Algorithms

The simulation of the simple harmonic motion and damped oscillation of Cassy-E 524000 have been developed. The results of Cassy-E 524000 experiment are used as input. The pattern of displacement versus time graph in experiment result by using the Cassy-E 524000 can be approximated by the graph in cassy simulation program. Cassy simulation program is used to determine the variable amplitude, omega, horizontal shift, vertical shift and damping coefficients. Derived variables are used to formulate the equations of motion of the oscillating displacement versus time. Equation of the speed simulation versus time and acceleration versus time were obtained by the first and second derivation of the displacement versus time equation. The equations of motion obtained oscillation are used to simulate the displacement versus time, velocity versus time and acceleration versus time. ABSTRAK Telah berhasil dibuat simulasi gerak harmonik sederhana dan osilasi teredam pada Cassy-E 524000 dengan menggunakan perangkat lunak Borland Dephi 7.0. Hasil eksperimen menggunakan Cassy-E 524000 digunakan sebagai input pada program cassy simulation. Pola grafik simpangan terhadap waktu hasil eksperimen menggunakan Cassy-E 524000 dapat didekati oleh grafik pada program cassy simulation. Program cassy simulation digunakan untuk menentukan variabel amplitudo, omega, pergeseran horizontal, pergeseran vertikal dan koefisien redaman. Variabel yang diperoleh digunakan untuk menyusun persamaan gerak osilasi simpangan terhadap waktu. Persamaan simulasi kecepatan terhadap waktu dan percepatan terhadap waktu diperoleh dari turunan pertama dan kedua dari persamaan simpangan terhadap waktu. Persamaan gerak osilasi yang diperoleh digunakan untuk mensimulasikan grafik simpangan terhadap waktu, kecepatan terhadap waktu dan percepatan terhadap waktu. Kata kunci : Cassy-E 524000, gerak harmonik sederhana, osilasi teredam PENDAHULUAN Jika suatu sistem berosilasi di sekitar posisi setimbangnya maka pada sistem tersebut bekerja gaya balik atau gaya pemulih (restoring force) yang besarnya sebanding dengan jarak sistem dari posisi setimbangnya. Gaya tersebut akan cenderung mengembalikan system pada posisi setimbangnya. Getaran merupakan gerakan osilasi dari suatu sistem yang dapat berupa gerakan beraturan dan berulang secara kontinyu atau dapat juga berupa gerakan tidak beraturan atau acak [1]. Setiap gerak yang terjadi secara berulang dalam selang waktu yang sama disebut gerak periodik. Gerak periodik yang terjadi secara

The prefrontal cortex has long been thought to subserve both working memory (the holding of information online for processing) and executive functions (deciding how to manipulate working memory and perform processing). Although many computational models of working memory have been developed, the mechanistic basis of executive function remains elusive, often amounting to a homunculus. This article presents an attempt to deconstruct this homunculus through powerful learning mechanisms that allow a computational model of the prefrontal cortex to control both itself and other brain areas in a strategic, task-appropriate manner. These learning mechanisms are based on subcortical structures in the midbrain, basal ganglia, and amygdala, which together form an actor-critic architecture. The critic system learns which prefrontal representations are task relevant and trains the actor, which in turn provides a dynamic gating mechanism for controlling working memory updating. Computationally, the learning mechanism is designed to simultaneously solve the temporal and structural credit assignment problems. The model's performance compares favorably with standard backpropagation-based temporal learning mechanisms on the challenging 1-2-AX working memory task and other benchmark working memory tasks.

The problem of sorting is a problem that arises frequently in computer programming. Many different sorting algorithms have been developed and improved to make sorting fast. As a measure of performance mainly the average number of operations or the average execution times of these algorithms have been investigated and compared.There is no one sorting method that is best for every situation. Some of the factors to be considered in choosing a sorting algorithm include the size of the list to be sorted, the programming effort, the number of words of main memory available, the size of disk or tape units, the extent to which the list is already ordered, and the distribution of values

of the target gene relative to some reference group The two most commonly used methods to analyze data from such as an untreated control or a sample at time zero real-time, quantitative PCR experiments are absolute quantificain a time-course study.

