Miracle-dz/UniFAR-FTUs huggingface dataset:
Robust Capsule Network Based on Maximum Correntropy Criterion for Hyperspectral Image Classification

Recently, deep learning-based algorithms have been widely used for classification of hyperspectral images (HSIs) by extracting invariant and abstract features. In our conference paper presented at IEEE International Geoscience and Remote Sensing Symposium 2018, 1-D-capsule network (CapsNet) and 2-D-CapsNet were proposed and validated for HSI feature extraction and classification. To further improve the classification performance, the robust 3-D-CapsNet architecture is proposed in this article by following our previous work, which introduces the maximum correntropy criterion to address the noise and outliers problem, generating a robust and better generalization model. As such, discriminative features can be extracted even if some samples are corrupted more or less. In addition, a novel dual channel framework based on robust CapsNet is further proposed to fuse the hyperspectral data and light detection and ranging-derived elevation data for classification. Three widely used hyperspectral datasets are employed to demonstrate the superiority of our proposed deep learning models.
SGNN: A Graph Neural Network Based Federated Learning Approach by Hiding Structure

Networks are general tools for modeling numerous information with features and complex relations. Network Embedding aims to learn low-dimension representations for vertexes in the network with rich information including content information and structural information. In recent years, many models based on neural network have been proposed to map the network representations into embedding space whose dimension is much lower than that in original space. However, most of existing methods have the following limitations: 1) they are based on content of nodes in network, failing to measure the structure similarity of nodes; 2) they cannot do well in protecting the privacy of users including the original content information and the structural information. In this paper, we propose a similarity-based graph neural network model, SGNN, which captures the structure information of nodes precisely in node classification tasks. It also takes advantage of the thought of federated learning to hide the original information from different data sources to protect users’ privacy. We use deep graph neural network with convolutional layers and dense layers to classify the nodes based on their structures and features. The node classification experiment results on public data sets including Aminer coauthor network, Brazil and Europe flight networks indicate that our proposed model outperforms state-of-the-art models with a higher accuracy.
Narratives of International Women Entrepreneurs: An Exploratory Case Study of Identity Negotiation in Technology Startups

About the case: Female entrepreneurs play a significant role in new business creation, yet women's entrepreneurship stories remain largely absent in professional communication research. Therefore, a need exists to “give voice” to female entrepreneurship stories, and this exploratory case examines the unique identities that three female entrepreneurs express in their narratives. This case asks how three female entrepreneurs reconciled the discourses of entrepreneurship, gender, and culture to construct a unique entrepreneurial identity in their reflective narratives. Situating the case: Professional communication has only recently begun to explore entrepreneurship communication, and little of that literature explicitly investigates women's experiences. This case, by comparison, uses three conceptual categories—entrepreneurial identity, gender identity, and cultural identity—to explore how three women negotiated their workplace identities. Methods: We recruited three women who self-identified as technology company entrepreneurs, each from a different culture, and recorded their oral narratives about their entrepreneurial journeys. Three raters independently coded data drawing on dimensions extracted from prior literature to build “identity curves” for each narrative. Results: Analysis suggests that each participant negotiated discourses of entrepreneurship, gender, and culture differently, with the greatest divergence appearing on cultural codes, and the least divergence appearing on gender codes. Conclusions: Based on these results, we suggest that future research should begin with the assumption that no single “entrepreneurial identity” exists for female entrepreneurs, and more broadly that professional communication research should foreground differences among individuals rather than attempt to aggregate individual experiences into homogenous characterizations.
PACE: Platform for Android Malware Classification and Performance Evaluation

Android malware has become the topmost threat for ubiquitous and useful Android eco-system. Multiple solutions leveraging big data and machine learning capabilities to detect android malware are being constantly developed. Too often, many of these solutions are either limited to the research output or remain isolated and unable to reach to end-users or malware researchers. In this paper, we propose, PACE, a unified solution to offer open and easy implementation access to several machine learning-based Android malware detection techniques that make most of the research in this domain reproducible. The benefits of PACE are offered using three interfaces i.e. through REST API, Web Interface and ADB interface. Multiple interfaces enable users with different expertise such as IT administrator, security practitioners, malware researcher, etc. to avail its offered services. A community-accepted dataset is used for testing of all the techniques to provide a better comparison of performance. A prototype of the proposed platform is introduced and our vision is that it will help malware analysts to tackle challenges and reduce the amount of manual work.
Basic Forensic Procedures for Cyber Crime Investigation in Smart Grid Networks

