Reviewerly/exHarmony huggingface dataset:
Detection of Malicious URLs using Machine Learning Techniques

The primitive usage of URL (Uniform Resource Locator) is to use as a Web Address. However, some URLs can also be used to host unsolicited content that can potentially result in cyber attacks. These URLs are called malicious URLs. The inability of the end user system to detect and remove the malicious URLs can put the legitimate user in vulnerable condition. Furthermore, usage of malicious URLs may lead to illegitimate access to the user data by adversary. The main motive for malicious URL detection is that they provide an attack surface to the adversary. It is vital to counter these activities via some new methodology. In literature, there have been many filtering mechanisms to detect the malicious URLs. Some of them are Black-Listing, Heuristic Classification etc. These traditional mechanisms rely on keyword matching and URL syntax matching. Therefore, these conventional mechanisms cannot effectively deal with the ever evolving technologies and webaccess techniques. Furthermore, these approaches also fall short in detecting the modern URLs such as short URLs, dark web URLs. In this paper, we propose a novel classification method to address the challenges faced by the traditional mechanisms in malicious URL detection. The proposed classification model is built on sophisticated machine learning methods that not only takes care about the syntactical nature of the URL, but also the semantic and lexical meaning of these dynamically changing URLs. The proposed approach is expected to outperform the existing techniques.
Dynamic Control Method and Application of Coastal Engineering Project Construction Cost Based on Rough Sets

Zhang, D. and Liu, X., 2020. Dynamic control method and application of coastal engineering project construction cost based on rough sets. In: Bai, X. and Zhou, H. (eds.), Advances in Water Resources, Environmental Protection, and Sustainable Development. Journal of Coastal Research, Special Issue No. 115, pp. 7-9. Coconut Creek (Florida), ISSN 0749-0208.The traditional cost analysis method of construction engineering has low operation efficiency and poor convergence performance, which leads to inaccurate cost analysis. With the increasingly fierce competition in the construction market, construction enterprises must strengthen the control and management of project costs in terms of systems and measures in order to continuously find profit space in low-cost and low-profit projects. Due to the complexity of the construction process and the uncertainty of many influencing factors, it is difficult to formulate a scientific cost control strategy, predict the degree of influence of various cost factors and reveal the correlation between them and the total cost before construction. Construction cost management of engineering project is the most concerned topic in coastal engineering project, and also the basis and key point of cost control of coastal engineering project. In order to judge the importance of cost factors and find the relationship between cost factors in coastal engineering projects so as to realize scientific cost control decision-making, it is necessary to objectively judge the main influencing factors of cost based on as many cost data as possible.
A Robust Blind Watermarking Scheme for Color Images Using Quaternion Fourier Transform

With the advancement of image devices, massive image data are being generated exponentially, which indirectly leads to more copyright issues over the images. Image watermarking is an important method for copyright protection. Considering that color images dominate the real-world image data, designing copyright protection techniques specially for color images are very meaningful. In this paper, we propose a robust blind watermarking scheme for color images based on quaternion Fourier transform (QFT). After converting the color image data into QFT coefficients, we embed the watermark message into the four channels in QFT domain, to improve the embedding capacity and robustness. We also conduct experiment to investigate the performance of visual quality and robustness, by comparing with some other common signal transforms. The experimental results show that our scheme achieves a satisfactory performance.
Parallel Fault-Tolerant Programming and Optimization of Photonic Neural Networks

We propose and numerically demonstrate a fault-tolerant, efficient parallel nullification protocol to program and error-correct photonic neural networks for energy- efficient machine learning tasks.
WELL-ROUNDED LATTICES VIA POLYNOMIALS WITH REAL ROOTS

Well-rounded lattices have been a topic of recent studies with applications in wiretap channels and in cryptography.A lattice of full rank in Euclidean space is called well-rounded if its set of minimal vectors spans the whole space.In this paper, we investigate the well-roundedness of lattices coming from polynomials with integer coefficients and real roots.
Hiding Traces of Camera Anonymization by Poisson Blending

Sensor noise caused by photo response non-uniformity (PRNU) has been widely accepted as a reliable fingerprint for source camera identification (SCI). An interesting research topic in this area concerns the repudiability of PRNU-based SCI, which includes methods of removing or synthesizing the fingerprint on which forensic methods rely. Removing the PRNU fingerprint from a given image, also known as camera anonymization, is important for privacy protection and anti-tracking. However, camera anonymization sometimes introduces annoying visual artifacts in the resultant image. In this work, Poisson blending is used to hide the traces left by camera anonymization. Theoretical analysis and experimental results show that the proposed method can suppress the visual artifacts caused by camera anonymization effectively while maintaining the anti-forensic effectiveness.
Multiobject Detection Algorithm Based on Adaptive Default Box Mechanism

