance is undeniable in an emerging and expanding field such as Islamic finance. In this context, the purpose of this article is to study the integration of the blockchain and one of its important components, namely the smart contract in the management of the compulsory Islamic charity the zakat. To do this, we have developed a funding model linking all the stakeholders in question and the diversities of blockchain technology. We were thus able to conclude huge benefits and technical contributions in this context which encourages Islamic financial institutions to develop more models likely to support this technology without ignoring the compliance with the Islamic jurisprudence rules.
Multi-section images parallel encryption based on optical scanning holographic cryptography technology

In this paper, the function of parallel encrypting multiple images and reproducing arbitrary layers of images is realized by improving the double pupil function in optical scanning holography. In an optical scanning holography (OSH) system, a dual-pupil heterodyne incoherent image processing technique is used to record holographic images. By adjusting the two pupil functions in the optical system, the interference fringes can be modified to achieve different imaging effects. In this paper, the ring pupil and random phase plate are used to act as two pupil functions to interfere to form a ring random phase plate, and thus realizing the fast scanning of multi-layer images. Then the multi-layer images can be quickly encrypted by one imaging technique. The scanned signals are quickly collected by photoelectric detectors, and they synthesize encrypted holograms by computer. By using the digital holography to decrypt the holograms, the precise reproduction of any layer image can be achieved. The OSH system with random phase pupil is strongly dependent on the longitudinal position of the system in digital reconstruction. The defocusing noise can be converted into random noise and the effect of defocusing layer on imaging can be effectively suppressed. However, in practice, it is necessary to average multiple images to achieve better imaging effect, and the accuracy of random phase plate is required. In this paper, most of the random noise can be filtered with the aid of ring pupil, and all the information about multi-layer graphics can be recorded and reconstructed by one scan. In the process of reconstruction, the influence of defocusing image can be effectively eliminated, and the decryption of any layer image can be realized. This method collects encrypted image by photoelectric detector, and does not need complex algorithm reconstruction nor phase iteration, which greatly reduces the time expended in the encryption process. In the process of encryption, the key space of the system is increased, and the encrypted image obtained has high security. In this paper, correlation coefficient is used to evaluate the encryption effect of this method, and the effectiveness and security of this method are verified by simulation experiments. For cutting resistance, when 75% of the information is lost, the correlation coefficient can still reach more than 0.5. For the sensitivity of information, the integrity of decrypted image will be seriously damaged when the wavelength and distance shift very little. For the anti-noise ability, under the influence of Gauss noise and salt and pepper noise, the correlation coefficient and image recognition degree are high. This method is very time-saving, and the result of encryption has high security, high sensitivity, strong ability to resist clipping and noise.
Protocol: Triple Diamond method for problem solving and design thinking. Rubric validation

There is a set of tools that we can use to improve the results of each of the phases that continuous improvement projects must go through (8D, PDCA, DMAIC, Double diamond, etc.). These methods use divergent techniques, which help generate multiple alternatives, and convergent techniques that help analyze and filter the generated options. However, the tools used in all those frameworks are often very similar. Our goal, in this research, is to develop a comprehensive model that allows it to be used both for problem-solving and for taking advantage of opportunities. This protocol defines the main terms related to our research, makes a framework proposal, proposes a rubric that identifies observable milestones at each stage of the model and proposes the action plan to validate this rubric and the model in a given context. The action plan will be implemented in a future research.
Improving the Efficiency of Optimally-Resilient Statistically-Secure Asynchronous Multi-party Computation

We present an optimally-resilient, statistically-secure asynchronous multi-party computation (AMPC) protocol for n parties, capable of corrupting up to $$t < \frac{n}{3}$$ parties. Our protocol needs a communication of $$\mathcal {O}(n^4)$$ field elements per multiplication gate. This is to be compared with previous best AMPC protocol (Patra et al., ICITS 2009) in the same setting, which needs a communication of $$\mathcal {O}(n^5)$$ field elements per multiplication gate. To design our protocol, we present a simple and highly efficient asynchronous verifiable secret-sharing (AVSS) protocol, which is of independent interest.
Pluriversal design and desire-based design: desire as the impulse for human flourishing

