Reviewerly/exHarmony huggingface dataset:
A Consistent Systems Mechanics Model of the 3D Architecture and Dynamics of Genomes

Already for thousands of years mankind is aware of inheritance and its manipulation by mating and breeding. The discovery of the cell nucleus by A. van Leeuwenhook in the 17th century marks a start to elucidate the epically discussed evolutionary transfer of information in detail. Now after more than 170 years of research on the 3D architecture and dynamics of genomes and the co-evolved interaction networks of regulatory elements creating genome function - i.e. the storage, replication, and expression of genetic information—a consistent systems statistical mechanics genomics framework emerges for the first time. Obviously the structure and function of genomes co-evolved as an inseparable system allowing the physical storage, expression, and replication of genetic information. The DNA double helix and the nucleosome had been determined structurally at the very highest level already, including genome sequences and epigenetic histone modifications. That chromosomes form territories with functional relevant positioning within the cell nucleus and that chromosomal subdomains exist has been also determined to a fair degree of detail. Only recently, however, we were finally able to fill the much debated gap in-between by establishing that nucleosomes compact into a quasi-fibre folded into stable loops which form stable multi-loop aggregates/rosettes connected by linkers and hence creating chromosome arms and entire chromosomes. Interestingly, this has lead immediately to a consistent and cross-proven systems statistical mechanics genomic framework which is balancing stability/flexibility ensuring genome integrity, enabling expression/regulation of genetic information, as well as genome replication - all this in evolutionary perspectives as the natural outcome of Darwinian natural selection and Lamarkian self-referenced manipulation. Thus, genotype and phenotype are multilisticly entangled and beyond are embedded in genome ecology i(!)n- and environments. This not only opens the door to a true universal sequencing of genetic information, but also is the key for a general understanding of genomes, their function and evolution, as well as for applied diagnostics and treatment of disease, for future genome manipulation and engineering efforts, as far as the creation of artificial or extra-terrestrial live contexts.
Memory Augmented Matching Networks for Few-Shot Learnings

Despite many successful efforts have been made in one-shot/few-shot learning tasks recently, learning from few data remains one of the toughest areas in machine learning.Regarding traditional machine learning methods, the more data gathered, the more accurate the intelligent system could perform.Hence for this kind of tasks, there must be different approaches to guarantee systems could learn even with only one sample per class but provide the most accurate results.Existing solutions are ranged from Bayesian approaches to meta-learning approaches.With the advances in Deep learning field, meta-learning methods with deep networks could be better such as recurrent networks with enhanced external memory (Neural Turing Machines -NTM), metric learning with Matching Network framework, etc.In our research, we propose a metric learning method for few-shot learning tasks by taking advantage of NTMs and Matching Network to improve few-shot learning task's learning accuracy on both Omniglot dataset and Mini-Imagenet dataset.In addition, a weighted prototype is also introduced to improve the overall performance of the proposed model, especially on the complicated benchmark datasets such as mini-ImageNet.
Towards Blockchains for architectural design Consensus mechanisms for collaboration in BIM

We present a Blockchain collaboration mechanism on optimisation problems between distributed participants who work with building information modelling tools.The blockchain mechanism is capable of executing smart contracts, acting as a reward mechanism of independent designers attempting to collaborate or compete on optimising a design performance problem.Earlier work has described the potential integration through different levels of Computer Aided Design and Blockchain.We present an expanded version of that integration and we showcase how a team can collaboratively and competitively work, using BIM tools, through the blockchain.The original contribution of the paper is the use of the design optimisation performance as a consensus mechanism for block writing in blockchains.To accomplish that we introduce mechanisms for BIM to Blockchain Integration but also describe a special category of blockchains for architectural design and the built environment.The paper concludes with an analysis of the relationship between trust and values as encapsulated in the blockchain and how these could affect the design collaboration.
Development of Offshore Platform Stress Monitoring System based on Internet of Things Technology

This paper mainly analyzes the main external load types of offshore platforms and the current status of offshore platform health monitoring technology. On this basis, a platform health monitoring system which is consist of a wireless sensor network and a satellite communication system is an typical application of Internet of Things Technology in the field of offshore platform monitoring. This paper has a detailed discussion of the overall system and key equipment. It has certain reference significance to engineers and technicians in related fields.
Construction of Equipment Maintenance Guiding System and Research on Key Technologies Based on Augmented Reality