Multiobject detection tasks in complex scenes have become an important research topic, which is the basis of other computer vision tasks. Considering the defects of the traditional single shot multibox detector (SSD) algorithm, such as poor small object detection effect, reliance on manual setting for default box generation, and insufficient semantic information of the low detection layer, the detection effect in complex scenes was not ideal. Aiming at the shortcomings of the SSD algorithm, an improved algorithm based on the adaptive default box mechanism (ADB) is proposed. The algorithm introduces the adaptive default box mechanism, which can improve the imbalance of positive and negative samples and avoid manually set default box super parameters. Experimental results show that, compared with the traditional SSD algorithm, the improved algorithm has a better detection effect and higher accuracy in complex scenes.
A Multi Ant Colony Optimization Approach For The Traveling Salesman Problem

In this paper, we propose a new approach to solving the Traveling Salesman Problem (TSP), for which no exact algorithm is known that allows to find a solution in polynomial time. The proposed approach is based on optimization by ants. It puts several colonies in competition for improved solutions (in execution time and solution quality) to large TSP instances, and allows to efficiently explore the range of possible solutions. The results of our experiments show that the approach leads to better results compared to other heuristics from the literature, especially in terms of the quality of solutions obtained and execution time.
Building an Ethereum-Based Decentralized Vehicle Rental System

Blockchain technology, beyond cryptocurrencies, is called to be the new information exchange ecosystem due to its unique properties, such as immutability and transparency. The main objective of this work is to introduce the design of a decentralized rental system, which leverages smart contracts and the Ethereum public blockchain. The work started from an exhaustive investigation on the Ethereum platform, emphasizing the aspect of cryptography and all the technology behind this platform. In order to test the proposed scheme in a realistic use, the implementation of a web application for the rental of vehicles has been carried out. The application covers the entire vehicle rental process offered in traditional web applications, adding more autonomy and ease of use to users. Following Ethereum application development guidelines, all business logic is located in the smart contracts implemented in the Ethereum network, where these contracts control the entire vehicle rental system of customers. While this is a work in progress, the results obtained in the first proof of concept have been very promising.
Complex Object Illumination Transfer Through Semantic and Material Parsing and Composition

Complex object illumination transfer presents a particular challenge in computer vision. We took up the challenge and proposed a novel complex object illumination transfer method through semantic and material parsing and composition. Firstly, we parsed the subject complex object into several parts through semantic parsing. We could easier match similar common objects that own same material and similar geometry with subject object parts as example objects through material parsing. For each subject object part, we need two example objects, one is same illumination to the subject object part, and the other is example illumination. Then, we warped two example objects to each corresponding subject object part through patch match. The example illumination transfer to each subject object part through the local and global transfer model learned from two warped example objects. Lastly, we combined each relighting subject object part into relighting subject object through semantic and material composition. Our results reveal that the method could produce similar illumination as the relighting ground truth subject object.
Text Detection on Images using Region-based Convolutional Neural Network

In this paper, a new text detection algorithm that accurately locates picture text with complex backgrounds in natural images is applied. The approach is based primarily on the region-based convolutional neural network anchor system, which takes into account the unique features of the text area, compares it to other object detection tasks, and turns the text area detection task into an object sensing task. Thus, the proposed text to be observed directly in the neural network’s convolutional characteristic map, and it can simultaneously predict the text/non-text score of the proposal and the coordinates of each proposal in the image. Then, we proposed an algorithm for the construction of the text line, to increase the text detection model accuracy and consistency. We found that our text detection operates accurately, even in multiple language detection functions. We also discovered that it meets the 2012 and 2014 International Conference on Document Analysis and Recognition thresholds of 0.86 F-measure and 0.78 F-measure, which clearly shows the consistency of our model. Our approach has been programmed and implemented using Python programming language 3.8.3 for Windows.
Penerapan Pewarnaan Graf Terhadap Penyusunan Jadwal Seminar Proposal Skripsi di Prodi Pendidikan Matematika UIN Raden Intan Lampung

