scholarly journals Polymath: Low-Latency MPC via Secure Polynomial Evaluations and Its Applications

2021 ◽  
Vol 2022 (1) ◽  
pp. 396-416
Author(s):  
Donghang Lu ◽  
Albert Yu ◽  
Aniket Kate ◽  
Hemanta Maji
Keyword(s):  
Decision Tree ◽  
Privacy Preserving ◽  
Secure Computation ◽  
Transition Matrices ◽  
Polynomial Degree ◽  
Tree Models ◽  
Numerous Data ◽  
High Level ◽  
Traditional Approaches ◽  
High Degree

Abstract While the practicality of secure multi-party computation (MPC) has been extensively analyzed and improved over the past decade, we are hitting the limits of efficiency with the traditional approaches of representing the computed functionalities as generic arithmetic or Boolean circuits. This work follows the design principle of identifying and constructing fast and provably-secure MPC protocols to evaluate useful high-level algebraic abstractions; thus, improving the efficiency of all applications relying on them. We present Polymath, a constant-round secure computation protocol suite for the secure evaluation of (multi-variate) polynomials of scalars and matrices, functionalities essential to numerous data-processing applications. Using precise natural precomputation and high-degree of parallelism prevalent in the modern computing environments, Polymath can make latency of secure polynomial evaluations of scalars and matrices independent of polynomial degree and matrix dimensions. We implement our protocols over the HoneyBadgerMPC library and apply it to two prominent secure computation tasks: privacy-preserving evaluation of decision trees and privacy-preserving evaluation of Markov processes. For the decision tree evaluation problem, we demonstrate the feasibility of evaluating high-depth decision tree models in a general n-party setting. For the Markov process application, we demonstrate that Poly-math can compute large powers of transition matrices with better online time and less communication.

ANTICYTOKINE ACTIVITY OF THE PROTOZOA BLASTOCYSTIS SPP

2020 ◽  
pp. 44-48
Author(s):  
Bugero N.V. ◽  
Ilyina N.A. ◽  
Aleksandrova S.M.
Keyword(s):  
Gastrointestinal Tract ◽  
Gastrointestinal Diseases ◽  
Control Group ◽  
Ulcer Disease ◽  
Cytokine Balance ◽  
High Prevalence ◽  
Blastocystis Spp ◽  
High Level ◽  
Eukaryotic Organisms ◽  
High Degree

In addition to the classical pathogens, which are well understood and well identified, new pathogens with the potential to spread epidemiologically are being identified. Some of these little-known organisms are the simplest Blastocystis spp. blastocystostosis. The clinical significance of Blastocystis spp. and its pathogenicity are still under discussion. This parasite belongs to a group of single-celled eukaryotic organisms living in the colon of the human intestine. Blastocystis spp. is known to be found both in people with reduced immune status and in individuals without any clinical manifestation. It has been established that a sufficiently high degree of invasiveness is observed in persons with gastrointestinal tract diseases, dermatosis, allergic reactions, in patients with carriers of the human immunodeficiency virus, etc. Possessing persistence factors, protozoa blastocysts contribute to the inactivation of host defensive mechanisms, providing a stable anthogonistic effect. In recent years, many works have been devoted to the characteristics of the persistent properties of Blastocystis spr., however, individual properties of blastocysts, in particular, anticytokine activity (ACA), have not yet been studied. In this regard, the work studied the anticytokine activity of microorganisms isolated from healthy subjects and patients with gastrointestinal tract diseases. A high prevalence of the studied characteristic in the subjects was shown. The expression of anticytokine activity in the obtained isolates of blastocysts was the highest in the group of persons with gastric ulcer disease, which decreased in the order of duodenal ulcer, chronic cholecystitis, chronic gastritis, etc. The data obtained in this work on the high level of ACA expression in blastocyst isolates obtained from individuals with gastrointestinal diseases as compared with the control group enables to conclude that their exometabolites may influence the local cytokine balance [1], which supports the inflammatory process.

