Reviewerly/exHarmony huggingface dataset:
Empirical test of employee incentive in supply chain network based on asymmetric information game analysis and fuzzy model

The construction of the evaluation index system of employee satisfaction level is the basis for an enterprise to measure the level of employee satisfaction. In this paper, the author analyzes the employee incentive in supply chain network based on asymmetric information game analysis and fuzzy model. Through the correction of network weight and threshold value, the error function decreases along the gradient direction. The construction and training of the network can be realized by MATLAB. The newff function in the software is used to construct the network, and the train function is used to train. This evaluation index system is a multi-level target evaluation system based on asymmetric information game, and its basic principle is to simplify complex problems. Long term effort is bigger when the salesperson’s risk averse parameter is more than a certain value or risk averse parameter is less but discount factor is more than a threshold; short term effort is bigger when risk averse parameter and discount factor is both less. For both information scenarios, the compensation contracts are designed and comparison analyses are conducted.
Digital Economy and Cloud

This chapter aims to present the trends and challenges healthcare organizations will face as a result of the digital revolution. In particular, the healthcare industry needs to look for a new strategic focus, acquiring new specialties, and establishing new ways of working, defined in new business models in which cloud computing technology will be increasingly present. Understanding what cloud computing is is the first step to better understand the challenges and trends ahead.
Teleportation based non-degenerate discordant remote state preparation

Remotely preparing quantum states, which possess some desired features, is an important task for future quantum network host providers. On the other hand, the non-degenerate discordant two-qubit states, the states with different left and right quantum discords, is necessary for the implementation of some quantum information and quantum computation processes. This paper presents a new preparation scheme of such states realized by the asymmetric quantum correlation teleportation (AQCT) protocol i.e. quantum correlation teleportation via two different quantum channels. In this way, some properties of AQCT protocol are studied to achieve the most appropriate and least expensive procedure of preparing the asymmetric discordant two-qubit quantum states.
Key Exchange Protocols for Parallel Network File Systems Using Optimized Cryptography

Abstract The utilization of parallel file system is expanding quickly nowadays; security moves toward becoming are significant worry about inside this work is to structure capable and secure affirmed key trade conventions that meet explicit necessities of pNFS. The current techniques neglected to achieve alluring properties, for instance, scalability, viability, escrow free and forward mystery. A large portion of existing techniques either has not been alluringly practiced or are not reachable by the current Kerberos-based arrangement. These issues overwhelmed by a late technique which is utilizing an assortment of authenticated key trade conventions that are intended to address the above issues. This technique utilized AES calculation for security. In this undertaking, It is giving that a new AES calculation objective of accomplishing speed and security. This new AES is called as IAES (improved AES). The proposed security technique will accomplish better execution as far as speed, security, and correspondence overhead when contrasted with existing strategies.
Why can’t we be friends?

Abstract The 2017 Unite the Right Rally in Charlottesville, Virginia represented a watershed moment for the alt-right movement in the United States, involving a highly visible demonstration of multiple far-right hate groups. Understanding how multiple groups such as those that “united” in the Unite the Right Rally is essential in potentially disrupting future events and curbing their ability to create consensus. In this paper, we note that participants often engage in conflict through evaluative and authoritative stance taking. Aggression is sometimes ignored, and other times gets escalated through interpersonal conflict. Throughout, rapport or consensus is rarely prioritized. These findings offer insight into the workings of the alt-right and provide an example of how discourse analysis can be used in intelligence gathering and research on these dangerous groups.
A Flexible High and Low Level Multi Task Behavior Framework for Multi-agent Systems in Complex Environments

This paper introduces a framework for behavior modeling of software agents using the Robot Operating System. We developed a framework to simplify behavior design and model conventional software agent design principles as known for example from belief desire intention BDI agents or adaptive agents. We provide a toolbox that is capable of supporting the developer with easy to implement methods written in python. Finally we present two brief example applications and evaluations in both simulation and using a social automated transport vehicle for intralogistical processes.
E-ALPHA: Edge-based Assisted Living Platform for Home cAre

Novel and emerging IoT-based AAL (Ambient Assisted Living) services promise to notably improve elderly's lifestyles in terms of health and well-being, particularly in the care facilities context (senior neighborhood, clinics, retirement villages, etc). A simulation-driven platform named E-ALPHA (Edge-based Assisted Living Platform for Home cAre) is presented in this paper, investigating its main potential in supporting i) both Cloud and Edge Computing paradigms and their specific deployments; ii) several communication protocols to guarantee a satisfactory level of interoperability among different IoT platforms; and iii) system developers through a simulation-based design. This last feature is particularly important to outline the most appropriate applications/platform configuration for a real deployment and the related expected performance according to the chosen configuration (in terms of number of involved devices, hardware characteristics, required connectivity specifications, etc). Realistic input, coming from a solid and already developed real testbed, have been used in a specific use case to show and validate the potential of E-ALPHA.
An Adversarial Learning Mechanism for Dealing with the Class-Imbalance Problem in Land-Cover Classification