Mathematics Education of UIN Raden Intan Lampung has a problem in the process of preparing the thesis proposal seminar schedule, because there are many students who conduct seminars in the adjacent period. During this time the preparation of the proposal seminar schedule is done manually, not infrequently many schedule lecturers and examiners are clashing with other student proposal seminar schedules. To overcome these problems, a thesis proposal seminar schedule was arranged by applying the concept of point coloring to graphs using the Welch Powell Algorithm. The points on the graph are represented as students who will conduct a thesis proposal seminar, while the side that connects the two points states that these two points have one and / or two supervisors. The research method used is the study method of literature study. The results of this study indicate that graph coloring using Welch Powell algorithm can be applied to arrange seminar schedule for students' thesis proposal for Mathematics Education, Faculty of Tarbiyah and Teacher Training. UIN Raden Intan Lampung.
Application of Offshore Culture in Elderly Community Pension in China's Seaside City

Zhang, Y., 2020. Application of offshore culture in elderly community pension in China's seaside city. In: Bai, X. and Zhou, H. (eds.), Advances in Water Resources, Environmental Protection, and Sustainable Development. Journal of Coastal Research, Special Issue No. 115, pp. 157-159. Coconut Creek (Florida), ISSN 0749-0208.The security problem of community pension in coastal cities has always been the object of safety key management. Generally speaking. In order to ensure the proper operation of the data of coastal cities and all kinds of equipments, coastal cities need to adopt comprehensive and timely intelligent monitoring of the electronic equipments in the community pension to ensure the safety of the data center. Through the research and analysis of the community old-age care in the process of community old-age care there are still many safety problems, according to these problems summarized about the coastal city community old-age security risks and risks, and put forward the coastal city community old-age care risk solutions, but also for the coastal city coastal city community old-age security problems brought effective protection. This paper is based on the application of coastal urban community pension research and discussion, hoping to propose practical solutions.
Encryption Algorithm for TCP Session Hijacking

Distributed network of the computer and the design defects of the TCP protocol are given to the network attack to be multiplicative. Based on the simple and open assumptions of the TCP protocol in academic and collaborative communication environments, the protocol lacks secure authentication. In this paper, by adding RSA-based cryptography technology, RSA-based signature technology, DH key exchange algorithm, and HAMC-SHA1 integrity verification technology to the TCP protocol, and propose a security strategy which can effectively defend against TCP session hijacking.
Network Topology Boundary Routing IP Identification for IP Geolocation

The only few existing methods for network topology boundary routing IP identification are often based on a single network characteristic, with poor applicability, low accuracy, and difficult to meet the IP geolocation requirements. This paper proposes a network topology boundary routing IP identification algorithm for IP geolocation. The proposed algorithm is no longer limited to a specific delay distribution used in D-Based, but identifies the boundary routing IP according to the difference between each single-hop delay in the path and the city delay threshold; more different from traditional methods, when the delay difference characteristic is not obvious, the proposed algorithm combines the differences of routing IP hostnames in different cities to further identify the boundary routing IP and the proportion of identifiable paths is increased. Experiments are carried out using the probing results of millions of landmarks in 10 target cities in China and the US. Results show that compared with D-Based and P-Based, the ratio of identifiable paths is increased by about 103.0% and 69.5%; the number of nodes in the target city is about 1.7 and 1.9 times, and the accuracy of the node location is improved by about 48.3% and 16.9%; using the topology obtained by the proposed algorithm, the success rate of three classic street-level IP geolocation methods such as SLG, LENCR, and Geo-RMP is increased by 75.8%, 61.2%, and 71.7%.
Generative Augmented Dataset and Annotation Frameworks for Artificial Intelligence (GADAFAI)

Recent Advances in Artificial Intelligence (AI), particularly in the field of compute vision, have been driven by the availability of large public datasets.However, as AI begins to move into embedded devices there will be a growing need for tools to acquire and re-acquire datasets from specific sensing systems to train new device models.In this paper, a roadmap in introduced for a data-acquisition framework that can build the large synthetic datasets required to train AI systems from small seed datasets.A key element to justify such a framework is the validation of the generated dataset and example results are shown from preliminary work on biometric (facial) datasets.
LET’S HEAR CHILDREN’S VOICE. AN IMPLEMENTATION OF A DESIGN PROCESS MODEL TO UNDERSTAND CHILDREN’S VIEWS ON TANGIBLE INTERACTION

