A Matlab Code for Univariate Time Series Forecasting

This M-File forecasts univariate time series such as stock prices with a feedforward neural networks. It finds best (minimume RMSE) network automatically and uses early stopping method for solving overfitting problem.Neural Networks, Time Series, Early Stopping, Forecasting

The Impact of Joinder and Severance on Federal Criminal Cases: An Empirical Study

Dave is in trouble. It was bad enough to be arrested for bank robbery; now he has learned that the prosecutor plans to join the current charge with three other, unrelated bank robberies and present all four counts in a single trial. To his priest and to his lawyer, Dave admits that he committed the first and the second robberies, but he did not commit the third or fourth. Dave is smart enough to realize, however, that once the jury starts hearing evidence of some of the crimes-all of which will sound quite similar-his ability to cast doubt on the remaining charges will be dimmed. And Dave\u27s lawyer is smart enough to know that once the charges are joined, the chances of splitting them apart are relatively small. It is widely assumed that criminal defendants who face multiple charges in a single trial have a harder time prevailing than those who face several trials of one count each. Conventional wisdom also has it that a defendant who is joined for trial with other suspects is in a worse position than one who stands trial alone. These assumptions have never been tested empirically; this Article tries to fill the gap. Looking at nearly 20,000 federal criminal trials over a five-year period, the Article asks if the traditional beliefs are true and, if so, tries to measure the impact on trial outcomes of joining counts and defendants. The effect of joinder on criminal cases is part of a larger debate about how best to manage a growing criminal docket while still providing individual justice. The battle lines are easy to describe: courts and prosecutors typically want joined proceedings, defendants usually don\u27t. Courts believe that consolidated proceedings play a vital role \u27 in the administration of justice; defendants believe that they are a source of great prejudice. The problem is that both sides are right. The details of joinder and severance law are dry, even boring, and perhaps as a result, the impact of consolidated trials has received little scholarly attention. But the consequences are widespread: more than half of all federal defendants are charged with multiple counts, roughly one-third are joined with other defendants, and an overlapping one-quarter face both-a single proceeding with multiple charges plus one or more co-defendants. If joinder makes a conviction significantly more likely, it should have a bearing on prosecutors\u27 charging decisions, judicial rulings on severance motions, and defense decisions on whether to plead or stand trial. More importantly, understanding the dimensions of any prejudice should tell us something important about the tradeoffs we make between fairness to the accused and efficiency in processing criminal cases. Part II provides some background and describes the risks created by joinder. Part III(A) sets forth some working hypotheses and then offers an original empirical case for the prejudicial impact of joinder on the defense. Part III(B) then tests the empirical case with statistical models, trying to control for various features besides joinder that might explain the differences in trial outcome. To preview the results: it turns out that there is a measurable and significant prejudicial effect from joining multiple counts in a single trial, but the impact of joining multiple defendants is far less clear. With the results of the empirical test in hand, Part 1V argues for a reconsideration of the competing interests and poses questions for future study

Detecting Specific Types of DDoS Attacks in Cloud Environment by Using Anomaly Detection

