Google Play Apps energy rating model: multi-criteria evaluation model to generate tentative energy ratings for Google Play Store Apps

info:eu-repo/semantics/publishedVersio

Multi-Valued Quantum Neurons

The multiple-valued quantum logic is formulated systematically such that the truth values are represented naturally as unique roots of unity placed on the unit circle. Consequently, multi-valued quantum neuron (MVQN) is based on the principles of multiple-valued threshold logic over the field of complex numbers. The training of MVQN is reduced to the movement along the unit circle. A quantum neural network (QNN) based on multi-valued quantum neurons can be constructed with complex weights, inputs, and outputs encoded by roots of unity and an activation function that maps the complex plane into the unit circle. Such neural networks enjoy fast convergence and higher functionalities compared with quantum neural networks based on binary input with the same number of neurons and layers. Our construction can be used in analyzing the energy spectrum of quantum systems. Possible practical applications can be found using the quantum neural networks built from orbital angular momentum (OAM) of light or multi-level systems such as molecular spin qudits.Comment: 14 pages, 3 figures, accepted for publicatio

Complex Analysis of Intelligent Systems

Logic gates can be written in terms of complex differential operators where the inputs and outputs are analytic functions with several variables. Using the polar representation of complex numbers, we arrive at an immediate connection between the oscillatory behavior of the system and logic gates. We explain the universal programming language (UPL) used by physical objects to process information. To assure the causality structure in UPL, we introduce the concept of layers that characterizes the computations for each time scale.Comment: 18 pages; comments are welcome

Modular neural network to predict the distribution of nitrate in ground water using on-ground nitrogen loading and recharge data

Artificial neural networks have proven to be an attractive mathematical tool to represent complex relationships in many branches of hydrology. Due to this attractive feature, neural networks are increasingly being applied in subsurface modeling where intricate physical processes and lack of detailed field data prevail. In this paper, a methodology using modular neural networks (MNN) is proposed to simulate the nitrate concentrations in an agriculture-dominated aquifer. The methodology relies on geographic information system (GIS) tools in the preparation and processing of the MNN input–output data. The basic premise followed in developing the MNN input–output response patterns is to designate the optimal radius of a specified circular-buffered zone centered by the nitrate receptor so that the input parameters at the upgradient areas correlate with nitrate concentrations in ground water. A three-step approach that integrates the on-ground nitrogen loadings, soil nitrogen dynamics, and fate and transport in ground water is described and the critical parameters to predict nitrate concentration using MNN are selected. The sensitivity of MNN performance to different MNN architecture is assessed. The applicability of MNN is considered for the Sumas-Blaine aquifer of Washington State using two scenarios corresponding to current land use practices and a proposed protection alternative. The results of MNN are further analyzed and compared to those obtained from a physically-based fate and transport model to evaluate the overall applicability of MNN

Digital Marketing sebagai Metoda Alternatif Wirausaha Bagi Mahasiswa di Universitas Negeri Padang

Digital technology and the internet have opened opportunities for people to develop social interaction through this technology, with the birth of web technology, media and social networks, which led to the industrial revolution 4.0. This technology presents a new trend in building a business called Digital Marketing (DM). DM provides new opportunities for anyone to do entrepreneurship without being limited by time, place and region. More than a decade of entrepreneurship has become the focus of attention of the government in Education, as one of the ways to reduce national unemployment. Universitas Negeri Padang (UNP) answers the entrepreneurship education policy by making Entrepreneurship as a compulsory subject, promoting entrepreneurial student programs and integrated service units for career guidance and entrepreneurship. This paper examines more deeply how DM can be used as an alternative method of entrepreneurship for UNP students, which has direct touching student life as a millennial generation. The experimental method is used to see of improvement the knowledge and skills of students in DM through DM Training and Development of DM eLearning Resources (DMLR). To measure the success of the program, instruments were developed before and after training, as well as a questionnaire to assess the results of the DMLR development. The results of this study showed an increase in student knowledge and skills in DM and a good assessment of the developed DMLR

Integrated modeling of nitrate contamination of groundwater in agriculture-dominated watersheds

