A Hybrid Recommender System based on Collaborative Filtering and Cloud Model

User-based Collaborative filtering (CF), one of the most prevailing and efficient recommendation techniques, provides personalized recommendations to users based on the opinions of other users. Although the CF technique has been successfully applied in various applications, it suffers from serious sparsity problems. The cloud-model approach addresses the sparsity problems by constructing the user-s global preference represented by a cloud eigenvector. The user-based CF approach works well with dense datasets while the cloud-model CF approach has a greater performance when the dataset is sparse. In this paper, we present a hybrid approach that integrates the predictions from both the user-based CF and the cloud-model CF approaches. The experimental results show that the proposed hybrid approach can ameliorate the sparsity problem and provide an improved prediction quality.

Characteristics Analysis of Voltage Sag and Voltage Swell in Multi-Grounded Four-Wire Power Distribution Systems

In North America, Most power distribution systems employ a four-wire multi-grounded neutral (MGN) design. This paper has explained the inherent characteristics of multi-grounded three-phase four-wire distribution systems under unbalanced situations. As a result, the mechanism of voltage swell and voltage sag in MGN feeders becomes difficult to understand. The simulation tool that has been used in this paper is MATLAB under Windows software. In this paper the equivalent model of a full-scale multigrounded distribution system implemented by MATLAB is introduced. The results are expected to help utility engineers to understand the impact of MGN on distribution system operations.

The Spiral_OWL Model – Towards Spiral Knowledge Engineering

The Spiral development model has been used successfully in many commercial systems and in a good number of defense systems. This is due to the fact that cost-effective incremental commitment of funds, via an analogy of the spiral model to stud poker and also can be used to develop hardware or integrate software, hardware, and systems. To support adaptive, semantic collaboration between domain experts and knowledge engineers, a new knowledge engineering process, called Spiral_OWL is proposed. This model is based on the idea of iterative refinement, annotation and structuring of knowledge base. The Spiral_OWL model is generated base on spiral model and knowledge engineering methodology. A central paradigm for Spiral_OWL model is the concentration on risk-driven determination of knowledge engineering process. The collaboration aspect comes into play during knowledge acquisition and knowledge validation phase. Design rationales for the Spiral_OWL model are to be easy-to-implement, well-organized, and iterative development cycle as an expanding spiral.

A Serializability Condition for Multi-step Transactions Accessing Ordered Data

In mobile environments, unspecified numbers of transactions arrive in continuous streams. To prove correctness of their concurrent execution a method of modelling an infinite number of transactions is needed. Standard database techniques model fixed finite schedules of transactions. Lately, techniques based on temporal logic have been proposed as suitable for modelling infinite schedules. The drawback of these techniques is that proving the basic serializability correctness condition is impractical, as encoding (the absence of) conflict cyclicity within large sets of transactions results in prohibitively large temporal logic formulae. In this paper, we show that, under certain common assumptions on the graph structure of data items accessed by the transactions, conflict cyclicity need only be checked within all possible pairs of transactions. This results in formulae of considerably reduced size in any temporal-logic-based approach to proving serializability, and scales to arbitrary numbers of transactions.

Shape Restoration of the Left Ventricle

This paper describes an automatic algorithm to restore the shape of three-dimensional (3D) left ventricle (LV) models created from magnetic resonance imaging (MRI) data using a geometry-driven optimization approach. Our basic premise is to restore the LV shape such that the LV epicardial surface is smooth after the restoration. A geometrical measure known as the Minimum Principle Curvature (κ2) is used to assess the smoothness of the LV. This measure is used to construct the objective function of a two-step optimization process. The objective of the optimization is to achieve a smooth epicardial shape by iterative in-plane translation of the MRI slices. Quantitatively, this yields a minimum sum in terms of the magnitude of κ 2, when κ2 is negative. A limited memory quasi-Newton algorithm, L-BFGS-B, is used to solve the optimization problem. We tested our algorithm on an in vitro theoretical LV model and 10 in vivo patient-specific models which contain significant motion artifacts. The results show that our method is able to automatically restore the shape of LV models back to smoothness without altering the general shape of the model. The magnitudes of in-plane translations are also consistent with existing registration techniques and experimental findings.

