LASH Tree: LASSO Regression Hoeffding for Streaming Data

Background: Stock price prediction is a challenging task. The social, economic, political, and various other factors cause frequent abrupt changes in the stock price. This article proposes a historical data-based ensemble system to predict the closing stock price with higher accuracy and consistency over the existing stock price prediction systems. Objective: The primary objective of this article is to predict the closing price of a stock for the next trading in more accurate and consistent manner over the existing methods employed for the stock price prediction. Method: The proposed system combines various machine learning-based prediction models employing least absolute shrinkage and selection operator (LASSO) regression regularization technique to enhance the accuracy of stock price prediction system as compared to any one of the base prediction models. Results: The analysis of results for all the eleven stocks (listed under Information Technology sector on the Bombay Stock Exchange, India) reveals that the proposed system performs best (on all defined metrics of the proposed system) for training datasets and test datasets comprising of all the stocks considered in the proposed system. Conclusion: The proposed ensemble model consistently predicts stock price with a high degree of accuracy over the existing methods used for the prediction.

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EDCrammer: An Efficient Caching Rate-Control Algorithm for Streaming Data on Resource-Limited Edge Nodes

Applied Sciences ◽

10.3390/app9122560 ◽

2019 ◽

Vol 9 (12) ◽

pp. 2560 ◽

Cited By ~ 2

Author(s):

Yunkon Kim ◽

Eui-Nam Huh

Keyword(s):

Intelligent Transportation System ◽

Streaming Data ◽

Data Traffic ◽

High Quality ◽

Data Caching ◽

Resource Limited ◽

Quality Video ◽

Key Factor ◽

Efficient Data ◽

Art Research

This paper explores data caching as a key factor of edge computing. State-of-the-art research of data caching on edge nodes mainly considers reactive and proactive caching, and machine learning based caching, which could be a heavy task for edge nodes. However, edge nodes usually have relatively lower computing resources than cloud datacenters as those are geo-distributed from the administrator. Therefore, a caching algorithm should be lightweight for saving computing resources on edge nodes. In addition, the data caching should be agile because it has to support high-quality services on edge nodes. Accordingly, this paper proposes a lightweight, agile caching algorithm, EDCrammer (Efficient Data Crammer), which performs agile operations to control caching rate for streaming data by using the enhanced PID (Proportional-Integral-Differential) controller. Experimental results using this lightweight, agile caching algorithm show its significant value in each scenario. In four common scenarios, the desired cache utilization was reached in 1.1 s on average and then maintained within a 4–7% deviation. The cache hit ratio is about 96%, and the optimal cache capacity is around 1.5 MB. Thus, EDCrammer can help distribute the streaming data traffic to the edge nodes, mitigate the uplink load on the central cloud, and ultimately provide users with high-quality video services. We also hope that EDCrammer can improve overall service quality in 5G environment, Augmented Reality/Virtual Reality (AR/VR), Intelligent Transportation System (ITS), Internet of Things (IoT), etc.

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Prediction of Fruity Aroma Intensity and Defect Presence in Virgin Olive Oil Using an Electronic Nose

Sensors ◽

10.3390/s21072298 ◽

2021 ◽

Vol 21 (7) ◽

pp. 2298

Author(s):

Pablo Cano Marchal ◽

Chiara Sanmartin ◽

Silvia Satorres Martínez ◽

Juan Gómez Ortega ◽

Fabio Mencarelli ◽

...

Keyword(s):

Olive Oil ◽

Low Cost ◽

Virgin Olive Oil ◽

General Purpose ◽

Quality Parameter ◽

Lasso Regression ◽

Virgin Olive Oils ◽

Electronic Noses ◽

Olive Oils ◽

Instrumental Technique

The organoleptic profile of a Virgin Olive Oil is a key quality parameter that is currently obtained by human sensory panels. The development of an instrumental technique capable of providing information about this profile quickly and online is of great interest. This work employed a general purpose e-nose, in lab conditions, to predict the level of fruity aroma and the presence of defects in Virgin Olive Oils. The raw data provided by the e-nose were used to extract a set of features that fed a regressor to predict the level of fruity aroma and a classifier to detect the presence of defects. The results obtained were a mean validation error of 0.5 units for the prediction of fruity aroma using lasso regression; and 88% accuracy for the defect detection using logistic regression. Finally, the identification of two out of ten specific sensors of the e-nose that can provide successful results paves the way to the design of low-cost specific electronic noses for this application.