This paper presents and implements a framework for modeling the impact of land use practices and protection alternatives on nitrate pollution of groundwater in agricultural watersheds. The framework utilizes the national land cover database (NLCD) of the United State Geological Survey (USGS) grid and a geographic information system (GIS) to account for the spatial distribution of on-ground nitrogen sources and corresponding loadings. The framework employs a soil nitrogen dynamic model to estimate nitrate leaching to groundwater. These estimates were used in developing a groundwater nitrate fate and transport model. The framework considers both point and non-point sources of nitrogen across different land use classes. The methodology was applied for the Sumas–Blaine aquifer of Washington State, US, where heavy dairy industry and berry plantations are concentrated. Simulations were carried out using the developed framework to evaluate the overall impacts of current land use practices and the efficiency of proposed protection alternatives on nitrate pollution in the aquifer

Integral Transforms and PT\mathcal{PT}-symmetric Hamiltonians

The exponential Fourier transform of a given non-Hermitian $\mathcal{PT}$ -symmetric potential in the position space is Hermitian. We prove this proposition for any $\mathcal{PT}$-symmetric non-Hermitian Hamiltonians. The hermiticity of the Fourier transformed non-Hermitian Hamiltonian operator can be used as a condition for the reality of energy spectra. In the broken $\mathcal{PT}$-symmetric regime, pairs of complex eigenvalues may appear for potentials written in the position space. However, these complex pairs disappear in the momentum space and we are left only with real eigenvalues. Moreover, we comment on the holomorphic representation of non-Hermitian spin chains in which the Hamiltonian operator is written in term of analytical phase-space coordinates and their partial derivatives in the Bargmann space rather than matrices in the complex Hilbert space. Specifying to non-Hermitian $XX$ spin chain, we prove by numerically solving the quantum master equation its ability to flip from dynamical to static system by running the coupling constant from weak to strong. This would be used in building novel non-volatile memories. Finally, we test our proposition in the case of Swanson Hamiltonian.Comment: 20 pages, added section on XX spin chains and non-volatile memorie

How to Accommodate Different Learning Styles in the Same Classroom: Analysis of Theories and Methods of Learning Styles

Effective learning has always been a major concern for many educational associations. It is considered one of the most important learning processes that occur in the classroom. Teachers who are interested in understanding the process of the methods of achieving effective learning look hard for the appropriate pedagogical methods that enable them to improve classroom instruction and cover all types of students in the classroom. When the effective learning is achieved in the classroom, students can benefit from what they learn not only inside classroom but also outside classrooms. To achieve effective learning as well as effective teaching, it might be necessary for teachers to become familiar with students’ methods and theories of learning (Hunt, 2011; Kumar, & Chacko, 2010). This research paper sheds light on the theories and the models of learning and teaching styles and how they play an important role in the lives of students in classroom

Sensor Fusion Based Model for Collision Free Mobile Robot Navigation

Autonomous mobile robots have become a very popular and interesting topic in the last decade. Each of them are equipped with various types of sensors such as GPS, camera, infrared and ultrasonic sensors. These sensors are used to observe the surrounding environment. However, these sensors sometimes fail and have inaccurate readings. Therefore, the integration of sensor fusion will help to solve this dilemma and enhance the overall performance. This paper presents a collision free mobile robot navigation based on the fuzzy logic fusion model. Eight distance sensors and a range finder camera are used for the collision avoidance approach where three ground sensors are used for the line or path following approach. The fuzzy system is composed of nine inputs which are the eight distance sensors and the camera, two outputs which are the left and right velocities of the mobile robot’s wheels, and 24 fuzzy rules for the robot’s movement. Webots Pro simulator is used for modeling the environment and the robot. The proposed methodology, which includes the collision avoidance based on fuzzy logic fusion model and line following robot, has been implemented and tested through simulation and real time experiments. Various scenarios have been presented with static and dynamic obstacles using one robot and two robots while avoiding obstacles in different shapes and sizes.https://doi.org/10.3390/s1601002

Fuzzy Logic Control for Autonomous Mobile Robots in Static and Dynamic Environments

Autonomous mobile robots have been widely used in many researches and applications. In this work, we develop collision avoidance and line following techniques for mobile robot navigation in static and dynamic environments with the integration of fuzzy logic fusion. Eight proximity sensors are used to detect different obstacles whereas three ground sensors are used to detect the line underneath the robot. The proposed method has been successfully tested in Webots Pro simulator and in in real time experiment