On the Wreath Product of Group by Some Other Groups

In this paper, we will generate the wreath product 11 12 M wrM using only two permutations. Also, we will show the structure of some groups containing the wreath product 11 12 M wrM . The structure of the groups founded is determined in terms of wreath product k (M wrM ) wrC 11 12 . Some related cases are also included. Also, we will show that 132K+1 S and 132K+1 A can be generated using the wreath product k (M wrM ) wrC 11 12 and a transposition in 132K+1 S and an element of order 3 in 132K+1 A . We will also show that 132K+1 S and 132K+1 A can be generated using the wreath product 11 12 M wrM and an element of order k +1.

Satellite Data Classification Accuracy Assessment Based from Reference Dataset

In order to develop forest management strategies in tropical forest in Malaysia, surveying the forest resources and monitoring the forest area affected by logging activities is essential. There are tremendous effort has been done in classification of land cover related to forest resource management in this country as it is a priority in all aspects of forest mapping using remote sensing and related technology such as GIS. In fact classification process is a compulsory step in any remote sensing research. Therefore, the main objective of this paper is to assess classification accuracy of classified forest map on Landsat TM data from difference number of reference data (200 and 388 reference data). This comparison was made through observation (200 reference data), and interpretation and observation approaches (388 reference data). Five land cover classes namely primary forest, logged over forest, water bodies, bare land and agricultural crop/mixed horticultural can be identified by the differences in spectral wavelength. Result showed that an overall accuracy from 200 reference data was 83.5 % (kappa value 0.7502459; kappa variance 0.002871), which was considered acceptable or good for optical data. However, when 200 reference data was increased to 388 in the confusion matrix, the accuracy slightly improved from 83.5% to 89.17%, with Kappa statistic increased from 0.7502459 to 0.8026135, respectively. The accuracy in this classification suggested that this strategy for the selection of training area, interpretation approaches and number of reference data used were importance to perform better classification result.

Utilization of Advanced Data Storage Technology to Conduct Construction Industry on Clear Environment

Construction projects generally take place in uncontrolled and dynamic environments where construction waste is a serious environmental problem in many large cities. The total amount of waste and carbon dioxide emissions from transportation vehicles are still out of control due to increasing construction projects, massive urban development projects and the lack of effective tools for minimizing adverse environmental impacts in construction. This research is about utilization of the integrated applications of automated advanced tracking and data storage technologies in the area of environmental management to monitor and control adverse environmental impacts such as construction waste and carbon dioxide emissions. Radio Frequency Identification (RFID) integrated with the Global Position System (GPS) provides an opportunity to uniquely identify materials, components, and equipments and to locate and track them using minimal or no worker input. The transmission of data to the central database will be carried out with the help of Global System for Mobile Communications (GSM).

A Thought on Exotic Statistical Distributions

The statistical distributions are modeled in explaining nature of various types of data sets. Although these distributions are mostly uni-modal, it is quite common to see multiple modes in the observed distribution of the underlying variables, which make the precise modeling unrealistic. The observed data do not exhibit smoothness not necessarily due to randomness, but could also be due to non-randomness resulting in zigzag curves, oscillations, humps etc. The present paper argues that trigonometric functions, which have not been used in probability functions of distributions so far, have the potential to take care of this, if incorporated in the distribution appropriately. A simple distribution (named as, Sinoform Distribution), involving trigonometric functions, is illustrated in the paper with a data set. The importance of trigonometric functions is demonstrated in the paper, which have the characteristics to make statistical distributions exotic. It is possible to have multiple modes, oscillations and zigzag curves in the density, which could be suitable to explain the underlying nature of select data set.

A Microcontroller Implementation of Model Predictive Control

Model Predictive Control (MPC) is increasingly being proposed for real time applications and embedded systems. However comparing to PID controller, the implementation of the MPC in miniaturized devices like Field Programmable Gate Arrays (FPGA) and microcontrollers has historically been very small scale due to its complexity in implementation and its computation time requirement. At the same time, such embedded technologies have become an enabler for future manufacturing enterprises as well as a transformer of organizations and markets. Recently, advances in microelectronics and software allow such technique to be implemented in embedded systems. In this work, we take advantage of these recent advances in this area in the deployment of one of the most studied and applied control technique in the industrial engineering. In fact in this paper, we propose an efficient framework for implementation of Generalized Predictive Control (GPC) in the performed STM32 microcontroller. The STM32 keil starter kit based on a JTAG interface and the STM32 board was used to implement the proposed GPC firmware. Besides the GPC, the PID anti windup algorithm was also implemented using Keil development tools designed for ARM processor-based microcontroller devices and working with C/Cµ langage. A performances comparison study was done between both firmwares. This performances study show good execution speed and low computational burden. These results encourage to develop simple predictive algorithms to be programmed in industrial standard hardware. The main features of the proposed framework are illustrated through two examples and compared with the anti windup PID controller.