RÉSUMÉ Un des avantages les plus importants de l'utilisation du cloud computing est d'avoir des services sur demande, et donc la méthode de paiement dans l'environnement du cloud est de type payer selon l'utilisation (pay per use). Cette caractéristique introduit un nouveau type d'attaque de déni des services appelée déni économique de la durabilité (Economic Denial of Sustainability EDoS) où le client paie des montants supplémentaires au fournisseur du cloud à cause de l'attaque. Les attaques DDoS avec leur nouvelle version sont divisées en trois catégories: 1) Les attaques de consommation de la bande passante. 2) Les attaques qui ciblent des applications spécifiques. 3) Les attaques d'épuisement sur la couche des connections. Dans ce travail, nous avons proposé un nouveau modèle pour détecter précisément les différents types des attaques DDoS et EDoS en comparant le trafic et l'utilisation des ressources dans des situations normale et d'attaque. Des caractéristiques (features) qui sont liées au trafic et à l'utilisation des ressources dans le cas de chaque attaque ont été recueillies. Elles constituent les métriques de notre modèle de détection. Dans la conception de notre modèle, nous avons utilisé les caractéristiques liées à tous les 3 types d'attaques puisque les caractéristiques d'un type d'attaque jouent un rôle important pour détecter un autre type. En effet, pour trouver un point de changement dans l'utilisation des ressources et le comportement du trafic nous avons utilisé l'algorithme des sommes cumulées CUSUM. La précision de notre algorithme a ensuite été étudiée en comparant sa performance avec celle d'un travail populaire précédent. Le taux de détection du modele était élevé, Ce qui indique la haute précision de l'algorithme conçu.----------ABSTRACT One of the most important benefits of using cloud computing is to have on-demand services; accordingly the method of payment in cloud environment is pay per use. This feature results in a new kind of DDOS attack called Economic Denial of Sustainability (EDoS) in which the customer pays extra to the cloud provider because of the attack. DDoS attacks and a new version of these attacks which called EDoS attack are divided into three different categories: 1) Bandwidth–consuming attacks, 2) Attacks which target specific applications and 3) Connection–layer exhaustion attacks. In this work we proposed a novel and inclusive model to precisely detect different types of DDoS and EDoS attacks by comparing the traffic and resource usage in normal and attack situations. Features which are related to traffic and resource usage in each attack were collected as the metrics of our detection model. In designing our model, we used the metrics related to all 3 types of attacks since features of one kind of attack play an important role to detect another type. Moreover, to find a change point in resource usage and traffic behavior we used CUSUM algorithm. The accuracy of our algorithm was then investigated by comparing its performance with one of the popular previous works. Achieving a higher rate of correct detection in our model proved the high accuracy of the designed algorithm

Structural Changes in NICs: Some Evidences on Attractor Points

In this paper we develop a regression and a kernel density based model for finding fixed points and attractors of dynamical systems to explore attractors of structural change for NICs. The results show that countries consume longer time in some structures than the others. This can be interpreted as existence of attractors that pull countries to themselves in the first stage of the development. In the other words one attractor (low level attractor) prevent countries to reach industrial structure. Awareness of this can be helpful in policymaking for transition from one structure to another. This analysis shades light on the problem that 'why some countries can not get ride of traditional structure?' or bad structure phenomena.Attractors, Structural changes, Fixed Points, Multidimensional Kernel Density, Regression Analysis.

Structural Changes in NICs: Some Evidences on Attractor Points

In this paper we develop a regression and a kernel density based model for finding fixed points and attractors of dynamical systems to explore attractors of structural change for NICs. The results show that countries consume longer time in some structures than the others. This can be interpreted as existence of attractors that pull countries to themselves in the first stage of the development. In the other words one attractor (low level attractor) prevent countries to reach industrial structure. Awareness of this can be helpful in policymaking for transition from one structure to another. This analysis shades light on the problem that 'why some countries can not get ride of traditional structure?' or bad structure phenomena.Attractors, Structural changes, Fixed Points, Multidimensional Kernel Density, Regression Analysis.

Analytical and Laboratory Evaluation of the Solubility of Gypsiferous Soils

Gypsum soil is one of the problematic soils because of considerable solubility for Gypsum particles in contact with water. In this research the effects of three factors including; gypsum percent, hydraulic gradient and soil texture were studied on solubility of gypsum soils. To do this, samples of gypsum soils were provided artificially by adding various rates of natural gypsum rock including 0, 5, 10, 20 and 30 percent weight of 3 kinds of soil textures including clay, silty clay and sand. Totally, 15 types of gypsum soils were prepared. Then each of gypsum soils were leached under five hydraulic gradients levels 0.5, 1, 2, 5 and 10. The results of the test indicated that the rate of Gypsum in the soil had direct effect on the rate of soluble and by increasing the percent of Gypsum, the rate of solubility was increased. In addition, by increasing hydraulic gradient, the speed of water existing soil media in a specified time was increased and also higher rate of Gypsum was derived. Also the soil texture has a considerable effect on the rate of solubility of soil. In this study, rate of solubility of gypsum soils with sandy soils was determined as 1.5 to 2 times more than the rate of clay soils. The   statistical   results show the highest impact of gypsum percentage and lowest impact of hydraulic gradient soil on solubility of particles in different types of soils and it has no significant effect on the overall equation of the soil texture