Reviewerly/exHarmony huggingface dataset:
Efficiency and Precision Enhancement of Code Clone Detection Using Hybrid Technique-Based Web Tool

With the advent and growth in the field of software reuse, the maintenance of code and respective repositories is becoming a great challenge. Code cloning is one of the major causes behind this. Code clone is a code portion which is identical or similar to other potions of code. Copy and paste of a code fragment is also considered as a form of code cloning which makes maintenance of software more complicated. Software maintenance (SM) is defined as the modification done to the existing software after development and implementation. Using SM process, the software companies provide add-ons and updates as per working environment and need to remove bugs and to correct any fault identified during it execution to improve the performance. This research work presents a large-scale study of existing tools which has been carried out for detection of code clones. These suggested tools employ different methodology for code clone detection. The work focus on pragmatic and detailed study on the detection of code clones. The research work further explores the various challenges in code clone detection in terms of bug propagation, irregularities in change propagation, design mistakes, increased challenge in refactoring, and increased code comprehension efforts. The study carried out suggests that more efficient algorithm and techniques are required to detect code cloning. The study also shows that a web-based tool to detect clones in code would be more beneficial. The authors propose a hybrid methodology for web-based code clone detection tool (WCCD) which can be used to detect code clones in any browser. The proposed tool implements a more powerful clone detector to identify clones in code in an efficient and precise manner. Repetition of code clones that seems to be vulnerable could be a malware whose detection using the existing tool is an issue. Hence, the proposed work has been further extended to detect malware to make the process of code clone detection more effective and efficient.
Inversion of Sio<sub>2</sub> Content in Surface Rock by Thermal Infrared Remote Sensing

The content of Sio <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sub> in rocks is an important indicator of magmatic rock classification, and quartz vein is the main indicator of field prospecting. In this paper, 60 rock samples from USGS (U.S. Geological Survey), JPL (Jet Propulsion Laboratory) and JHU (Johns Hopkins University) are used to resample the thermal infrared band to the ASTER thermal infrared band to study the emissivity characteristics relationship with Sio <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sub> content in the thermal infrared band (8-15μm). Correlation analysis shows that the maximum negative relationship between the Sio <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sub> content and the logarithmic transformation ln(bl3/bl2) spectrum of the ASTER band is -0.873, and the maximum positive correlation coefficient between Sio <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sub> content and logarithmic transformation ln(bl3)/ln(bl2) of ASTER band is 0.793, which indicates that the correlation between Sio <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sub> content and ASTER thermal infrared band emission spectrum is better. Five regression equations were established by multivariate stepwise regression method and partial least squares regression method. The inversion of Sio <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sub> content in surface rocks in Lin xi area of Inner Mongolia was carried out by ASTER thermal infrared band. This study has important reference significance for the application of thermal infrared remote sensing to extract Sio <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sub> content in surface rocks and to divide lithology and prospecting.
Approaches and Measures to Educational Assessment Reform through an Internet+ Perspective

Educational assessment is an important method to improve the quality of education or promote the development of teaching. With the rapid development of information technology, the drawbacks of traditional assessment methods gradually revealed. Thus it is imperative to reform educational assessment. Taking educational assessment in Jiangsu Province as an example, this paper analyzes the current situation and problems of educational assessment operation, and puts forward the trend of educational assessment under the background of Internet +. The emphasis is laid on the approaches and measures for the reform of educational assessment, which lays a solid foundation for deepening the reform of educational assessment under the background of the new era.
Reconstructed Option Rereading Network for Opinion Questions Reading Comprehension

Multiple-choice reading comprehension task has seen a recent surge of popularity, aiming at choosing the correct option from candidate options for the question referring to a related passage. Previous work focuses on factoid-based questions but ignore opinion-based questions. Options of opinion-based questions are usually sentiment phrases, such as "Good" or "Bad". It causes that previous work fail to model the interactive information among passage, question and options, because their approaches are based on the premise that options contain rich semantic information. To this end, we propose a Reconstructed Option Rereading Network (RORN) to tackle it. We first reconstruct the options based on question. Then, the model utilize the reconstructed options to generate the representation of options. Finally, we fed into a max-pooling layer to obtain the ranking score for each opinion. Experiments show that our proposed achieve state-of-art performance on the Chinese opinion questions machine reading comprehension datasets in AI challenger competition.
Preprocessing of Correlation Power Analysis Based on Improved Wavelet Packet

