Reviewerly/exHarmony huggingface dataset:
InterCriteria Analysis of the Evaporation Parameter Influence on Ant Colony Optimization Algorithm: A Workforce Planning Problem

Optimization of the production process is an important task for every factory or organization. A better organization can be done by optimization of the workforce planing. The main goal is decreasing the assignment cost of the workers with the help of which, the work will be done. The problem is NP-hard, therefore it can be solved with algorithms coming from artificial intelligence. The problem is to select employers and to assign them to the jobs to be performed. The constraints of this problem are very strong and it is difficult to find feasible solutions. We apply Ant Colony Optimization Algorithm (ACO) to solve the problem. We investigate the algorithm performance by changing the evaporation parameter. The aim is to find the best parameter setting. To evaluate the influence of the evaporation parameter on ACO InterCriteria Analysis (ICrA) is applied. ICrA is performed on the ACO results for 10 problems considering average and maximum number of iterations needed to solve the problem. Five different values of evaporation parameter are used. The results show that ACO algorithm has best performance for two values of evaporation parameter – 0.1 and 0.3.
Image Aesthetic Quality Assessment Based on Photographic Composition Rules

Image composition is a vital factor in image aesthetics. In this paper, based on photographic composition of the image itself, we combine the aesthetic deep features with composition features by utilizing multi-task learning. We summarize a series of calculation formulas of the most classic photographic composition rules, such as the rule of thirds, and calculate the composition features and scores of the images. In multi-task learning module, we design double-column networks with static sharing structures. Features from different networks are fused by the method of soft parameter sharing. The composition score and the original aesthetic score of the image are used to supervise the training of the networks. Experiments on AVA-mini dataset show that the multi-task learning can make better use of the composition information of the image. Our method can outperform on the regression task of the image aesthetic quality assessment.
Usability Evaluation of "Inventory Information System" Design of Disaster Management in Yogyakarta Province - Indonesia

"Inventory Management System" is a website-based information system for disaster relief goods inventory designed for the Sleman Regency Regional Disaster Management Agency. Usability interface measurement has not been done when designing the information system. The usability interface is a quality attribute that is used to evaluate the convenience of people in obtaining information on a product, system, or service. This study aims to measure the usability of the existing website design interface and compare the usability value with the improved website design interface. Heuristic evaluation and usability testing methods are used to determine the usability interface design, both before and after repair. The results show that there were 18 problems found by evaluators. After interface improvements, the level of efficiency, effectiveness, satisfaction on all tasks, and usability values based on web-use have increased.
Sample-based Fixed-wing UAV Obstacle Avoidance Method

Compared with the quadrotors, the fixed-wing unmanned aerial vehicles (UAVs) have additional flight constraints such as minimum turning radius, minimum flight speed, and maximum climb rate, which makes it challenging to design obstacle avoidance algorithms for the fixed-wing UAVs. In this paper, we present a novel method to generate a collision-free path based on the Dubins kinetic model. The Monte Carlo sampling algorithm is adopted to solve the optimization problem of the non-analytic path. And the Density-Based Spatial Clustering of Applications with Noise (DBSCAN) method is utilized to optimize the sampling area for accelerating the solving process. Further, an evaluation function is designed which includes the task-performing efficiency and the fuel consumption to get the optimal flight path. Finally, the simulation results demonstrate the effectiveness of the proposed method.
On Building the Largest and Cross-Linguistic Turkish Dependency Corpus

In this paper, we aim to introduce the dependency annotation process of the largest and the only cross-linguistic Turkish dependency treebank which was translated from the original Penn Treebank corpus. Within the scope of this project, 16.400 sentences have been morphologically and semantically annotated, and the dependency relations were manually carried out by a team of linguists. It is hoped that this project will serve as a base for a successful dependency parser and a system which can automatically perform the bi-directional conversion between constituency and dependency trees.
Possible solutions of a linear homogeneous system of differential equations

In the present paper it is shown that the fundamental zero-normalized solution of a system of linear homogeneous differential equations can be represented as a formal series of products of exponential matrices. If the system satisfies the conditions of the Perron theorem on the triangulation of a system of equations, then the solution of such a system can be represented as a finite product of exponential matrices. In addition, a formula for differentiating an exponential matrix function is derived, and the problem of constructing a transformation that reduces a system of homogeneous differential equations to a triangular form is considered.
Bank Endorsement Classification: A Novel Content Based Approach Using Pupil Tracking Technology

