Reviewerly/exHarmony huggingface dataset:
Towards Just-In-Time Rational Refactoring

Code smells have been defined as symptoms of poor design and implementation choices. Empirical studies showed that code smells can have a negative impact on the maintainability of code. For this reason, tools have been developed to auto-matically detect design flaws and, in some cases, to recommend developers how to remove them via refactoring. However, these tools are not able to prevent the introduction of design flaws. This means that the code has to experience a quality decay before state-of-the-art tools can be applied. In addition, existing tools recommend refactoring operations that mostly target the improvement of quality metrics (e.g., cohesion) rather than the generation of refactorings that are meaningful from the developers' perspective. Our goal is to develop techniques serving as the basis for a new generation of refactoring recommenders able to (i) predict code components likely to be affected by code smells in the near future, to refactor them before they experience a quality decay and (ii) recommend meaningful refactorings emulating the ones that developers would perform, rather than the ones targeting the improvement of metrics. We refer to such a perspective on refactoring as just-in-time rational refactoring.
QoS-PN Ontology Model for Service Selection

In order to solve the existing QoS (Quality of Service) model lack of descriptions on the dynamic changes of attributes as well as user personalization QoS-PN, a new ontology model for QoS, is presented to provide users with a sharable and unified service quality description framework. By introducing User Personalize class and Status class. The QoS-PN model can rationally describe user’s personalized requirements and dynamic changes of attributes, which solve the problem of service reliability and service personalization requirement. QoS-PN is described as three-layer ontology model: QoS configuration layer, QoS attributes layer, and QoS metric layer. QoS-PN can describe detailed information related to QoS attributes, metric methods; QoS attribute values, and units for the QoS, which improve the accuracy of service matching. An example of travel route inquiry is presented to show the feasibility of the QoS-PN model. Empirical results show that this model supports rich semantic description and has strong extensibility. The stability and accuracy of selected service are effectively improved when QoS-PN model is used to describing QoS information. The QoS-PN enhances descriptive ability for QoS information and the description of dynamic Attribute and personalization has been expanded. The problem of QoS stability and user personalization in service selection is solved.
A Biogeography-Based Optimization Algorithm for Criminisi Algorithm

The criminisi algorithm is a useful image inpainting approach, but it cost high computational complexity. In order to reduce the computational complexity of image inpainting, an improved Criminisi algorithm is proposed in this paper based on biogeography optimization (BBO). According to the characteristic of Criminisi, the new method uses the migration and mutation of BBO to search the best matching block and overcome the shortcomings of the Criminisi algorithm by searching the best matching block in the unbroken regions in the image. Experimental results show that this algorithm reduces the computational complexity significantly for Criminisi algorithm with maintaining still the good performance.
Guided image filtering using data mining and decomposition

Owing to local linear model, guided image filter may contain from ringing artefacts. A modified guided image filter based on data mining techniques and decomposition is proposed in this paper. Image is split into patches, passing through the guided filter, clustered into number of clusters and transformed into compact domain using principal component analysis. Edges are preserved and halo artefacts are removed using detail enhancement based on weighted least square. Simulation results demonstrate the strength of the proposed technique as compared with other techniques especially around the edges where noise and halo artefacts may be present in the image.
Predicting User Preference in Pairwise Comparisons Based on Emotions and Gaze

Emotions have an impact to almost all decisions. They affect our choices and are activated as feedback during the decision process. This work aims at investigating whether behavior patterns can be learned and used to predict the user’s choice. Specifically, we focused on pairwise image comparisons in a preference elicitation experiment, and exploited a Process Mining approach to learn preferences. We proposed and evaluated a strategy based on experienced emotions and gaze behaviour, whose results show promising prediction performance.
An Approach to Product Design Involving Heterogeneous Stakeholders

This chapter discusses communication and data sharing among multiple stakeholders in a product design group and describes eight relevant techniques: inputs, brainstorming, ideation, matrix expansion, persona design, data journey mapping, prototyping, and review and reflection. Inputs provide additional domain knowledge obtained from sources that may include lectures, expert interviews, field investigations, and data analysis. This knowledge can be further elaborated through brainstorming. Ideation and matrix expansion contribute to idea development by linking different aspects of a few fundamental ideas. Design is the process of detailing what, when, how, where, and for whom we construct. As products become increasingly complex, the design process must accommodate interactions between heterogeneous stakeholders from different backgrounds. Data on consumer characteristics and behaviors can be linked to product satisfaction. Finally, after prototyping, review and reflection involves the exchange of outcomes with other participants. The involvement of heterogeneous participants serves to integrate diverse knowledge and skills.
Design and Implementation of the School Sports Management System Based on WEB

