A Monolithic Stochastic Computing Architecture for Energy and Area Efficient Arithmetic

As the energy and hardware investments necessary for conventional high-precision digital computing continues to explode in the emerging era of artificial intelligence, deep learning, and Big-data [1-4], a change in paradigm that can trade precision for energy and resource efficiency is being sought for many computing applications. Stochastic computing (SC) is an attractive alternative since unlike digital computers, which require many logic gates and a high transistor volume to perform basic arithmetic operations such as addition, subtraction, multiplication, sorting etc., SC can implement the same using simple logic gates [5, 6]. While it is possible to accelerate SC using traditional silicon complementary metal oxide semiconductor (CMOS) [7, 8] technology, the need for extensive hardware investment to generate stochastic bits (s-bit), the fundamental computing primitive for SC, makes it less attractive. Memristor [9-11] and spin-based devices [12-15] offer natural randomness but depend on hybrid designs involving CMOS peripherals for accelerating SC, which increases area and energy burden. Here we overcome the limitations of existing and emerging technologies and experimentally demonstrate a standalone SC architecture embedded in memory based on two-dimensional (2D) memtransistors. Our monolithic and non-von Neumann SC architecture consumes a miniscule amount of energy < 1 nano Joules for s-bit generation and to perform arithmetic operations and occupy small hardware footprint highlighting the benefits of SC.

INSIGHTS INTO CORONA/CORONAVIRUS DISEASE 2019 PANDEMIC – OPINION VERSUS EVIDENCE

The pandemic of coronavirus disease 2019 (COVID-19) struck the globe in December 2019, killing lakhs of people and it is continuing in many countries to create havoc. There are lakhs of publications creating evidence about the management of the disease. After seeing thousands of cases, we formed opinions in each field of management and these findings may look more logical. We accept that our opinions differ subtly from the evidence. Regarding the transmission of the disease, it is spread from person to person through inhaled aerosols. If this is going to be 100% true, then the need for personal protective equipment covering the legs seems illogical. Povidone-iodine is antiviral and spreading the same as an ointment inside the nose must be effective to decrease viral load. The other antivirals with questionable efficiency like remdesivir are being used frequently, especially in the pulmonary phase. There are no clear-cut guidelines for primary contacts. Any protective drug intake could have decreased the transmission. It’s a simple logic that the act of sneezing will decrease the viral load. The practice of inhaling turmeric smoke to induce sneezing in the outdoor could have decreased the viral load. We opine that a lymphopenia of <15% can predict a worse outcome in the next 2 days. A computerized computed tomography scan of the chest is to be taken 7 days after the onset of symptoms as the disease usually enters the pulmonary phase only then. The date of onset of symptoms rather than the positive testing date should be considered for timeline management of the case. The undue tachycardia in the 1st week and desaturation below 92% in the 2nd week are the warning signs. The steroids are to be usually prescribed after the 5–6 days. The roles of psychiatric counseling and nutrition were largely underplayed.

Gratitude and that which we cannot return: Critical reflections on gratitude

Gratitude is often perceived from the perspective of economic reciprocity, i.e., from the simple logic of quid pro quo. It is for this reason that Marcel Mauss ignores the topic of gratitude in his famous work on gift-giving, and that Seneca believes that gratitude is something which is given in return: ‘for the benefit that is accomplished by an act has been repaid by our gratitude if we give it friendly welcome’. In this paper I will demonstrate that gratitude is not something that is given in return or a cancelation of debt. Instead, I will argue for the claim that gratitude is the recognition of that which cannot be returned, which leads, in ideal cases, to a sense of responsibility for the other.

A Simple Logic of Functional Dependence

This paper presents a simple decidable logic of functional dependence LFD, based on an extension of classical propositional logic with dependence atoms plus dependence quantifiers treated as modalities, within the setting of generalized assignment semantics for first order logic. The expressive strength, complete proof calculus and meta-properties of LFD are explored. Various language extensions are presented as well, up to undecidable modal-style logics for independence and dynamic logics of changing dependence models. Finally, more concrete settings for dependence are discussed: continuous dependence in topological models, linear dependence in vector spaces, and temporal dependence in dynamical systems and games.