These days System security dangers are expanding quickly. Particularly client approval is focused for validation could be used. The eye scanner follows the positions of eye and eye development for perceptible upgrade introduced on PC framework. Different highlights like look point, student proportions and mouse location can be removed and it tends to spoken to utilizing representation strategies, for example, obsession, saccade, check way. The sweep way is perceived as an example and the information is utilized give validation from the server database. The understudy district is followed regard to make a beeline for by and large break down and make a constant extraordinary example that is given to every person. The example framed is confirmed utilizing design that is put away in the database. Here we show a chance on how business eye tracker could be connected with equipment and programming to upgrade bank security.
Deep Memcapacitive Network

Deep networks have gained great momentum in the neural network research community. In deep networks, each layer represents an abstract feature of input data, and information is propagated in a feedforward or a circular fashion through recurrent connections between layers. Training such deep networks requires a complex algorithm. Deep Reservoir Computing (RC) is an alternative to overcome the training complexity of deep networks. In deep RC, the deep network (or reservoir) remains untrained and training only takes place at an output node with a simple algorithm. So far, deep RC was a software-based approach in which the traditional Echo State Networks (ESNs) serve as computing layers within a deep RC structure. Here, we propose a hardware-based platform for deep RC using memcapacitive networks. Our simulation results demonstrate that deep memcapacitive RC is able to compete with the state-of-the-art deep ESN and requires 3.45× fewer layers to accomplish similar tasks. Our deep memcapacitive RC networks offer a potential platform for building novel neuromorphic hardware.
Study of Safe Elliptic Curve Cryptography over Gaussian Integer

Gaussian integer has a potential to enhance the safety of elliptic curve cryptography (ECC) on system under the condition fixing bit length of integral and floating point types, in viewpoint of the order of a finite field. However, there seems to have been no algorithm which makes Gaussian integer ECC safer under the condition. We present the algorithm to enhance the safety of ECC under the condition. Then, we confirm our Gaussian integer ECC is safer in viewpoint of the order of finite field than rational integer ECC or Gaussian integer ECC of naive methods under the condition.
Security for Healthcare Organizations in the Cloud with HITRUST® Assurance

Cloud computing provides a number of valuable advantages for fast-paced business handling sensitive data, and the medical field is no exception. That’s ...
3D visualization of temporal data: exploring Visual Attention and Machine Learning

Temporal data visualization supports planning and decision-making processes as it helps understanding patterns and relationships among time-based data. In many fields of study, users deal with a large volume of valuable information, which is usually analyzed based on temporal aspects. In this scenario, the use of three-dimensional space opens interesting opportunities in time representation, interpretation, and exploration of temporal data. Approaches based on Virtual Reality (VR) techniques are still underexplored to visualize temporal data, most of the times as an extension of the bi-dimensional space, although they can provide more natural interaction in real time. Visual Attention (VA) has grown in relevance in many study areas due to its ability to help humans explore a complex visual scene. Contributing to overcome the limited use of three-dimensional (3D) space in temporal data visualization, in this article, we present a VR approach named 3D BlocK <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">ARL</sup> to support interactive visualization of temporal data. The environment is built based on VA concepts. Our approach uses a rule-based Machine Learning method, generating new ways to visualize temporal information in 3D environments. The results of two controlled experiments with volunteers shows that the visualizations generated by our approach had a good acceptance and were able to decrease the mistake rate while performing a specific task when compared to a traditional approach.
Performace Analysis and Optimization for Short-time Rendering Frames

The rendering cloud platform provides rendering cloud service for animated films, special effects, animated series, effect drawing, creative design and other rendering work. In this paper, a deep research is made into the efficiency and time consumption of short-time rendering frames in a rendering cloud platform with a management scheduling node. An optimized dynamic requesting-interval system is exposed to enhance the performance of this rendering platform to achieve the maximum utilization of rendering nodes when rendering short-time frames. An evaluation experiment between the non-optimized system and the optimized one is done, which shows that the optimized system can achieve a good performance compared to the old system.
The Innovation That Information Science Proposes

Faced with the multiple understandings assumed by different institutions about the concept of Innovation, the need to locate the semantic principles related to this concept was identified, which has ensured that information science (CI) is contemplated by funding agencies in the development of research projects. The objective was to understand the epistemological relationship between innovation and IC in order to construct a semantic indication of both the conceptual compound of innovation according to the logic of the achievement bodies and an indication of what is taken as relevant for funding in development and research by the agency FAPESP (Foundation for the Support of Research of the State of São Paulo, Brazil). It is concluded that since 1992, CI's research projects, subsidized by FAPESP, have had, in a preponderant way, technology (perception of promotion) and interdisciplinarity (communicative efficiency) as determining elements of the relationship of this area with innovation.
Analyzing the Expectation Value of the Hamiltonian for a Single Photon Gaussian Wave Packet State

