Reviewerly/exHarmony huggingface dataset:
POMP: Pomcp-based Online Motion Planning for active visual search in indoor environments

In this paper we focus on the problem of learning an optimal policy for Active Visual Search (AVS) of objects in known indoor environments with an online setup. Our POMP method uses as input the current pose of an agent (e.g. a robot) and a RGB-D frame. The task is to plan the next move that brings the agent closer to the target object. We model this problem as a Partially Observable Markov Decision Process solved by a Monte-Carlo planning approach. This allows us to make decisions on the next moves by iterating over the known scenario at hand, exploring the environment and searching for the object at the same time. Differently from the current state of the art in Reinforcement Learning, POMP does not require extensive and expensive (in time and computation) labelled data so being very agile in solving AVS in small and medium real scenarios. We only require the information of the floormap of the environment, an information usually available or that can be easily extracted from an a priori single exploration run. We validate our method on the publicly available AVD benchmark, achieving an average success rate of 0.76 with an average path length of 17.1, performing close to the state of the art but without any training needed. Additionally, we show experimentally the robustness of our method when the quality of the object detection goes from ideal to faulty.
Two-perspective Biomedical Named Entity Recognition with Weakly Labeled Data Correction

Biomedical Named Entity Recognition (BioNER) is one of the most essential tasks in biomedical information extraction. Previous studies suffer from inadequate annotation datasets, especially the limited knowledge inside. This paper proposes a two-perspective named entity recognition method with Weakly Labeled (WL) data correction. Firstly, from the perspective of coverage and accuracy, we utilize PubTator and multiple knowledge bases to construct two large-scale WL datasets, which are then revised by their corresponding label correction models respectively, obtaining two high-quality datasets. Finally, we compress the knowledge in the two datasets into a BioNER model with partial label integrating. Our approach achieves new state-of-the-art performances on three BioNER datasets.
The University of Hong Kong Research Data Management Introduction (RPg students)

The presentation slides about the Research Data Management workflow, DMP tool and Data repository for the new RPg students in the University of Hong Kong.
Manajemen keamanan informasi menggunakan framework COBIT 5 dan ISO 27001:2013 dalam pembuatan dokumen standard operating procedure

This research to improve the quality of public services in accordance with the expectations of the community as service users. According to ISO 27001: 2013, an information security management system is an integrated part of an organizational process and in overall information security management in maintaining confidentiality, integrity and availability of information, managing and controlling security risks. information. To maintain consistency in providing optimal services, internal improvements need to be made to build a management system that will guarantee the quality of the education process according to the set standards. So, one of which is a standard that will become a reference in the form of an SOP (Standard Operating Procedure) on information security management. This research was conducted in Regional Financial and Aset Management Board (BPKAD) East Java Province. Therefore, this study proposes the making of SOP (Standard Operating Procedure) as a standard regarding information management using the Cobit 5 and ISO 27001:2013 framework. This study proposes the making of SOP (Standard Operating Procedure) as a standard regarding information management using the Cobit 5 and ISO 27001:2013 framework. This research will produce SOP documents that refer to Cobit 5 and ISO 27001: 2013 regarding information system security management. This research resulted, (1) document processing problems procedures; (2) aset management procedures; (3) server and network access room management system; (4) facility management procedures; (5) change management procedures; (6) management of capacity management procedures; (7) LOG management procedures; (8) management of service continuity procedures; (9) remote access management procedures; (10) backup management procedures.
CONCEPTUAL MODEL OF FORMATION OF ECOLOGICAL COMPETENCY OF FUTURE TEACHERS OF NATURAL SCIENCES

The aim of this paper is to substantiate the approaches to modeling the pedagogical system of formation of ecological competencу of future teachers of natural sciences in the process of professional training in higher education. The essence of the terminological apparatus of the researched problem is analyzed and the pedagogical concept of research is offered. The content and structure of the conceptual model of formation of ecological competencу of future teachers of natural sciences are determined. The structure of the model includes the following interconnected component blocks: conceptual-methodological, theoretical-contents, organizational- procedural, diagnostic-evaluation. The conceptual and methodological block contains methodological principles and approaches to the formation of ecological competencу of future teachers of natural sciences, pedagogical patterns and a system of principles of organization of the educational process aimed at achieving this goal. The theoretical-contents block of the model represents the components of the content of the educational process of ecological training of future teachers of natural sciences, which have a psychological and pedagogical influence on the formation of structural components of ecological competencу of the individual. The organizational-procedural block includes components that directly reflect the interconnected forms, means and technologies of realization of the content of the educational process aimed at the formation of ecological competencу of future teachers of natural sciences. Diagnostic and evaluation unit is represented by diagnostic tools and methods of its application, as well as reflects the criteria, indicators and levels by which the assessment of the state of formation of ecological competencу of future teachers of natural sciences.
FEATURES OF COMPOSITION IN THE ART OF CHILDREN’S BOOKS BY ARTHUR RACKHAM

