Miracle-dz/UniFAR-FTUs huggingface dataset:
Collaborative Representation and Sparsity are Both Indispensable for Hyperspectral Imagery Classification

As a recently proposed technique, sparse representation based classifier (SRC) has been widely used for hyperspectral imagery classification and detection. The collaborative representation (CR) and the sparse coding are two key points in SRC scheme. More recently, the proposition that which one of them plays a dominant role in SRC scheme has attracted much attention from researchers in fields of image processing, computer vision, and pattern recognition. In this paper, we first discuss why CR or sparsity works and why one of them alone is not sufficient, and then analyze how CR and sparsity interact with each other. Although we focus on how sparsity augments CR, the necessity of CR for sparsity is also illustrated in both pixel-wise model and joint sparsity model. Inspired by the analysis, we indicate that CR is a powerful tool for solving the high-dimensional pattern recognition with small sample in SRC scheme; sparsity augments CR-based classification in stabilizing, making sure unique solution and rejecting outlying samples. In other words, CR and sparsity complement each other and are both indispensible for hyperspectral imagery classification. The experimental results on simulated data and real hyperspectral imagery confirm the conclusion.
Analysing Monetary Policy Statements of the Reserve Bank of India

We quantitatively analyse the monetary policy statements of the Reserve Bank of India (RBI) between 1998â€“2018, across five governor regimes. Using natural language processing tools, we show that there has been a persistent semantic shift in RBIâ€™s monetary policy communication since adoption of inflation targeting. We construct measures of linguistic and structural complexity that capture governor-specific trends in communication. RBIâ€™s communication is linguistically complex on average, but the length of monetary policy statements has gone down and readability has improved significantly recently. Our results indicate that lengthier statements are linked to higher volatility in equity and currency markets, but not bond markets.
LoRa in a haystack: a study of the LORA signal behavior

Over the years, LoRa has been raising a lot of interest, both from the academia and the industry. LoRa is indeed a promising technology that enables long range and low power communications to connect IoT devices to the Internet. LoRa is often envisioned for several applications such as regular reporting but it is also aimed to be exploited for other applications, such as geolocation for instance. However, current implementations of LoRa geolocation system or other alternative applications suffer from severe inaccuracy. The purpose of this paper is to investigate where the inaccuracy comes from but also to determine LoRa technology based geolocation best uses-cases. The paper characterizes the LoRa radio signal properties, through a real validation campaign, over different contexts and different LoRa physical layer settings. Our results show that the signal properties, such as RSSI or SNR, are more stable in a peri-urban area than in a high density urban area. In the latter scenario, we also observe an asymmetric reception.
Japan's "Free and Open Indo-Pacific" Strategy: Tokyo's Tactical Hedging and the Implications for ASEAN

Abstract:This article argues that by creating a "Free and Open Indo-Pacific Strategy" (FOIPS) in 2016, Japan has engaged in "tactical hedging" to cope with the strategic uncertainty engendered by China's growing economic power and political influence in Asia and the Trump administration's uncertain foreign policy towards the region. Tactical hedging refers to a declaratory policy doctrine that aims to utilize temporal strategic ambiguity to understand and determine whether any long-term strategy shift is necessary or possible. In doing so, Japan has bided its time in order to understand strategic trends and coordinate policies and principles with allies and partners—especially the United States and ASEAN—and shaped the concept of a "Free and Open Indo-Pacific" (FOIP) in accordance with those consultations since 2016. Nevertheless, the emerging trend—especially the clear division between America's more hardline stance towards China and ASEAN's own conceptualization of the Indo-Pacific which aims to facilitate cooperation with China—indicates that the benefits of tactical hedging are diminishing, and that Japan needs to clarify its political stance if it wants to maintain its own FOIP concept as a viable strategic vision.
The genetics of Alzheimer's disease, modelling disability and adverse selection in the long-term care insurance market

The discovery in 1991 that a person’s apolipoprotein E (APOE) genotype provides an indication of their predisposition to Alzheimer’s disease (AD), which accounts for a significant proportion of long-term care costs, raises the question of adverse selection in the long-term care insurance market and about long-term care costs in general. The aims of this thesis are: to develop multi-state models that help to quantify this potential for adverse selection; to parameterize such models using the available data; and to use these parameterized models to estimate the potential costs of adverse selection in the long-term care insurance market. This thesis is in two parts. The first part (Chapters 1 and 2) concentrates on Alzheimer’s disease (AD). In Chapter 1, I discuss the epidemiology and genetics of Alzheimer’s disease and I propose a simple model for estimating the long-term care costs of Alzheimer’s disease attributable to each of the APOE genotypes. I parameterize the model using data from the medical and epidemiolocal literature. Then in Chapter 2, the parameterized model is used to estimate the potential costs of adverse selection in the long-term care insurance market under the crude assumption that non-AD related care costs are a proportion of AD related care costs. The second part (Chapters 3 to 7) concentrates on modelling the disability process in order to independently estimate the care costs arising from disability in long-term care insurance. In Chapter 3, I introduce a model of disability and discuss the datasets that I use to parameterize the model (the 1982, 1984, 1989 and 1994 National Long-Term Care Surveys) and discuss previous relevant research that
Exploring the Asymmetric Linkage between Commodity Prices and Fiscal Performance in Nigeria

