VeriSparse: Training Verified Locally Robust Sparse Neural Networks from Scratch

Several safety-critical applications such as self-navigation, health care, and industrial control systems use embedded systems as their core. Recent advancements in Neural Networks (NNs) in approximating complex functions make them well-suited for these domains. However, the compute-intensive nature of NNs limits their deployment and training in embedded systems with limited computation and storage capacities. Moreover, the adversarial vulnerability of NNs challenges their use in safety-critical scenarios. Hence, developing sparse models having robustness guarantees while leveraging fewer resources during training is critical in expanding NNs' use in safety-critical and resource-constrained embedding system settings. This paper presents 'VeriSparse'-- a framework to search verified locally robust sparse networks starting from a random sparse initialization (i.e., scratch). VeriSparse obtains sparse NNs exhibiting similar or higher verified local robustness, requiring one-third of the training time compared to the state-of-the-art approaches. Furthermore, VeriSparse performs both structured and unstructured sparsification, enabling storage, computing-resource, and computation time reduction during inference generation. Thus, it facilitates the resource-constraint embedding platforms to leverage verified robust NN models, expanding their scope to safety-critical, real-time, and edge applications. We exhaustively investigated VeriSparse's efficacy and generalizability by evaluating various benchmark and application-specific datasets across several model architectures.Comment: 21 pages, 13 tables, 3 figure

Cooking State Recognition from Images Using Inception Architecture

A kitchen robot properly needs to understand the cooking environment to continue any cooking activities. But object's state detection has not been researched well so far as like object detection. In this paper, we propose a deep learning approach to identify different cooking states from images for a kitchen robot. In our research, we investigate particularly the performance of Inception architecture and propose a modified architecture based on Inception model to classify different cooking states. The model is analyzed robustly in terms of different layers, and optimizers. Experimental results on a cooking datasets demonstrate that proposed model can be a potential solution to the cooking state recognition problem.Comment: 6 pages, 8 figures, 4 table

An Empirical Study on the Role of the Courts in Environmental Protection in India, Bangladesh and Ireland: Bridging the Gaps Between Academics and Practitioners

What determines the stance of the judiciary of a country? Is it the individual characteristics of judges or the understanding of legal norms by judges or the legal and political culture of a country? How much influence do academic writings have in judicial pronouncements? Existing literature shows that there are various determining factors behind judicial decision-making. With the development of legal scholarship on the environment, it is important to see how far judicial decision-making is getting the benefit of that research. It is also important to know how environmental academics and practitioners are viewing the stance taken by the courts in environmental litigations. This research applies socio-legal methods, particularly qualitative research, based on data gathered through semistructured interviews of judges, lawyers, academics, and researchers from India, Bangladesh, and Ireland to understand how they view the roles of the courts in environmental matters and how far the understandings of legal norms and writings of academics are reflected in environmental judicial decision making. Countries both from the east and the west based on constitutional and legal similarities have been selected to compare and contrast and to see if the research result is similar notwithstanding the socio-economic-political differences. This research adopts Thornberg’s informed grounded theory and in addition constant comparative method of data analysis is applied in analysing the collected data. Acknowledging the polycentric and interdisciplinary nature of environmental problems and considering the gaps accrued from collected data this paper provides recommendations to bridge the gaps between academics and practitioner

This patient is not breathing properly: is this COPD, heart failure, or neither?

© 2017 Informa UK Limited, trading as Taylor & Francis Group. Introduction: Heart failure (HF) and chronic obstructive pulmonary disease (COPD) are two common, heterogeneous, long-term illnesses which cause significant morbidity and mortality. Although they both present with breathlessness, they are treated differently. Treatment of COPD focuses mainly on relieving short-term breathlessness, whilst treatment of HF has focused on long term morbidity and mortality. Areas covered: In this review, we aim to highlight the diagnostic challenges in distinguishing COPD from HF. We also explore the implications of their overlap, and the use of biomarkers and treatments for HF in patients with COPD to improve long-term outcomes. Expert commentary: Cardiovascular morbidity and mortality amongst patients with COPD is substantial. Approaches which identify patients with COPD at highest cardiovascular risk may therefore be helpful. A trial targeting those patients with COPD and raised natriuretic peptide levels might be the way to test whether cardiovascular medication has anything to offer the respiratory patient

Psychopathy, Empathy, and Perspective -Taking Ability in a Community Sample: Implications for the Successful Psychopathy Concept

This study examined the relationship between psychopathy and two components of empathy including a cognitive component (e.g., perspective-taking ability) and an affective component (e.g., compassion) in a community sample. The Psychopathic Personality Inventory Short Form was used to assess psychopathy and several psychological measures were used to test empathy including the Interpersonal Reactivity Index, the Diagnostic Analysis of Nonverbal Accuracy-2, and the Test of Self Conscious Affect -3. Across instruments, psychopathy (as a unitary construct) appeared to be negligibly correlated with perspective-taking scales and negatively correlated with the affective components of empathy. Findings indicated that the emotional deficits were noted most prominently for the behavioral component of psychopathy. Results also showed that higher psychopathy scores in community participants were linked to higher levels of antisocial conduct

Assessing the Real-Life Socio-Economic Scenario of Established Slums in Dhaka: The Cases of Korail and Sattola

The research aims to assess the current situation of three primary socio-economic indicators, namely education, health and water availability at the two most established slums of Bangladesh’s capital Dhaka – Korail and Sattola. Surveys, using cluster and then random sampling to target households, and analysis, found that both slums' children's education level was moderate with 52% - 68% and 20% - 28% availing primary and secondary education, respectively; several NGOs had helped to establish brick-and-mortar latrines and disseminate necessary and effective awareness about sanitation; and surveyed slum dwellers were economically strong, with 68% - 70% of the interviewed households' income levels being 10,000 – 15,000 BDT (USD 118 – 178) per month. A comparative analysis with national level statistics also yielded that the conditions in these slums are truly better than previously thought. Primary recommendation includes in-depth monitoring to understand why such large numbers live in slums, even though they can afford better