Reviewerly/exHarmony huggingface dataset:
A literature review of quality, costs, process-associated with digital pathology

Digital pathology incorporates the acquisition, management, sharing, and interpretation of pathological information, including slides and data, in a digital environment. Digital slides are created using a scanning device to capture a high-resolution image on glass slides for analysis on a computer or a mobile device. Though digital pathology has drastically grown over the last 10 years and has created opportunities to support specialists, few have attempted to address its full-scale implementation in routine clinical practice. To incorporate new technologies in diagnostic processes, it is necessary to study their application, the value they provide to specialists, and their effects on improvements across the entire workflow, rather than studying a particular element. In this study, we aimed to identify what have the current digital pathology systems contributed to the pathological and diagnostic process. We retrieved articles published between 2010 and 2020 from the databases PubMed and Google Scholar. We explored how digital pathology systems can better utilize existing medical data and new technologies within the current diagnostic workflow. While the evidence concerning the efficacy and effectiveness of digital pathology is mounting, high-quality evidence regarding its impact on resource allocation and value for diagnosis is still needed to support clinical diagnosis and policy decision-making. Keywords: Digital pathology, Workflow, Quality, Artificial intelligence, Computational pathology
Competitive Self-Organizing Neural Network Based UAV Path Planning

Path planning is the fundamental aspect of applications for autonomous Unmanned Aerial Vehicles (UAVs) system. It allows UAV to find an optimal path relevant to some specific missions within limited time, especially in large sized scenarios. In this paper, a novel competitive self-organizing neural network algorithm is proposed to improve the search ability and speed up the convergence of traditional algorithms. More specifically, in the initialization phase, a new opposition-based learning is adopted to generate better neurons. Next, a secondary competitive layer is added above the hidden layer, thus enhancing accuracy of the algorithm. Simulations validate the proposed algorithm outperforms some intelligence algorithms in terms of optimization ability.
Design and Application Data-Based Employee Eat Barcode Scanner

Abstract The process of managing data and eating employees is underway now in the process of counting the number of employees who take servings still use conventional methods. Collection without using other tools so that in calculating the number of employees who take portions of food is very susceptible to errors, and making reports are still handwritten on paper so that it cannot present reports quickly and accurately. A system development process to produce software that facilitates the process of managing employee meal data. This application is to develop design software to manage employee data input using a barcode scanner and prepare reports for parties involved in management. This software development process uses the system development life cycle method that starts from the system analysis phase, system design, to the system implementation stage. The expected results of the development of this software can help officers involved in the process of managing employee data, such as the calculation of the number of employees taking food portions, and reporting by the system designed based on the results of the analysis of the running system, so that it can present the information needed more quickly, accurately, relevant and as expected.
VCKSCF: Efficient Verifiable Conjunctive Keyword Search Based on Cuckoo Filter for Cloud Storage

Searchable Symmetric Encryption(SSE) remains to be one of the hot topics in the field of cloud storage technology. However, malicious servers may return incorrect search results intentionally, which will bring significant security risks to users. Therefore, verifiable searchable encryption emerged. In the meantime, single-keyword query limits the applications of searchable encryption. Accordingly, more expressive searchable encryption schemes are desirable. In this paper, we propose a verifiable conjunctive keyword search scheme based on Cuckoo filter (VCKSCF), which significantly reduces verification and storage overhead. Security analysis indicates that the proposed scheme achieves security in the face of indistinguishability under chosen keyword attack and the unforgeability of proofs and search tokens. Meanwhile, the experimental evaluation demonstrates that it achieves preferable performance in real-world settings.
Visible-Imperceptible Image Watermarking based on Reversible Data Hiding with Contrast Enhancement

Currently the use and production of multimedia data such as digital images have increased due to its wide use within smart devices and open networks. Although this has some advantages, it has generated several issues related to the infraction of intellectual property. Digital image watermarking is a promissory solution to solve these issues. Considering the need to develop mechanisms to improve the information security as well as protect the intellectual property of the digital images, in this paper we propose a novel visible-imperceptible watermarking based on reversible data hiding with contrast enhancement. In this way, a watermark logo is embedded in the spatial domain of the original image imperceptibly, so that the logo is revealed applying reversible data hiding increasing the contrast of the watermarked image and the same time concealing a great amount of data bits, which are extracted and the watermarked image restored to its original conditions using the reversible functionality. Experimental results show the effectiveness of the proposed algorithm. A performance comparison with the current state-of-the-art is provided.
Context-Based Expert Finding in Online Communities Using Ant Colony Algorithm