A world of many centers is a world where multiple worlds can flourish—where communities outside of the Center can design their own life projects, which reflect who they are, what they value, and who their ancestors had been. This paper argues that a Pluriversal Design—which aims to nurture alternative models of life and ways of world- making—is necessarily desire-based, in contrast with conventional needs-based approaches. I make a case for Social Design researchers and practitioners to hone our craft to respond primarily to the communities' desire, in contrast with the current focus on their needs, problems and deficits. I argue that needs-based approaches are conservative, implying the reproduction of a model of life —i.e., what is ‘desirable’ is supposedly know from the start and/or externally defined. Such approaches do not encourage the creation of new ‘possibles’. On the other hand, a desire-based approach is open-ended. In terms of creating a world of many worlds, what is the final result? We do not know yet; we will be doing something that has never been done before. Metaphorically, desire-based social change is about trailblazing with the help of a compass. Desire is the force that we have to engage when our task is to create new ways of shaping the human presence on this planet and new ways of world-making—an open- ended process towards the Pluriverse.
The Use of Audio-Visual Materials as Strategies to Enhance Speaking Skills among ESL Young Learners

There are four main skills in English language namely listening, speaking, reading and writing respectively.Speaking skills is considered the most essential skills as it helps the learners to communicate with others effectively.Some of the factors that contributing to the low level of speaking skills are lack of exposure, low confidence level, and high level of anxiety towards English Language.Thus, these issues should be addressed in order to enhance ESL learners' speaking skills.In this 21 st -century learning and teaching, various strategies involving ICT have been invented by teachers to improve speaking skills among ESL learners.One of the strategies is the use of audio-visual materials to enhance speaking skills.An audio-visual material is a technology-based strategy that has gotten many positive results from the ESL learners.Therefore, it is believed that this strategy would develop speaking skills among ESL learners.Hence, this paper explains how audio-visual materials assist in improving speaking skills and the benefits of using audio-visual materials.
A Privacy-Preserving Protocol for the Kidney Exchange Problem

Kidney donations from living donors form an attractive alternative to long waiting times on a list for a post-mortem donation. However, even if a living donor for a given patient is found, the donor's kidney might not meet the patient's medical requirements. If several patients are in this position, they may be able to exchange donors in a cyclic fashion. Current algorithmic approaches for determining such exchange cycles neglect the privacy requirements of donors and patients as they require their medical data to be centrally collected and evaluated. In this paper, we present the first distributed privacy-preserving protocol for kidney exchange that ensures the correct computing of the exchange cycles while at the same time protecting the privacy of the patients' sensitive medical data. We prove correctness and security of the new protocol and evaluate its practical performance.
Transition from Serverfull to Serverless Architecture in Cloud-Based Software Applications

This paper makes a practical comparison between serverfull and serverless architectures for the same specific cloud application used for face recognition. It turns out that both approaches have advantages and disadvantages and their specific use needs to be carefully assessed in the design phase of the software life cycle.
Innovative Task Scheduling Algorithm in Cloud Computing

Abstract This work concentrates around the task scheduling depends on QoS and imperative of desire. Under nature of vibrant cloud computing, effectiveness improving of scheduling of task and load balancing are interminable issues. For clients, be that as it may, it’s progressively imperative to meet their necessities of QoS. This paper identifies with an improvement decency intention depends on new Berger’s model under the earth of vibrant cloud computing. As indicated by the distinctive kind of task scheduling, we portray the need of decency, proficiency and the Balance among advantage and reasonableness separately. We recompile the CloudSim and recreate the three undertaking task scheduling above based on expanded CloudSim individually. The exploratory outcomes show that this calculation portion not just meet the guideline of offering need to profit with because of thought to decency, yet additionally address clients’ issues of orchestrated QoS.
A Neural Relation Extraction Model for Distant Supervision in Counter-Terrorism Scenario

