Coding based Synchronization Algorithm for Secondary Synchronization Channel in WCDMA

A new code synchronization algorithm is proposed in this paper for the secondary cell-search stage in wideband CDMA systems. Rather than using the Cyclically Permutable (CP) code in the Secondary Synchronization Channel (S-SCH) to simultaneously determine the frame boundary and scrambling code group, the new synchronization algorithm implements the same function with less system complexity and less Mean Acquisition Time (MAT). The Secondary Synchronization Code (SSC) is redesigned by splitting into two sub-sequences. We treat the information of scrambling code group as data bits and use simple time diversity BCH coding for further reliability. It avoids involved and time-costly Reed-Solomon (RS) code computations and comparisons. Analysis and simulation results show that the Synchronization Error Rate (SER) yielded by the new algorithm in Rayleigh fading channels is close to that of the conventional algorithm in the standard. This new synchronization algorithm reduces system complexities, shortens the average cell-search time and can be implemented in the slot-based cell-search pipeline. By taking antenna diversity and pipelining correlation processes, the new algorithm also shows its flexible application in multiple antenna systems.

One Hour Ahead Load Forecasting Using Artificial Neural Network for the Western Area of Saudi Arabia

Load forecasting has become in recent years one of the major areas of research in electrical engineering. Most traditional forecasting models and artificial intelligence neural network techniques have been tried out in this task. Artificial neural networks (ANN) have lately received much attention, and a great number of papers have reported successful experiments and practical tests. This article presents the development of an ANN-based short-term load forecasting model with improved generalization technique for the Regional Power Control Center of Saudi Electricity Company, Western Operation Area (SEC-WOA). The proposed ANN is trained with weather-related data and historical electric load-related data using the data from the calendar years 2001, 2002, 2003, and 2004 for training. The model tested for one week at five different seasons, typically, winter, spring, summer, Ramadan and fall seasons, and the mean absolute average error for one hour-ahead load forecasting found 1.12%.

Proximate and Mineral Composition of Chicken Giblets from Vojvodina (Northern Serbia)

Proximate (moisture, protein, total fat, total ash) and mineral (K, P, Na, Mg, Ca, Zn, Fe, Cu and Mn) composition of chicken giblets (heart, liver and gizzard) were investigated. Phosphorous content, as well as proximate composition, were determined according to recommended ISO methods. The content of all elements, except phosphorus, of the giblets tissues were determined using inductively coupled plasma-optical emission spectrometry (ICP-OES), after dry ashing mineralization. Regarding proximate composition heart was the highest in total fat content, and the lowest in protein content. Liver was the highest in protein and total ash content, while gizzard was the highest in moisture and the lowest in total fat content. Regarding mineral composition liver was the highest for K, P, Ca, Mg, Fe, Zn, Cu, and Mn, while heart was the highest for Na content. The contents of almost all investigated minerals in analysed giblets tissues of chickens from Vojvodina were similar to values reported in the literature, i.e. in national food composition databases of other countries.

An Exploration on On-line Mass Collaboration: Focusing on its Motivation Structure

The Internet has become an indispensable part of our lives. Witnessing recent web-based mass collaboration, e.g. Wikipedia, people are questioning whether the Internet has made fundamental changes to the society or whether it is merely a hyperbolic fad. It has long been assumed that collective action for a certain goal yields the problem of free-riding, due to its non-exclusive and non-rival characteristics. Then, thanks to recent technological advances, the on-line space experienced the following changes that enabled it to produce public goods: 1) decrease in the cost of production or coordination 2) externality from networked structure 3) production function which integrates both self-interest and altruism. However, this research doubts the homogeneity of on-line mass collaboration and argues that a more sophisticated and systematical approach is required. The alternative that we suggest is to connect the characteristics of the goal to the motivation. Despite various approaches, previous literature fails to recognize that motivation can be structurally restricted by the characteristic of the goal. First we draw a typology of on-line mass collaboration with 'the extent of expected beneficiary' and 'the existence of externality', and then we examine each combination of motivation using Benkler-s framework. Finally, we explore and connect such typology with its possible dominant participating motivation.

A Fast Adaptive Content-based Retrieval System of Satellite Images Database using Relevance Feedback

In this paper, we present a system for content-based retrieval of large database of classified satellite images, based on user's relevance feedback (RF).Through our proposed system, we divide each satellite image scene into small subimages, which stored in the database. The modified radial basis functions neural network has important role in clustering the subimages of database according to the Euclidean distance between the query feature vector and the other subimages feature vectors. The advantage of using RF technique in such queries is demonstrated by analyzing the database retrieval results.