We show a new analysis to address the problem of assigning a singular frequency and energy for the single photon state understood as a wave packet in the Quantum Field Theory formalism.
Agile Development of a Custom-Made Vocabulary Mobile Application: A Critical Qualitative Approach

There have been some observed studies and developed applications (apps), with a concentration on Mobile Assisted Language Learning (MALL), and no consideration of communicative needs of the learners; besides, these studies focused on either the theoretical aspects or the utilization of the available apps in the market (Burston & Athanasiou, 2020). Hence, Vocabulary Guru (VG), a custom-made mobile application, was developed based on a critical framework and an agile approach to fill out the gap. To tackle the issue, after carrying out a qualitative needs analysis via interviews, the first version of the app was developed and released to the target intermediate EFL university students. The next iterations were developed interactively and creatively, in congruence with the feedback received from the target learners. This cycle of incrementing and re-coding of the app continued until the attractor basins superseded. In the current paper, to shed light on how dynamically the interaction between learners and developers can yield in applications, which are more user-friendly and appropriate for a unique pedagogical setting, the life cycle of VG has been discussed. The agile app development processes of the current study may be useful for vocabulary specialists, teachers, educators, app developers, and pedagogical foundations involved in or considering the design and development of mobile apps by critically analyzing the unique needs of the target population in an interactive dynamic, agile life cycle. The developed app (i.e., VG) may also be utilized by EFL learners who would like to learn academic vocabulary in an educational context.
Noise Removal Method with Super-resolution for Surveillance Camera Images

It is necessary to remove noise from images in order to prevent deterioration due to noise during super-resolution for surveillance camera images. We propose to apply time-domain Total Variation regularization, and it is possible to separate noise and moving objects, and we have achieved to remove noise before super-resolution by applying noise removable process to surveillance camera images.
An Application of Text Detection and Recognition for Electronic Design Automation

This work proposed an application of text detection and character recognition which is used for improving electronic design automation (EDA). Images used in this work contain colored regions and texts enclosed by an external boundary such as a circle or a polygon. Instead of using complicated methods, this work adopts several efficient image processing methods to extract true text regions followed by optical text recognition (OCR). Since the desired texts are not in normal form, we proposed some mechanisms to classify the characters into several types: normal, superscript, and subscript. In the experiments, the accuracy of judging the location information of block text can reach 93.36%. The proposed design can significantly improve the application of text detection and recognition in EDA.
Cryogenic Optical Transitions Of 77Se+ Deep Donors In Silicon Photonic Crystal Cavity Platforms

We aim to develop a spin-photon interface to control long-living Se deep donor qubits. As a first step, we examine their mid-infrared transition under weak and strong coupled regime using a photonic crystal cavity.
Online Auction System

Auction through site is done, which is an extremely monster potential commercial center for merchants and supporters. This undertaking, a web Auction System has two classes as customer interface and administrator interface. The venture includes the look and execution of a web sell off framework. This strategy presents a web show of class insightful item they have to sell or offer. There’s Associate in nursing administrator board by that Associate in nursing administrator will the board the total offering framework. Administrator will endorse item by the classes and can likewise the executives the enlisted clients. The examination organize is performed first for the contextual analysis. Furthermore, the expectation to figure out what goes on operationally inside the web house. It conjointly characterizes the format in humanoid application. Inside which a few assortments of bidders offer the auction and last the sale won can store the consequences of the triumphant bidder subtleties and send through mail face to face and in the long run the load technique can applied.
Hue Correction Scheme for Multi-Exposure Image Fusion Considering Hue Distortion in Input Images

We propose a novel hue-correction scheme for multi-exposure image fusion (MEF). Various MEF methods have so far been studied to generate higher-quality images. However, there are few MEF methods considering hue distortion unlike other fields of image processing, due to a lack of a reference image that has correct hue. In the proposed scheme, we generate an HDR image as a reference for hue correction, from input multi-exposure images. After that, hue distortion in an image fused by an MEF method is removed by using hue information of the HDR one, on the basis of the constant-hue plane in the RGB color space. In simulations, the proposed scheme is demonstrated to be effective to correct hue-distortion caused by conventional MEF methods. Experimental results also show that the proposed scheme can generate high-quality images, regardless of exposure conditions of input multi-exposure images.
Global a Priori Inference in Algebraic Bayesian Networks

