Reviewerly/exHarmony huggingface dataset:
On disks of the triangular grid: An application of optimization theory in discrete geometry

Chamfer (or weighted) distances are popular digital distances used in various grids. They are based on the weights assigned to steps to various neighborhoods. In the triangular grid there are three usually used neighbor relations, consequently, chamfer distances based on three weights are used. A chamfer (or digital) disk of a grid is the set of the pixels which have distance from the origin that is not more than a given finite bound called radius. These disks are well known and well characterized on the square grid. Using the two basic (i.e., the cityblock and the chessboard) neighbors, the convex hull of a disk is always an octagon (maybe degenerated). Recently, these disks have been defined on the triangular grid; their shapes have a great variability even with the traditional three type of neighbors, but their complete characterization is still missing. Chamfer balls are convex hulls of integer points that lie in polytopes defined by linear inequalities, and thus can be computed through a linear integer programming approach. Generally, the integer hull of a polyhedral set is the convex hull of the integer points of the set. In most of the cases, for example when the set is bounded, the integer hull is a polyhedral set, as well. The integer hull can be determined in an iterative way by Chvátal cuts. In this paper, sides of the chamfer disks are determined by the inequalities with their Chvátal rank 1. The most popular coordinate system of the triangular grid uses three coordinates. By giving conditions depending only a coordinate, the embedding hexagons of the shapes are obtained. These individual bounds are described completely by Chvátal cuts. They also give the complete description of some disks. Further inequalities having Chvátal rank 1 are also discussed.
An Asynchronous Serial Communication Learning Media: Usability Evaluation

Abstract The availability of a good acceptable learning media is a vital part of the learning process. This paper presents a usability evaluation of the asynchronous serial communication module, which can exhibit the level of acceptance of Data Communication‘s students. The survey was performed based on ten simple statements of the System Usability Scale (SUS) questionnaire. The research‘s findings have been analyzed in three different approaches, i.e., visual “five-pointed star” shape assessment, Bangor et al. model verification, and curved grading scale justification. The analysis showed that the serial communication module is in the acceptable category.
Controlled movement of portable underwater system (PUS)

Purpose of research . The article contains mathematic simulation and research of movement of a portable underwater robot designed to monitor pollution of hydrosphere objects. Modern methods of environmental monitoring suggest the presence of stationary sites. The task of mobile controlled monitoring remains unresolved currently. One of the ways to solve this problem is the transition to control systems that provide a given movement of the water system both on the surface and under water. Therefore, the purpose of this article is to study and set the basic laws and algorithms based on mathematical models that describe the controlled movement of portable underwater systems. Methods . When developing the motion control algorithm for PUS, a mathematical model was used to determine the spati-temporal location of PUS with a variable thrust vector. The basic mathematical expressions that determine the movement of PUS in a predetermined path are obtained. Particular attention is paid to that part of the algorithm that ensures the movement of PUS in a predetermined path in underwater mode if there is no contact with the global navigation system, taking into accounts the underwater GPS and the distance to the bottom and obstacles. As the main criterion of quality of control system we have used the deviation of the actual position of PUS from the position datum. Results . To select the direction of movement when monitoring water, a method of planning the trajectory, built on piecewise linear sections, has been developed that allows probing the space of water in such a way as to ensure maximum efficiency of the monitoring process with a minimum number of sampling points. For this, each new segment of the trajectory and sampling points are planned taking into account information on the concentration of pollutants at the previous stage, as well as the coastline and the depth of water. Conclusion The article discusses the method for monitoring water bodies using a portable unmanned underwater system. The kinematic and dynamic models of the PUS movement are developed. It is proposed a method of planning a trajectory of motion based on piecewise linear segments. We have developed an algorithm of controlling the autonomous movement of the underwater vehicle.
Combining Learning and Hand-crafted Based Features for Face Recognition in still Images

This paper presents a combined face recognition method based on Context-Aware Local Binary Feature Learning (CA-LBFL) which is learned based Descriptor and Dual-Cross Patterns (DCP) which is hand-crafted Descriptors. Both features are extracted and concatenated into a single enhanced feature vector which can be used as a face descriptor. In unconstrained face images the intra personal variations, pose and illumination changes are more, hence the combination of features can effectively solve this problem. The experimental results illustrate that this method has better recognition rate and more robust than single individual methods on the FERET database.
APRNET: Achieving Privacy-Preserving Real-Name Authentication over Blockchain for Online Services