Natural language processing (NLP) is the best solution to extensive, unstructured, complex, and diverse network big data for counter-terrorism. Through the text analysis, it is the basis and the most critical step to quickly extract the relationship between the relevant entities pairs in terrorism. Relation extraction lays a foundation for constructing a knowledge graph (KG) of terrorism and provides technical support for intelligence analysis and prediction. This paper takes the distant-supervised relation extraction as the starting point, breaks the limitation of artificial data annotation. Combining the Bidirectional Encoder Representation from Transformers (BERT) pre-training model and the sentence-level attention over multiple instances, we proposed the relation extraction model named BERT-att. Experiments show that our model is more efficient and better than the current leading baseline model over each evaluative metrics. Our model applied to the construction of anti-terrorism knowledge map, it used in regional security risk assessment, terrorist event prediction and other scenarios.
Exploiting the Massey Gap

In this paper, we find new refinements to the Massey inequality, which relates the Shannon and guessing entropies, introducing a new concept: the Massey gap. By shrinking the Massey gap, we improve all previous work without introducing any new parameters, providing closed-form strict refinements, as well as a numerical procedure improving them even further.
DATA, INFORMATION AND IT SECURITY - SOFTWARE SUPPORT FOR SECURITY ACTIVITIES

Data protection, information and IT security became number one priorities in these fast- paced days that top management needs to focus on. A number of IT solutions have been developed on the market to address the security challenges that require prompt actions. These solutions contribute to a control environment that is robust and stand the potential threats. This research describes the framework of governance, risk and compliance and provides an integrated, holistic approach which helps to increase process performance and to ensure that the organization follows its own rules, risk appetite, and complies with external regulations. These systems fulfil a core role in the enterprise’s defense system. This research reviews the features of security packages relevant to IT GRC and provides an overview of the security elements and describes their main characteristics. This review covers the configuration database related to the enterprise business model; the business impact analysis; the risk management-, governance and compliance functions; the data security; the data protection and GDPR; the business continuity management; the network -, IoT - and industrial control system safety, the access - and log management. Embedding these solutions to the business and operations processes strengthens the response of an organization to the various risks and requirements that it faces and reduces the likelihood of major non-compliance or security gaps. Keywords: data protection, GRC software solutions, information security
Exploring wav2vec 2.0 on speaker verification and language identification

Wav2vec 2.0 is a recently proposed self-supervised framework for speech representation learning. It follows a two-stage training process of pre-training and fine-tuning, and performs well in speech recognition tasks especially ultra-low resource cases. In this work, we attempt to extend self-supervised framework to speaker verification and language identification. First, we use some preliminary experiments to indicate that wav2vec 2.0 can capture the information about the speaker and language. Then we demonstrate the effectiveness of wav2vec 2.0 on the two tasks respectively. For speaker verification, we obtain a new state-of-the-art result, Equal Error Rate (EER) of 3.61% on the VoxCeleb1 dataset. For language identification, we obtain an EER of 12.02% on 1 second condition and an EER of 3.47% on full-length condition of the AP17-OLR dataset. Finally, we utilize one model to achieve the unified modeling by the multi-task learning for the two tasks.
Topological States in Qubit Arrays Induced by Density-Dependent Coupling

Topological states of light open exciting possibilities in quantum photonics promising the topological protection of quantum entanglement. Here, we put forward an approach to realize the topological states of photon pairs mediated by the effective density-dependent coupling which is manifested as the dependence of the tunneling amplitude on the number of photons. As a specific platform, we investigate the arrays of nearest-neighbor coupled transmon qubits, where the effective density-dependent coupling is engineered by inserting auxiliary frequency-detuned resonators. We prove the topological origin of the designed model by the direct evaluation of the Zak phase highlighting the feasibility of our proposal for state-of-the-art fabrication technologies.
Genetic Information Insecurity as State of the Art