The article presents methods for solving the problem of global a priori inference in algebraic Bayesian networks (ABN) for scalar and interval estimates in knowledge patterns of network. The practical significance is that the ability to solve these problems allows us to evaluate the probability of the truth of logical formulas based on the already formed algebraic Bayesian network. Issue is being addressed for the first time. The relevance of the study is emphasized by the fact that ABN is one of the few probabilistic graphic models capable of working with inaccurate data.
Wearable Technologies

Wearable technologies have a large potential to amplify human abilities. Thanks to their close contact to the human body, their miniaturized dimensions and continuous data collection, wearables are versatile, meeting system requirements across domains. Wearable technologies have grown in quantity and quality over the past decades, gaining popularity. However, to foster users' acceptance and sustain their engagement, wearables must be useful, and their interface design must carefully consider user interaction on the go as well as transient requirements from diverse contexts of use. Without such design considerations, not only wearable technologies may become a burden for end users, but also abandonment rates increase. Through illustrative examples of wearable technologies, in this talk I provide an overview of wearable computing, I will discuss the applications, challenges and opportunities in the design of user interfaces for wearable interaction. I conclude the talk presenting a roadmap for next-generation wearables.
Comparative Study of Features Selection Methods

Today, and across the world, denial of service attacks has increased by a significant frequency and takes different forms. The costs of downtime, outages and failures caused by these attacks are very important.
Performance and error analysis of recursive edge-aware Gaussian filters on GPUs

We present a schematic for image edge-aware Gaus-sian GPU filtering which has linear complexity on the number of pixels of the image. It allows us to reduce the execution time as we increase the number of Streaming Multiprocessors (SMs) on the GPU. We make use of a domain transformation and use a complex-valued recursive formulation of the Gaussian filter. The algorithm partitions the image in disjoint regions, where we compute in parallel the filtering operations, avoiding communication between regions. Our implementation leads to a real-time solution using a modern GPU. With the RTX 2080 Ti, we achieved an execution time of less than 10 milliseconds for 2 filtering iterations on high-resolution RGB images of dimensions $2048\times 2048$.
Improved image defogging method based on adaptive neighborhood window size of PMS network

Aiming at the failure of prior theory of dark channel in bright area, an improved algorithm based on PMS-Net is proposed. First, the selection of atmospheric light in dark channel images under different neighborhood windows is optimized, and the atmospheric light value is accurately estimated. Then an improved transmittance estimation method is used to make the transmission map estimation of the bright area more accurate. The improved PMS-Net defogging algorithm is compared with the existing excellent algorithms, and the experimental results show that the algorithm can overcome the color distortion of existing algorithm in processing bright areas. The effectiveness of the algorithm is verified by objective evaluation indicators.
Cloud capability maturity model: A study of South African large enterprises

Background: The adoption of cloud services can enable enterprises to realise improved cost structures, agility and productivity, yet the rate of adoption has been measured. Despite the benefits of cloud computing and the fact that the overall adoption of public cloud services is gaining momentum, South African large enterprises are cautious in adopting the services of cloud service providers because of perceived challenges of cloud adoption. Objectives: The objective of this study was to examine how do South African large enterprises assess and advance their cloud readiness and maturity such that cloud service practices contribute positively to business efficiency and agility whilst mitigating against the perceived risks of cloud computing. Method: This research employed a qualitative approach using in-depth interviews. Sixteen South African large enterprise cases were studied by interacting with respondents associated with cloud decision-making. Data were collected from specific cases, utilising non-probability sampling. Results: Reinvention of the organisation can be enabled through the advanced, integrated cloud and analytic features available through the global public cloud providers such as artificial intelligence and machine learning. A cloud maturity framework and a cloud capability maturity model to optimise and advance cloud maturity status are presented. Conclusion: This article guides information technology (IT) managers to achieve an optimal cloud maturity status level using a proposed cloud capability maturity model. The cloud framework developed in this study will assist IT managers and decision-makers to use evidence-based management principles to determine their maturity of cloud adoption.
Security analysis of Li-Li mixture XOR scheme

Li and Li et al. proposed the HER-XOR scheme in 2013 which differs from the work by Ivy et al. To Li-Li scheme, there have errors since they misused RSA algorithm. In this paper the author would like to point out this incorrect and also fixed it.