With the proliferation of mobile Internet applications, online services become a double-edge sword to our daily life, wherein security and privacy are notable. To ensure data security, service providers may require users to register using real-name data. Thus, verifying the real-name information without privacy leakage is critical. In this paper, we propose a privacy-preserving real-name authentication scheme based on a classic blockchain paradigm, named APRNET. By taking advantages of cloud-enabled trusted authorities and bilinear pairing, APRNET verifies users' data in an encrypted form, which guarantees data security and user privacy. Detailed security and performance analysis validate the effectiveness of APRNET.
Handling Imbalanced Data Classification Problem using Artificial Immune System with Mahalanobis Distance

Most of the data in the classification domain are imbalanced data, meaning that the answers of each class are not the same. The data prediction in the majority class has been accurate while the answer that is interested is in the data in the minor class. To overcome this problem, we propose a sampling technique using the artificial immune system with Mahalanobis distance (AIS/MD) for the imbalanced class distribution. The proposed method is to reduce the complexity of the original process used by the artificial immune system class, which has proven to be beneficial and promising in different applications. Experimental results on 10 typical imbalanced datasets from UCI Machine Learning Repository show that the proposed method achieves better general implications compared to other methods.
Providing the Sharing of Heterogeneous Ontology Design Patterns in the Development of the Ontologies of Scientific Subject Domains

The paper describes an approach to solving the problems of using ontology design patterns (ODPs) for the development of the ontologies of scientific subject domains (SSDs). This approach offers a system of the heterogeneous ODPs, including both universal patterns and patterns oriented to the presentation of scientific knowledge, as well as methods of their joint use for building ontologies of SSDs. The use of this approach allows us to save resources spent on the development of ontologies, avoid errors common in ontological modeling, as well as ensure a consistent presentation of all the entities of the ontologies of scientific subject domains.
A Complete Scheme of Word Spotting System for the Balinese Palm Leaf Manuscripts

The word spotting system is urgently needed to be able to work with thousand pages of digitized ancient Balinese palm leaf manuscript. This system will be very helpful for the scholars to perform a keyword searching in all manuscript collections with a query image. In this paper, we present a complete scheme of word spotting system for the Balinese palm leaf manuscripts. Our proposed complete scheme of word spotting system for the Balinese palm leaf manuscripts consists of three main sub schemes: the offline patch images extraction process, the feature extraction method, and the patch ranking scheme. We applied six filters of Gabor from six different orientations for the patch image extraction process, and we proposed the use of 64 Gabor filters which are combined with seven different Zoning methods for the feature extraction methods. We also propose an adaptive sliding patch algorithm to spot all possible patches in manuscript page and the patch ranking scheme to rank the spotting results. For the test and evaluation, we used a published dataset of AMADI_LontarSet. Our scheme shows a very promising results. The word spotting system is able to spot many query patch images in different manuscript pages.
Performance Analysis of Different Decision Tree Based Methods for Identifying Drop Out Students

The main concern of an educational institution is to enhance the performance of students. But dropping out of students is a large obstacle that creates bad impact in this purpose. For this reason, most of the educational institutions are conscious about reducing the rate of drop out students. To reduce the drop out students, firstly it is needed to identify the reasons behind the drop out students. In this paper to address the issue, different Decision Tree (DT) based methods as well as the boosted approaches have been used. Firstly, the features of the dataset have been sorted according to their importance based on Information Gain (IG). After the features being sorted, the dataset is partitioned into three categories: the all features, two-third of the features and one-third of the features. Thereafter the standard DTs and the boosted DTs are being experimented over the partitioned dataset to identify drop out students.
Having Fun Doing Research on Agile Methods

In this paper, we summarize the research done by the first author on Agile Methods in Brazil in a historical setting. In the beginning, Alfredo Goldman started as an enthusiast of Agile Methods, without pretending to become an agile advocate. However, as he perceived the importance of this new form of software development and in the belief of promoting a different way of looking at software engineering, naturally his contributions and achievements took him in this regard. We present Goldman’s agile software development research topics, and their respective contributions. We had the hard task to summarize more than a decade of research in only one short text. We show the influence of his work within Agile Methods since 2001, not only on teaching, but also on the research field and on the Brazilian software development industry.
Assessing landscape response to tectonics in the Jalisco block and adjacent areas (west-central Mexico) using topographic analysis