The article studies the book illustration by the English artist Arthur Rackham (1867–1939), the features of his work in the context of time and the experience that can be used in the process of teaching the book design and illustration. Here, research interest is focused on six main techniques that the artist actively used when illustrating in the children’s books in England in the late 19 – early 20th century. The name of A. Rackham and his graphics, are entirely associated with the English Art Nouveau. Having studied the graphic heritage of A. Rackham, on the example of his seven illustrations for children’s books, one can trace how A. Rackham’s creative credo was formed. The artist managed to move away from imitation of the English Victorian style, the Eastern and Western charts, medieval manuscripts and came to his own version of the Neo-Gothic in the art of the English book
Measuring secure software development awareness and usage among software developers

Abstract: Secure software development practices adoption could be the most influential factor for the future of softwareindustry. Awareness and knowledge about security mechanisms and secure coding techniques plays a vital role in decision to consider security during software development by the software developers. This study aims to explore thesecurity and secure software development awareness among software developers. The results of the study related to the use of secure software development methodologies showed a very low level of adoption level by the developers. It was revealed by the respondents that 82.72% respondents have never used any secure development methodology, about 13.67% respondents were using secure software development methodology in their software development from 1 to 4 years, 2.09% respondents using secure software development methodology in their software development from more than five years and only 1.57% respondents were using secure software development methodologies in their software development from less than a year. All the respondents were well aware of the software security but only 22.51% of the respondents were aware of the latest secure software development methodologies.
Data Hiding Techniques Using Steganography Algorithms

Steganography is the method of hiding information or data in a very peculiar manner using cover objects and various techniques. In the last two decades, the adaptability of the digital communication and information sharing arouses the need for data susceptibility and thus steganography comes into play. Derived from Greek word “steganos” meaning hidden, comes steganography or “concealed writing”. It focuses on creating a safe and secure communication link between the parties. It aims at hiding the existence of the message as opposed to its complement cryptography, which deals with making the message illegible through encryption. It is very useful in various fields and might be a crucial key in countries where public use of cryptography is prohibited. Here, we brush upon current techniques and ideas that are used along with the algorithms and future scope of study in this area. This review paper touches each point primarily with the intention of creating awareness. The main objective of this review paper is to briefly understand the present methods used in steganography and to compare them with the old cryptography methods and then to wonder of an approach that could learn from the mistakes of cryptography and work on the present methods in such a manner that would lead towards the growth of the field. Keywords: Steganography, data hiding technique, algorithms, cryptography, communication Cite this Article Ashi Tyagi, Rahul Veer Singh, Srishti Sharma. Data Hiding Techniques using Steganography Algorithms. Journal of Advanced Database Management & Systems. 2020; 7(1): 12–14p.
Why research data management

In the first few sections of this article series, we answered the question: What is research data management (RDM)? In this article, we will provide more detail on the changes in the research process that relate to RDM and explain why it has become increasingly important to understand the significance of RDM.
MultiScale Fusion of Histogram-based Features for Robust Off-line Handwritten Signature Verification

Developing robust signature verification systems is one of the most attracting topics in the handwriting recognition field. In fact, dealing with signature spoofing requires the use of robust features that help to distinguish authentic signatures from the forged ones. Presently, we propose a multiscale fusion of two histogram-based features to perform signatures description. Precisely, we introduce the Local Difference Feature as new descriptor that is fused with the Histogram Of Templates. These features are calculated on a multiscale neighborhood to highlight pixels distribution within the signature shape. The verification stage is achieved by using SVM classifier. Performance assessment is carried out on GPDS-300 and MCYT-75 datasets. Results in terms of average error rates evince the robustness of the proposed features, which outperform various state of the art methods.
Big Data Privacy Management: A Vision Paper

The growing trend towards big data and cloud computing provides enormous data-driven applications such as location-based services. However, it also creates many potential risks for some individuals in big data scenarios. These risks are further complicated by the security and privacy constraints on the individuals' data that are inherently sensitive. To handle these risks and challenges, this paper proposes our vision of an active, adaptive, and scalable framework for sharing and processing potentially sensitive data. We identify the main privacy risks and technical challenges and present some preliminary solutions. The key idea of this framework is that it integrates risk active monitoring, risk active assessment, privacy active management, accountable systems, and law and regulation to ensure big data security and privacy in the whole system. We believe that this conceptual framework may provide a helpful and useful foundation for big data privacy management and will open up many existing research challenges.
Sensing defects: Collaborative seeing in engineering work