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Modeling advanced security aspects of key exchange and secure channel protocols

it - Information Technology ◽

10.1515/itit-2020-0029 ◽

2020 ◽

Vol 62 (5-6) ◽

pp. 287-293

Author(s):

Felix Günther

Keyword(s):

Building Blocks ◽

Key Exchange ◽

Internet Security ◽

Streaming Data ◽

Transport Layer ◽

Security Model ◽

Secret Key ◽

Multi Stage ◽

Key Exchange Protocols ◽

Secure Channel

AbstractSecure connections are at the heart of today’s Internet infrastructure, protecting the confidentiality, authenticity, and integrity of communication. Achieving these security goals is the responsibility of cryptographic schemes, more specifically two main building blocks of secure connections. First, a key exchange protocol is run to establish a shared secret key between two parties over a, potentially, insecure connection. Then, a secure channel protocol uses that shared key to securely transport the actual data to be exchanged. While security notions for classical designs of these components are well-established, recently developed and standardized major Internet security protocols like Google’s QUIC protocol and the Transport Layer Security (TLS) protocol version 1.3 introduce novel features for which supporting security theory is lacking.In my dissertation [20], which this article summarizes, I studied these novel and advanced design aspects, introducing enhanced security models and analyzing the security of deployed protocols. For key exchange protocols, my thesis introduces a new model for multi-stage key exchange to capture that recent designs for secure connections establish several cryptographic keys for various purposes and with differing levels of security. It further introduces a formalism for key confirmation, reflecting a long-established practical design criteria which however was lacking a comprehensive formal treatment so far. For secure channels, my thesis captures the cryptographic subtleties of streaming data transmission through a revised security model and approaches novel concepts to frequently update key material for enhanced security through a multi-key channel notion. These models are then applied to study (and confirm) the security of the QUIC and TLS 1.3 protocol designs.

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Incidence, characteristics, determinants and prognostic impact of recurrent syncope

European Heart Journal ◽

10.1093/ehjci/ehaa946.0700 ◽

2020 ◽

Vol 41 (Supplement_2) ◽

Author(s):

T Zimmermann ◽

J Du Fay De Lavallaz ◽

T Nestelberger ◽

D Gualandro ◽

P Badertscher ◽

...

Keyword(s):

Patient Characteristics ◽

Coronary Intervention ◽

Final Diagnosis ◽

Major Adverse Cardiovascular Events ◽

Unknown Etiology ◽

Funding Source ◽

Prognostic Impact ◽

Lasso Regression ◽

Recurrence Rates ◽

Increased Risk

Abstract Background The incidence, characteristics, determinants, and prognostic impact of recurrent syncope are largely unknown, causing uncertainty for both patients and physicians. Methods We characterized recurrent syncope including sex-specific aspects and its impact on death and major adverse cardiovascular events (MACE) in a large prospective international multicenter study enrolling patients ≥40 years presenting with syncope to the emergency department (ED). Syncope etiology was centrally adjudicated by two independent and blinded cardiologists using all information becoming available during syncope work-up and 12-month follow-up. MACE were defined as a composite of all-cause death, acute myocardial infarction, surgical or percutaneous coronary intervention, life-threatening arrhythmia including cardiac arrest, pacemaker or implantable cardioverter defibrillator implantation, valve intervention, heart-failure, gastrointestinal bleeding or other bleeding requiring transfusion, intracranial hemorrhage, ischemic stroke or transient ischemic attack, sepsis and pulmonary embolism. Results Incidence of recurrent syncope among 1790 patients was 20% (95%-confidence interval (CI) 18% to 22%) within 24 months. Patients with an adjudicated final diagnosis of cardiac syncope (hazard ratio (HR) 1.50, 95%-CI 1.11 to 2.01) or syncope of unknown etiology even after central adjudication (HR 2.11, 95%-CI 1.54 to 2.89) had an increased risk for syncope recurrence (Figure). LASSO regression fit on all patient information available early in the ED identified more than three previous episodes of syncope as the only independent predictor for recurrent syncope (HR 2.13, 95%-CI 1.64 to 2.75). Recurrent syncope within the first 12 months after the index event carried an increased risk for all-cause death (HR 1.59, 95%-CI 1.06 to 2.38) and MACE (HR 2.24, 95%-CI 1.67 to 3.01), whereas recurrences after 12 months did not have a significant impact on outcome measures. Conclusion Recurrence rates of syncope are substantial and vary depending on syncope etiology. There seem to be no reliable patient characteristics available early on the ED that allow for the prediction of recurrent syncope with only a history of more than three previous syncope being associated with a higher risk for future recurrences. Importantly, recurrent syncope within the first 12 months carries an increased risk for death and MACE. Figure 1 Funding Acknowledgement Type of funding source: Public grant(s) – National budget only. Main funding source(s): Swiss National Science Foundation, Swiss Heart Foundation

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