To elucidate how landscapes respond to either tectonic and climatic changes through time, geomorphologists use the analysis of river and basin morphometry. Many studies have evaluated how rivers, and consequently hillslopes, respond to changes in the rate of rock uplift in compressional settings. The case of extensional settings, however, has received less attention. We examine the case of landscape response to tectonics in west-central Mexico to identify zones where there is notable increase in the tectonic activity. The study of west-central Mexico is challenging for the morphometric analysis since there is an interplay between the development of extensional structures and pulses of volcanism, mainly from Eocene to Oligocene and Pliocene to Pleistocene, that have buried large parts of the landscape. For our purpose we use the normalized channel steepness index (ksn) to evaluate how this index correlates with other morphometric parameters such as the hillslope gradient, hillslope convexity and concavity, terrain rugosity and first order stream gradient (Fosg). We use the landform units map as the spatial unit of analysis and from this, we estimate the morphometric properties of the landscape. The results of the morphometric analysis indicate that the topography of Eocene to Oligocene volcanic landscapes are well explained (~70%) by the ksn and in less degree for Pliocene to Pleistocene landscape where ksn accounts for ~55–66% of landscape morphometry. Our results also indicate that the ksn is the best suited among all morphometric variables used in this study and confirm that the landscape of west-central Mexico is dominated by river incision. Landscape incision is particularly high on the northern part of the Jalisco block, mainly along the Ameca river and its tributaries such as Atenguillo river, and north of the Jalisco block, along the Santiago river and on tributaries incising the Sierra Madre Occidental. Finally, the morphometric analysis indicates that even for the case where the volcanic rocks and sediments are filling up large parts of the landscape, river incision resulting from the tectonic activity is capable to cut into lavas, propagating the change imposed by the tectonic activity.
Integration of Fuzzy Clustering into the Case Base Reasoning for the Prediction of Response to Immunotherapy Treatment

The functioning of the medical diagnostic process is very similar to the pattern of the case-based reasoning cycle (CBR). This resemblance has prompted several research groups to build on the CBR, which is a paradigm of problem solving based on past experiences, in the design of medical decision support systems. In this article, we propose a medical decision support system specifically in dermatology based on fuzzy logic to predict the response of a patient with plantar and common warts to immunotherapy treatment. The aim of this work is to improve the retrieval step, which is a very important phase in the CBR cycle, by incorporating segmentation techniques “fuzzy clustering”. The proposed approach is composed of two parts; the part of the clustering by the Fuzzy C-Means algorithm and the part of case-based reasoning realized by the JColibri platform. The use of the FCM is to reduce the search space and solve the problem of rapid retrieval of similar cases.
Mobile MIM: a Portable Solution in Imaging

Clinicians experience various situations, such as peer consultation or tumor boards, in which they need to access and view radiologic studies without a full radiologic workstation. Mobile MIM is a diagnostic medical imaging device on the Apple App Store that is FDA-approved and can meet the portable needs of clinicians. The goal of the app is to give physicians the opportunity to visualize scans from multiple modalities on a single iOS mobile device. The intended uses include reviewing complex aspects of radiation treatment plans and analyzing medical images from a wide array of modalities. The key limitation is incompatibility for mammography. The free app allows users to manipulate image sets from ten sample patients before an organization can commit to extensive systems integration with MIMcloud 2.0 to store, encrypt, and route image sets for real-time patients. This review explores the app’s strengths and weaknesses through discussion of its features and usability.
Infinite families of MDR cyclic codes over <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" display="inline" id="d1e27154" altimg="si467.svg"><mml:msub><mml:mrow><mml:mi mathvariant="double-struck">Z</mml:mi></mml:mrow><mml:mrow><mml:mn>4</mml:mn></mml:mrow></mml:msub></mml:math> via constacyclic codes over <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" display="inline" id="d1e27164" altimg="si20.svg"><mml:mrow><mml:msub><mml:mrow><mml:mi mathvariant="double-struck">Z</mml:mi…

We study α-constacyclic codes over the Frobenius non-chain ring R≔Z4[u]∕〈u2−1〉 for any unit α of R. We obtain new MDR cyclic codes over Z4 using a close connection between α-constacyclic codes over R and cyclic codes over Z4. We first explicitly determine generators of all α-constacyclic codes over R of odd length n for any unit α of R. We then explicitly obtain generators of cyclic codes over Z4 of length 2n by using a Gray map associated with the unit α. This leads to a construction of infinite families of MDR cyclic codes over Z4, where a MDR code means a maximum distance with respect to rank code in terms of the Hamming weight or the Lee weight. We obtain 202 new cyclic codes over Z4 of lengths 6, 10, 14, 18, 22, 26, 30, 34, 38, 42, 46, 50 and 54 by implementing our results in Magma software; some of them are also MDR codes with respect to the Hamming weight or the Lee weight.
Libraries and Innovative Thinking in the Digital Age

Librarianship, as is quite obvious, is changing very fast with the high rate of technological infusion in every aspect of the profession. Books and other information resources that are managed by libraries and information professionals are being transformed to electronic platforms. Also, the information users are becoming more technology savvy as well as sophisticated in their information needs and the quest to satisfy these needs. Users are vast in the use of search engines, and it is like they do not need libraries and the services of librarians anymore. All these and many more developments have put great strains on libraries and librarians. This chapter therefore discusses how librarians can provide services for 21st century users through innovative thinking.
F-2 Robot Toolkit: Model for Speech Comprehension and Communicative Behavior

