Reviewerly/exHarmony huggingface dataset:
A new block cipher for image encryption based on multi chaotic systems

In this paper, a new algorithm for image encryption is proposed based on three chaotic systems which are Chen system,logistic map and two-dimensional (2D) Arnold cat map. First, a permutation scheme is applied to the image, and then shuffled image is partitioned into blocks of pixels. For each block, Chen system is employed for confusion and then logistic map is employed for generating subsititution-box (S-box) to substitute image blocks. The S-box is dynamic, where it is shuffled for each image block using permutation operation. Then, 2D Arnold cat map is used for providing diffusion, after that XORing the result using Chen system to obtain the encrypted image.The high security of proposed algorithm is experimented using histograms, unified average changing intensity (UACI), number of pixels change rate (NPCR), entropy, correlation and keyspace analyses.
When Specialists Transition to Generalists: Evolutionary Pressure in Lexicase Selection

Generalized behavior is a long standing goal for evolutionary robotics.Behaviors for a given task should be robust to perturbation and capable of operating across a variety of environments.We have previously shown that Lexicase selection evolves high-performing individuals in a semi-generalized wall crossing task-i.e., where the task is broadly the same, but there is variation between individual instances.Further work has identified effective parameter values for Lexicase selection in this domain but other factors affecting and explaining performance remain to be identified.In this paper, we expand our prior investigations, examining populations over evolutionary time exploring other factors that might lead to generalized behavior.Results show that genomic clusters do not correspond to performance, indicating that clusters of specialists do not form within the population.While early individuals gain a foothold in the selection process by specializing on a few wall heights, successful populations are ultimately pressured towards generalized behavior.Finally, we find that this transition from specialists to generalists also leads to an increase in tiebreaks, a mechanism in Lexicase, during selection providing a metric to assess the performance of individual replicates.
Teaching Exploration of Case-Based Data Modeling Optimization for Database System

Database system is a very important information infrastructure of modern society.The consistent sharing of data is the key to the realization of reliable application of database system in different fields of society.With respect to the problems of data inconsistency that are widely existed in database system applications, we focus on the entity-relation modeling, the origin of data generation, combine with practical application cases and propose active and effective prior precautions which are extracted from our many years of teachings and scientific researches.First, we use the objective uniqueness of recognizing entity and relation to overcome the subjective biases in data modeling fundamentally.Next, some empirical rules for optimizing the entity-relation model are employed to further rectify the inappropriateness in the model.The effectiveness and feasibility of the proposed principles of the entity-relation modeling optimization for database system are sufficiently approved by the demonstration of practical application cases.
Academic Staff and Industry Revolution 4.0: Knowledge, Innovation and Learning Factor

The higher education institutions play a very important role in developing the readiness of academic staff on IR 4.0 which might increase the quality of education system through implementing the effective learning factors, efficiency knowledge management factors, and creative thinking with the innovation capability. Here, the academic staff must further explore the new knowledge, innovation, and learning factors that could be used in their teaching and learning. The research model was taken from previous studies on examining the feasibilities of Industry 4.0 for the hospitality sector with the lens of management practice. The data was analyzed by using the IBM SPSS Statistics v21 and the five-point Likert scale represented by Information Literacy Education Implementation Readiness Scale was used to measure the respondents’ readiness level on IR 4.0. Descriptive analysis than was used in this research to further explore the mean factors which are learning, knowledge management and innovation capability, and the academic staffs’ readiness for IR 4.0.. The results indicated that the learning institutions played a very important role in developing the readiness of academic staff on IR 4.0 which may increase the quality of education system through implementing the effective learning factors, efficiency knowledge management factors and creative thinking with innovation capability factors.
Limitations of Hartree–Fock with quantum resources

The Hartree-Fock problem provides the conceptual and mathematical underpinning of a large portion of quantum chemistry. As efforts in quantum technology aim to enhance computational chemistry algorithms, the fundamental Hartree-Fock problem is a natural target. While quantum computers and quantum simulation offer many prospects for the future of modern chemistry, the Hartree-Fock problem is not a likely candidate. We highlight this fact from a number of perspectives including computational complexity, practical examples, and the full characterization of the energy landscapes for simple systems.
Radar Signal Sorting Method Based on Radar Coherent Characteristic