Children provide innovative insights and perspectives when designing and evaluating prospective technologies and interaction methods.However, working with children as design informants requires careful consideration of the methodologies used in different steps of the design process.In this paper, we present our insights on a case-study of a design process with 24 children (9-12-year-olds), aiming for understanding children's view on new technologies and their perception on tangible interaction.We utilized a lightweight design process model: children first reflected on the use of technologies and participated in an ideation session.Based on the results, researchers built prototypes which were evaluated by the children in the final step of the process.We expect our learnings to help researchers in the field of collaborative design when organizing design activities with children.
Considering User Experience Parameters in the Evaluation of VR Serious Games

Serious Games for Virtual Reality (SG-VR) is still a new subject that needs to be explored. Achieving the optimal fun and learning results depends on the application of the most suitable metrics. Virtual Reality environments offer great capabilities but at the same time make difficult to record User Experience (UX) to improve it. Moreover, the continuous evolution of Virtual Reality technologies and video game industry tendencies constantly change these metrics. This paper studies the Mechanics, Dynamics and Aesthetic (MDA) framework and User Experience metrics to develop new ones for SG-VR. These new parameters are focused on the intrinsic motivations the players need so they engage with the game. However, the development team budget must be taken into account, since it limits items and interactions but still have to aim to the learning goals. New VR metrics will be 1) UX features: chosen VR headsets, training interactions tutorials to learn control and interactive adaptions to avoid VR inconveniences; and 2) MDA features: exclusive VR aesthetical elements and its interactions.
Support Relation Analysis for Objects in Multiple View RGB-D Images

Understanding physical relations between objects, especially their support relations, is crucial for robotic manipulation. In this paper, we propose a method for extracting more detailed physical knowledge from a set of RGB-D images taken from the same scene but from different views using qualitative reasoning and intuitive physical models. Rather than providing a simple contact relation graph and approximating stability over convex shapes, our method is able to provide a detailed supporting relation analysis based on a volumetric representation. Specifically, true supporting relations between objects (e.g., if an object supports another object by touching it on the side or if the object above contributes to the stability of the object below) are identified. We apply our method to real-world structures captured in warehouse scenarios and show our method works as desired.
Four Approaches to Developing Autonomous Facilitator Agent for Online and Face-to-Face Public Debate

Recently, the importance of public debate is increasing both globally and locally for addressing sustainability problems such as pandemics, climate change, and economic crisis. To support such public debate, software agents need to be developed to facilitate discussions, for example, to recommend relevant information by detecting stagnation and flaming in online public debate, to invite debate participants from SNS, or to record face-to-face public debates. In this study, we prototyped four software agents for facilitation: (1) an agent for detecting stagnation and flaming while quantifying the degree of discussion progress in a Web-based debate, (2) an agent for providing relevant information in accordance with the preceding context of a Web-based debate, (3) an agent for finding people who are interested in the content of the discussion and inviting them to a public debate from Twitter, and (4) an agent for recording a face-to-face public debate and supporting users’ reviewing of the debate. In this paper, we overview these four agents and evaluation experiments and present the feedback from the participants in an event organized by Facilitation Association of Japan.
Taking back control: Taming the Feral Cello

Whilst there is a large body of NIME papers that concentrate on the presentation of new technologies there are fewer papers that have focused on a longitudinal understanding of NIMEs in practice. This paper embodies the more recent acknowledgement of the importance of practice-based methods of evaluation [1,2,3,4] concerning the use of NIMEs within performance and the recognition that it is only within the situation of practice that the context is available to actually interpret and evaluate the instrument [2]. Within this context this paper revisits the Feral Cello performance system that was first presented at NIME 2017 [5]. This paper explores what has been learned through the artistic practice of performing and workshopping in this context by drawing heavily on the experiences of the performer/composer who has become an integral part of this project and co-author of this paper. The original philosophical context is also revisited and reflections are made on the tensions between this position and the need to ‘get something to work’. The authors feel the presentation of the semi-structured interview within the paper is the best method of staying truthful to Hayes understanding of musical improvisation as an enactive framework ‘in its ability to demonstrate the importance of participatory, relational, emergent, and embodied musical activities and processes’ [4].
Needs Assessment: Watershed Science for Water Resources Directors

We conducted a needs assessment to identify watershed science training needs for locally elected directors of Nebraska's 23 natural resources districts (NRDs). We interviewed NRD staff and surveyed NRD directors to determine training needs and identify relevant topics and preferred delivery formats. We found that training would be valuable; however, directors are busy, meaning that opportunities for training are limited. Additionally, we learned that directors rely on printed material and other NRD personnel for watershed science information. Therefore, web-based information may be most useful if designed for collaborative learning through hybrid delivery during regular NRD activities. Our findings are relevant to current and future regulatory systems reliant on locally elected boards.