A Look Behind the Curtain: Traffic Classification in an Increasingly Encrypted Web

Traffic classification is essential in network management for operations ranging from capacity planning, performance monitoring, volumetry, and resource provisioning, to anomaly detection and security. Recently, it has become increasingly challenging with the widespread adoption of encryption in the Internet, e.g., as a de-facto in HTTP/2 and QUIC protocols. In the current state of encrypted traffic classification using Deep Learning (DL), we identify fundamental issues in the way it is typically approached. For instance, although complex DL models with millions of parameters are being used, these models implement a relatively simple logic based on certain header fields of the TLS handshake, limiting model robustness to future versions of encrypted protocols. Furthermore, encrypted traffic is often treated as any other raw input for DL, while crucial domain-specific considerations exist that are commonly ignored. In this paper, we design a novel feature engineering approach that generalizes well for encrypted web protocols, and develop a neural network architecture based on Stacked Long Short-Term Memory (LSTM) layers and Convolutional Neural Networks (CNN) that works very well with our feature design. We evaluate our approach on a real-world traffic dataset from a major ISP and Mobile Network Operator. We achieve an accuracy of 95% in service classification with less raw traffic and smaller number of parameters, out-performing a state-of-the-art method by nearly 50% fewer false classifications. We show that our DL model generalizes for different classification objectives and encrypted web protocols. We also evaluate our approach on a public QUIC dataset with finer and application-level granularity in labeling, achieving an overall accuracy of 99%.

An area efficient memory-less ROM design architecture for direct digital frequency synthesizer

This paper introduces a new technique of designing a read-only memory (ROM) circuit, namely; memory-less ROM as a novel approach to designing the ROM lookup table (LUT) circuit for use in a direct digital frequency synthesizer (DDFS). The proposed DDFS design uses the pipelined phase accumulator (PA) based on the kogge-stone (KS) adder. Verilog HDL programming is encoded on the architecture circuit of pipelined PA and contrasted with other PA based on various adders. The obtained results define the KS adder as having good capabilities for improving the throughput. In addition to the quarter symmetry technique, the built memory-less ROM to obtain the quarter sine amplitude waveform is proposed and implemented in the DDFS system. The implementation of the proposed technique replaces the necessary ROM registers (384 D flip-flops) and multiplexers with simple logic gate circuits instead of traditional ROMs. This technique would reduce the area size and cell count by 56% and 32.6% respectively.

Alpha-emitting nanoparticles and the Warburg Effect, skin diseases, eating disorders, musculoskeletal disorders, alcoholism, cigarette, hypersexuality and neurofibromatosis type 1

Alpha emitting nanoparticulates in internal contamination, an IARC Class 1 carcinogen, have an extremely wide list of effects. New effects are here demonstrated based on a wide epidemiological survey. WHO data in particular is used together with other large sets and juxtaposed to known sources of variations of radioactivity contamination in the environment to demonstrate the link which is always explained by the strong decay energy and its impact on the organism. Some behaviours are shown to be strategies of pain reduction, others of decontamination. This article confirms the simple logic of biophysics (the linear-no-threshold model) outlined by the author in previous publications.

Number Recognition System of Real time Indian Sign Language

Too many research has been done in the field of Human Computer Interaction (HCI). One of the system called Hand Gesture Recognition (HGR) gives solution to build the HCI systems. Now a days, computer is used as a interpreter between humans. The proposed system is used to recognize the real time static hand gesture of Indian sign language number system zero to nine. In this paper we propose a system for hand gesture recognition which is simple and fast. Based on the proposed algorithm, this system can automatically convert the input hand gesture into the text and audio. The system first capture the image of hand gesture shown by user using a simple webcam then using our proposed algorithm it recognize the gesture. This system can use for real time application due to the use of simple logic condition applied to recognize the gesture. The proposed system is size invariant and implemented using OpenCV.

THE USE OF PACEMAKER DIAGNOSTICS FOR SUPPORTING THE ANTICOAGULATION TREATMENT MANAGEMENT

In this work, the analysis of data on atrial fibrillation (AF) burden from dual chamber pacemakers is used for supporting the anticoagulation treatment management. The aim is to evaluate the benefit of basic diagnostic functions to support oral anticoagulation therapy in patients with atrial fibrillation. These patients have increased risk of thromboembolism. If patients have an implanted pacemaker, the device’s diagnostic features monitor the frequency and duration of atrial fibrillation episodes. This data can then be used for further decisions. Statistical data processing was performed on a group of 117 patients with an implanted dual chamber pacemaker. From these results, we evaluated the benefits of the algorithms. In the whole group, a trend was observed in increase of the AF burden between the two monitored periods. The increase of AF burden occurred in 17 patients, while the decrease occurred in 6 patients only. Using simple logic functions, the numbers of patients with different binary values of the presence of AF, the presence of oral anticoagulation therapy, the risk CHA2DS2-VASc score and the values of AF burden were determined. Thus, in the whole group of patients, the diagnostic functions of the implanted devices contributed to the change in oral anticoagulation therapy for 24% of patients.