In order to solve the problems such as the complicated principle structure existing in the process of equipment maintenance, the inability of visual guidance with the maintenance technical manual, and the difficulty of ensuring the quality and safety of maintenance, a kind of maintenance method for the virtual-real fusion of equipment in the intelligent factory is proposed. Firstly, on the basis of analyzing the advantages of augmented reality technology applied to equipment maintenance, a system of equipment maintenance guiding based on augmented reality is constructed, and secondly, the key technologies involved in the maintenance guiding system are introduced, focusing on the key technologies such as 3D tracking registration technology, virtual-real masking technology and human-computer interaction technology. Finally, the research content of equipment maintenance guiding is introduced, and the operation process of the maintenance guiding system based on augmented reality is given.
Fostering oral presentation skills by the timing of feedback: an exploratory study in virtual reality

Abstract Although scholars emphasised the essence of feedback delivered on virtual reality-based tasks, it remains unclear whether the acquisition of students’ oral presentation skills can be enhanced by the timing of feedback. An exploratory study, recently conducted in a Dutch university, explores the potential differential impact of immediate versus delayed feedback within a virtual reality-based task, in which students present to a virtual audience and receive feedback generated by the computer on presentation behaviour. By making use of an experimental study design, the potential effects of immediate feedback are compared with a control condition of a virtual reality-based presentation task with delayed feedback directly provided after the presentation. Performance assessments, including validated rubrics for oral presentation skills, were used for data collection. The results demonstrated no differences between the impact of immediate and delayed feedback on students’ presentation performance. However, significant differences in performance were traceable for students from differing study domains. As such, students following a technical study showed lower presentation scores in comparison to students from non-technical higher education curricula. More studies are needed to investigate comprehensive learning environments on students’ presentation skills in virtual reality, since combining different forms of feedback could foster students’ learning outcomes.
Monogamy and polygamy relations of multiqubit entanglement based on unified entropy*

Monogamy relation is one of the essential properties of quantum entanglement, which characterizes the distribution of entanglement in a multipartite system. By virtual of the unified-( q , s ) entropy, we obtain some novel monogamy and polygamy inequalities in general class of entanglement measures. For the multiqubit system, a class of tighter monogamy relations are established in term of the α -th power of unified-( q , s ) entanglement for α ≥ 1. We also obtain a class of tighter polygamy relations in the β -th (0 ≤ β ≤ 1) power of unified-( q , s ) entanglement of assistance. Applying these results to specific quantum correlations, e.g., entanglement of formation, Renyi- q entanglement of assistance, and Tsallis- q entanglement of assistance, we obtain the corresponding monogamy and polygamy relations. Typical examples are presented for illustration. Furthermore, the complementary monogamy and polygamy relations are investigated for the α -th (0 ≤ α ≤ 1) and β -th ( β ≥ 1) powers of unified entropy, respectively, and the corresponding monogamy and polygamy inequalities are obtained.
Stakeholder approach to the implementation of the ‘third mission’ of universities

The implementation of the ‘third mission’ by universities is a significant area of research that has been explored by many Russian and international experts. The ‘third mission’ means engaging with society. Alongside education and research, it is an important factor in the successful development of a contemporary university. In this article, we explore how stakeholder theory, which is successfully employed in the management of large organisations, may be applied for the development of mechanisms for effective implementation of the ‘third mission’ by universities. We identify the main problems in organising stakeholder interactions at Russian universities and analyse possible strategies to improve the situation. We use the examples of Polish, Swedish, and Russian universities to illustrate the practical aspects of interactions at different levels between universities and stakeholders., forms, and methods in the field. Further, we propose a classification of key stakeholders of universities, describe their mutual relations, interests, and resources available to them as well as reflect on stakeholder participation models in educational management. Our findings may contribute to better management at Russian educational institutions and benefit national education authorities.
Efficient Infrequent Pattern Mining Using Negative Itemset Tree

In this work, weLu, Yifeng focus on a simple and fundamental question: How to find infrequent patterns, i.e. patternsRichter, Florian with small support value, in a transactional database. In variousSeidl, Thomas practical applications such as science, medical and accident data analysis, frequent patterns usually represent obvious and expected phenomena. Really interesting information might hide in obscure rarity. Existing rare pattern mining approaches are mainly adapted from frequent itemset mining algorithms, which either suffered from the expensive candidate generation step or need to traverse all frequent patterns first. In this paper, we propose an infrequent pattern mining algorithm using a top-down and depth-first traversing strategy to avoid the two obstacles above. A negative itemset tree is employed to accelerate the mining process with its dataset compressing and fast counting ability.
Interactive Learning with Corrective Feedback for Policies Based on Deep Neural Networks