The paper outlines some aspects of developing a cyber-forensic framework for Smart Grid cyber-crime investigations. In this research, we examine a key forensic instrument in reconstructing events, the timeline, followed by correlation of data from different sources. Then, we deal with the tasks of collecting and storing the monitored data. The paper also covers some aspects of the legal ramifications from collecting this data and touches on the preconditions that must be met to enable network forensics. Then we present the logging architecture, based on the recommendations of the UK National Cyber Security Center. The final part presents the methodological framework that is the result of applying the OSCAR methodology and relevant open source tools in order to ensure that necessary forensic information can be collected, stored and used as legal evidence in court.
IoT Malware Dynamic Analysis Profiling System and Family Behavior Analysis

Not only the number of deployed IoT devices increases but also that of IoT malware increases. We eager to understand the threat made by IoT malware but we lack tools to observe, analyze and detect them. We design and implement an automatic, virtual machine-based profiling system to collect valuable IoT malware behavior, such as API call invocation, system call execution, etc. In addition to conventional profiling methods (e.g., strace and packet capture), the proposed profiling system adapts virtual machine introspection based API hooking technique to intercept API call invocation by malware, so that our introspection would not be detected by IoT malware. We then propose a method to convert the multiple sequential data (API calls) to a family behavior graph for further analysis.
Challenges facing female executives inthe banking sector in South Africa in thepost-apartheid period

The dawn of democracy in South Africa (SA) in 1994 i.e. post-apartheid era came with inherent societal gender deficiencies and in all Sectors of the SA economy women experienced challenges. Specifically in the Banking Sector women were under represented in leadership and executive positions. The legal framework changed to correct the inequalities of the past resulting in various charters encouraging the private and public sector to transform. Today the advancement of women to executive positions in South Africa can no longer be viewed as an option but rather a requirement. The legal framework in South Africa places companies under pressure by compelling them legislatively to meet Employment Equity quotas as per the Employment Equity Act of 1988, the Labour Relations Act of 1996, the Financial Services Charter and other sector Charters. Corporate South Africa’s commitment to transformation and employment equity has led industries to establish charters that set out specific transformational goals in a particular industry. Despite the fact that the laws have changed and access to equal opportunities are available, the number of women holding executive positions in the financial sector has not increased at the pace that one would have expected given the country’s new democracy. Only 6.6% of CEO positions and board chairs are held by women (BWA, 2007), while the latest 2015 BWA survey states that in South Africa women comprise 51.2% of the working-age population, yet 45.8% form part of the employment workforce. Only 29.3% of all Executive Management positions and 21.9% of all Directorship positions are held by women. The top of the glass ceiling has far less levels of representation by women, only 11.6%, with CEO’s at 2.4% and Chairpersons at 9.2%. These figures indicate that the challenges are surmountable and that there is room for females to play a more http://etd.uwc. ac.za/ xii significant role in leadership and managerial positions in all sectors of the economy, specifically in the financial services. This thesis has evaluated the current situation of female executives in the banking sector in SA, has explored and identified the challenges facing female executives in the banking sector, and has made recommendations based on an exploratory qualitative research method. http://etd.uwc. ac.za/ 1 Chapter 1: Introduction and statement of the problem
Differences in Recruitment Preparation Between Business Fraternities and Social Greek Organizations

2 INTRODUCTION 3 TABLE OF CONTENTS 6 LITERATURE REVIEW 8 The Importance of Recruiting 8 Recruitment Preparation 8 Recruitment Preparation and Career Success 8 Overview of Greek Life and Business Fraternities 12 Cultural Social Greek Organizations 12 Perceptions and Effects of Greek Life 13 METHODOLOGY 15 Survey Structure 15 Distribution 16 Expert Interviews 17 ANALYSIS 18 Survey Data and Demographics 18 Business Fraternity versus Social Greek Organizations 23 Overall Impact 24 High Level Differences Based on Expert Interviews 26 Interview Preparation and Resume/Cover Letter 27 Networking 33 Mentorship 35 Skill Development 37 Segmenting the Data 38 Industry Post-Graduation (Finance versus Non-Finance) 40 Business School Students versus Non-Business School Students 45 Gender Differences 49 Current Students versus Alumni 53 Ethnicity Differences 57
Parliamentary Election and Political Violence in Bangladesh