Aiming at the problem of reliability reduction of signal sorting in terms of the traditional five parameters and intrapulse feature in a complex electromagnetic environment, a new signal sorting method based on radar coherent characteristics is proposed. The main idea of this method is using spectrum analysis to obtain the spectrum images of coherent and noncoherent signals. Image-processing technology is used to extract the feature difference between the two spectrum images, and the central-moment feature is introduced to describe this difference. Through simulation analysis, the feasibility of using the central-moment feature as the coherent feature for signal sorting was proved. In order to check the effectiveness of the proposed feature, a number of simulations were conducted to demonstrate the sorting capability in terms of the coherent feature. From the simulations, it can be seen that the proposed feature not only can be used as a new feature for signal sorting but also that it can be utilized as a supplement for five typical parameters and the intrapulse feature to improve the sorting accuracy rate. Simulations also showed the proposed method could achieve satisfactory sorting results in a low signal-to-noise ratio (SNR). When the SNR was 5 dB, the sorting accuracy rate could reach 98%.
A Distributed Exam Item Bank System Based on Hadoop Ecosystem

Exam item bank system is an important precondition for the separation of teaching and examination and helpful for easing the burden of teachers. It is also the foundation of assessing teaching achievements equitably and objectively, being useful for supervising teachers teaching. Therefore, this paper designed a distributed item bank system with high scalability based on a popular big data processing platform, Hadoop. The system exploited Hadoop distributed file system for unstructured item data storage, and utilized Hadoop ecosystem to respectively design functions of test paper generation, test paper search, item retrieval, test result check, test result analysis, item similarity retrieval, and so on. The paper presented the formalization description of the test paper generation problem, based on which users could design smart and efficient test paper generation algorithms based on the methods of heuristic, metaheuristic, machine learning, or any others in the system.
Real-Time Obstacle Avoidance for Manned/Unmanned Aircraft Cooperative System Based on Improved Velocity Obstacle Method

To adapt the autonomous level of agents in current, and to perform the advantages of multi-agent in air combat, the form of manned/unmanned aircraft cooperative system has gradually become a hot topic. To solve the issue of three-dimensional (3D) real-time obstacle avoidance, the 3D maneuvering obstacle model is established firstly based on the traditional velocity obstacle method. Then the flight mode is selected and the optimal obstacle avoidance plane is determined by setting the Right-of-way rules when the system encountering obstacles. Finally, the difference of obstacle avoidance plane, the feasibility of avoiding maneuvering obstacle and the effectiveness of obstacle avoidance of cooperative system are verified by several flight simulations. The results show that the proposed method can realize the avoidance of 3D maneuvering obstacle for manned/unmanned aircraft cooperative system safely and efficiently.
Updating ontology alignments based on new concepts and their context

Ontologies and their associated mappings play a central role in several semantic-enabled tasks. However, the continuous evolution of ontologies requires updating existing concept alignments. Whereas mapping maintenance techniques have mostly handled revision and removal type of ontology changes, the addition of concepts demands further studies. This article proposes techniques to refine a set of established mappings based on the evolution of ontologies. We investigate ways of suggesting correspondences with the new version of the ontology without applying a matching operation to the whole set of ontology entities. Obtained results explore the neighbourhood of concepts in the alignment process to update mapping sets. Our experimental evaluation with several versions of aligned biomedical ontologies shows the effectiveness in considering the context of new concepts.
Context-aware auction solution of cooperative fish market monitoring system for intelligent user

Abstract This study proposes a context-aware auction solution suitable for the intelligent user. The solution informs the most reasonable prices for brokers after considering the size of each species of the catch along with other information and their effects on the fish price. This solution is expected to improve the safety of the catch and increase the competitiveness of auction sites by introducing a digitalized auction system to replace the traditional analog system which could be unsanitary sometimes. The solution’s Unified Modeling Language has been developed with Java Android and the data obtained from the proposed solution is useful in simplifying the bidding process, avoiding over-heated bidding, or stabilizing the fish prices for consumers in the distribution process starting from a broker, distributor and then to consumers. Such a simplified procedure will be able to maintain the freshness of the catch and strengthen the food safety as well as the competitiveness of auction sites, assisting brokers who often experience some difficulties in making a decision on the bidding price due to many variables. This study has focused on the new paradigms, software, middleware and systems for intelligent user. Thus, cost reduction was considered mainly in terms of software engineering. The proposed system is to be supplied with a price 30% less than the existing systems.
Quantifying nonlocality as a resource for device-independent quantum key distribution