Online communities are the most popular interactive environments on the Internet, which provide users with a platform to share their knowledge and expertise. The most important use of online communities in cyberspace is sharing knowledge. These communities are a great place to ask questions and find answers. The important challenges of these communities are the large volume of information and the lack of a method to determine their validity as well as expert finding which attracted a lot of attention in both industry and academia in. Therefore, identifying persons with relevant knowledge on a given topic and ranking them according to their expertise score can help to calculate the accuracy of the comments submitted on the internet. In this research, a model for finding experts and determining their domain expertise level by the aid of statistical calculations and the ant colony algorithm in the MetaFilter online community was presented. The WordNet Dictionary was used to determine the relevance of the user's questions with the intended domain. The proposed algorithm determines the level of people's expertise in the intended field by using the pheromone section of the Ant colony algorithm, which is based on the similarity of the questions sent by the users and the shared knowledge of the users from their interactions in the online community
On-Orbit Image Sharpness Assessment Using the Edge Method: Methodological Improvements for Automatic Edge Identification and Selection from Natural Targets

The metrics traditionally used for assessing the sharpness level of optical imagery acquired by spaceborne sensors (e.g., relative edge response, point spread function, full width at half maximum of the line spread function, modulation transfer function) are usually measured before launch using a set of standard simulated inputs. However, vibrations occurring during launch and satellite deployment, as well as sensor degradation through time, may alter the nominal characteristics significantly. Therefore, post-launch assessment analyses are necessary for monitoring data quality. To this end, on-orbit measurement techniques for sharpness assessment - e.g., the edge method (EM) - were developed. Selection of suitable targets to be used for such techniques is a crucial step for carrying out the assessment successfully. The objective of this paper is to describe an automatic method for identification of suitable edges to be used for on-orbit sharpness assessment via the EM by taking into account the widespread presence of natural targets - like agricultural fields - on Earth. The presented approach is expected to ease the continuous monitoring of the sharpness level of optical data acquired by spaceborne sensors.
LbR: A New Regression Architecture for Automated Feature Engineering

In recent years, machine learning has developed rapidly and has been widely applied in many fields, such as finance and medical treatment. Many studies have shown that feature engineering is the most important part of machine learning and the most creative part of data science. However, in the traditional feature engineering step, it often requires the participation of experienced domain experts and is very time-consuming. Therefore, automatic feature engineering technology arises, aiming at improving the performance of the model by automatically generating high informative features without expert domain knowledge. However, in these methods, new features are generated by pre-defining a set of identical operators on datasets, ignoring the diversity of data sets. So there is room for improvement in performance. In this paper, we proposed a method named LbR (Label based Regression), which can fully mine correlations between feature pairs and then select feature pairs with high discrimination to generate informative features. We conducted many experiments to show that LbR has better performance and efficiency than other methods in different data sets and machine learning models.
SAR Image Registration Based on Optimized Ransac Algorithm with Mixed Feature Extraction

In this paper, to address the problem in the registration of synthetic aperture radar (SAR), the speeded up robust features (SURF) approach based on multi-level FAST and improved random sampling consistency is proposed. This approach is used to address the high mismatch rate in SAR image registration, and it is based on the characteristics of SAR images. We construct a new corner detection by combining with the hierarchical theory of the system, which is referred to as multi-level FAST (MFAST). The contribution of MFAST algorithm mainly lies in the efficiency of SURF algorithm, which determines the main direction and feature descriptor. And improving the random sampling consistency (RANSAC) to remove mismatched feature points and ameliorate the registration effectiveness. The proposed algorithm is suitable for multi-sensor images with large gray differences and significant edge features. The experimental results show that the registration efficiency of the proposed algorithm is more than three times of the SURF algorithm, and the registration accuracy also is better than traditional SURF algorithm, which can reach 0.39 pixels.
Entanglement-assisted quantum MDS codes from generalized Reed–Solomon codes

In this paper, some new classes of entanglement-assisted quantum MDS codes (EAQMDS codes for short) are constructed via generalized Reed–Solomon codes over finite fields of odd characteristic. Among our constructions, there are many EAQMDS codes with new lengths. The lengths of these EAQMDS codes may not be divisors of $$q^2\pm 1$$ , which are new and have never been reported.
SketchingInterfaces: A Tool for Automatically Generating High-Fidelity User Interface Mockups from Hand-Drawn Sketches