Politics of Bangladesh has been criminalized over the last four decades resulting multi-level political violence. Political violence is particularly high during the parliamentary election period. This study analyses the nature, causes, and immediate fatalities of political violence during parliamentary election in Bangladesh. Secondary research methods have been used to conduct this study. Data were collected using structured checklist technique analyzing the newspaper contents. This study has revealed that incidents of violence in the month of parliamentary election as well as before and after the month of election are higher than other months. People also become more victim of violence in the month of parliamentary election, before and after the month of parliamentary election than other months. This study has found that the main causes of political violence are strike, blockade, internal and external conflict between political parties, political conflicts, political revenge and establishing political supremacy over a certain area. This study also found that police responses to the incidents of political violence is very low. This rationale of the study implies on that the descriptive findings of the study that can be used to understand the issues and formulate policy to prevent political violence as well as to improve political environment in Bangladesh encouraging the democratic culture to fulfill their goals avoiding the means of violence and conflict. Keywords: Politics, Violence, Election, Political conflicts, Democracy DOI : 10.7176/JLPG/89-11 Publication date :September 30 th 2019
Life cycle assessment of emerging technologies: Evaluation techniques at different stages of market and technical maturity

Life cycle assessment (LCA) analysts are increasingly being asked to conduct life cycle‐based systems level analysis at the earliest stages of technology development. While early assessments provide the greatest opportunity to influence design and ultimately environmental performance, it is the stage with the least available data, greatest uncertainty, and a paucity of analytic tools for addressing these challenges. While the fundamental approach to conducting an LCA of emerging technologies is akin to that of LCA of existing technologies, emerging technologies pose additional challenges. In this paper, we present a broad set of market and technology characteristics that typically influence an LCA of emerging technologies and identify questions that researchers must address to account for the most important aspects of the systems they are studying. The paper presents: (a) guidance to identify the specific technology characteristics and dynamic market context that are most relevant and unique to a particular study, (b) an overview of the challenges faced by early stage assessments that are unique because of these conditions, (c) questions that researchers should ask themselves for such a study to be conducted, and (d) illustrative examples from the transportation sector to demonstrate the factors to consider when conducting LCAs of emerging technologies. The paper is intended to be used as an organizing platform to synthesize existing methods, procedures and insights and guide researchers, analysts and technology developer to better recognize key study design elements and to manage expectations of study outcomes.
Loss and damage: an opportunity for transformation?

ABSTRACT As observed and predicted losses and damages from climate change impacts grow increasingly severe, calls for transformation as a response to long-term climate change have become more frequent. Transformational approaches have also been integrated into the global climate change regime under the UN Framework Convention on Climate Change (UNFCCC) as part of the workplan of the Executive Committee guiding the implementation of the Warsaw international mechanism, the oversight body on loss and damage. However, there has as yet been no attempt to define what is meant by transformation in the context of loss and damage. This paper attempts to clarify the burgeoning academic and policy literature by positing three types of transformation as a response to loss and damage: transformation as adaptation (an intensification of dominant socio-ecological relationships), transformation as extension (when the limits of established adaptive capacity are reached) and transformation as liberation (adopting development pathways that address the root causes of vulnerability). Transformation as liberation is proposed as a deeper change to social-technological systems to avoid and minimize loss and damage in ways that enhance social justice and sustainability. To provide the kind of information decision makers need to plan and implement transformation as liberation, more research is needed on how to plan in a way that ensures the most equitable outcomes. Key policy insights Loss and Damage is an opportunity to scrutinize and address the root causes of vulnerability. Framing climate change as a development crisis will allow opportunities for transformation as liberation to emerge. Transformation as liberation to address the root causes of vulnerability requires meaningful engagement with processes at all levels. A new model of global governance is needed in which global equity is a moral imperative. The transition to transformation as liberation must be just, which requires leadership, inclusive and participatory decision making and building alliances. The global Loss and Damage agenda could open up space for a broader discussion on how transformation as liberation can be facilitated to address inequalities both between and within countries.
Crime script for mandate fraud