The Study of the Variability of Anticipatory Postural Adjustments in Recurrent Non-specific LBP Patients

The study of the variability of the postural strategies in low back pain patients, as a criterion in evaluation of the adaptability of this system to the environmental demands is the purpose of this study. A cross-sectional case-control study was performed on 21 recurrent non-specific low back pain patients and 21 healthy volunteers. The electromyography activity of Deltoid, External Oblique (EO), Transverse Abdominis/Internal Oblique (TrA/IO) and Erector Spine (ES) muscles of each person was recorded in 75 rapid arm flexion with maximum acceleration. Standard deviation of trunk muscles onset relative to deltoid muscle onset were statistically analyzed by MANOVA . The results show that chronic low back pain patients exhibit less variability in their anticipatory postural adjustments (APAs) in comparison with the control group. There is a decrease in variability of postural control system of recurrent non-specific low back pain patients that can result in the persistence of pain and chronicity by decreasing the adaptability to environmental demands.

E-Commerce Adoption and Implementation in Automobile Industry: A Case Study

The use of Electronic Commerce (EC) technologies enables Small Medium Enterprises (SMEs) to improve their efficiency and competitive position. Much of the literature proposes an extensive set of benefits for organizations that choose to adopt and implement ECommerce systems. Factors of Business –to-business (B2B) E-Commerce adoption and implementation have been extensively investigated. Despite enormous attention given to encourage Small Medium Enterprises (SMEs) to adopt and implement E-Commerce, little research has been carried out in identifying the factors of Business-to-Consumer ECommerce adoption and implementation for SMEs. To conduct the study, Tornatsky and Fleischer model was adopted and tested in four SMEs located in Christchurch, New Zealand. This paper explores the factors that impact the decision and method of adoption and implementation of ECommerce systems in automobile industry. Automobile industry was chosen because the product they deal with i.e. cars are not a common commodity to be sold online, despite this fact the eCommerce penetration in automobile industry is high. The factors that promote adoption and implementation of E-Commerce technologies are discussed, together with the barriers. This study will help SME owners to effectively handle the adoption and implementation process and will also improve the chance of successful E-Commerce implementation. The implications of the findings for managers, consultants, and government organizations engaged in promoting E-Commerce adoption and implementation in small businesses and future research are discussed.

Utilization Juice Wastes as Corn Replacement in the Broiler Diet

An experiment was conducted with 80 unsexed broilers of the Arbor Acress strain to determine the capability of a carrot and fruit juice wastes mixture (carrot, apple, manggo, avocado, orange, melon and Dutch egg plant) in the same proportion for replacing corn in broiler diet. This study involved a completely randomized design (CRD) with 5 treatments (0, 5, 10, 15, and 20% of juice wastes mixture in diets) and 4 replicates per treatment. Diets were isonitrogenous (22% crude protein) and isocaloric (3000 kcal/kg diet). Measured variables were feed consumption, average daily gain, feed conversion, as well as percentages of abdominal fat pad, carcass, digestive organs (liver, pancreas and gizzard), and heart. Data were analyzed by analysis of variance for CRD. Increasing juice wastes mixture levels in diets increased feed consumption (P

Integrated Evaluation of Green Design and Green Manufacturing Processes Using a Mathematical Model

In this research, a mathematical model for integrated evaluation of green design and green manufacturing processes is presented. To design a product, there can be alternative options to design the detailed components to fulfill the same product requirement. In the design alternative cases, the components of the product can be designed with different materials and detailed specifications. If several design alternative cases are proposed, the different materials and specifications can affect the manufacturing processes. In this paper, a new concept for integrating green design and green manufacturing processes is presented. A green design can be determined based the manufacturing processes of the designed product by evaluating the green criteria including energy usage and environmental impact, in addition to the traditional criteria of manufacturing cost. With this concept, a mathematical model is developed to find the green design and the associated green manufacturing processes. In the mathematical model, the cost items include material cost, manufacturing cost, and green related cost. The green related cost items include energy cost and environmental cost. The objective is to find the decisions of green design and green manufacturing processes to achieve the minimized total cost. In practical applications, the decision-making can be made to select a good green design case and its green manufacturing processes. In this presentation, an example product is illustrated. It shows that the model is practical and useful for integrated evaluation of green design and green manufacturing processes.

Multi-algorithmic Iris Authentication System

The paper proposes a novel technique for iris recognition using texture and phase features. Texture features are extracted on the normalized iris strip using Haar Wavelet while phase features are obtained using LOG Gabor Wavelet. The matching scores generated from individual modules are combined using sum of score technique. The system is tested on database obtained from Bath University and Indian Institute of Technology Kanpur and is giving an accuracy of 95.62% and 97.66% respectively. The FAR and FRR of the combined system is also reduced comparatively.