Sketches are an integral part of designing user interfaces and despite advances in design tools, many user interface designers still rely on pen and paper when creating these sketches because of their reliability, familiarity and ease of use. Rough sketches are well suited for quick ideation and experimentation, but are typically lacking in detail, resulting in limited readability and clarity when presented to others. In this paper we present the SketchingInterfaces tool, which uses machine learning to translate hand-drawn UI sketches into high-fidelity UI mockups in real-time. The goals of this tool are the following: (1) to speed up the design process, (2) to allow rapid iteration on near-final design artifacts, (3) to improve group collaboration and (4) to lower the threshold of required design skills. We present the results of a study evaluating the tool with six participants to demonstrate the viability of the approach.
Enacting into Reality: Using User Enactment to Explore the Future of Autonomous Vehicle Design

Self-driving vehicles have been heralded as a dramatic new advancement in personal mobility. This emerging technology, beyond potentially improving driving safety, also represents a redefined relationship between the human driver and the vehicle. As this artificial intelligence-based vehicular technology becomes more intelligent, conventional interaction design methodologies may be challenged in their ability to fully encompass this redefined relationship. This problem may be even more pronounced for specific populations like older adults (60+) whose perspectives, we argue, have been underexplored in the self-driving vehicle context. Within this report we describe an emerging methodology, user enactment, and explore its use as a generative design process in two studies focused on older adults. This work adds additional support to the contention that user enactment may be an effective methodological tool for researchers in exploring the relationship between humans and intelligent technologies.
Online Optimized Product Quantization

Recently, approximate nearest neighbor(ANN) search has achieved great success in quantization models due to its high search performance, strong expression ability, and small memory space. However, most existing quantization methods are batch-based models, such as product quantization and optimized product quantization, they are not suitable for processing data with a streaming style, and an existing online product quantization model can not decompose the space optimally. To address this problem, we propose an online optimized product quantization(online OPQ) model. This model can dynamically update the quantization codebooks and the rotation matrix. To track the movement of quantization codewords, we design a strategy for the model to update the orthonormal matrix. Furthermore, we derive the distortion bound to measure the difference of codebooks learned by our online model and OPQ method. The experiments demonstrate that our online OPQ model is efficient for ANN search compared with baseline models and that the method of tracking sub-codebooks further improves the performance.
Potential and Challenges of Prototyping in Product Development and Innovation

Prototyping represents an established, essential method of product development and innovation, widely accepted across the industry. Obviously, the use of prototypes, i. e., simple representations of a product in development, in order to explore, communicate and evaluate the product idea, can provide many benefits. From a business perspective, a central advantage lies in cost-efficient testing. Consequently, the idea to “fail early”, and to continuously rethink and optimize design decisions before cost-consuming implementations, lies at the heart of prototyping. Still, taking a closer look at prototyping in practice, many organizations do not live up to this ideal. In fact, there are several typical misunderstandings and unsatisfying outcomes regarding the effective use of prototypes (e. g. Christoforakos & Diefenbach [3]; Diefenbach, Chien, Lenz, & Hassenzahl [4]). For example, although prominent literature repeatedly underlines the importance of the fit between a prototyping method or tool and its underlying research question and purpose (e. g. Schneider [7]), practitioners often seem to lack reflection and structure regarding their choice of prototyping approaches. Instead, the used prototypes often simply rest on organizational routines. As a result, prototypes can fail their purpose and might not contribute to the initial research question or aim of prototyping. Furthermore, the varying interests of different stakeholders within the prototyping process are often not considered with much detail either. According to Blomkvist and Holmlid [1], stakeholders of prototyping can be broadly categorized in colleagues (i. e. team members involved in the process of product development), clients (i. e. clients, whom the product is being developed for or potential new clients to be acquired) users (i. e. potential users of the final product). Each of these stakeholders employ different purposes of prototyping due to their distinct responsibilities within the process of product development. Moreover, they can hold different expectations regarding the prototyping process, and thus, have different preferences for certain methods or tools. Yet, the substantial role of stakeholders in the appropriate choice of prototyping approach and methods is often overlooked.
Hybrid Algorithm Combining Modified Diffie Hellman and RSA