This paper explores how professional engineers recognize and make sense of product defects in their everyday work. Such activities form a crucial, if often overlooked, part of professional engineering practice. By detecting, recognizing and repairing defects, engineers contribute to the creation of value and the optimization of production processes. Focusing on early-career engineers in an advanced steel mill in the United States, we demonstrate how learning specific ways of seeing and attending to defects take shape around the increasing automation of certain aspects of engineering work. Practices of sensing defects are embodied, necessitating disciplined eyes, ears, and hands, but they are also distributed across human and non-human actors. We argue that such an approach to technical work provides texture to the stark opposition between human and machine work that has emerged in debates around automation. Our approach to sensing defects suggests that such an opposition, with its focus on job loss or retention, misses the more nuanced ways in which humans and machines are conjoined in perceptual tasks. The effects of automation should be understood through such shifting configurations and the ways that they variously incorporate the perceptual practices of humans and machines.
Fuzzy Cognitive Maps and Spiritual Modeling of Management Systems: Issues and Challenges

Modeling of Management Systems has been gaining recently the attention of many researchers. Complex dynamic systems are no longer static but most of its subsystems are dynamic and highly nonlinear. Management of such systems has become a challenging and difficult problem. Decisions must be made everywhere and by different people assuring the efficient performance of a business or an enterprise. Old management models and methods cannot solve effectively today’s most management problems and challenges. The human behavior cannot be neglected. There is a need to consider the concept of spirituality in modeling management systems. Advanced mathematical theories and methods can benefit a lot on this effort. Artificial intelligence (AI) and Fuzzy Cognitive Maps (FCM) are considered as appropriate advanced methods. A new unified method is proposed utilizing Intelligence and Wisdom in an integrated way. Spirituality is playing a central and crucial role on management systems. The Plato–Aristotle approach to developing a Spiritual Model for Management Systems is proposed for the first time and briefly explained.
Thermal-Based Pedestrian Detection Using Convolutional Neural Networks and Multi-Regions Dropout Technique

Pedestrian detection is one of the most common research topics in the area of computer vision. It has a significant impact on the safety of autonomous driving and related surveillance applications. Recently, because of the rising of Convolutional Neural Networks (CNN) in deep learning techniques, object detection algorithms have made a significant breakthrough in their accuracy and robustness. However, most detection algorithms can only perform stably under the environments where lighting is sufficient. Nighttime pedestrian detection remains a challenging problem. In this paper, we present a thermal-based framework to solve the nighttime pedestrian detection problem, which utilizes the thermal camera and extends the Faster R-CNN method. In addition, a multi-scale model scheme is used to enrich the learning information of pedestrian features, and a feature region segmentation method is added to solve the occlusion issue. From the experimental results, it demonstrates that our proposed method achieves higher performance compared to current classic deep learning pedestrian detection methods.
Video Object Detection and Tracking based on Angle Consistency between Motion and Flow.

Detect and Track (D&T) extracts a foreground region by using a feature map and region proposal network (RPN) and estimates an object class by using fully connected layers. A correlation layer, which is a hidden layer that obtains displacement between adjacent frames, estimates the movement and size of an object between the adjacent frames. Then, object class and regression are estimated by the feature maps obtained from the correlation layer and RPN. Finally, D&T estimates the moving direction and movement of a bounding box from the detection results obtained from the correlation layer and adjacent frames. Although D&T can achieve accurate object detection and tracking, the object detection and movement estimation of the correlation layer relies on the detection results of the RPN. Therefore, the correlation layer does not acquire local and global pixel changes in video frames and has to estimate the moving direction only from the similarity of detected regions. As a result, the estimation of the moving direction tends to fail. In this work, we propose a method to improve the moving direction estimation by performing the estimation in such a way as to maintain the consistency between the estimated direction and optical flow. Experimental results show that the proposed method can successfully estimate the moving direction and thereby improves both the detection and the tracking accuracy.
Denoising method of rail point cloud data based on morphological filtering

When using a three-dimensional point cloud scanner to collect data points, due to the influence of various uncertain factors, the data points obtained by the three-dimensional electronic scanning device are always mixed with some noise points. If the noise contained in the point cloud is not filtered through technical methods, these noises will definitely have an impact on the subsequent extraction and recognition of the target set characteristics. Therefore, based on the accurate acquisition of 3D data, we research and design a fast denoising preprocessing algorithm that can be used for high-density 3D data to provide more accurate and effective 3D measurement data for subsequent 3D reconstruction and recognition processing.
Recognizing Gestures from Videos using a Network with Two-branch Structure and Additional Motion Cues