Purpose The purpose of this paper is to critically analyse research surrounding mandate fraud and to devise a crime script identifying the crime commission process. It is hoped this will assist in standardising investigation of mandate fraud by law enforcement. Design/methodology/approach The design of this paper follows on from the approach taken by van Hardeveld et al. (2017) in identifying a cybercrime script for carding activity. The current environment surrounding the investigation of digital fraud in the UK is examined through a review of the existing literature. Analysis of the crime commission process for mandate fraud is then outlined in a potential crime script identifying possible intervention points for law enforcement. Findings UK law enforcement’s current response to digital fraud is struggling to provide positive outcomes for victims. There is inconsistency in the investigative approach and practical issues surrounding how the digital fraud problem is tackled. Changing the emphasis of digital fraud investigation to focus on the money laundering networks based in the UK also needs to be considered. Standardising investigation into digital fraud by mapping out digital criminality using crime scripts and routine activity theory could be beneficial for law enforcement. The results of this process could also assist in effectively identifying where law enforcement resources may be best deployed to solve some of the practical issues highlighted. Originality/value There is little literature directly focused on a crime script for mandate fraud. This is despite it being a significant contributor to fraud losses in the UK. For law enforcement, both digital and financial investigation skill sets are required to investigate such offences. Therefore, mapping the crime commission process has significant value for clearly identifying investigative intervention points.
Preparing to transition from pediatric to adult HIV-related care: qualitative assessment and model development

ABSTRACT Prior to the emergence of highly active antiretroviral therapy (HAART) in the mid-1990s, HIV-infected adolescents and young adults (AYA) had poor long-term prognoses. The changing landscape of treatment has led to improved survival outcomes for HIV-infected youth, yet the health care structure for addressing the needs of this population is underdeveloped, in particular, when transitioning from pediatric to adult HIV care. Previous literature has proposed general recommendations for successful HIV transition programs, but limited model development exists to guide these recommendations. In order to better understand and address these shortcomings, the current study qualitatively assessed transition preparedness of 20 HIV-infected AYA (ages 13–24) at a comprehensive care center in the Southeastern United States. The study consisted of individual, semi-structured interviews exploring participants’ preparation for transition. Through qualitative analysis of interview transcripts, a model was proposed to establish transition readiness. The model was based on three key themes encompassing multiple factors that influence transition readiness: (a) social cognition, (b) responsibility and skill development, and (c) health-related stressors. Based on the current study, we surmise that healthcare providers, patients, and their families can use this transition readiness model to better inform and prepare HIV-infected AYA to assume increased responsibility for their own health care.
From Spacewar! to Twitch.tv: The Influence of Competition in Video Games and the Rise of eSports

Since their inception in the 1950s, video games have come a long way; with that advancement came more popularity, a growing demand, and an evolving culture. The first person shooter (FPS) video game genre and the competitive scene that was born out of it is an ideal case study to analyze this change over time. To understand how video games became so popular, one must examine their history: specifically, their development, impacts the games have had on society, and economic trajectories. Similar to traditional professional sports, video games experienced a cultural shift around their lucrative profit margins and unfolding professionalization of gamers as entertainers/athletes. Professional gaming started in the 1980s, where 10,000 participants competed in the Space Invaders Championship. Since then, video games evolved from being a casual past time to a career for some gamers. The resulting professional gaming community has attracted the attention of wealthy businessman, including a disproportionate number of iconic sports names, including the New York Yankees, Golden State Warriors, Magic Johnson, and Robert Kraft, who have all bought into eSports. All of this is possible due to advancement in technology and significantly improved graphics which allows game developers to increase the amount of content and quality of their games. Without continual advancement in these areas, gamers start to lose interest, which means no economic and societal growth. For example, games released in the early 2000s such as Counter Strike, World of Warcraft, and Halo have utilized online features to allow players to compete with whoever they want from the comfort of home, making it easier than ever for gamers to hone their skills against others. Today, constant updates and new titles are now the