Enhance Halorespiration in Rhodopseudomonas palustris with Cytochrome P450cam System from Pseudomonas putida

To decompose organochlorides by bioremediation, co-culture biohydrogen producer and dehalogenation microorganisms is a useful method. In this study, we combined these two characteristics from a biohydrogen producer, Rhodopseudomonas palustris, and a dehalogenation microorganism, Pseudomonas putida, to enchance halorespiration in R. palustris. The genes encoding cytochrome P450cam system (camC, camA, and camB) from P. putida were expressed in R. palustris with designated expression plasmid. All tested strains were cultured to log phase then presented pentachloroethane (PCA) in media. The vector control strain could degrade PCA about 78% after 16 hours, however, the cytochrome P450cam system expressed strain, CGA-camCAB, could completely degrade PCA in 12 hours. While taking chlorinated aromatic, 3-chlorobenzoate, as sole carbon source or present benzoate as co-substrate, CGA-camCAB presented faster growth rate than vector control strain.

Fuzzy Logic PID Control of Automatic Voltage Regulator System

The application of a simple microcontroller to deal with a three variable input and a single output fuzzy logic controller, with Proportional – Integral – Derivative (PID) response control built-in has been tested for an automatic voltage regulator. The fuzzifiers are based on fixed range of the variables of output voltage. The control output is used to control the wiper motor of the auto transformer to adjust the voltage, using fuzzy logic principles, so that the voltage is stabilized. In this report, the author will demonstrate how fuzzy logic might provide elegant and efficient solutions in the design of multivariable control based on experimental results rather than on mathematical models.

Supercompression for Full-HD and 4k-3D (8k)Digital TV Systems

In this work, we developed the concept of supercompression, i.e., compression above the compression standard used. In this context, both compression rates are multiplied. In fact, supercompression is based on super-resolution. That is to say, supercompression is a data compression technique that superpose spatial image compression on top of bit-per-pixel compression to achieve very high compression ratios. If the compression ratio is very high, then we use a convolutive mask inside decoder that restores the edges, eliminating the blur. Finally, both, the encoder and the complete decoder are implemented on General-Purpose computation on Graphics Processing Units (GPGPU) cards. Specifically, the mentio-ned mask is coded inside texture memory of a GPGPU.

Heat Exchanger Design

This paper is intended to assist anyone with some general technical experience, but perhaps limited specific knowledge of heat transfer equipment. A characteristic of heat exchanger design is the procedure of specifying a design, heat transfer area and pressure drops and checking whether the assumed design satisfies all requirements or not. The purpose of this paper is how to design the oil cooler (heat exchanger) especially for shell-and-tube heat exchanger which is the majority type of liquid-to-liquid heat exchanger. General design considerations and design procedure are also illustrated in this paper and a flow diagram is provided as an aid of design procedure. In design calculation, the MatLAB and AutoCAD software are used. Fundamental heat transfer concepts and complex relationships involved in such exchanger are also presented in this paper. The primary aim of this design is to obtain a high heat transfer rate without exceeding the allowable pressure drop. This computer program is highly useful to design the shell-and-tube type heat exchanger and to modify existing deign.

High Performance VLSI Architecture of 2D Discrete Wavelet Transform with Scalable Lattice Structure

In this paper, we propose a fully-utilized, block-based 2D DWT (discrete wavelet transform) architecture, which consists of four 1D DWT filters with two-channel QMF lattice structure. The proposed architecture requires about 2MN-3N registers to save the intermediate results for higher level decomposition, where M and N stand for the filter length and the row width of the image respectively. Furthermore, the proposed 2D DWT processes in horizontal and vertical directions simultaneously without an idle period, so that it computes the DWT for an N×N image in a period of N2(1-2-2J)/3. Compared to the existing approaches, the proposed architecture shows 100% of hardware utilization and high throughput rates. To mitigate the long critical path delay due to the cascaded lattices, we can apply the pipeline technique with four stages, while retaining 100% of hardware utilization. The proposed architecture can be applied in real-time video signal processing.

