1995 ◽  
Vol 4 (2) ◽  
pp. 62-69 ◽  
Author(s):  
Katherine Verdolini ◽  
Ingo R. Titze

In this paper, we discuss the application of mathematical formulas to guide the development of clinical interventions in voice disorders. Discussion of case examples includes fundamental frequency and intensity deviations, pitch and loudness abnormalities, laryngeal hyperand hypoadduction, and phonatory effort. The paper illustrates the interactive nature of theoretical and applied work in vocology


2018 ◽  
Author(s):  
Sigit Haryadi

The preprint will show that most of the sciences for hundreds of years have lived with the mathematical formulas that are "half-correct" and offers a solution to find formulas that are one hundred percent correct.Here we show that the existing mathematical formulas so far are only "half-correct" since philosophically they have applied bad habits of humans who only judge the goodness of people or things that they loved, and only judges the ugliness of things they did not like. On the other hand, the formulas are one hundred percent correct if they are willing to assess both the goodness and ugliness of things.Here is give a proof that only the formula of Harmony in Gradation or the formulas that contain its spirit are one hundred percent correct because of they able to show the level of perfection of everything being assessed accurately and precisely.


IZUMI ◽  
2017 ◽  
Vol 6 (1) ◽  
pp. 1
Author(s):  
Ningrum Tresnasari

[Title: The formation of goroawase pattern in Japanese]Goroawase ( Japanese wordplay in number) is one of the phenomenon of language in japan.Goroawase can be defined as a language game that is widely used as a technique to memorize numbers or important numbers in Japan.This study aims to determine how the pattern formation of goroawase in Japanese. The method used in this research is descriptive qualitative method.Goroawase formed by means of use way read numbers in japanese to form a word which has a particular meaning. The formation of goroawase is divided into two types, there are derived from number into word and word into number. The formation of derived from numbers into a word generally used as a mnemonic ( memorizing techniques ) as in considering important years in Japan, mathematical formulas, and to remember the spesific of anniversary date.for example, the discovery of America , namely the year 1492 read as iyokuni. Goroawase which comes from the words into numbers is generally used as the making of a password , email address ( e-mail) or a private telephone number that can be customized with its own name or by words such desired aishiteru written words into 14 106 .


Author(s):  
Petar Radanliev ◽  
David De Roure ◽  
Kevin Page ◽  
Max Van Kleek ◽  
Omar Santos ◽  
...  

AbstractMultiple governmental agencies and private organisations have made commitments for the colonisation of Mars. Such colonisation requires complex systems and infrastructure that could be very costly to repair or replace in cases of cyber-attacks. This paper surveys deep learning algorithms, IoT cyber security and risk models, and established mathematical formulas to identify the best approach for developing a dynamic and self-adapting system for predictive cyber risk analytics supported with Artificial Intelligence and Machine Learning and real-time intelligence in edge computing. The paper presents a new mathematical approach for integrating concepts for cognition engine design, edge computing and Artificial Intelligence and Machine Learning to automate anomaly detection. This engine instigates a step change by applying Artificial Intelligence and Machine Learning embedded at the edge of IoT networks, to deliver safe and functional real-time intelligence for predictive cyber risk analytics. This will enhance capacities for risk analytics and assists in the creation of a comprehensive and systematic understanding of the opportunities and threats that arise when edge computing nodes are deployed, and when Artificial Intelligence and Machine Learning technologies are migrated to the periphery of the internet and into local IoT networks.


2021 ◽  
Vol 89 (2) ◽  
pp. 15
Author(s):  
M. R. Mozafari ◽  
E. Mazaheri ◽  
K. Dormiani

Introduction: Bioactive encapsulation and drug delivery systems have already found their way to the market as efficient therapeutics to combat infections, viral diseases and different types of cancer. The fields of food fortification, nutraceutical supplementation and cosmeceuticals have also been getting the benefit of encapsulation technologies. Aim: Successful formulation of such therapeutic and nutraceutical compounds requires thorough analysis and assessment of certain characteristics including particle number and surface area without the need to employ sophisticated analytical techniques. Solution: Here we present simple mathematical formulas and equations used in the research and development of drug delivery and controlled release systems employed for bioactive encapsulation and targeting the sites of infection and cancer in vitro and in vivo. Systems covered in this entry include lipidic vesicles, polymeric capsules, metallic particles as well as surfactant- and tocopherol-based micro- and nanocarriers.