With the continuous improvement of the levels of the sports informationization, the sports information management system is more and more widely used in school sports, competitive sports and social sports. From the single-machine system to the file/server model-based system, to the client/server (C/S) model-based system to the browser/server-based system, various forms of the management information systems serve the sports management work at the same time. With the development of the network technology, the Browser/Server-based system has become the mainstream network system.
An Interactive Practical Approach for Traditional Cryptanalysis of Vigenere Cipher

Vigenere cipher is a polyalphabetic cipher with a very large key space capable of generating streaming cipher text. The difficulty level of cryptanalysis somewhat depends on the size of the key space. However, there are methods of pattern analysis and statistical analysis that can overrule the difficulties of cryptanalysis due to the large key space. Cryptanalysis of Vigenere cipher is one such method of testing code breaking even if the key domain is very large. The proposed algorithm of cryptanalysis works best when the size of the key string is less than the size of the dataset. Cryptanalysis is a way to break the cipher text by either brute force method or some analytical techniques. The paper describes a traditional method of deciphering encrypted message of Vigenere cipher cryptosystems irrespective of whether the message is long or short using Kasiski test and Friedman test or Kappa test. The ready algorithm and the program execution lead to success of key finding with high probability. The paper also surveys the other methods applied for cryptanalysis of Vigenere Cipher, such as cryptanalysis using Particle Swarm Optimization with Markov chain random walk and Genetic algorithm with Elitism. The existence of a cryptanalysis library for cracking polyalphabetic cipher such as Vigenere Cipher is analysed.
Optimum operation planning for a PVG/Battery standalone installation

The electrification of rural areas by autonomous renewable energy generators becomes attractive as it has good effect on people lifecycle. So far, the Photovoltaic Generator (PVG) associated to storage bank is widely used to cover loads' need during the whole day. Nevertheless, many energy supply issues may appear following weather perturbation. In this paper, an algorithm is proposed to plan the basic loads operation, via relays unit, of a PVG/battery based installation namely: cold room, light and water pump. Planification is mainly based on the PVG generation forecast. The algorithm ensures a continuous operation for the cold room then plans the rest of generated energy for lighting and pumping with respect to optimization criteria: maximum use of available energy and battery safety. Obtained results confirm the respect of the prefixed criteria: no lost energy and the battery protection.
cGAAM – An Algorithm for Simultaneous Feature Selection and Clustering

In this paper the modified version of cGAAM (a genetic algorithm for feature selection for clustering) is introduced. As it can be shown, the algorithm is able to find significant subsets of features in data sets that differ in size and number of classes. The common feature of the sets that were used to test the cGAAM is that the examples are provided with class labels. Due to this, although the clustering process was performed without the class labels, the chosen feature sets could be compared with feature subsets returned by Lasso method in terms of classification accuracy. The most important observation from the results presented in the paper is that the classification accuracy obtained with feature subsets returned by cGAAM was not only comparable with accuracy obtained with feature subsets returned by Lasso but almost always was higher than 80% (ionsphere dataset) and 90% (humanactivity dataset).
Augmented Fast-Forwarding

The trend of time-shifted viewing worries television networks and advertisers, as time-shifting viewers often fast-forward through commercials, resulting in lower advertising impact. The present research tests an alternative solution to this problem by augmenting fast-forwarded commercials with brand logos placed in the center of the screen. We tested the potential of augmented fast-forwarding in an experiment in which participants watched a television show interrupted by a commercial break using three experimental conditions: commercials played at regular speed, at fast-forwarded speed, or at fast-forwarded speed but enriched with logos. Advertising impact was measured during the commercial break (using eye-tracking glasses), right after the TV show (brand recognition), and the day after the TV show (day after brand recognition). Interestingly, the results showed that augmented fast-forwarding performed equally well as regular-speed viewing on two out of three advertising impact measures.
Towards Adversarial Training for Mobile Robots

This paper reports some preliminary work on learning on a physical robot. In particular, we report on an experiment to learn how to strike a ball to hit a target on the ground. We compare learning based just on previous trials with the robot with learning based on those trials plus additional data learnt using a generative adversarial network (GAN). We find that the additional data generated by the GAN improves the performance of the robot.
Research on Making Nature Smart with Children