CSim 2

2021 ◽  
Vol 43 (1) ◽  
pp. 1-46
Author(s):  
David Sanan ◽  
Yongwang Zhao ◽  
Shang-Wei Lin ◽  
Liu Yang
Keyword(s):  
Programming Languages ◽  
Concurrent Systems ◽  
Theorem Prover ◽  
Compositional Techniques ◽  
Machine Code ◽  
Top Down ◽  
Hol Theorem Prover ◽  
High Level ◽  
High Degree

To make feasible and scalable the verification of large and complex concurrent systems, it is necessary the use of compositional techniques even at the highest abstraction layers. When focusing on the lowest software abstraction layers, such as the implementation or the machine code, the high level of detail of those layers makes the direct verification of properties very difficult and expensive. It is therefore essential to use techniques allowing to simplify the verification on these layers. One technique to tackle this challenge is top-down verification where by means of simulation properties verified on top layers (representing abstract specifications of a system) are propagated down to the lowest layers (that are an implementation of the top layers). There is no need to say that simulation of concurrent systems implies a greater level of complexity, and having compositional techniques to check simulation between layers is also desirable when seeking for both feasibility and scalability of the refinement verification. In this article, we present CSim 2 a (compositional) rely-guarantee-based framework for the top-down verification of complex concurrent systems in the Isabelle/HOL theorem prover. CSim 2 uses CSimpl, a language with a high degree of expressiveness designed for the specification of concurrent programs. Thanks to its expressibility, CSimpl is able to model many of the features found in real world programming languages like exceptions, assertions, and procedures. CSim 2 provides a framework for the verification of rely-guarantee properties to compositionally reason on CSimpl specifications. Focusing on top-down verification, CSim 2 provides a simulation-based framework for the preservation of CSimpl rely-guarantee properties from specifications to implementations. By using the simulation framework, properties proven on the top layers (abstract specifications) are compositionally propagated down to the lowest layers (source or machine code) in each concurrent component of the system. Finally, we show the usability of CSim 2 by running a case study over two CSimpl specifications of an Arinc-653 communication service. In this case study, we prove a complex property on a specification, and we use CSim 2 to preserve the property on lower abstraction layers.

Deep AI Enabled Ubiquitous Wireless Sensing

2021 ◽  
Vol 54 (2) ◽  
pp. 1-35
Author(s):  
Chenning Li ◽  
Zhichao Cao ◽  
Yunhao Liu
Keyword(s):  
Great Success ◽  
Wireless Sensing ◽  
Ubiquitous Sensing ◽  
Sensing Systems ◽  
The Status ◽  
Sensing Model ◽  
High Level ◽  
Traditional Approaches ◽  
The Internet Of Things ◽  
High Level Feature

With the development of the Internet of Things (IoT), many kinds of wireless signals (e.g., Wi-Fi, LoRa, RFID) are filling our living and working spaces nowadays. Beyond communication, wireless signals can sense the status of surrounding objects, known as wireless sensing , with their reflection, scattering, and refraction while propagating in space. In the last decade, many sophisticated wireless sensing techniques and systems were widely studied for various applications (e.g., gesture recognition, localization, and object imaging). Recently, deep Artificial Intelligence (AI), also known as Deep Learning (DL), has shown great success in computer vision. And some works have initially proved that deep AI can benefit wireless sensing as well, leading to a brand-new step toward ubiquitous sensing. In this survey, we focus on the evolution of wireless sensing enhanced by deep AI techniques. We first present a general workflow of Wireless Sensing Systems (WSSs) which consists of signal pre-processing, high-level feature, and sensing model formulation. For each module, existing deep AI-based techniques are summarized, further compared with traditional approaches. Then, we provide a view of issues and challenges induced by combining deep AI and wireless sensing together. Finally, we discuss the future trends of deep AI to enable ubiquitous wireless sensing.