Deep Reinforcement Learning (DRL) has become a powerful strategy to solve complex decision making problems based on Deep Neural Networks (DNNs). However, it is highly data demanding, so unfeasible in physical systems for most applications. In this work, we approach an alternative Interactive Machine Learning (IML) strategy for training DNN policies based on human corrective feedback, with a method called Deep COACH (D-COACH). This approach not only takes advantage of the knowledge and insights of human teachers as well as the power of DNNs, but also has no need of a reward function (which sometimes implies the need of external perception for computing rewards). We combine Deep Learning with the COrrective Advice Communicated by Humans (COACH) framework, in which non-expert humans shape policies by correcting the agent’s actions during execution. The D-COACH framework has the potential to solve complex problems without much data or time required. Experimental results validated the efficiency of the framework in three different problems (two simulated, one with a real robot), with state spaces of low and high dimensions, showing the capacity to successfully learn policies for continuous action spaces like in the Car Racing and Cart-Pole problems faster than with DRL.
Counterfactual logic gates

We present how basic logic gates including NAND, NOR and XOR gates can be implemented counterfactually. The two inputs (Bob and Charlie) and the output (Alice) of the proposed counterfactual logic gate are not within the same station but rather separated in three different locations. We show that there is no need to pre-arrange entanglement for the gate, and more importantly, there is no real physical particles traveling among Alice, Bob and Charlie during the information processing. Bob and Charlie only need to independently control the blocking and unblocking of the transmission channels that connect them to Alice. In this way, they can completely determine the state of a real photon at Alice's end, thereby leading to implement a counterfactual logic gate. The functionality of a particular counterfactual logic gate is determined only by an appropriate design of Alice's optical device. Furthermore, by utilizing the proposed counterfactual logic gates, we demonstrate how to counterfactually prepare the Greenberger-Horne-Zeilinger state and W state with three remote quantum objects, which are in superposition states of blocking and unblocking the transmission channel.
Algorithmic Strategies for a Fast Exploration of the TSP 4-OPT Neighborhood

The 4-OPT neighborhood for the TSP contains Θ(n 4) moves so that finding the best move effectively requires some ingenuity. Recently, de Berg et al. have given a Θ(n 3) dynamic program, but the cubic complexity is still too large for using 4-OPT in practice. We describe a new procedure which behaves, on average, slightly worse than a quadratic algorithm. This is much faster than the DP procedure, achieving speedups of two to three orders of magnitude on all instances we tested.
Software Process Capability Self-Assessment Support System Based on Task and Work Product Characteristics: A Case Study of ISO/IEC 29110 Standard

A key driver of software business growth in developing countries is the survival of software small and medium-sized enterprises (SMEs). Quality of products is a critical factor that can indicate the future of the business by building customer confidence. Software development agencies need to be aware of meeting international standards in software development process. In practice, consultants and assessors are usually employed as the primary solution, which can impact the budget in case of small businesses. Self-assessment tools for software development process can potentially reduce time and cost of formal assessment for software SMEs. However, the existing support methods and tools are largely insufficient in terms of process coverage and semi-automated evaluation. This paper proposes to apply a knowledge-based approach in development of a self-assessment and gap analysis support system for the ISO/IEC 29110 standard. The approach has an advantage that insights from domain experts and the standard are captured in the knowledge base in form of decision tables that can be flexibly managed. Our knowledge base is unique in that task lists and work products defined in the standard are broken down into task and work product characteristics, respectively. Their relation provides the links between Task List and Work Product which make users more understand and influence self-assessment. A prototype support system was developed to assess the level of software development capability of the agencies based on the ISO/IEC 29110 standard. A preliminary evaluation study showed that the system can improve performance of users who are inexperienced in applying ISO/IEC 29110 standard in terms of task coverage and user's time and effort compared to the traditional self-assessment method.
Photon waiting-time distributions: A keyhole into dissipative quantum chaos

Open quantum systems can exhibit complex states, which classification and quantification is still not well resolved. The Kerr-nonlinear cavity, periodically modulated in time by coherent pumping of the intra-cavity photonic mode, is one of the examples. Unraveling the corresponding Markovian master equation into an ensemble of quantum trajectories and employing the recently proposed calculation of quantum Lyapunov exponents [I.I. Yusipov {\it et al.}, Chaos {\bf 29}, 063130 (2019)], we identify `chaotic' and `regular' regimes there. In particular, we show that chaotic regimes manifest an intermediate power-law asymptotics in the distribution of photon waiting times. This distribution can be retrieved by monitoring photon emission with a single-photon detector, so that chaotic and regular states can be discriminated without disturbing the intra-cavity dynamics.
Hopfield Neural Network-Based Algorithm Applied to Differential Scanning Calorimetry Data for Kinetic Studies in Polymorphic Conversion