Preprocessing is a very important step in side channel analysis. The quality of the collected power traces seriously affects the efficiency of side channel analysis. Therefore, the preprocessing of Wavelet Transform (WT) and Wavelet Packet Denoising (WPD) are widely used. However, WT has certain defects in characterizing detail information of power traces. The threshold of WPD is not universal and adaptive. In order to solve these problems, it provides a preprocessing of power traces by combining WPD and Singular Spectrum Analysis (SSA), which takes advantage of the former to resolve the power consumption data, and the latter is used to extract the information of the low frequency and high frequency parts. Then, according to the fluctuation trend of singular entropy, the key information contained in the two parts is extracted adaptively, so as to improve the quality of power traces. Finally, through the selection of plaintext attack on the SM4 algorithm implemented by hardware, it can improve the efficiency of Correlation Power Analysis (CPA).
Research on Automatic Proofreading Method of Clinical Terminology of Traditional Chinese Medicine

With the development of TCM information, computers replace the traditional writing of medical records. However, the typos in the ERMs influence their qualities that bring disturb to the information work such as TCM data mining. We discover the error of TCM clinical terms in the TCM texts by using Chinese NLP technology and proofread these errors. In order to realize the automatic detecting error and automatic proofreading the wrong TCM clinical Terms, we use the fuzzy-matching algorithm to match the TCM clinical terms that are written wrong firstly, and then we use statistical method to verify the matching results. Experiments show that this method can effectively correct Chinese characters replacement errors, missing word errors and multi-word errors in TCM clinical terms and has high practical value.
Divide-and-Conquer CBS Design for Multi-Agent Path Finding in Large-scale Scenario

Abstract Multi-Agent Path Finding (MAPF) problem is intensively studied in theoretical computer science, robotics and so on. The key for MAPF problem is to plan a conflict-free path for each agent with different start and goal positions, and to minimize the cost of the paths. Conflict-Based Search (CBS) is one of the optimal algorithms, which can ensure that the optimal solution is obtained, in the case of small-scale maps and low number of agents. However, in many real-world multi-agent systems, the scale of the map is very large and the number of agents is more. In most cases, CBS is not applicable any more. Therefore, we develop Divide and Conquer CBS, called DC-CBS algorithm which divides large-scale map and the original problem into several smaller ones. For each subproblem, we use the CBS to get the optimal solution. The experimental results show that for the large-scale scenario, the DC-CBS algorithm can get the result more quickly and plan the paths for agents successfully. As for small-scale situation, the performance of DC-CBS is almost as good as that for CBS.
Case study to determinate the angle-dependence during the risk determination in lightning protection

To know the formation of the atmospheric discharge is one of the main starting point to create an accurate calculation model. In this paper a study will be discussed what kind of modifications are necessary improve PMAS (probability-Modulated Attractive Space) [1, 2] calculation by taking into consideration the geometrical position of downward leader, especially the direction of the last step between the striking point and the point of strike.
Extracting Code-relevant Description Sentences Based on Structural Similarity

Software developers often need to read code snippets that are dispersed among different documentation, e.g., Q&A posts, to reuse APIs to complete certain tasks. These code snippets are often surrounded by lengthy context text which are used to describe the functions of code snippets. It will be helpful for code comprehension if we can align a code snippet with its description. In this paper, we propose an approach to extracting code-relevant sentences from its context text. To quantify the relevance between code line and natural language sentence, we represent them with structure trees and calculate their structural similarity. We conduct two experiments to evaluate our approach. In Experiment I, the results show that our approach achieves 83.5% precision and 80.1% recall in aligning Lucene code snippets and corresponding comments. Our approach achieves 27.6% ~ 40.2% improvement in precision compared with existing method, and 33.8% ~ 39.7% improvement in recall. In Experiment II, the results show that our approach achieves 66.4% ~ 93.9% precision to extract code-relevant sentences.
A Study of RNN Based Online Handwritten Uyghur Word Recognition Using Different Word Transcriptions