The chiller system in a building accounts for the main part of the building's total energy consumption, so it is critical to optimize the operation of chiller system for the purpose of saving energy. A chiller system generally consists of evaporation side and condensing side. The condensing side includes chillers, cooling water pumps and cooling towers, which form a subsystem of cooling water. It is a typical optimization problem to minimize the total energy consumption of cooling water subsystem. This paper discusses how to solve the optimization problem of the cooling water subsystem and proposes a simple optimal control rule for field operation based on the optimization results.
Revised Successive Search GMDH Algorithm with Recurrent Estimating Model Parameters

The paper presents a successive search algorithm MULTI-R GMDH being an improved and revised version of the known algorithm MULTI. This new version differs from the original algorithm by using a recurrent procedure of parameters estimation and additional optimizing the model structure. The numerical characteristics of the processing speed and structural accuracy of this algorithm are given for several test tasks.
The Semi-Automatic Approach to Extract the Features of Human Facial Region

The segmantation of the human facial region from a complex background is the basis for the success of today's applications such as facial recognition, expression extraction, surveillance systems, and the guilty people finding. Finding the face region and then extracting attributes that represent the face is another problematic process that needs to be overcome. In general, as is well done in the literature, using the Viola-Jones method or functions in libraries such as D-lib, the above-mentioned operations can be performed fully automatically. This means that the methods applied automatically to use reference data (e.g., XML data format for Viola-Jones) or detectors (D-lib landmark detection) to find keypoints independent of the given object as input. In this study, it is aimed to extract the face region from the image containing the frontal human face with semi-automatic approaches and to mark the area with eye and nose keypoints on the obtained area. Human face contour and face geometry information are used in face positioning. The eye map (i.e., EyeMap) algorithm was used for eye keypoint extraction, while facial geometry, morphological operations and computer vision library OpenCV template matching functions were used for the nasal region. As a result, the main purpose of this study is to obtain the facial region via ensuring the appropriate features with our semi-automatic approach instead of extracting automatically by using known libraries or mostly by machine learning methods. In addition, some discussion and conclusion are involved by our study as well.
Anchor Point based Hough Transformation for Automatic Line Detection of Engineering Drawings

We propose an algorithm that connects the edge graph by anchor points in advance and then performs line detection. The algorithm can generate valid edge segments, each of which is a valid pixel chain. Unlike some traditional edge detection algorithms, which works on threshold gradient amplitude clustering to determine edge elements. Our algorithm firstly obtains the anchor points according to the edge boundary direction of the image and the gradient values, and then connects the anchor points through the intelligent routing algorithm to obtain the edge images, and generates effective edge segments, which are valid pixel chains, then, according to the half-sampled Hough transform line detection, so as to realize the detection of graphics in a straight line, The edge map generated by the previous stage always contains a clean, perfectly continuous, well-positioned single-pixel wide edge. In addition, the quality of the edge pixel chain is also very good, and then the line is fitted by the least squares method again, and the final detected line effect is significant.
Pose Control for Rigid Body Motion with an Input-to-state Safe Control Barrier Function

In this paper, we present a pose control method for rigid body motion via an input-to-state safe control barrier function (ISSf-CBF). After discussing the kinematic model for a rigid body, we design an ISSf-CBF for obstacle avoidance. Next, we present a control Lyapunov function (CLF) for a control error system which possesses a passivity property. By using the ISSf-CBF and CLF, we discuss a unified quadratic program formulation that ensures both safety and stability for pose control of rigid body motion under input disturbances. Our proposed approach, which deals with both the position and the orientation of rigid body motion, connects the safety and the stability via the ISSf-CBF and the CLF under input disturbances. Finally, simulation results confirm the validity of the proposed ISSf-CBF control method compared to the stabilizing one.
Applying MASI Algorithm to Improve the Classification Performance of Imbalanced Data in Fraud Detection

Imbalanced data is recognized as one of the most attractive matters to many researches. It is shown by numerous publications on this which is a growing interest. The hardest challenge is the failure of generalizing inductive rules by learning algorithms. such as difficulty in forming good classification on decision boundary over more features but fewer samples and risk of overfitting of the sampling. So many solutions have been applied to deal with these problems. In our article, we propose a novel method called MASI (Moving to Adaptive Samples in Imbalanced) in term of changing majority class samples’ label into minor class samples based on data distribution. This proposed method rebalances the classes before training a model in order to improve the classification performance in imbalanced data. We tested on some unbalanced datasets from data of UCI. The empirical results showed that our method has a significant achievement in Sensitivity and G-mean values than other classification models, such as Random Over-sampling, Random Under-sampling, SMOTE, and Borderline SMOTE in using different machine learning approaches, including SVM, C5.0, and RF.