A Practical Tutorial for Decision Tree Induction

2021 ◽  
Vol 54 (1) ◽  
pp. 1-38
Author(s):  
Víctor Adrián Sosa Hernández ◽  
Raúl Monroy ◽  
Miguel Angel Medina-Pérez ◽  
Octavio Loyola-González ◽  
Francisco Herrera
Keyword(s):  
Decision Tree ◽  
Decision Trees ◽  
Machine Learning Techniques ◽  
Evaluation Measures ◽  
Decision Tree Induction ◽  
Learning Techniques ◽  
Tree Models ◽  
Evaluation Measure ◽  
Main Components ◽  
Support Decision Making

Experts from different domains have resorted to machine learning techniques to produce explainable models that support decision-making. Among existing techniques, decision trees have been useful in many application domains for classification. Decision trees can make decisions in a language that is closer to that of the experts. Many researchers have attempted to create better decision tree models by improving the components of the induction algorithm. One of the main components that have been studied and improved is the evaluation measure for candidate splits. In this article, we introduce a tutorial that explains decision tree induction. Then, we present an experimental framework to assess the performance of 21 evaluation measures that produce different C4.5 variants considering 110 databases, two performance measures, and 10× 10-fold cross-validation. Furthermore, we compare and rank the evaluation measures by using a Bayesian statistical analysis. From our experimental results, we present the first two performance rankings in the literature of C4.5 variants. Moreover, we organize the evaluation measures into two groups according to their performance. Finally, we introduce meta-models that automatically determine the group of evaluation measures to produce a C4.5 variant for a new database and some further opportunities for decision tree models.

Addiction and schizophrenia

2000 ◽  
Vol 15 (2) ◽  
pp. 115-122 ◽  
Author(s):  
P. Batel
Keyword(s):  
Epidemiologic Studies ◽  
Self Medication ◽  
Addictive Disorders ◽  
Co Morbidity ◽  
Dependency Type ◽  
Active Research ◽  
Social Environmental ◽  
High Level ◽  
Environmental Hypothesis ◽  
High Degree

SummaryEpidemiologic studies in the general population and those based on the clinical assessment of schizophrenic populations have revealed a high degree of overlap between schizophrenia and addictive disorders. The abuse of psychoactive substances (including alcohol) throughout life is so frequent (50%) that the possibility of a specific link inevitably arises. Various hypotheses have been suggested to explain the high co-morbidity between schizophrenia and addiction: 1) The social-environmental hypothesis has been developed but studies have provided poor evidence to validate it. 2) The possible shared biological vulnerability between schizophrenia and addictions led researchers to explore common genetic determinants and study the involvement of the dopaminergic and opioid systems in the aetiology of both schizophrenia and the abuse of and dependence on psychoactive drugs. 3) Finally, the theory of self-medication suggests that schizophrenics may be attempting to counter the deficit linked to their disorders by using the substances they take or their dependency-type behaviour to cope with their emotional problems. The clinical profile of schizophrenic addicts does seem to display some distinctive features, such as the high level of depressive co-morbidity, very high nicotine and alcohol dependence, with a very poor prognosis. These patients are difficult to manage; the possibility of pharmacologic interactions between the substances they are taking and neuroleptic medication calls for prudence, and their compliance is also poor. Addictive disorders in schizophrenics are currently a topic of active research intended to lead to identifying specific treatments. The early identification of addictive disorders in schizophrenics should make it possible to limit their development and improve the prognosis.

Living in the end times: a short course addressing end of life issues for older people in an English parish church setting

2015 ◽  
Vol 19 (3) ◽  
pp. 140-149 ◽  
Author(s):  
Joanna Collicutt
Keyword(s):  
Older People ◽  
End Of Life ◽  
Group Dynamics ◽  
Death And Dying ◽  
Community Context ◽  
Content Type ◽  
End Of Life Issues ◽  
End Times ◽  
High Level ◽  
High Degree