Recurrent neural networks-RNN based online handwriting Uyghur word recognition experiments are conducted applying connectionist temporal classification in this paper. Handwritten trajectory is fed to the network without explicit or implicit character segmentation. The network is trained to transcribe the input word trajectory to a string of characters directly. According to the writing characteristics of Uyghur, experiments are designed using two Unicode word transcriptions respectively based on 32+2 basic character types and 128 specific character forms to represent a word. The training process and recognition results based on same network architecture show that both transcription methods are applicable. The word transcription system using basic 34 character types showed better performance than the one using 128 specific character forms in our experiments. 13.96%, 14.73% character error rates (CER) have been observed respectively for char34 system and char128 system.
Designing for Perspective Challenging Moments in Games

Reflection has become a core design interest for HCI, with increasing work exploring the role of reflection in games and player experience. However, research into the causes for reflection within games is scarce. I present the findings from an online questionnaire where participants (n=101) openly reported perspective-challenging moments within games, their causes, experience, and impact within or outside the game's context. We observed that narrative reveals emerge as a key cause of perspective challenge, as one of my key findings to date. I highlight the ongoing plan for my research, including three differing studies to aid the creation of perspective challenging games through interviews, case studies, and developing game prototypes.
Active Learning of Identity Agnostic Roles for Character Grounding in Videos

A popular approach for storyline grounding in videos is centered on the consistent classification of main characters in videos. This work investigates learning identity agnostic characters for video grounding. The system starts without any knowledge about the character identities and their facial images, and learns to build individual character models as the video frames stream in. It is challenging to establish character models, especially in movies where characters can go through a lifetime in a clip, and their facial appearances change dramatically between scenes. We designed an active learning algorithm on top of metric learning, with an interactive interface to query users. Different from conventional active learning algorithms, our query proposal function depends not only on appearance, but also on story context of these characters.
The Use of Drones and Deep Learning to Identify Igneous Rocks and Fractures

Abstract Igneous (or magmatic) rocks may be critical elements in the petroleum systems. They may be related with generation, migration and trapping of oil and gas and also generate hydrothermal processes that can affect the reservoirs. In Campos and Santos basins, they occur as volcanic and intrusive bodies, affecting the pre-, intra- and post-salt sequences. Associated with fractures and faults, igneous intrusives were emplaced during reactivation of preexisting discontinuities or weakness zones, although they also cross cut them. In the continental area, adjacent to the Campos and Santos basins, intrusive igneous bodies crop out as dykes, sills and stocks. The area selected for this study is the "Pontal do Atalaia", in the city of Arraial do Cabo (RJ). The use of drone images allowed to identify the structural framework of the igneous bodies and fractures patterns associated with them. By developing tools of deep learning, it was possible to analyze the fractures and compare the results with visual interpretation. In both cases, the results indicate the predominance of fractures along roughly N-S and E-W trends. The outcomes allow the comparison and correlation to the offshore geological features to better understand the role of the igneous rocks and fractures in the tectonic evolution of Campos and Santos basins.
Integrated Software Development Methodology for Real-time Precise Control of UAV

Abstract Recently, drones have been widely used in education and industry. In this paper, we propose a navigation and control algorithm to develop unmanned drones quickly. To limit the proposed framework, we analysed the existing drone solution and simulation framework. We also used Hardware-in-the-Loop (HIL) simulation for rapid development. HIL will simulate physical systems that interface with embedded control equipment on real-time hardware. The code generated in this process can be experimented on a hardware device so that the control performance of the drones can be verified without draining the drones in the outdoor environment. Using the proposed method, you save time and money on drone development while providing stability.
Interdisciplinary Internship Projects Utilizing Legacy Robotic Equipment under Budget Constraints at a Small-sized Institution

In this paper we would like to share interdisciplinary project experiences with other small universities who intend or hold an interest in participating interdisciplinary STEM projects with their students. The interdisciplinary science and engineering projects attract students from various disciplines and backgrounds such as computer science, electrical engineering, physics, mathematics, and others. When initiating a robotic vision project at East Stroudsburg University, it began with open discussions upon what resources were available to us, what topics we were interested in, and and what we might be albe to accomplish. The students participating in the project were exposed to diverse challenging problems which were hardly seen in their class course works, and to encounter technical difficulties related to the project. The students were encouraged to work first upon their interests and specialties such as hardware, software, and programming languages. The students routinely presented their understanding of possible problems and solutions to other team members because the projects require sharing the knowledge and helping each other to achieve a common goal of the project success. All the team members including faculty adviser were generally in discussions upon finding and solving the problems, with self-motivated learning and helping each other, and in playing their roles for the project development, management, and technological entrepreneurship of rebuilding the old robot arms within university budget constraints. The projects using robot arms seemed to have outperformed in the students' learning outcomes, motivated the students to enhance their career interests into research fields, and prepared them to an advanced science and technology level in solving practical problems.
A Modeling Tool for Sensor-based Mobile Applications