Artificial neural networks (ANNs) are biologically inspired computer programs designed to simulate the way in which the human brain processes information. ANNs gather their knowledge by detecting the patterns and relationships in data and learn (or are trained) through experience, not from programming. An ANN is formed from hundreds of single units, artificial neurons or processing elements (PE), connected with coefficients (weights), which constitute the neural structure and are organised in layers. The power of neural computations comes from connecting neurons in a network. Each PE has weighted inputs, transfer function and one output. The behavior of a neural network is determined by the transfer functions of its neurons, by the learning rule, and by the architecture itself. The weights are the adjustable parameters and, in that sense, a neural network is a parameterized system. The weighed sum of the inputs constitutes the activation of the neuron. The activation signal is passed through transfer function to produce a single output of the neuron. Transfer function introduces non-linearity to the network. During training, the inter-unit connections are optimized until the error in predictions is minimized and the network reaches the specified level of accuracy. Once the network is trained and tested it can be given new input information to predict the output. Many types of neural networks have been designed already and new ones are invented every week but all can be described by the transfer functions of their neurons, by the learning rule, and by the connection formula. ANN represents a promising modeling technique, especially for data sets having non-linear relationships which are frequently encountered in pharmaceutical processes. In terms of model specification, artificial neural networks require no knowledge of the data source but, since they often contain many weights that must be estimated, they require large training sets. In addition, ANNs can combine and incorporate both literature-based and experimental data to solve problems. The various applications of ANNs can be summarised into classification or pattern recognition, prediction and modeling. Supervised associating networks can be applied in pharmaceutical fields as an alternative to conventional response surface methodology. Unsupervised feature-extracting networks represent an alternative to principal component analysis. Non-adaptive unsupervised networks are able to reconstruct their patterns when presented with noisy samples and can be used for image recognition. The potential applications of ANN methodology in the pharmaceutical sciences range from interpretation of analytical data, drug and dosage form design through biopharmacy to clinical pharmacy.

Modern metaheuristic algorithms such as bee algorithms and harmony search start to demonstrate their power in dealing with tough optimization problems and even NP-hard problems. This book reviews and introduces the state-of-the-art nature-inspired metaheuristic algorithms in optimization, including genetic algorithms, bee algorithms, particle swarm optimization, simulated annealing, ant colony optimization, harmony search, and firefly algorithms. We also briefly introduce the photosynthetic algorithm, the enzyme algorithm, and Tabu search. Worked examples with implementation have been used to show how each algorithm works. This book is thus an ideal textbook for an undergraduate and/or graduate course. As some of the algorithms such as the harmony search and firefly algorithms are at the forefront of current research, this book can also serve as a reference book for researchers.

The ICD-9-CM adaptation of the Charlson comorbidity score has been a valuable resource for health services researchers. With the transition into ICD-10 coding worldwide, an ICD-10 version of the Deyo adaptation was developed and validated using population-based hospital data from Victoria, Australia.

In information societies, operations, decisions and choices previously left to humans are increasingly delegated to algorithms, which may advise, if not decide, about how data should be interpreted and what actions should be taken as a result. More and more often, algorithms mediate social processes, business transactions, governmental decisions, and how we perceive, understand, and interact among ourselves and with the environment. Gaps between the design and operation of algorithms and our understanding of their ethical implications can have severe consequences affecting individuals as well as groups and whole societies. This paper makes three contributions to clarify the ethical importance of algorithmic mediation. It provides a prescriptive map to organise the debate. It reviews the current discussion of ethical aspects of algorithms. And it assesses the available literature in order to identify areas requiring further work to develop the ethics of algorithms.

In October 2016, the White House, the European Parliament, and the UK House of Commons each issued a report outlining their visions on how to prepare society for the widespread use of AI. In this article, we provide a comparative assessment of these three reports in order to facilitate the design of policies favourable to the development of a 'good AI society'. To do so, we examine how each report addresses the following three topics: (a) the development of a 'good AI society'; (b) the role and responsibility of the government, the private sector, and the research community (including academia) in pursuing such a development; and (c) where the recommendations to support such a development may be in need of improvement. Our analysis concludes that the reports address adequately various ethical, social, and economic topics, but come short of providing an overarching political vision and long-term strategy for the development of a 'good AI society'. In order to contribute to fill this gap, in the conclusion we suggest a two-pronged approach.

The basic theory of Markov chains has been known to mathematicians and engineers for close to 80 years, but it is only in the past decade that it has been applied explicitly to problems in speech processing. One of the major reasons why speech models, based on Markov chains, have not been developed until recently was the lack of a method for optimizing the parameters of the Markov model to match observed signal patterns. Such a method was proposed in the late 1960's and was immediately applied to speech processing .in several research institutions. Continued refinements in the theory and implementation of Markov modelling techniques have greatly enhanced the method, leading to a wide range of applications of these models. It is the purpose of this tutorial paper to give an introduction to the theory of Markov models, and to illustrate how they have been applied to problems in speech recognition.

