SSM-Net for Plants Disease Identification in Low Data Regime

Plant disease detection is an essential factor in increasing agricultural production. Due to the difficulty of disease detection, farmers spray various pesticides on their crops to protect them, causing great harm to crop growth and food standards. Deep learning can offer critical aid in detecting such diseases. However, it is highly inconvenient to collect a large volume of data on all forms of the diseases afflicting a specific plant species. In this paper, we propose a new metrics-based few-shot learning SSM net architecture, which consists of stacked siamese and matching network components to address the problem of disease detection in low data regimes. We demonstrated our experiments on two datasets: mini-leaves diseases and sugarcane diseases dataset. We have showcased that the SSM-Net approach can achieve better decision boundaries with an accuracy of 92.7% on the mini-leaves dataset and 94.3% on the sugarcane dataset. The accuracy increased by ~10% and ~5% respectively, compared to the widely used VGG16 transfer learning approach. Furthermore, we attained F1 score of 0.90 using SSM Net on the sugarcane dataset and 0.91 on the mini-leaves dataset. Our code implementation is available on Github: https://github.com/shruti-jadon/PlantsDiseaseDetection.Comment: 5 pages, 7 Figure

False Binaries: Recentering South Asian Identity for Healing

Many thoughts emerge attempting to define South Asian, Asian, Desi, or Indian. One approach refers to a country, the other cultural norms, and yet another, a racial and ethnic category far too vast. For the sake of this article, South Asian and Desi refer to the composition of individuals with ancestry in Sri Lanka, Bangladesh, Pakistan, Bhutan, Maldives, Nepal, and India. Indian refers to individuals with ancestry solely in India. Asian is the larger United States racial construct for all individuals from the continent of Asia, more specifically South and East Asia such as Japanese, Thai, or Indian. South Asians have a broad definition in terms of racial and ethnic categorization and are one of the fastest-growing minorities in the U.S. (Census, 2012). South Asians, as a racial group, experience a great deal of complexity regarding racial and ethnic constructs in the U.S. These include processes of assimilation, meaning making within the Black and White racial binary, and confronting the stereotypical ‘model minority myth’ as unwavering truth. Because South Asians exist in a racial gray space, they are stereotyped in a contradictory manner as both “model minority” and “dangerous.” Wingfield (2016) describes model minority as “a group whose hard work, initiative, personal responsibility, and success offer proof that American meritocracy works as intended” (para. 1). These challenges positively and negatively affect their narrative. South Asians have started to take political office, to change the societal climate, and to affect the future of the United States. This shift of South Asians being visible in the U.S. is dramatically different from the historic conflict of whether or not South Asians identified as Black or White in their first days of settlement in America. South Asians still face many challenges that immigrants face in the U.S., but these challenges are not necessarily uniquely associated to South Asian identity. The dynamic of living on the margins and responding to systemic oppression and racial categorization demands greater attention to understand South Asian identity as in-between.Educatio

\u3ci\u3eChevron\u3c/i\u3e Without the Courts? The Supreme Court\u27s Recent \u3cem\u3eChevron\u3c/em\u3e Jurisprudence Through an Immigration Lens

The limits of administrative law are undergoing a seismic shift in the immigration arena. Chevron divides interpretive and decision-making authority between the federal courts and agencies in each of two steps. The Supreme Court may now be transforming this division in largely unrecognized ways. These shifts, currently playing out in the immigration context, may threaten to reshape deference jurisprudence by handing more power to the immigration agency just when the agency may be least able to handle that power effectively. An unprecedented surge in immigration cases—now approximately 90% of the federal administrative docket—has arrived just as the Court is whittling away the judicial role while expanding agency authority, significantly transforming traditional deference doctrine. In its immigration docket, the Court is shifting the judicial role away from questions of statutory interpretation and towards a mere evaluation of when the agency’s interpretation should be granted deference. Assessment of the “reasonableness” of the agency’s action has given way to marking the outer boundaries of agency action, merging the court’s traditional oversight analysis into a form of “arbitrary and capriciousness” review. The costs of the Court’s reformulation of Chevron are particularly visible in immigration law because recent legislation and structural changes at the immigration agency have already constrained judicial review. However, the reformulation of Chevron occurring in immigration law may threaten to remake administrative law generally. Unfortunately, these developments have received little scholarly attention. Understanding this transformation is imperative as ultimately we may be heading towards “Chevron without the Courts”—wherein the judicial interpretive role is being constrained in the very instances where agencies are least able to function effectively

Maximizing resource utilization by slicing of superscalar architecture

Superscalar architectural techniques increase instruction throughput from one instruction per cycle to more than one instruction per cycle. Modern processors make use of several processing resources to achieve this kind of throughput. Control units perform various functions to minimize stalls and to ensure a continuous feed of instructions to execution units. It is vital to ensure that instructions ready for execution do not encounter a bottleneck in the execution stage; This thesis work proposes a dynamic scheme to increase efficiency of execution stage by a methodology called block slicing. Implementing this concept in a wide, superscalar pipelined architecture introduces minimal additional hardware and delay in the pipeline. The hardware required for the implementation of the proposed scheme is designed and assessed in terms of cost and delay. Performance measures of speed-up, throughput and efficiency have been evaluated for the resulting pipeline and analyzed

Partial Identification in Matching Models for the Marriage Market

We study partial identification of the preference parameters in models of one-to-one matching with perfectly transferable utilities, without imposing parametric distributional restrictions on the unobserved heterogeneity and with data on one large market. We provide a tractable characterisation of the identified set, under various classes of nonparametric distributional assumptions on the unobserved heterogeneity. Using our methodology, we re-examine some of the relevant questions in the empirical literature on the marriage market which have been previously studied under the Multinomial Logit assumption

Evaluating the Stream Control Transmission Protocol Using Uppaal

The Stream Control Transmission Protocol (SCTP) is a Transport Layer protocol that has been proposed as an alternative to the Transmission Control Protocol (TCP) for the Internet of Things (IoT). SCTP, with its four-way handshake mechanism, claims to protect the Server from a Denial-of-Service (DoS) attack by ensuring the legitimacy of the Client, which has been a known issue pertaining to the three-way handshake of TCP. This paper compares the handshakes of TCP and SCTP to discuss its shortcomings and strengths. We present an Uppaal model of the TCP three-way handshake and SCTP four-way handshake and show that SCTP is able to cope with the presence of an Illegitimate Client, while TCP fails. The results confirm that SCTP is better equipped to deal with this type of attack.Comment: In Proceedings MARS 2017, arXiv:1703.0581