The paper examines the asymmetric relationship between commodity prices and fiscal performance in Nigeria between 1984 and 2017 using the non-linear autoregressive distributed lag (NARDL) cointegration technique. In the analysis, the existence of a long-run cointegration relationship between the oil prices, cocoa prices and fiscal outcome is confirmed as well as the asymmetric impact of commodity prices. The study shows that changes in oil prices have a substantial influence on both debt (% of GDP) and external debt stocks. It is demonstrated that since Nigeria’s fiscal operation is largely financed by the proceeds from commodity exports, especially crude oil, in the long run, unanticipated rise or decline in oil prices could have significant effect on public debt levels in the country. Further evidence reveals that an increase in cocoa prices positively and strongly enhances debt (% of GDP), but with no evidence of such effect on external debt stocks, indicating that an increase in cocoa price may not result to a large reduction in external debt stocks. In sum, the study asserts that there is a host of potential significant impacts associated with primary commodity prices (cocoa) on fiscal policy design and economic development in both long and short run. Hence, the study posits that to cushion the effect of commodity price fluctuations, it is crucial to launch several initiatives that would enhance the diversification of the economy. This can be better achieved through the provision of financial incentives and strong regulatory framework for the development of agricultural sector. This study contributes to the existing literature by examining empirically possible asymmetry in the nexus between commodity prices and fiscal outcomes in the context of Nigeria. alternative medium the use of OLS and Johansen co-integration as a whereas structural primary depict in their findings revealed that improvements in institutions could trigger counter cyclical behaviour unlike pro cyclical behaviour associated with weak institutions. A panel study comprising 93 countries was conducted by Arezki and Brückner (2010) to examine the relative effects of commodity price shocks on external debt under two regimes; autocracy and democracy. Employing Least Squares and system-GMM techniques, the study confirms (in the presence of positive commodity price shocks) a significant reduction in external debt, risk of default, expenditures in democracies; but no significant decrease was found for autocracies.
A Platform Agnostic Dual-Strand Hate Speech Detector

Hate speech detectors must be applicable across a multitude of services and platforms, and there is hence a need for detection approaches that do not depend on any information specific to a given platform. For instance, the information stored about the text’s author may differ between services, and so using such data would reduce a system’s general applicability. The paper thus focuses on using exclusively text-based input in the detection, in an optimised architecture combining Convolutional Neural Networks and Long Short-Term Memory-networks. The hate speech detector merges two strands with character n-grams and word embeddings to produce the final classification, and is shown to outperform comparable previous approaches.
Control Systems and Strategy: A Literature Review

Objective - Organisational change necessarily requires an adaptation of a company's information structure, particularly its Management Accounting and Control Systems (MACSs). These systems should be designed according to the defined strategies to assist managers in the decision-making process. This paper reviews research that analyzes the MACSs concept and the elements that characterise it, so that it may be used to identify and characterise the existing systems in any company. Methodology/Technique - Based on a contingency approach to management, the authors perform a broad literature review. Among other aspects, MACS information outputs will be analyzed in terms of the style of use, its nature and the type of decisions supported. In an attempt to broaden the scope of MACS functions, this paper reviews the present literature and provides a theoretical framework for studying the operationalization of MACS. Findings - The results obtained indicate that the operationalization of the MACS concept can be achieved through the way information is managed and characterised, establishing three categories and six different dimensions. Novelty - Theoretically, this framework characterises the existing MACS concept to analyse its impact on company strategy. The authors conclude that knowledge on the relationship between MCAS and strategy is limited, providing considerable scope for further research. In the future, the authors intend to develop a case study to analyse the impact of this framework on companies' internationalisation strategy. Type of Paper: Review. Keywords: Management Accounting and Control Systems; Accounting Information System; Organizational Change; Strategy; Operationalization of Concepts. JEL Classification: M16; M40; F23.
Performance Evaluation and Feasibility Study of Near-data Processing on DRAM Modules (DIMM-NDP) for Scientific Applications