Designs ◽  
2021 ◽  
Vol 5 (1) ◽  
pp. 16
Author(s):  
Akshay Salwan ◽  
Said M. Easa ◽  
Narayana Raju ◽  
Shriniwas Arkatkar

A turbo roundabout uses spiral circulatory roads for effectively counteracting the problems faced in modern multilane roundabouts. First developed in 1996, the turbo roundabout has an advantage over the conventional roundabout regarding capacity and safety. Turbo roundabouts are still in the developing phase in North America, but even in the European subcontinent where they exist in large numbers, reliable analytical studies on the critical parameters of roundabout visibility are lacking. Visibility (sight distance) helps to shape the geometry of the intersection and aids in safety. This paper presents the mathematical characteristics of the intersection geometry and intersection sight distance (ISD) of the turbo roundabout. Mathematical formulas are presented for the sight distance from the approaching vehicle to the conflicting-entering and circulating vehicles. The maximum lateral clearances to the conflicting vehicles are derived using mathematical optimization. The developed analytical method is verified graphically using AutoCAD. To assist in practical applications, design aids for the maximum lateral clearance are presented. The presented method and design aids should aid in promoting safety at turbo roundabouts.


Proceedings ◽  
2021 ◽  
Vol 77 (1) ◽  
pp. 17
Author(s):  
Andrea Giussani

In the last decade, advances in statistical modeling and computer science have boosted the production of machine-produced contents in different fields: from language to image generation, the quality of the generated outputs is remarkably high, sometimes better than those produced by a human being. Modern technological advances such as OpenAI’s GPT-2 (and recently GPT-3) permit automated systems to dramatically alter reality with synthetic outputs so that humans are not able to distinguish the real copy from its counteracts. An example is given by an article entirely written by GPT-2, but many other examples exist. In the field of computer vision, Nvidia’s Generative Adversarial Network, commonly known as StyleGAN (Karras et al. 2018), has become the de facto reference point for the production of a huge amount of fake human face portraits; additionally, recent algorithms were developed to create both musical scores and mathematical formulas. This presentation aims to stimulate participants on the state-of-the-art results in this field: we will cover both GANs and language modeling with recent applications. The novelty here is that we apply a transformer-based machine learning technique, namely RoBerta (Liu et al. 2019), to the detection of human-produced versus machine-produced text concerning fake news detection. RoBerta is a recent algorithm that is based on the well-known Bidirectional Encoder Representations from Transformers algorithm, known as BERT (Devlin et al. 2018); this is a bi-directional transformer used for natural language processing developed by Google and pre-trained over a huge amount of unlabeled textual data to learn embeddings. We will then use these representations as an input of our classifier to detect real vs. machine-produced text. The application is demonstrated in the presentation.


2015 ◽  
Vol 32 (6) ◽  
pp. 835-842 ◽  
Author(s):  
Filippo Utro ◽  
Valeria Di Benedetto ◽  
Davide F.V. Corona ◽  
Raffaele Giancarlo

Abstract Motivation: Thanks to research spanning nearly 30 years, two major models have emerged that account for nucleosome organization in chromatin: statistical and sequence specific. The first is based on elegant, easy to compute, closed-form mathematical formulas that make no assumptions of the physical and chemical properties of the underlying DNA sequence. Moreover, they need no training on the data for their computation. The latter is based on some sequence regularities but, as opposed to the statistical model, it lacks the same type of closed-form formulas that, in this case, should be based on the DNA sequence only. Results: We contribute to close this important methodological gap between the two models by providing three very simple formulas for the sequence specific one. They are all based on well-known formulas in Computer Science and Bioinformatics, and they give different quantifications of how complex a sequence is. In view of how remarkably well they perform, it is very surprising that measures of sequence complexity have not even been considered as candidates to close the mentioned gap. We provide experimental evidence that the intrinsic level of combinatorial organization and information-theoretic content of subsequences within a genome are strongly correlated to the level of DNA encoded nucleosome organization discovered by Kaplan et al. Our results establish an important connection between the intrinsic complexity of subsequences in a genome and the intrinsic, i.e. DNA encoded, nucleosome organization of eukaryotic genomes. It is a first step towards a mathematical characterization of this latter ‘encoding’. Supplementary information: Supplementary data are available at Bioinformatics online. Contact: [email protected].


2018 ◽  
Vol 36 (2) ◽  
pp. 186-202
Author(s):  
Francesco Tajani ◽  
Pierluigi Morano

Purpose The purpose of this paper is to develop a method to support the definition of efficient and fair divisional projects in particularly complex cases concerning inheritance disputes. Design/methodology/approach First, the approach involves an appraisal of the market value of the assets, along with an analysis of the respective conditions of concrete divisibility; then, two mathematical models have been developed for the assignment of the assets to the subjects involved in the divisional projects. The logic underlying of both models has been translated into mathematical algorithms that allow for the minimization of the monetary compensations resulting from the differences between the legal right shares and the actual portions to be attributed to them. Findings Both models have been developed through mathematical formulas that can be easily implemented by using an appropriate calculation software. They can be used in particularly complex inheritance divisions, in which the deceased’s assets are numerous and there are several heirs with similar or different legal right shares. Originality/value The methodology is useful in the disputes that could arise in hereditary successions. The fundamental value is that the models could support the definition of the best solution in particularly complex situations, characterized by a large number of assets to be assigned and/or the existence of “preferential” constraints for the assignment of the assets.


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