Recent research invites children to be the protagonists of the design of novel smart nature ecosystems for them. Games and card-based workshops can help engage them in co-design and serve as a tool for generating ideas and designing new concepts. The SNaP game is a collaborative card-based board game that aims at engaging 11–14 years old children as protagonists in the design of novel smart nature ecosystems. This paper outlines the main features of the game, the workshops it was used in and the resulting reflections.
Rewarding device-to-device content dissemination using Proof-of-Prestige

This demo shows an implementation of a device-to-device data dissemination system for mobile phones. We develop and Android application allowing users to exchange content and collects rewards for transfers using Proof of Prestige scheme deployed on Ethereum blockchain. To interact with the system, mobile devices require to store uniquely their public and private keys reducing the memory footprint. Our implementation inherits blockchain security features and remains resistant to Sybil and collude attacks. We make our application available on Google Play Store for public use.
We need to know

This forum highlights conversations at the intersection of design methods and social studies of technology. By highlighting a diversity of perspectives on design interventions and programs, we aim to forge new connections between HCI design and communication, science and technology studies, and media studies scholarship. --- Daniela Rosner, Editor
Dynamics of Interactions

The article summarizes premises for the construction of simulation models of dynamics of task performing teams. It presents theoretical foundations and discusses models which in further research will be used to analyze group dynamics. The modelling assumes that it is possible to describe human behavior in man – man and man – machine interactions by means of control theory tools. Here, man has been considered a reactive object as characterized within behavioral framework and what follows are descriptions of basic types of dynamical blocks which can be used to form objects: people, working environment. The analysis was performed in the research lab SYDYN.
Attacks Detection Method Based on Free Space Quantum Secure Direct Communication

Quantum secure direct communication is a new communication mode in the free space. Quantum secure direct communication utilizes single photon with the information to transmit ciphertext in the quantum channel directly, and it distinguishes from Quantum key distribution. Its outstanding characteristics are as follows: super velocity of light, high power capacity, high security, and anti-interference, so quantum secure direct communication can break the traditional secret communication frame to ensure the absolute secure communication. However, the imperfection of optical devices can leave loopholes for quantum attacks. Based on free space, this paper puts forward one kind of attack detection method in the field of quantum secure direct communication. This paper introduces quantum bit error rate analysis and decoy-state photon transmission rate analysis for designing security detection process to effectively detect the eavesdropping and improve security.
On Relation Between Swarm and Evolutionary Dynamics and Complex Networks

This paper is an introduction to a novel method for visualizing the dynamics of evolutionary algorithms in the form of networks. The whole idea is based on the obvious similarity between interactions between individuals in a swarm and evolutionary algorithms and for example, users of social networks, linking between web pages, etc. In this paper, two completely different areas of research are merged: (complex) networks and evolutionary computation. As already mentioned, interactions among the individuals in a swarm and evolutionary algorithms can be considered like user interactions in social networks or just people in society. This induces hypothesis whether interactions inside of EAs can be taken like interactions in society or swarm colonies. The analogy between individuals in populations in an arbitrary evolutionary algorithm and vertices of a network is discussed, as well as between edges in a network and communication between individuals in a population.
An Adaptive Chirplet Filter for Range Profiles Automatic Target Recognition

An adaptive Chirplet filter approach is proposed to deal with the aircraft recognition problem based on high-resolution range profiles. The Chirplet filter is a joint feature extraction and target identification method derived from the feed-forward neural networks, which consists of two layers: the Chirplet-atoms transform in the input layer is used for replacing the conventional sigmoid function, and the weights between the input and the output layer are taken as the linear classifier. The Chirplet-atoms parameters and the weights are adaptively adjusted by using the nonstationarity degree as the measurement of the features. The simulation results suggest that the adaptive Chirplet filter has advantages especially in noisy conditions.
Are Monitoring Crosscutting Concerns Really Refactorable into Aspects? An Empirical Study

Monitoring concerns' implementation crosscuts a software's system core concerns' implementation, leading to difficult to maintain and understand source code. Other paradigms have been proposed for crosscutting concerns implementation that should improve the understandability and maintainability of the software system. However, can we easily refactor monitoring concerns implementation in order to implement them using these paradigms? How will the new implementation affect the software system's source code? In this paper we present our study of monitoring concerns implementation in Java-based software systems, from the point of view of refactoring into aspects. We discuss the challenges that have to be overcome and how will the refactoring impact important characteristics of the overall system.
How Can Robotics Be Integrated into the Field of Care and Acceptance by the Population for the Use of Artificial Intelligence Be Strengthened?