A general kinetic equation to simulate differential scanning calorimetry (DSC) data was employed along this work.Random noises are used to generate a thousand data, which are considered to evaluate the performance of Levenberg-Marquardt (LM) and a Hopfield neural network (HNN) based algorithm in the fitting process.The HNN-based algorithm showed better results for two different initial conditions: exact and approximated values.After this statistical analysis, DSC experimental data at three heating rates for losartan potassium, an antihypertensive drug, was adjusted by the HNN method using different initial conditions to obtain the activation energy and frequency factor.Additionally, it was possible to recover the parameters for the kinetic model with accuracy, showing that the conversion is described by a complex process, once these values do not correspond to any ideal models described in the literature.
Life-swap: how discussions around personal data can motivate desire for change

Abstract Personal informatics technologies support the collection of and reflection on personal data, but enabling people to learn from and act on this data is still an on-going challenge. Sharing and discussing data is one way people can learn from it, but as yet, little research explores how peer discourses around data can shape understandings and promote action. We ran 3 workshops with 5-week follow-ups, giving 18 people the opportunity to swap their data and discuss it with another person. We found that these workshops helped them to recontextualise and to better understand their data, identify new strategies for changing their behaviour and motivated people to commit to changes in the future. These findings have implications for how personal informatics tools could help people identify opportunities for change and feel motivated to try out new strategies.
A comparison of two automatic solar tracking algorithms

Due to global climate change as a result of pollution caused by the burning of fossil fuels, the world has changed its view when it comes to power generation. The focus is now more on natural and clean energy, such as solar PV systems. An effective solar PV system is not a simple system, as the sun is not a stationery object. The sun moves from east to west daily and that makes the design and installation of an effective solar PV system challenging for optimal power harvesting. The purpose of this paper is to compare two algorithms (linear regression and fuzzy logic) that are applied to a dual-axis tracker in order to maximize the output power yield that may be obtained from a fixed-axis system. One fixed-axis PV module serves as the baseline for comparing the results of the dual-axis trackers that are controlled by the two algorithms. A key recommendation is to align a PV module perpendicular to the sun from sunrise to sunset using a control algorithm based on fuzzy logic principles in order to extract the maximum amount of available energy.
Research on Effective Learning Strategies among Schools under Internet Environment

In this paper, a novel teaching method is proposed, which is realized by employing the network technology based on intercollegiate cooperation.The proposed inter-school network collaborative learning is a special teaching method of remote cooperative learning.The particularity is embodied in being able to extract the excellent teaching resources from other school.Under the network environment for the intercollegiate cooperation, the interests of students can be greatly motivated.And the learning efficiency can also be obviously improved.The concrete concept of inter-school network collaborative learning is analyzed and its advantages are also presented in this paper.Finally, a investigate experiment is carried out based on different subjects and terms.The results show that the average score, the percentage of proficiency and pass are clearly enhanced by utilizing the inter-school network collaborative learning.
FastGCN + ARSRGemb: a novel framework for object recognition

Purpose: Recent research has been producing an important effort in encoding of digital image content. Most of the adopted paradigms only focus on local features and lack of information about location and relationships between them. Approach: To fill this gap, we propose a framework built on three cornerstones. First, the adoption of attributed relational scale-invariant feature transform regions graph, for image representation. Second, the application of a graph embedding model, to work in a simplified vector space, is performed. Finally, fast graph convolutional networks address classification task on a graph-based dataset representation. Results: The framework is evaluated on state of art object recognition datasets with uniform background. Conclusions: A wide experimental phase is performed through a comparison to well-known competitors.
A Study of Various Natural Language Processing Works for Assamese Language

A natural language or an everyday language is an accustomed form of communication used by the people to speak, express and write. Besides, these languages are called natural because they are evolved naturally among the communities. Natural Language Processing is a very vital field in connection with Artificial Intelligence, where research has exponentially taken place. This research aims to explore the techniques that have been used to process the Assamese language, the focus will be basically on Parsing, Part-of-Speech tagging, Word-Sense Disambiguation, Machine Translation, WordNet.