The Classic Diffie-Hellman (CDH) algorithm encounters several security problems. The algorithm security depends on the complexity of solving the discrete logarithm and the integer factorization problem. The security also depends on the length of bits keys used. In this paper, we proposed a hybrid algorithm, the combination of Modified Diffie Hellman (MDH) with the Rivest, Shamir, and Adelman (RSA) algorithm. The MDH will not use primitive root (g). Instead, it will use two prime numbers (P and Q) for key exchange. It reduces the possibility of a man-in-the-middle attack. Furthermore, the MDH has an authentication mechanism. If both shared keys are equal, the communication will continue. Otherwise, it will stop because it is compromised. Also, the RSA algorithm will use the two prime numbers generated by MDH (P and Q). The RSA algorithm will perform the encryption and decryption message. The Diffie Hellman (DH) and the RSA Algorithms are the basis of several security standards and services on the internet, especially TLS and SSL. If the security of both algorithms is compromised, such systems will collapse. In this proposal, the combined cryptography system aims to achieve secret message exchange; it uses random prime numbers after multiplication and eventually shared with the other end of a communication. The proposed algorithm secretly generate a value so that the security level increases.
Deterministic Dynamic Network-Based Just-in-Time Delivery for Distributed Edge Computing

For distributed Edge Computing, we propose to leverage the deterministic data delivery in optical Determinist Dynamic Networks to jointly optimize compute and network resource allocation. Numerical results show that our DDN-based approach can accelerate the application total execution time by 50-70% from baseline approaches.
Design of Waste Management System Using QR Code for Effective Management in Wastebank

Abstract Waste management is one of the problems faced in almost every city in Indonesia. One way to manage waste is through the waste bank. The business process of a waste bank is similar to a bank, but it is processed in the form of inorganic waste that has been sorted. In general, data management in waste banks is still conventional but the others have used of web-based or mobile technology. But in this way there are still some weaknesses such as the the time needed to input the collected waste data because the data cannot be directly entered into the system. In addition it can occur inaccurately entered data. The proposed method is using the QR code for the waste management system. In this method, admin only need to scan the QR code label attached on the waste bin stored above the weighing device using a smartphone camera. With this system QR scanner application based on mobile can be synchronized automatically with anroid smartphone. Admin then input the weight of the waste that is weighed and will be stored in the database. In this way the data input process can be faster and with the use of QR code, more data can be stored.
Distance Estimation Using Self-Induced Noise of an Aerial Vehicle

In this letter, we propose an algorithm to estimate the distance between an aerial vehicle and a large obstacle using the self-induced noise present during the vehicle's normal operation. We demonstrate the feasibility of using the proposed estimation method in real-time as a feedback mechanism to actively control the altitude of a blimp-like vehicle. The method is built upon a physics-based acoustic model of an unknown source emitting sound near an acoustically reflective surface. By placing two microphones beneath a motor-propeller system used to control the altitude of the vehicle, a real-time processing algorithm of the audio signals is presented that can accurately detect the distance from the microphones to the ground. The method is based upon computing the cross-correlation matrix of the signals on the two microphone channels. We develop a novel cross-correlation processor that is capable of filtering out the unknown source term and extracting the relevant time-delay representing the time it takes for an acoustic wave traveling from the microphone to the ground and back. Furthermore, we show that the method is also robust to the more complex noise source generated by a quadrotor in a static, tethered experiment. To the best of our knowledge, this is the first framework and demonstration of obstacle sensing onboard an aerial vehicle using only the self-generated noise.
Efficient Designs of Reversible Shift Register Circuits with Low Quantum Cost

Reversible computations have attracted a lot of attention in recent years due to the ability to reduce energy dissipation that is needed in nanocircuits. The main purpose of designing reversible circuits is to reduce the energy consumption that occurs due to the loss of input bits in irreversible circuits. In this paper, we initially proposed a new [Formula: see text] reversible block and then its quantum realization is given using the Miller et al. method. In the following, an effective reversible design of D flip-flop is introduced using the proposed reversible block. Finally, four types of reversible shift register including serial-in to parallel-out (SIPO), parallel-in to parallel-out (PIPO), parallel-in to serial-out (PISO) and shift counter are proposed using the proposed reversible flip-flop. The evaluation results show that the proposed circuits are superior compared to the existing designs in terms of quantum cost (QC).
Application Analysis of VR Virtual Technology in Environmental Art Design Teaching

Abstract VR technology has been widely used in various industries, and has brought huge benefits. The field also needs VR to inject more new vitality. The purpose of this paper is to analyze the application of vr virtual technology in environmental art design teaching. This paper introduces the basic concepts of panoramic video projection, then briefly analyzes the implementation principles and layout methods of mainstream projection methods. Using the knowledge and analyzing the advantages of practical teaching cases, constructions scheme of desktop virtual reality course. And the use of software for VR display. For the current art design teaching proposed new teaching methods. This paper evaluates the teaching effect of the application. The experimental results show that in the investigation, when you think that the use to create environment design situation is conducive to improving students’ enthusiasm for learning environment design, 37 students in the experimental class choose to promote, while 12 students choose to have no change, one of the students chose to be a hindrance.