With the variety of the sensors on mobile devices, sensor-based mobile applications are constantly emerging. Usually, it is necessary to model sensor-based mobile applications, and the modeling requires the domain metamodels and the modeling tools. This paper presents a set of the modeling concepts from the aspects of sensor data perception, sensor data understanding, and sensor data processing, and then builds a metamodel with UML profile mechanism. Moreover, the paper proposes a modeling tool architecture and discusses the design and implementation of key modules in the architecture based on this metamodel. According to the metamodel, architecture, and key modules, the developers can build the tools to model sensor-based mobile applications and generate key code to greatly improve the development productivity and quality of the applications.
Handling the Thorny Issue of Coauthorship in Scientific Publishing

Publication practices, like most things in science, have evolved over time. Long gone is the monograph that marked the culmination of a career. The “publish or perish” mantra has become increasingly demanding, with expectations regarding publication counts inexorably climbing. Those competing for academic positions may notice that the publication records of the evaluators often reflect a different standard from that which they are told they will need to meet in order to advance. On its face, encouraging productivity can be positive, fostering more engagement and creating additional opportunities.
A Computational System for Structural Visual Analysis of Labor Accident Data

This paper presents a computational system that employs Information Visualization techniques to facilitate and enhance the analysis of labor accident data, a serious social problem. Our system uses associated geographical information to create interactive layouts to explore the underlying structure of the data. We present the results of applying our proposed system on data provided by the Brazilian Federal Labor Prosecution Office, demonstrating the potential of our strategy in revealing accident profiles, peculiar behaviors, and patterns associated with all levels of regional hierarchy, as well as in comparing the behavior of localities in the same/distinct regions, among other tasks. We believe that the proposed system provides effective and efficient means to help governments to evaluate current public policies and foment the creation of new ones to reduce these accidents and grant safety for employees, and also encourage citizen participation and transparency in governments.
Student's status in contemporary teaching: Problems and perspectives

It is widely known that teaching as a social and historical category, during various periods of civilizational development, was characterized by several direct and specific factors, with the pupil (student) as a specific category.The status of the student in the process of teaching has been changing during the historical development of the society, which resulted in the change of their role.During the teaching process, the student is preparing for various roles in the society.Therefore, teaching should be in the function of accommodating conditions and enabling the student to participate in decision-making, to develop skills and habits, as well as to develop the ability for learning, thinking, remembering, problem solving, and intellectual independence, as well as the ability to use the gained knowledge in practice.
How Do Technology-Enhanced Learning Tools Support Critical Thinking?

This paper reviews existing computer-supported learning systems that have claimed to adopt Socratic methods for enhancing critical thinking. Several notions of Socratic methods are differentiated: the critical thinking framework of Paul and Elder, the classic Socratic method, the modern Socratic method, and the neo-Socratic group discussion method. Three lessons are highlighted. First, the development of learning systems specifically supporting critical thinking is still lacking Thus, further research in this area is urgent. Second, most developed computer-supported learning systems claim to support Socratic approaches (e.g., Socratic tutoring) which are based on human tutoring strategies and do not show a systematic Socratic method. Third, the classic Socratic method has not been applied in any reviewed learning system.
3D Turntables: Humanizing Architectural Technology Through Hip-Hop

This paper explores the potential impacts of hip-hop culture on architectural technology through arguments on humanizing technology, embracing a post-Western mindset, and reflecting cultural values within creative products. It further documents the results of a design research study that sought to explore the architectural applicability of digital fabrication techniques derived from hip-hop DJ performance. By understanding the DJ’s ability to humanize technology through manual manipulation of analog and digital phonographic equipment, new design methodologies emerged—including the architectural application of “scratch,” “spin,” and “cross-fade” DJ techniques—that deploy a set of disruptions to the 3-D printing process with the potential to transform derelict buildings into community assets.