Purpose – The purpose of this paper is to report a pilot study that evaluated an innovative practice in a faith community context designed to help older people live well at the end of life and prepare for death. Design/methodology/approach – A simple audit of the intervention using a contemporaneous journal kept by the author, and a follow up questionnaire completed by participants. Findings – Rich findings on the process are reported. These indicate a high degree of engagement by participants, the establishment of a high degree of group intimacy and trust, a high level of articulation of wisdom, the emergence of significant anxiety in some isolated cases, and the use made of tea and cake to manage the transition between the existentially demanding nature of the discussions and normal life. The outcome indicated very high levels of appreciation and increased confidence in relation to issues of death and dying. Practical implications – The findings of the pilot have been used to inform training of clergy in the principles of working in this area (e.g. in ways of managing group dynamics and anxiety, pacing, tuning in to archetypes and the natural symbols that people use to talk about death and dying, self-care and supervision of the programme leader/facilitator). Originality/value – The paper adds to knowledge in terms of an in depth description of processes at work in a group of older people working on spiritual and practical issues in relation to death, and offers ideas for supporting older people in this process, some of which are specific to the Christian tradition, and some of which are more widely applicable to people of all faiths and none. It gives a specific worked example of what “spiritual care” in this area might look like.

scholarly journals Evolutionary Algorithm for Improving Decision Tree with Global Discretization in Manufacturing

Sensors ◽  
2021 ◽  
Vol 21 (8) ◽  
pp. 2849
Author(s):  
Sungbum Jun
Keyword(s):  
Decision Tree ◽  
Evolutionary Algorithm ◽  
Decision Trees ◽  
Manufacturing Systems ◽  
Ensemble Methods ◽  
Machine Learning Techniques ◽  
Learning Techniques ◽  
Industrial Internet ◽  
Tree Models ◽  
Real World Datasets

Due to the recent advance in the industrial Internet of Things (IoT) in manufacturing, the vast amount of data from sensors has triggered the need for leveraging such big data for fault detection. In particular, interpretable machine learning techniques, such as tree-based algorithms, have drawn attention to the need to implement reliable manufacturing systems, and identify the root causes of faults. However, despite the high interpretability of decision trees, tree-based models make a trade-off between accuracy and interpretability. In order to improve the tree’s performance while maintaining its interpretability, an evolutionary algorithm for discretization of multiple attributes, called Decision tree Improved by Multiple sPLits with Evolutionary algorithm for Discretization (DIMPLED), is proposed. The experimental results with two real-world datasets from sensors showed that the decision tree improved by DIMPLED outperformed the performances of single-decision-tree models (C4.5 and CART) that are widely used in practice, and it proved competitive compared to the ensemble methods, which have multiple decision trees. Even though the ensemble methods could produce slightly better performances, the proposed DIMPLED has a more interpretable structure, while maintaining an appropriate performance level.

scholarly journals Individual synaptic vesicles mediate stimulated exocytosis from cochlear inner hair cells

2018 ◽  
Vol 115 (50) ◽  
pp. 12811-12816 ◽  
Author(s):  
Chad Paul Grabner ◽  
Tobias Moser
Keyword(s):  
Hair Cells ◽  
Synaptic Vesicles ◽  
Basolateral Membrane ◽  
Mean Amplitude ◽  
Auditory Pathway ◽  
Inner Hair Cell ◽  
Excitatory Postsynaptic Currents ◽  
High Level ◽  
High Degree ◽  
Channel Type

Spontaneous excitatory postsynaptic currents (sEPSCs) measured from the first synapse in the mammalian auditory pathway reach a large mean amplitude with a high level of variance (CV between 0.3 and 1). This has led some to propose that each inner hair cell (IHC) ribbon-type active zone (AZ), on average, releases ∼6 synaptic vesicles (SVs) per sEPSC in a coordinated manner. If true, then the predicted change in membrane capacitance (Cm) for such multivesicular fusion events would equate to ∼300 attofarads (aF). Here, we performed cell-attached Cm measurements to directly examine the size of fusion events at the basolateral membrane of IHCs where the AZs are located. The frequency of events depended on the membrane potential and the expression of Cav1.3, the principal Ca2+-channel type of IHCs. Fusion events averaged 40 aF, which equates to a normal-sized SV with an estimated diameter of 37 nm. The calculated SV volumes showed a high degree of variance (CV > 0.6). These results indicate that SVs fused individually with the plasma membrane during spontaneous and evoked release and SV volume may contribute more variability in EPSC amplitude than previously assumed.

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