In this paper, we propose a method for recognizing gestures from videos which implicitly incorporates multimodal data during training, and makes classification by only using RGB modality data. The network is 3d-convolutional, and includes a shared network for implicitly incorporating multiple modalities, a generation branch for estimating motion regions and a classification branch for classifying gestures. We introduce a type of efficient modality data, binarized motion cues, which include information of moving hand regions, and are learned by using the generation network. The binarized motion cues are given as extra supervision for learning motion in the generation branch. Since features of additional motion cues learned by the generation branch are implicitly fused with features learned by the classification branch, the classification performance can be improved. Experimental results showed that the shared network can extract more discriminable intermediate features, and the network with the classification branch can achieve improved performance by only using RGB modality input data.
Potentiality of Uranium Mineralisation in the Environs of Chhattisgarh Basin, India: a new occurrence in Chhibra

The Meso-Proterozoic intracratonic basins are known for hosting medium to high grade, large tonnage, low cost unconformity-type uranium deposits in the world like-Athabasca Basin, Saskatchewan, Canada and the Pine Creek Geosyncline, Northern Territory, Australia. Similarly, there are fourteen Proterozoic basins in India, out of which, the unconformity-related uranium deposits are identified at Lambapur-Yellapur-Chitrial in the northern part of the Cuddapah basin. Based on the geological setting, age and fertile basement provenance, the other Proterozoic basins in India also hold promise for uranium mineralisation. In this context, the Chhattisgarh basin which is third largest Proterozoic basin in Central India occupying an area of 33,000 sq. km. with 2500m thick sediments, is identified as one of the major favourable targets for uranium mineralisation. It is located at the northern fringe of Bastar Craton in parts of Odisha and Chhattisgarh and comprises mostly siliciclastic sediments of Singhora, Chandrapur and Raipur Groups. &#x0D; Uranium exploration carried out in the environs of Chhattisgarh basin mostly along the basin margins, have brought to light a number of uranium occurrences having sizeable dimensions hosted by both the basement rocks viz. Malaikhaman (0.026-0.11% U3O8), Makarumunda (0.013-3.3% U3O8), Damdama (0.026-0.43% U3O8) , Kashipali (0.010-0.96% U3O8), Karichhapar (0.011-0.40% U3O8) and the cover sediments viz. Juba-Banjhapali (0.010-0.078% U3O8), Govardhangiri-Bagia Nala (&lt;0.010-0.80% U3O8), Chitakhol-Renkhol-Bokarda (&lt;0.012-0.39% U3O8). The newly located uranium mineralisation in the sandstones of Rehatikhol Formation near Chhibra which is exposed intermittently over a strike length of 800m with grab samples (n=43) physically assayed 0.014 to 0.140% eU3O8, 0.010 to 0.120% U3O8 (Î²/Î³) and &lt;0.005% ThO2. Uraninite and pitchblende have been identified as uranium minerals. The favourable factors like geological, geochemical, geophysical, sedimentological, tectonic framework and presence of fertile granitic rocks (n=33, 5-26ppm U) in the provenance indicate its potentiality for uranium mineralisation. The exploration so far, has been mostly confined around shallow basin margins leaving deeper part unexplored. With the advancement of geophysical techniques like airborne magnetic, radiometric and electromagnetic surveys it would be possible to explore the deeper part of the basin. In addition, geochemical techniques such as hydro and litho-geochemical sampling could also be applied around suitable litho-structural settings, especially along the shear/fault zones trending NNE-SSW to NW-SE and their intersections with the ENE-WSW trending shear/fault zones. &#x0D; The present paper deals with the potentiality of uranium mineralisation in the environs of Chhattisgarh basin with emphasis on recently located significant occurrence of uranium mineralisation near Chhibra in the Rehatikhol Formation of Singhora Group along the southeastern margin of Chhattisgarh basin.
Smoothening Junctions of Engineering Drawings Using C2 Continuity

Vector representation of images has numerous advantages such as storing, analyzing and editing of the same. The processed vector information can be used to reconstruct the images. This paper proposes a vectorization algorithm followed by smoothening of the drawings by applying C2 continuous Bézier curve approximation technique. For vectorization, text-graphics separation and skeletonization has been carried out on the input images followed by computing vector information based on the geometric features of different shapes. Junctions has been detected from the vector information and C2 continuity is applied on them for smoothening the shapes. The results of the proposed algorithm demonstrate that it can transform the input images into smoothen ones by individually correcting the shapes of different objects in the images.