The interviews with experts from the field of nursing science and robotics, which were conducted as part of a project study, were intended to provide an overview of the current status of the use of AI, especially with focus on acceptance research. It was found that there is a change towards a service society. During this change, acceptance would have to be created partly trough participation and education, in addition to the focus on transparency in action. The focus here is on the degree of autonomy of the robots and the overcoming of technical knowledge barriers.
Specificities of Organisational Communication in European Universities’ Digitalised Environments

In the contemporary digital era, with universities being at the core of the global changes, boosting and leading them, issues of university digitalisation and organisational communication are topics of particular interest, as well as the presence of artificial intelligence in their policies and strategies and communicating it both to their employees and students. The presented research focuses on issues of university digitalisation, in particular when it comes to organisational communication practices. The relevance of the topic is stipulated by the need to study the existing practices in organisational communication and approaches to the establishment and development of digitalisation policies and strategies and analyse the current practices in the chosen Russian and Finnish universities as part of their digitalisation processes aimed at ensuring their competitiveness in the globalised world.
Application of Raman Spectroscopic Measurement for Banknote Security Purposes

The development of science and technology brings new tools to improve security features on banknotes as well as methods to verify their authenticity. This development also expands the technical possibilities for money counterfeiting. The paper deals with the experimental examination of selected protective elements - paper and inks used on euro banknotes. The advanced analytical method Raman spectroscopy was used for experimental analysis, as method meets the requirements crucial for forensic examination. The main aim is to obtain characteristic Raman spectra of selected security features that can serve for testing the authenticity of questioned banknotes. The results show an apparent diversity of spectral markers in individual samples and the method suitability for the authentication. A comparison of the results for euro banknotes of the first and the Europa series is discussed in the paper.
A Research About a Conflict-Capture Method in Software Evolution

Software evolution is an important research direction and research focus in the field of software engineering. During the process of software dynamic evolution, the existence of conflicts between evolutionary components and original components is one of the key factors determining whether the dynamic evolution process is corrected or not. To solve this problem, resource management method is introduced and the concept of resource in software evolution process is redefined. According to the different patterns of resources used, sequence, selection and conflict relationship models among components are defined. And at last, a conflict-capture algorithm, which is used to capturing the components involved in the conflict relationships, based on recourse management. The results of this paper lay a theoretical foundation for maintaining consistency before and after evolution and ensuring the correctness of dynamic evolution.
Classification method at acceptance of new student at public university on the national written test

Abstract Acceptance of new students at public universities through the national written test is based on the total score and the capacity of the study program. This causes the study program accepts several students who have low scores on the main subject of the study program. The purpose of this study is to find the best method in predicting the probability of being accepted on the national written test and find the minimum score for each subject that must be achieved by participants to be accepted at a public university. There are two classification methods in statistics that are studied to overcome this problem, i.e. logistic regression and random forest. The results showed that the best logistic regression model had an accuracy of 97.11 percent, whereas the random forest method had an accuracy of 96.59 percent. Furthermore, the minimum score for each subject was developed based on the univariate logistic regression model.
Security analysis of the first phase mask in double random phase encryption

We study the security of double random phase encoding when partial knowledge of the first mask is available. We propose a greedy algorithm that can be parallelized efficiently and converges with low errors.
Management of Lecturers Quality in a University in Medan.

Abstract The quality management system essentially refers to continuous improvement to strengthen and develop the quality of graduates and the lectuters. This research was designed to know the performance of lecturers as key roles in teaching learning process. A survey research was applied to measure the periodical report and performances of lecturers in a university in Medan of North Sumatra. The performance of lecturers was measured through filling application through web rkts.uma.ac.id. Data obtained were the uploaded documents which were recorded the activities of the lecturers on the Tridharma Perguruan Tinggi basis. In accordance with the policy of KEMENRISTEK through Ministry Regulation No. 92 Year 2014, the element of Teaching, Research, Community Service and other Supporting Elements are included. The population were all lecturers at M A Private University in Medan; the sample took 200 respondents from 7 Faculties, namely Faculty of Engineering, Faculty of Agriculture, Faculty of Economics, Faculty of Biology, Faculty of Psychology, Faculty of Law and Faculty of Politics. From the evaluation result there was a mismatch of documents uploaded with the elements or field measured. Non-compliance that occurs during the examination process which caused the scoring to be inconsistent with the uploaded documents. This study suggests the lecturers are more carefully in uploading documents; it aavoids the redundency of documenting files of Tridharma Perguruan Tinggi .