Performance Assessment of Motorized Solar Photovoltaic Louvers System Using PVSYST Software

In the realm of technological market penetration of solar photovoltaiclouvers (PVL) addressing environmental difficulties and the industrialrevolution, a new avenue of renewable energy is introduced. Moreover,solar energy exploitation through building façades was addressedthrough motorized solar photovoltaic louvers (MPVL). On the otherhand, proponents exalted the benefits of MPVL overlooking the typicalanalyses. In this communication, we attempted to perform a thoroughindustrial system evaluation of the MPVL. This communication presentsa methodology to validate the industrial claims about MPVL devices andtheir economic efficiency and the insight on how geographical locationinfluences their utilization and augment their potential benefits. This taskis carried out by evaluating the extent of solar energy that can be harvestedusing solar photovoltaic system (PVSYST) software and investigatingwhether existing product claims are associated with MPVL are feasible indifferent locations. The performance and operational losses (temperature,internal network, power electronics) were evaluated. To design and assessthe performance of different configurations based on the geographicalanalogy, simulation tools were successfully carried out based on differenttopographical locations. Based on these findings, various factors affect theemployment of MPVL such as geographical and weather conditions, solarirradiation, and installation efficiency. tt is assumed that we successfullyshed light and provided insights into the complexity associated withMPVL.

The Development and Creation of Intelligent Systems in the next one hundred years

Today the intelligent systems are technological implemented as advanced machines [1] which have high perception, interaction and response to the real world being in much cases an extension of the reality, anticipating events,intertwining remote events, saving life and predicting preferences of human been [2,3] through of robust programming and electronic systems with high performance, optimization and design in operations where are required machines with an strong and complete interacting with the environment [2]; environment which also goes increasing until; in the very near future, to the ends of the Universe.

Finding Non-liner Register on Binary M-Sequence Generating Binary Multiplication Sequence

In the current time there is an important problem that is for a received linear or nonlinear binary sequence {zn} how we can find the nonlinear feedback shift register and its linear equivalent which generate this sequence. The linear orthogonal sequences, special M-Sequences, play a big role in these methods for solving this problem. In the current research trying give illuminations about the methods which are very useful for solving this problem under short sequences, and study these methods for finding the nonlinear feedback shift register of a multiplication sequence and its linear equivalent feedback shift register of a received multiplication binary sequence{zn} where the multiplication on h degrees of a binary linear sequence {an}, or finding the equivalent linear feedback shift register of {zn}, where the sequence {zn}of the form M-sequence, and these methods are very effectively. We can extend these methods for the large sequences using programming and modern computers with large memory.

Representing Increasing Virtual Machine Security Strategy in Cloud Computing Computations

This paper proposes algorithm for Increasing Virtual Machine Security Strategy in Cloud Computing computations. Imbalance between load and energy has been one of the disadvantages of old methods in providing server and hosting, so that if two virtual severs be active on a host and energy load be more on a host, it would allocated the energy of other hosts (virtual host) to itself to stay steady and this option usually leads to hardware overflow errors and users dissatisfaction. This problem has been removed in methods based on cloud processing but not perfectly, therefore,providing an algorithm not only will implement a suitable security background but also it will suitably divide energy consumption and load balancing among virtual severs. The proposed algorithm is compared with several previously proposed Security Strategy including SC-PSSF, PSSF and DEEAC. Comparisons show that the proposed method offers high performance computing, efficiency and consumes lower energy in the network.

Cyber Security Professionals’ Challenges: A Proposed Integrated Platform Solution

As cyber threats and attacks are immensely increasing and broadly spreading catastrophically worldwide, cyber security professionals need to cope up with such a highly demanding environment. Security teams, such as Security operation Centre (SOC), Incident Response (IR) and Threat management teams are the people responsible for dealing with cyber security threats and attacks from detection to containment and preventing future incidents; which encompasses some significant challenges that might impose some limitations to the efficiency and effectiveness of activities cyber security professionals conduct, as these processes are time-consuming. In this paper we propose an integrated platform to help cyber security professionals to proactively manage cyber security threats and emerging incidents by providing an automated functionality that can optimize the workflow. The proposed security platform is supposed to diminish the average time taken by cyber security professionals to respond to cyber incidents with an average of 42%. This study can be used as a preliminary design for such an integrated platform.