Big data et la numérisation de l'exclusion sociale L'idée selon laquelle l'Internet serait une révolution sociale et cognitive, et qu'il permettrait une ère de démocratie généralisée laisse le plus souvent dans l'ombre la dynamique de transfert des représentations entre les cyberespaces et le monde réel. Il y a une relation de détermination mutuelle entre la technique (les applications) et les valeurs que portent ses concepteur.trice.s (ex. ingenieur.es) et ses contrôleur.euse.s (les géants du numérique). Telle est la thèse générale de Sofya Umoja Noble dans Algorithms of Oppression: How Search Engines Reinforce Racism. S. Noble est professeure adjointe en études de l'information à l'Université de Californie. Sa recherche, indique-t-elle, est concentrée sur « unveiling the many ways that African American people have been contained and constrained in classification systems, from Google's commercial search engine to library databases » (2018, p. 5).

El dolor neuropá tico es un problema sanitario de importancia creciente, tanto por el nú mero de pacientes afectados como por la gran repercusió n sobre la calidad de vida de aquellos que lo experimentan 1 . En Españ a, los pacientes con dolor neuropá tico son atendidos por diversos especialistas, lo que origina una gran variabilidad en la prá ctica clínica 2 y, aunque existen varias guías de prá ctica clínica en la literatura mé dica 2-5 , no se ha publicado ningú n documento de consenso entre diferentes especialidades realizado en este país con el objetivo de estandarizar la atenció n a estos pacientes 6 . Este documento de consenso, realizado por representantes de 7 sociedades científicas, intenta resumir la informació n de la literatura mé dica disponible usando el manual metodoló gico para la elaboració n de guías de prá ctica clínica en el sistema nacional de salud 7 , evaluando la calidad de la informació n con los grados de pruebas especificados en la tabla 1.

This theme issue has the founding ambition of landscaping Data Ethics as a new branch of ethics that studies and evaluates moral problems related to data (including generation, recording, curation, processing, dissemination, sharing, and use), algorithms (including AI, artificial agents, machine learning, and robots), and corresponding practices (including responsible innovation, programming, hacking, and professional codes), in order to formulate and support morally good solutions (e.g. right conducts or right values). Data Ethics builds on the foundation provided by Computer and Information Ethics but, at the same time, it refines the approach endorsed so far in this research field, by shifting the Level of Abstraction of ethical enquiries, from being information-centric to being data-centric. This shift brings into focus the different moral dimensions of all kinds of data, even the data that never translate directly into information but can be used to support actions or generate behaviours, for example. It highlights the need for ethical analyses to concentrate on the content and nature of computational operations—the interactions among hardware, software, and data—rather than on the variety of digital technologies that enables them. And it emphasises the complexity of the ethical challenges posed by Data Science. Because of such complexity, Data Ethics should be developed from the start as a macroethics, that is, as an overall framework that avoids narrow, ad hoc approaches and addresses the ethical impact and implications of Data Science and its applications within a consistent, holistic, and inclusive framework. Only as a macroethics Data Ethics will provide the solutions that can maximise the value of Data Science for our societies, for all of us, and for our environments.

El objetivo principal es que el presente libro exprese de manera clara los conceptos, el
análisis requerido para desarrollar un algoritmo y mostrar a través de ejemplos de
Algoritmos, su fundamentación, conceptualización y creación de manera práctica, para que
sea utilizado por : estudiantes, catedráticos y todas aquellas personas que se inician en la
programación.

Provides conceptual overview of algorithms in subjective gate-keeping roles and examines case studies that highlight potential issues and harms.

J. on Telecomm. & High Tech. L. 203 (2015)
Algorithmic Harms beyond Facebook and Google: Emergent Challenges of Computational Agency, Tufekci, Zeynep
[ 16 pages, 203 to 218 ]