In this manuscript, a deep learning based approach has been investigated for land-cover classification capable of handling situations where there is an imbalance in the class-wise samples in the training set under a novel semi-supervised learning framework. This problem is persistent when the presence of some of the major land-cover classes affects the other recessive classes in a particular region and due to this the generated training set contains a fewer number of samples from the latter group of classes. Here, an adversarial auto-encoder has been used to generate synthetic samples from each of the minority classes so that each of the classes is well represented in the training set. A new training set has then been designed by including the ‘most confident’ artificial samples from the minority classes. This newly formed balanced training set is then shown to be more effective to classify the test samples as compared to the initially available imbalanced training set. The validation of the proposed approach has been performed using patterns collected from two multi-spectral satellite images captured by Ikonos-2 and landsat-8 satellites over different regions of India. The results show significant improvement in test class prediction when compared to that of other state-of-the-art imbalance handling schemes in land-cover classification.
A Developed Cloud Security Cryptosystem Using Minhash Technique

Data protection becomes an important issue for companies and organizations, especially for files uploaded in a place that can be accessed from anywhere and at any time such as cloud computing, which enables multiple users to access information through the provider by the cloud leased service. This access has enabled many unauthorized people to jeopardize files, and is considered a persistent problem at present. Thus, the increased demands for the adoption of cloud computing technologies has led to an increased focus on data protection. In this paper, cloud computing using Salesforce.com is used to access and upload the encrypted files using a hybrid cryptosystem from Advanced Encryption Standard (AES) and Blowfish algorithms. The implemented approach has used the principle of the Minhash technique to generate a group of keys in an efficient way using the k-shingle and Hash function. The implemented work is evaluated using the following performance criteria: encryption time, throughput, memory usage, avalanche effect and entropy by uploaded encrypted files to the cloud using Object Access Protocol- Application Programming Interface (SOAP API) with force.com web service connector cloud. The obtained results have shown a promising way to protect organizations’ sensitive files in less encryption time and high randomness. A hybrid cryptosystem of Blowfish and AES shows a better performance, in terms of encryption time and security (for 1 MB is 60.1 s), throughput (21249.28 bytes/sec), memory used (638561 KB) and avalanche effect (98%).
On the Trust Management Challenge of Asian Global Leadership

Journal of Leadership StudiesVolume 14, Issue 2 p. 67-70 Symposium On the Trust Management Challenge of Asian Global Leadership David De Cremer, Corresponding Author David De Cremer bizddc@nus.edu.sg orcid.org/0000-0002-6357-9385 NUS Business School, National University of Singapore, SingaporeCorrespondence: David De Cremer, National University of Singapore, Singapore. E-mail: bizddc@nus.edu.sgSearch for more papers by this author David De Cremer, Corresponding Author David De Cremer bizddc@nus.edu.sg orcid.org/0000-0002-6357-9385 NUS Business School, National University of Singapore, SingaporeCorrespondence: David De Cremer, National University of Singapore, Singapore. E-mail: bizddc@nus.edu.sgSearch for more papers by this author First published: 12 August 2020 https://doi.org/10.1002/jls.21698Read the full textAboutPDF ToolsRequest permissionExport citationAdd to favoritesTrack citation ShareShare Give accessShare full text accessShare full-text accessPlease review our Terms and Conditions of Use and check box below to share full-text version of article.I have read and accept the Wiley Online Library Terms and Conditions of UseShareable LinkUse the link below to share a full-text version of this article with your friends and colleagues. Learn more.Copy URL Share a linkShare onFacebookTwitterLinkedInRedditWechat Volume14, Issue2Summer 2020Pages 67-70 RelatedInformation
Spatiotemporal Phenomena Summarization through Static Visual Narratives

Information visualization commonly aids the understanding of the evolution of spatiotemporal phenomena. The current work proposes a novel approach to visually represent spatiotemporal phenomena based on the automated generation of static and interactive visual narratives that summarize the evolution of a spatiotemporal phenomenon. The visual narrative is composed of an interactive storyboard that consists of a set of frames that represent events of interest in the phenomenon. Towards corroborating the hypothesis that this approach would effectively and efficiently transmit the evolution of spatiotemporal phenomena, we conceptualized a visualization framework, identifying visual metaphors that map spatiotemporal transformations into visual content and defining the parameterization approaches for spatiotemporal features. We developed a functional prototype implementing the conceptual solution and presented issues encountered regarding visual clutter and parameterization. We conducted a user study based on a questionnaire which concluded that the proposed approach can be effective and efficient for understanding the evolution of these phenomena in terms of transformations for a subset of possible scenarios.
Specification with Class: A Brief History of Object-Z