Genetic information is being generated at an increasingly rapid pace, offering advances in science and medicine that are paralleled only by the threats and risk present within the responsible systems. Human genetic information is identifiable and contains sensitive information, but genetic information security is only recently gaining attention. Genetic data is generated in an evolving and distributed cyber-physical system, with multiple subsystems that handle information and multiple partners that rely and influence the whole ecosystem. This paper characterizes a general genetic information system from the point of biological material collection through long-term data sharing, storage and application in the security context. While all biotechnology stakeholders and ecosystems are valuable assets to the bioeconomy, genetic information systems are particularly vulnerable with great potential for harm and misuse. The security of post-analysis phases of data dissemination and storage have been focused on by others, but the security of wet and dry laboratories is also challenging due to distributed devices and systems that are not designed nor implemented with security in mind. Consequently, industry standards and best operational practices threaten the security of genetic information systems. Extensive development of laboratory security will be required to realize the potential of this emerging field while protecting the bioeconomy and all of its stakeholders.
Robust autonomous flight in cluttered environment using a depth sensor

This paper presents a novel collision-free navigation system for the unmanned aerial vehicle based on point clouds that outperform compared to baseline methods, enabling high-speed flights in cluttered environments, such as forests or many indoor industrial plants. The algorithm takes the point cloud information from physical sensors (e.g. lidar, depth camera) and then converts it to an occupied map using Voxblox, which is then used by a rapid-exploring random tree to generate finite path candidates. A modified Covariant Hamiltonian Optimization for Motion Planning objective function is used to select the best candidate and update it. Finally, the best candidate trajectory is generated and sent to a Model Predictive Control controller. The proposed navigation strategy is evaluated in four different simulation environments; the results show that the proposed method has a better success rate and a shorter goal-reaching distance than the baseline method.
LINKCALCULATOR – AN EFFICIENT LINK-BASED PHISHING DETECTION TOOL

The problem of phishing attacks continues to demand new solutions as existing solutions are limited by various challenges such as high computational requirements, zero-day attacks, needs for updates, complex ruled-based, etc. Besides, the emerging mobile market demands simple solutions to phishing due to several factors such as memory, fragmentation, etc. In response to the above challenges, a simple anti-phishing tool called LinkCalculator is presented. The proposed LinkCalculator anti-phishing scheme is based on an algorithm designed to extract link characteristics from loading URLs to determine their legitimacy. Unlike the other link-based extraction approaches, the proposed approach introduced the concept of weight to represent the different links found in a URL. This is because certain link information within parsed webpages or requests is sufficient to classify them as phishing without loss of generality. The approach is experimented using a dataset of 300 instances consisting of 150 legitimate URLs and 150 phishing URLs from openly-available research datasets. The experimental results indicate a significance performance of 100%. True Negative Rate and 0.00% False Positive Rate for legitimate instances and True Positive Rate of 96.67% with 0.03 % False Negative Rate for phishing instances which indicate that the approach offers a more efficient lightweight approach to phishing detection.
Hierarchical Planning for Long-Horizon Manipulation with Geometric and Symbolic Scene Graphs

We present a visually grounded hierarchical planning algorithm for long-horizon manipulation tasks. Our algorithm offers a joint framework of neuro-symbolic task planning and low-level motion generation conditioned on the specified goal. At the core of our approach is a two-level scene graph representation, namely geometric scene graph and symbolic scene graph. This hierarchical representation serves as a structured, object-centric abstraction of manipulation scenes. Our model uses graph neural networks to process these scene graphs for predicting high-level task plans and low-level motions. We demonstrate that our method scales to long-horizon tasks and generalizes well to novel task goals. We validate our method in a kitchen storage task in both physical simulation and the real world. Our experiments show that our method achieved over 70% success rate and nearly 90% of subgoal completion rate on the real robot while being four orders of magnitude faster in computation time compared to standard search-based task-and-motion planner.