In seinem Werk Überwachen und Strafen beschreibt Michel Foucault 1975 das von Jeremy Bentham erdachte Panopticon und visualisiert metaphorisch anhand dieses Konzepts die Funktionsweise einer Disziplinargesellschaft. Wer das Gefühl hat überwacht zu werden, beziehungsweise, wenn die Möglichkeit überwacht zu werden besteht, nimmt diese Tatsache Einfluss auf das Verhalten einer Person.
Die Beobachtungen Foucaults aus den 70er Jahren sind heute aktueller denn je und werden in der Wissenschaft zum Beispiel von David Lyon aufgenommen. Die aktuellen techno-politischen Entwicklungen gehen über die Beobachtungen und Theorien Foucaults hinaus. Sie zeichnen eine postpanoptische Gesellschaft in einer flüchtigen Moderne, in der die Macht sich längst in höhere Gefilde entfernt und von der Politik emanzipiert hat und in der jeder sein eigenes Panopticon mit sich herumträgt. Wir legen heutzutage freiwillig Daten offen, gegen deren Erhebung die vorherige Generation noch während der ersten Volkszählung gekämpft hat. Überträgt man heutiges Verhalten in die analoge Welt, zeigt sich die Absurdität unseres Habitus. Würden wir freiwillig eine Kopie unseres Adressbuches an Global Player und Geheimdienste verschiedener Regierungen senden? Wären wir dazu bereit, eine Kopie unserer E-Mails und SMS an die eben genannten Organisationen zu schicken? Ich kann es mir nicht vorstellen. Und doch willigen wir, durch die Installation verschiedener Programme oder Applikationen und deren AGB, in genau diesen Zustand ein.
Bis heute dient Überwachung dem Ziel transgressives Verhalten aufzudecken, um dieses zu bestrafen. So sind Überwachung und Bestrafung eng, ja unauflöslich miteinander verbunden. Die Bestrafung hat seit dem Mittelalter eine grundlegende Transformation durchlaufen. Vom Zurschaustellen des Verurteilten und der öffentlichen Strafausübung hin zu einem Konzept der Besserungs- und Umerziehungsanstalten.
Auch die Überwachung hat eine solche Transformation durchlaufen und ist insbesondere in den letzten Jahren immer umgreifender und omnipräsenter geworden. Nicht zuletzt, weil erst durch Big Data und algorithmische Auswertung eine nahezu lückenlose Überwachung der Bürger möglich geworden ist. In China wird nun der Versuch unternommen, der Bestrafung durch eine absolute Überwachung zuvorzukommen. Die chinesische Regierung baut das ganze Land im Zuge der Errichtung eines Social Credit Systems um. Vorrangiges Ziel dieses Systems soll eine ehrliche und vertrauenswürdige Gesellschaft sein. Ab 2020 wird ein großer Anteil der von Bürgern generierten Daten, darunter das Einkaufsvolumen, persönliche Daten wie Arbeitsplatz und Familienstatus, die Zahlungsmoral, sowie die Bewertungen von Freunden gesammelt und von Algorithmen in einen einheitlichen Score umgerechnet. Dieser Score bestimmt dann nicht nur, ob man einen Kredit bei einer Bank bekommt, wie das auch schon in Deutschland (SCHUFA) und Amerika üblich ist, sondern auch, ob man ein Visum beantragen kann, Bücher in einer Bibliothek ausleihen darf oder einen Platz in einem Schnellzug bekommt.

In this work, we present a novel approach for evaluating job applicants in online recruitment systems, leveraging machine learning algorithms to solve the candidate ranking problem. An application of our approach is implemented in the form of a prototype system, whose functionality is showcased and evaluated in a real-world recruitment scenario. The proposed system extracts a set of objective criteria from the applicants' LinkedIn profile, and infers their personality characteristics using linguistic analysis on their blog posts. Our system was found to perform consistently compared to human recruiters; thus, it can be trusted for the automation of applicant ranking and personality mining.

Empirical evidence is mounting that artificial intelligence applications driven by machine learning threaten to discriminate against legally protected groups. As ever more decisions are subjected to algorithmic processes, discrimination by algorithms is rightly recognized by policymakers around the world as a key challenge for contemporary societies. This article suggests that algorithmic bias raises intricate questions for EU law. The existing categories of EU anti-discrimination law do not provide an easy fit for algorithmic decision making, and the statistical basis of machine learning generally offers companies a fast-track to justification. Furthermore, victims won't be able to prove their case without access to the data and the algorithms, which they generally lack.

To remedy these problems, this article suggests an integrated vision of anti-discrimination and data protection law to enforce fairness in the digital age. More precisely, it shows how the concepts of anti-discrimination law may be combined with the enforcement tools of the GDPR to unlock the algorithmic black box. In doing so, the law should harness a growing literature in computer science on algorithmic fairness that seeks to ensure equal protection at the data and code level. The interplay of anti-discrimination law, data protection law and algorithmic fairness therefore facilitates "equal protection by design". In the end, however, recourse to technology does not prevent the law from making hard normative choices about the implementation of formal or substantive concepts of equality. Understood in this way, the deployment of artificial intelligence not only raises novel risks, but also harbors novel opportunities for consciously designing fair market exchange.

I verify a chronology in which seven groups of passages represent consecutive phases. A proposed chronology is verified if independent markers of style vary over its phases in a smooth fashion. Four markers of style follow smooth trajectories over the seven phases: The first is average verse length. The second encompasses the 28 most common morphemes in the Qurʾān. The percentages of these morphemes in a text constitute its stylistic profile. The thus-defined stylistic profile is shown to vary in a smooth fashion over "time", i.e. over the proposed chronological sequence of phases. Third, a similar thing holds for a profile based on the frequencies of 114 other common morphemes. Fourth, similar results are obtained for a list of 3693 relatively uncommon morphemes. In addition to establishing a relative chronology in seven phases, this essay demonstrates the stylistic unity of many large passages. It also shows that the Qurʾān has one author.