Effective bandwidth estimation in data networks: an analysis for two traffic characterizations

he Generalized Markov Fluid Model (GMFM) is assumed for modeling sources in the network because it is versatile to describe the traffic fluctuations. In order to estimate resources allocations or in other words the channel occupation of each source, the concept of effective bandwidth (EB) proposed by Kelly [5] is used. In this paper we use an expression to determine the EB for this model which is of particular interest because it allows expressing said magnitude depending on the parameters of the model. This paper provides EB estimates for this model applying Kernel Estimation techniques in data networking. In particular we will study two differentiated cases: dispatches following a Gaussian and Exponential distribution. The performance of the proposed method is analyzed using simulated traffic traces generated by Monte Carlo Markov Chain algorithms. The estimation process worked much better in the Gaussian distribution case than in the Exponential one.

Mental Communication of Internal Speech with Communicative Associative Robot via Spectral Neurointerface

Thought communications with an associative-communicative robot are carried out through the spectral neurointerface of internal speech. Internal speech is an energy physiological process. Internal speech is vibration from the mental vibration of thought. Mental vibration of thought is a process in the mental ethereal field. The vibrations of thoughts are reflected and observed by the mind in the form of semantic sensual images. Vibrations of semantic sensual images generate vibrations of internal speech action (internal speech) in the form of language communicative and associative stereotypes which are perceived by a touch zone of a brain of Wernicke. Internal speech is a linguistic mental vibration, It is felt and becomes internally audible and drawn to attention. The perception of vibrations of internal speech is carried out through energy channels, such as the internal posterior median canal of the spine. The spectral neurointerface perceives these vibrations. Neocortex makes us a reasonable person - allows us to think and talk. The spectral neurointerface is based on the principles of biosensors, bioenergy detectors, spectral analyzers and electrocorticography for neuroimaging parts of the brain that record vibrations of internal speech, such as the lower frontal gyrus, the upper and middle temporal gyrus, the medial prefrontal cortex, the hind parts of the wedge and precline and the dark temporal region, including the posterior Internal speech activity is associated with the semantic memory of the neocortex.

A new model for automatic text classification

In this paper, a new method for automatic classification of texts is presented. This system includes two phases; text processing and text categorization. In the first phase, various indexing criteria such as bigram, trigram and quad-gram are presented to extract the properties. Then, in the second phase, the W-SMO machine learning algorithm is used to train the system. In order to evaluate and compare the results of the two criteria of accuracy and readability, Macro-F1 and Micro-F1 have been calculated for different indexing methods. The results of experiments performed on 7676 standard text documents of Reuters showed that our proposed method has the best performance compared to the W-j48, Naïve Bayes, K-NN and Decision Tree algorithms.

Design and Realization of Automatic Warehouse Based on S7-1500PLC

为了提高自动仓库控制系统的效率，设计了带有s7-1500plc的立体仓库实验平台。该机械手由步进电机和伺服电机驱动，以实现X，Y和ž三轴空间运动。物料传输系统由通用G120变频器构建。HMI KTP700实现控制和状态监视。通过RFID传感器和其他传感器对物料进行识别和分类.TIAV15软件构建PROFINET通信和PROFIBUS通信网络。使用GRAPH语言编程可以提高应用的可视化程度，并解决仓库控制系统程序设计和调试的复杂问题。通过软硬件设计，形成了一套完整的控制系统设计方案，

Basic unit; as a common module of neural networks

In this paper, the logic is developed assuming that all parts of the brain are composed of a combination of modules that basically have the same structure. The feeding behavior of searching for food while avoiding the dangers of animals in the early stages of evolution is regarded as the basis of time series data processing. The module that performs the processing is presented by a neural network equipped with a learning function based on Hebb's rule, and is called a basic unit. The basic units are arranged in layers, and the information between the layers is bidirectional. This new neural network is an extension of the traditional neural network that has evolved from pattern recognition. The biggest feature is that in the processing of time series data, the activated part changes according to the context structure inherent in the data, and can be mathematically expressed the method of predicting events from the context of learned behavior and utilizing it in best action.