We introduce, for any bipartite Bell scenario, a measure that quantifies both the amount of nonlocality and the efficiency in device-independent quantum key distribution of a set of measurement outcome probabilities. It is a proper measure of nonlocality as it vanishes when this set is Bell local and does not increase under the allowed transformations of the nonlocality resource theory. This device-independent key rate $R$ is defined by optimizing over a class of protocols, to generate the raw keys, in which each legitimate party does not use just one preselected measurement but randomly chooses at each round one among all the measurements at its disposal. A common and secret key can certainly be established when $R$ is positive but not when it is zero. For any continuous proper measure of nonlocality $N$, $R$ is tightly lower bounded by a nondecreasing function of $N$ that vanishes when $N$ does. There can thus be a threshold value for the amount of nonlocality as quantified by $N$ above which a secret key is surely achievable. A readily computable measure with such a threshold exists for two two-outcome measurements per legitimate party.
Assessment of Corporate Social Responsibility: The Case of Manufacturing Companies in Gurage Zone, Ethiopia

The overall objective of this study is to assess the practice of corporate social responsibility in the case of manufacturing companies in Gurage Zone. The data analysis was conducted based on 176 employees from sample manufacturing companies. Parametric (SPSS Version 20) and non parametric test (Friedman test) to test the concern of companies in Corporate Social Responsibility implementation towards environment, customer, community, employee, ethical &amp; legal were conducted for analysis. Regarding the factors affects the implementation of corporation social responsibility (71.1%), (64.5%) and (61.2%) of the respondents agreed that government, awareness and media are the factors that can affect the implementation of CSR respectively. The majority, (67.8%) of the respondents said that the organization didn’t encourage employees to develop real skills and long term careers (via Performance Appraisal and Training &amp; Development. The result shows that responsibility of the firms towards environment (55.3%) of the respondents disagree, (46.7%) of the respondents argue positively, (59.2%) of the respondents disagree, the majority of respondents (60.5%) disagree, (46.1%) of the respondents agree, majority of the respondents (62.5%) disagree about the participation of the firms in west reduction, recycling, energy conservation, reduction of water consumption, use environmentally friendly packaging, air pollutant respectively. Therefore, it recommended that the firms should set the direction and scope over the long term with regard to CSR, allowing them to be successful by using their resources within their unique environment to meet market needs and fulfill stakeholder expectations. It is therefore vitally important that the firms should have to design a good CSR strategy that is related with that of their business strategy.
The implementation of self-explanation strategy to develop understanding proof in geometry

Proof is a key indicator for a student in developing mathematical maturity. However, in the process of learning proof, students have the difficulty of being able to explain the proof that has been compiled using good arguments. So we need a strategy that can put students in the process of clarifying proof better. One strategy that can explore student thought processes in explaining geometric proof is self-explanation strategy. This research aimed to analyze the ability to understand the geometric proof of prospective teacher students by implementing a self-explanation strategy in basic geometry classes. This study used a quasi-experimental research type of nonequivalent control group design. The participants of this research were 75 students of mathematics education study programs at one private university in Semarang. This research used four instrument tests of geometric proof. Before being used for research, the instruments were tested for validity and reliability using product-moment and Cronbach's alpha. Data analysis in this study used a two-way ANOVA test. The results showed that: the increased ability to understand the geometric proof of students who used self-explanation strategy was better than those who obtained direct learning; there was a significant difference between the increase of students’ mathematical proof ability in a group of students with a high and moderate level of initial mathematical ability; the initial ability (high, medium, low) of mathematics did not directly influence the learning process to improve the ability to understand the geometric proof. Hence, it can be concluded that the self-explanation strategy is effective to be used to improve the understanding of the geometric proof.
Adaptive On-the-Fly Changes in Distributed Processing Pipelines

Distributed data processing systems have become the standard means for big data analytics. These systems are based on processing pipelines where operations on data are performed in a chain of consecutive steps. Normally, the operations performed by these pipelines are set at design time, and any changes to their functionality require the applications to be restarted. This is not always acceptable, for example, when we cannot afford downtime or when a long-running calculation would lose significant progress. The introduction of variation points to distributed processing pipelines allows for on-the-fly updating of individual analysis steps. In this paper, we extend such basic variation point functionality to provide fully automated reconfiguration of the processing steps within a running pipeline through an automated planner. We have enabled pipeline modeling through constraints. Based on these constraints, we not only ensure that configurations are compatible with type but also verify that expected pipeline functionality is achieved. Furthermore, automating the reconfiguration process simplifies its use, in turn allowing users with less development experience to make changes. The system can automatically generate and validate pipeline configurations that achieve a specified goal, selecting from operation definitions available at planning time. It then automatically integrates these configurations into the running pipeline. We verify the system through the testing of a proof-of-concept implementation. The proof of concept also shows promising results when reconfiguration is performed frequently.
Comparison of Graph-based Model Transformation Rules.