The end of the 1980s saw a growing interest in object orientation as both a design and programming methodology with the advent of programming languages like C++ and Eiffel. The trend was taken up by some in the formal methods community, including a team of researchers in Australia. Their contribution was a formal specification language, Object-Z, which had immediate industrial impact, gained rapid international recognition, and then two decades later began to fade, along with some of its contemporaries, from the formal methods scene. This paper details the rise and fall of Object-Z from the perspective of two of its original developers.
Multi-objective Evolutionary Algorithms for Data Mining: A Survey

Real-world optimization problems usually involve multiple objectives to be optimized at the same time under multiple constraints and with reference to many variables, whereas multi-objective optimization itself will be a difficult task, equally tough is that the ability to form a sense of the obtained solutions. This article presents various data mining techniques that can be applied to extract information regarding problems of multi-objective optimization. Further, this knowledge provides a deeper insight into prediction for the decision-makers.
Research Support at University of Porto Libraries

This case study describes the research support services provided by the libraries of the University of Porto (U.Porto). The university is composed of 14 teaching units (each with its faculty library), and each faculty has a wide range of research units. U.Porto has a high research activity, which compels libraries to keep pace with the evolving researcher needs, adapting and creating new services that respond to those requirements. From a global perspective, the overall mission of these libraries is to ensure and promote access to information resources made available by U.Porto to the academic and scientific community, both in physical and electronic supports. More specifically, this case will detail the services already provided in the context of research support, ranging from specialized training sessions in scientific publishing, reference management software, or search in bibliographic databases to the creation of thematic guides, support on the publication of scientific journals from within the university, and bibliometric studies.
Fusion Tracking Algorithm for High Complexity Continuous Moving Image Based on Gray Pixel Space Reconstruction

To enhance the recognition ability of continuous motion images with high complexity and guide sports training, a fusion tracking algorithm is proposed based on gray pixel space reconstruction for continuous motion images with high complexity. The original continuous motion image with high complexity is decomposed by vector quantization, and the edge contour feature of the continuous motion image with high complexity is extracted by gray manifold segmentation technique. The method of pixel block matching is used to reconstruct the gray histogram of continuous motion image with high complexity, and the dynamic local feature quantity of continuous motion image with high complexity is obtained, combined with the method of gray pixel space reconstruction. The fusion of continuous motion with high complexity is realized. The proposed method can improve the recognition ability of the image and enhance the recognition accuracy of the motion action.
Big Data Security and Privacy Protection Policy in Cloud Computing Environment

In recent years, the rapid development of information technology has brought unprecedented changes to human society. People are more and more enjoying the benefits of this change, and all walks of life are more and more aware of the importance of information technology. In many emerging information technologies, cloud computing and big data are the two most typical representatives, and the combination of the two has become an inevitable trend. Just like all the network information technology, as long as it involves the network, there will be a problem of security and privacy. The cloud big data platform also has a problem of security and privacy.
Recommendation System for Wedding Service Organizer using Content-Boosted Collaborative Filtering Methods

Abstract The utilization of smartphones that grow continuously is as a result of the changing lifestyle from the peoples in the growing digital world era. This condition can be seen on the large penetration of smartphones in half of the world society. The high smartphones utilization can increase the chance of many businesses, especially in online businesses that are used for promotions and transactions. The efficient and effective process become the main issues in technology development. One example is to meet the needs of wedding services in online business, which most users still have difficulties or need more time in finding the product as desired. Therefore, a recommendation system concept is applied in this research that is able to help the process of product promotion or searching specifically related to new products and involve new users. The content-boosted collaborative filtering method is used in these systems that is implement two previous methods, namely content-based that is used to form a full product rating matrix by a user, while collaborative filtering is used to make recommendations. Based on the experimental results that the system can recommend with 69% accuracy and helpful especially for newly added items or newly registered users.
Stochastic Sequential Modeling: Toward Improved Prostate Cancer Diagnosis Through Temporal-Ultrasound