As the performance of DRAM devices falls more and more behind computing capabilities, the limitations of the memory and power walls are imminent. We propose a practical Near-Data Processing (NDP) architecture DIMM-NDP for mitigating the effects of the memory wall in the nearer-term targeting server applications for scientific computing. DIMM-NDP exploits existing but unused DRAM bandwidth on memory modules (DIMMs) and takes advantage of a subset of the forthcoming JEDEC NVDIMM-P protocol in order to integrate application-specific, programmable functionality near memory. DIMM-NDP works on shared memory with the host CPU by definition, takes advantage of abundant memory capacity in the main memory subsystem and remains economic by relying on standard, unmodified DRAM devices. We evaluate DIMM-NDP with a range of bandwidth, latency and compute-bound workloads from the domains of predictive data analytics and machine learning that depend on dense and sparse linear algebra. Simulation results show up to 6.3x better performance for bandwidth-limited applications, representing 79% of the theoretical peak, and up to 3x improved energy efficiency. We complement the evaluation with feasibility checks for DIMM-like form factors to offer 32GB to 128GB capacity per DIMM, hardware overhead costs (below 20%), and power envelopes for standard (13W) and custom DIMMs (40W). A sensitivity analysis of interface properties for comparison with traditional accelerator coupling over PCIe, as well as a case study on porting software kernels, showing in the order of one month programming effort per application, outline reasonable operating points for DIMM-NDP.
What Matters When? Time-Varying Sparsity in Expected Returns

We provide a measure of sparsity for expected returns within the context of classical factor models. Our measure is inversely related to the percentage of active predictors. Empirically, sparsity varies over time and displays an apparent countercyclical behavior. Proxies for financial conditions and for liquidity supply are key determinants of the variability in sparsity. Deteriorating financial conditions and illiquid times are associated with an increase in the number of characteristics that are useful to predict anomaly returns (i.e., the forecasting model becomes more dense). Looking at specific categories of characteristics, we find that variables classified as value, trading frictions and, in particular, profitability are robustly present throughout the sample. A strategy that exploits the dynamics of sparsity to time factors delivers substantial economic gain out-of-sample relative to both a random walk and a simple rolling window shrinkage estimator as well as standard models based on preselected, well-know characteristics like size, momentum, book-to-market, investment and accruals.
Measuring the Local Economic Impacts of Replacing On-Street Parking With Bike Lanes

Abstract Problem, research strategy, and findings: Bike lane projects on retail streets have proved contentious among merchant associations in North America, especially when they reduce on-street parking. A limited but growing number of studies, however, detect neutral to positive consequences for merchants following bike lane implementation. In 2016, the City of Toronto (Canada) removed 136 on-street parking spots and installed a pilot bike lane on a stretch of Bloor Street, a downtown retail corridor. Using a case–control and pre–post design, we surveyed merchants and shoppers to understand the impacts of the bike lanes on economic activities. We find no negative economic impacts associated with the bike lanes: Monthly customer spending and number of customers served by merchants both increased on Bloor Street during the pilot. Takeaway for practice: Our findings are consistent with an improving economic environment at the intervention site. Downtown retail strips may therefore be suited to tolerate bike lanes and even benefit from increased retail activity. Pre and post surveys can provide valuable insights into local economic impacts of streetscape changes affecting merchants along city streets, especially where access to sales data is limited.
Do traditional market consumers care about the halal meat label? A case study in Taiwan

The majority of Taiwanese consumers are not familiar with halal food, although the halal diet has been a global trend highlighting three attributes: cleanliness, animal welfare, and religious norms. This study explores the purchase intention of traditional market consumers in buying halal-labeled chicken measured by their willingness-to-pay (WTP). A total of 904 valid survey samples were collected in May 2017. A logit model and interval regression analysis are adopted to analyze the purchase intention and to elicit the WTP for halal-labeled chicken in traditional markets. Results show that although the attribute of religious norms still influences a small group of consumers, the majority of consumers for halal-labeled chicken in traditional markets are attracted to the attributes of cleanliness and animal welfare. Facing the ever-changing new market trend, this study can prove useful for government and enterprises in planning the marketing strategy and the development of local halal food products.
The social impact of AIDS in the United States

This is a report from the Panel on Monitoring the Social Impact of the AIDS Epidemic set up in 1989 by the Committee on AIDS Research in the Social Behavioral and Statistical Sciences which was in turn set up in 1987 by the National Research Council of the National Academy of Sciences. "Its objective is to form a picture of the effects of the AIDS epidemic on selected social and cultural institutions in the United States and to describe how those institutions have responded to the impact of the epidemic. " (EXCERPT)
Do Local Party Chairs Think Women and Minority Candidates Can Win? Evidence from a Conjoint Experiment