With model transformations arising to primary development artifacts in Model-Driven Engineering, dedicated tools supporting transformation developers in the development and maintenance of model transformations are strongly required.In this paper, we address the versioning of model transformations, which essentially relies on a basic service for comparing different versions of model transformations, e.g., a local workspace version and the latest version of a repository.Focusing on rule-based model transformations based on graph transformation concepts, we propose to compare such transformation rules using a maximum common subgraph (MCS) algorithm as the underlying matching engine.Although the MCS problem is known as a non-polynomial optimization problem, our research hypothesis is that using an MCS algorithm as a basis for comparing graph-based transformation rules is feasible for real-world model transformations and increases the quality of comparison results compared to standard model comparison algorithms.Experimental results obtained on a benchmark set for model transformation confirm this hypothesis.
Privacy Preserving Morphological Operations for Digital Images

Some image processing operations like segmentation or edge detection usually require complex computations. The emerging cloud technologies provide businesses and individuals with the possibility to outsource these computations on a remote platform with large resources and high availability. This approach substantially reduces the costs, but could rise privacy issues. To address these issues, the user data could be encrypted, sent to the cloud and processed there by taking advantage from the properties of a homomorphic encryption scheme. The result of the computation performed on encrypted data is sent back to the user to be decrypted. This paper studies the possibility of conducting some morphological operations on encrypted digital images. First, we model these processing using the two elementary operations in the ring F <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sub> . Second, we implement these computations using CSGNHE which is a recently proposed scheme by our team. Finally, we compare our results in terms of execution times and encrypted data size with some well-known schemes from the literature.
Safe Reinforcement Learning through Meta-learned Instincts

An important goal in reinforcement learning is to create agents that can quickly adapt to new goals while avoiding situations that might cause damage to themselves or their environments. One way ag...
The Influence of Demographic Factors on Investment Behaviour of Individual Investors: A Case Study of Edo State, Nigeria

This study empirically examines the influence of demographic factors on investment behaviour of individual investors using Edo state, Nigeria as its case study. Using the maximum likelihood method of estimation to estimate four multinomial logit equations, the results showed that educational level, occupation and marital status are the main demographic determinants of individual investors’ behaviour. Also, age and gender have strong influences on individual investor’s risk preference. Therefore, we recommend that it is pertinent that macroeconomic policies aimed at boosting investment should consider the expansionary effect of targeting civil servants and those in professional practice by providing them with investment incentives as these categories of persons have a much higher affinity for risk for investment purposes.
Efficient Vehicle Detection System using OCR and REST API

Number plate recognition has been one of the active and challenging research areas in the field of image processing and character recognition.It has numerous application which includes, law enforcement, fake vehicle registration, traffic control and electronic toll collection.In this paper an attempt is made to recognize characters in number plate using OCR through REST API.The vehicle plate image is obtained by the digital cameras and the image is processed in REST application program interface (API) to get the number plate information.In this context, the number plate area is recognised using Optical Character Recognition.The results show that the proposed system yields good recognition rates which are comparable to that neural network based number plate recognition.
Sufficient conditions and constraints for reversing general quantum errors

Reversing the effects of a quantum evolution, for example, as is done in error correction, is an important task for controlling quantum systems in order to produce reliable quantum devices. When the evolution is governed by a completely positive map, there exist reversibility conditions, known as the quantum error correcting code conditions, which are necessary and sufficient conditions for the reversibility of a quantum operation on a subspace, the code space. However, if we suppose that the evolution is not described by a completely positive map, necessary and sufficient conditions are not known. Here we consider evolutions that do not necessarily correspond to a completely positive map. We prove that the completely positive map error correcting code conditions can lead to a code space that is not in the domain of the map, meaning that the output of the map is not positive. A corollary to our theorem provides a class of relevant examples. Finally, we provide a set of sufficient conditions that will enable the use of quantum error correcting code conditions while ensuring positivity.