Experimental Study of the Metal Foam Flow Conditioner for Orifice Plate Flowmeters

The sensitivity of orifice plate metering to disturbed flow (either asymmetric or swirling) is a subject of great concern to flow meter users and manufacturers. The distortions caused by pipe fittings and pipe installations upstream of the orifice plate are major sources of this type of non-standard flows. These distortions can alter the accuracy of metering to an unacceptable degree. In this work, a multi-scale object known as metal foam has been used to generate a predetermined turbulent flow upstream of the orifice plate. The experimental results showed that the combination of an orifice plate and metal foam flow conditioner is broadly insensitive to upstream disturbances. This metal foam demonstrated a good performance in terms of removing swirl and producing a repeatable flow profile within a short distance downstream of the device. The results of using a combination of a metal foam flow conditioner and orifice plate for non-standard flow conditions including swirling flow and asymmetric flow show this package can preserve the accuracy of metering up to the level required in the standards.

Towards Growing Self-Organizing Neural Networks with Fixed Dimensionality

The competitive learning is an adaptive process in which the neurons in a neural network gradually become sensitive to different input pattern clusters. The basic idea behind the Kohonen-s Self-Organizing Feature Maps (SOFM) is competitive learning. SOFM can generate mappings from high-dimensional signal spaces to lower dimensional topological structures. The main features of this kind of mappings are topology preserving, feature mappings and probability distribution approximation of input patterns. To overcome some limitations of SOFM, e.g., a fixed number of neural units and a topology of fixed dimensionality, Growing Self-Organizing Neural Network (GSONN) can be used. GSONN can change its topological structure during learning. It grows by learning and shrinks by forgetting. To speed up the training and convergence, a new variant of GSONN, twin growing cell structures (TGCS) is presented here. This paper first gives an introduction to competitive learning, SOFM and its variants. Then, we discuss some GSONN with fixed dimensionality, which include growing cell structures, its variants and the author-s model: TGCS. It is ended with some testing results comparison and conclusions.

Analysis of Lightning Surge Condition Effect on Surge Arrester in Electrical Power System by using ATP/EMTP Program

The condition of lightning surge causes the traveling waves and the temporary increase in voltage in the transmission line system. Lightning is the most harmful for destroying the transmission line and setting devices so it is necessary to study and analyze the temporary increase in voltage for designing and setting the surge arrester. This analysis describes the figure of the lightning wave in transmission line with 115 kV voltage level in Thailand by using ATP/EMTP program to create the model of the transmission line and lightning surge. Because of the limit of this program, it must be calculated for the geometry of the transmission line and surge parameter and calculation in the manual book for the closest value of the parameter. On the other hand, for the effects on surge protector when the lightning comes, the surge arrester model must be right and standardized as metropolitan electrical authority's standard. The candidate compared the real information to the result from calculation, also. The results of the analysis show that the temporary increase in voltage value will be rise to 326.59 kV at the line which is done by lightning when the surge arrester is not set in the system. On the other hand, the temporary increase in voltage value will be 182.83 kV at the line which is done by lightning when the surge arrester is set in the system and the period of the traveling wave is reduced, also. The distance for setting the surge arrester must be as near to the transformer as possible. Moreover, it is necessary to know the right distance for setting the surge arrester and the size of the surge arrester for preventing the temporary increase in voltage, effectively.

Envelope Echo Signal of Metal Sphere in the Fresh Water

An envelope echo signal measurement is proposed in this paper using echo signal observation from the 200 kHz echo sounder receiver. The envelope signal without any object is compared with the envelope signal of the sphere. Two diameter size steel ball (3.1 cm & 2.2 cm) and two diameter size air filled stainless steel ball (4.8 cm & 7.4 cm) used in this experiment. The target was positioned about 0.5 m and 1.0 meter from the transducer face using nylon rope. From the echo observation in time domain, it is obviously shown that echo signal structure is different between the size, distance and type of metal sphere. The amplitude envelope voltage for the bigger sphere is higher compare to the small sphere and it confirm that the bigger sphere have higher target strength compare to the small sphere. Although the structure signal without any object are different compare to the signal from the sphere, the reflected signal from the tank floor increase linearly with the sphere size. We considered this event happened because of the object position approximately to the tank floor.

Learning Factory for Changeability

Amongst the consistently fluctuating conditions prevailing today, changeability represents a strategic key factor for a manufacturing company to achieve success on the international markets. In order to cope with turbulences and the increasing level of incalculability, not only the flexible design of production systems but in particular the employee as enabler of change provide the focus here. It is important to enable employees from manufacturing companies to participate actively in change events and in change decisions. To this end, the learning factory has been created, which is intended to serve the development of change-promoting competences and the sensitization of employees for the necessity of changes.