Abstract Prostate cancer (PCa) is a common, serious form of cancer in men that is still prevalent despite ongoing developments in diagnostic oncology. Current detection methods lead to high rates of inaccurate diagnosis. We present a method to directly model and exploit temporal aspects of temporal enhanced ultrasound (TeUS) for tissue characterization, which improves malignancy prediction. We employ a probabilistic-temporal framework, namely, hidden Markov models (HMMs), for modeling TeUS data obtained from PCa patients. We distinguish malignant from benign tissue by comparing the respective log-likelihood estimates generated by the HMMs. We analyze 1100 TeUS signals acquired from 12 patients. Our results show improved malignancy identification compared to previous results, demonstrating over 85% accuracy and AUC of 0.95. Incorporating temporal information directly into the models leads to improved tissue differentiation in PCa. We expect our method to generalize and be applied to other types of cancer in which temporal-ultrasound can be recorded.
A Brief Review of Socio-inspired Metaheuristics

There are several deterministic and approximation algorithms proposed so far. As the problem complexity grows the approximation algorithms have proven to be computationally cheaper as compared to the earlier ones. The approximation algorithms could be classified as bio-inspired algorithms, swarm-based algorithms and physical & chemical based algorithms. The notable bio-inspired algorithms are Genetic Algorithms, Differential Evolution, Artificial Immune System, etc.
Legalistic Entrepreneurship in the Digital World

This study aims to explain the legalistic entrepreneurship by introducing the type of legalistic entrepreneurship that transforms compliance with laws into entrepreneurship action, and answer the question of how information and communication facilities brought by the digital world can be turned into opportunities in the face of legal obstacles. In this chapter, the concept and components of legalism, the conceptual framework of legalistic entrepreneurship, processes, personal characteristics of legalistic entrepreneurs are explained. In the conclusion section, recommendations are made to policymakers, entrepreneurs, and academicians on virtual commerce and initiatives to be developed in the digital environment and legalistic entrepreneurship.
A General-Purpose Uniform Random Number Package

As computer capacities and simulation technologies advance, simulation has become the method of choice for modeling and analysis. The fundamental advantage of simulation is that it can tolerate far less restrictive modeling assumptions, leading to an underlying model that is more reflective of reality and thus more valid, leading to better decisions. Simulation studies are typically preceded by transforming in a more or less complicated way of a sequence of numbers between 0 and 1 produced by a pseudorandom generator into an observation of the measure of interest. Random numbers are a fundamental resource in science and technology. A facility for generating sequences of pseudorandom numbers is a fundamental part of computer simulation systems. Furthermore, random number generators also play an important role in cryptography and in the blockchain ecosystem. All samples of the sequence are generated independently of each other, and the value of the next sample in the sequence cannot be predicted, regardless of how many samples have already been produced.
Measurement and Analysis of Cloud User Interest: A Glance From BitTorrent

Cloud computing has recently emerged as a compelling method for deploying and delivering services over the Internet. In this paper, we aim to shed new light on the learning of cloud user interest. Our study for the first time shows the existence of cloud users in such real-world content distribution systems as BitTorrent. Based on this observation, we further explore the similarity of content preferences between cloud and non-cloud users. Surprisingly, our statistical model analysis indicates that the users in the cloud AS have significantly different interests from all the observed non-cloud ASes. More dedicated researches are therefore required to better manage this elevating yet unique cloud traffic in the future.
LibGuides: How to Find Juvenile Literature ebooks: Two easy ways to search

This guide will direct you how to find children's/juvenile/young adult literature online at UTSA Libraries and SAPL
The effectiveness of games learning method in national defense preparedness subject on basic training for civil servant candidates

The selection of suitable learning methods will determine the success of a learning process. In the state defense preparedness training program, games are one of the methods used to achieve learning objectives through the use of playful media. This study aims to assess the effectiveness of this learning method and the factors supporting the effectiveness. The study was conducted on participants in Basic Training for Civil Servants Candidates in 2019 in West Sumatra Province through the distribution of questionnaires online. The results showed that 98.8 % of respondents considered that this method was effective. &#x0D;
Linking digital wayfaring and creative writing: true fictions from ethnographic fieldwork

In this article, I explore how creative writing links to mobile media ethnographic practices. Through my digital ethnographies, I have found empirical evidence that socialising, art-making, and wayfaring can and do occur simultaneously in online and offline worlds. The more than textual, more than representational, material and corporeal experiences, and everyday processes are important to how we imagine and theorise art-making practices with mobile media. In this article, I pose the question: How can fiction techniques be used as a method to expose links between digital wayfaring and the creative writing practices? I explore this question through three fictionalised vignettes based on material from my ethnographies. These are grounded in a discussion of non-representational theory as a theoretical perspective to situate the everyday creative practices that go into mobile media art projects involving creative writing.