We conducted a national survey of local party chairs that included a conjoint experiment to assess the effects of candidates’ race and gender on chairs’ assessments of their likelihood of winning a state legislative primary election in their area. Chairs from both parties viewed women candidates as just as likely as men to win the support of their base but viewed Latinx and black candidates as substantially less likely to win. The disadvantage chairs believe minority candidates face is insensitive to variation in county demographics among Republican chairs but is attenuated among Democratic chairs serving counties with larger minority populations. Our findings suggest that officials from both parties believe that minority candidates face an uphill battle with their base. This perception may color chairs’ decisions about which candidates to recruit and most vigorously support.
Twin-Net Descriptor: Twin Negative Mining With Quad Loss for Patch-Based Matching

Local keypoint matching is an important step for computer vision based tasks. In recent years, Deep Convolutional Neural Network (CNN) based strategies have been employed to learn descriptor generation to enhance keypoint matching accuracy. Recent state-of-art works in this direction primarily rely upon a triplet based loss function (and its variations) utilizing three samples: an anchor, a positive and a negative. In this work we propose a novel “Twin Negative Mining” based sampling strategy coupled with a Quad loss function to train a deep neural network based pipeline (Twin-Net) for generating a robust descriptor that provides an increased discriminatory power to differentiate between patches that do not correspond to each other. Our sampling strategy and choice of loss function is aimed at placing an upper bound that descriptors of two patches representing same location could be at worst no more dissimilar than the descriptors of two similar looking patches that do-not belong to same 3D location. This results in an increase in the generalization capability of the network and outperforms its existing counterparts when trained over the same datasets. Twin-Net outputs a 128-dimensional descriptor and uses $L_{2}$ Distance as the similarity metric, and hence conforms to the classical descriptor matching pipelines such as that of SIFT. Our results on Brown and HPatches datasets demonstrate Twin-Net’s consistently better performance as well as better discriminatory and generalization capability as compared to the state-of-art.
Trust and Power as Determinants of Tax Compliance in Asia: A Cross-Country Analysis

Research aim: Prior to the emergence of the “Slippery Slope Framework”, studies on factors influencing tax compliance considered many independent variables. However, the framework simplified the tax compliance model in a parsimonious way with only two independent variables capable of explaining tax compliance. These are trust in authority and power of authority. In this study, an attempt is made to test the assumptions of the framework using cross-country data with a larger sample from Asia. Design/ Methodology/ Approach: A cross-sectional data from 41 Asian countries was generated and analysed through Ordinary Least Squares (OLS) regression analysis. Research finding: From the analysis, trust was found to have a significant influence on tax compliance across the countries investigated, while the power of authority was found to be weak in that regard. The interaction between the two variables in explaining tax compliance was also found to be weak across the sampled countries. Theoretical contribution/ Originality: Theoretically, the study supports not only the “Slippery Slope Framework” but also Social Exchange Theory as it shows that in social exchange contract such as paying tax by taxpayers and providing public goods and services by the central government. Trust plays an important role as taxpayers expect reciprocation. Practitioner/ Policy implication: The result highlights to the policymakers in 41 Asian countries that improving tax compliance requires a high level of trust from authorities. Taxpayers seek the judicious use of taxpayers’ money in executing projects and services needed by the nation. Research limitation/ Implication: Considering additional factors such as antecedents of trust and power will add to the explanation of tax compliance using the framework. Keywords: Power, Slippery Slope Framework, Tax Compliance, Trust Type of article: Research paper JEL Classification: H24, H25, H26
The Vanguard’s Voice: a Feminist Analysis of Female Political Potential within the Masculinist State

This analysis presents two comparative examples of the first female Australian Prime Minister, Julia Gillard, and former Prime Ministerial Chief of Staff, Peta Credlin, which demonstrate twofold how women in the political environment are inherently positioned as threats to patriarchal state processes and subconsciously adopt masculine behaviours in their professional practice. This reveals the coercive nature of the patriarchal state as it fundamentally subverts female political advancement and actively shapes political spaces to reproduce patriarchal hegemony.
The Effect of FDI on the Relationship between Fiscal Decentralisation and Economic Growth in Vietnam: Empirical Evidence from Provincial Data

Fiscal decentralization not only promotes economic growth but brings more power to local governments in attracting FDI inflows as well. However, economists and policy-makers often strongly debate the influence of FDI on the fiscal decentralization-growth relationship. This paper empirically investigates the role of FDI in the relationship between fiscal decentralization and economic growth for a panel dataset of 52 provinces in Vietnam during the period 2007-2016 using the two-step GMM Arellano-Bond and FE-2SLS estimators. The estimated results confirm that fiscal decentralization and FDI significantly enhance economic growth, but their interaction terms impede growth rate. In addition, public investment is a significant determinant. These findings suggest some important policy recommendations for central governments in developing countries, especially Vietnam.