The Importance of 3D Mesh Generation for Large Eddy Simulation of Gas – Solid Turbulent Flows in a Fluidized Beds

The objective of this work is to show a procedure for mesh generation in a fluidized bed using large eddy simulations (LES) of a filtered two-fluid model. The experimental data were obtained by [1] in a laboratory fluidized bed. Results show that it is possible to use mesh with less cells as compared to RANS turbulence model with granular kinetic theory flow (KTGF). Also, the numerical results validate the experimental data near wall of the bed, which cannot be predicted by RANS.model.

The Effects of Methionine and Acetate Concentrations on Mycophenolic Acid Production by Penicillium bervicompactum MUCL 19011 in Submerged Culture

Mycophenolic acid “MPA" is a secondary metabolite of Penicillium bervicompactum with antibiotic and immunosuppressive properties. In this study, fermentation process was established for production of mycophenolic acid by Penicillium bervicompactum MUCL 19011 in shake flask. The maximum MPA production, product yield and productivity were 1.379 g/L, 18.6 mg/g glucose and 4.9 mg/L.h respectively. Glucose consumption, biomass and MPA production profiles were investigated during fermentation time. It was found that MPA production starts approximately after 180 hours and reaches to a maximum at 280 h. In the next step, the effects of methionine and acetate concentrations on MPA production were evaluated. Maximum MPA production, product yield and productivity (1.763 g/L, 23.8 mg/g glucose and 6.30 mg/L. h respectively) were obtained with using 2.5 g/L methionine in culture medium. Further addition of methionine had not more positive effect on MPA production. Finally, results showed that the addition of acetate to the culture medium had not any observable effect on MPA production.

Electricity Consumption Prediction Model using Neuro-Fuzzy System

In this paper the development of neural network based fuzzy inference system for electricity consumption prediction is considered. The electricity consumption depends on number of factors, such as number of customers, seasons, type-s of customers, number of plants, etc. It is nonlinear process and can be described by chaotic time-series. The structure and algorithms of neuro-fuzzy system for predicting future values of electricity consumption is described. To determine the unknown coefficients of the system, the supervised learning algorithm is used. As a result of learning, the rules of neuro-fuzzy system are formed. The developed system is applied for predicting future values of electricity consumption of Northern Cyprus. The simulation of neuro-fuzzy system has been performed.

A 3.125Gb/s Clock and Data Recovery Circuit Using 1/4-Rate Technique

This paper describes the design and fabrication of a clock and data recovery circuit (CDR). We propose a new clock and data recovery which is based on a 1/4-rate frequency detector (QRFD). The proposed frequency detector helps reduce the VCO frequency and is thus advantageous for high speed application. The proposed frequency detector can achieve low jitter operation and extend the pull-in range without using the reference clock. The proposed CDR was implemented using a 1/4-rate bang-bang type phase detector (PD) and a ring voltage controlled oscillator (VCO). The CDR circuit has been fabricated in a standard 0.18 CMOS technology. It occupies an active area of 1 x 1 and consumes 90 mW from a single 1.8V supply.

Performance Enhancement of Dye-Sensitized Solar Cells by MgO Coating on TiO2 Electrodes

TiO2/MgO composite films were prepared by coating the magnesium acetate solution in the pores of mesoporous TiO2 films using a dip coating method. Concentrations of magnesium acetate solution were varied in a range of 1x10-4 – 1x10-1 M. The TiO2/MgO composite films were characterized by scanning electron microscopy (SEM), transmission electron microscropy (TEM), electrochemical impedance spectroscopy(EIS) , transient voltage decay and I-V test. The TiO2 films and TiO2/MgO composite films were immersed in a 0.3 mM N719 dye solution. The Dye-sensitized solar cells with the TiO2/MgO/N719 structure showed an optimal concentration of magnesium acetate solution of 1x10-3 M resulting in the MgO film estimated thickness of 0.0963 nm and giving the maximum efficiency of 4.85%. The improved efficiency of dyesensitized solar cell was due to the magnesium oxide film as the wide band gap coating decays the electron back transfer to the triiodide electrolyte and reduce charge recombination.

Transmission Planning – a Probabilistic Load Flow Perspective

Perhaps no single issue has been cited as either the root cause and / or the greatest challenge to the restructured power system then the lack of adequate reliable transmission. Probabilistic transmission planning has become increasingly necessary and important in recent years. The transmission planning analysis carried out by the authors, spans a 10-year horizon, taking into consideration a value of 2 % load increase / year at each consumer. Taking into consideration this increased load, a probabilistic power flow was carried out, all the system components being regarded from probabilistic point of view. Several contingencies have been generated, for assessing the security of the power system. The results have been analyzed and several important conclusions were pointed. The objective is to achieve a network that works without limit violations for all (or most of) scenario realizations. The case study is represented by the IEEE 14 buses test power system.

Detecting Email Forgery using Random Forests and Naïve Bayes Classifiers

As emails communications have no consistent authentication procedure to ensure the authenticity, we present an investigation analysis approach for detecting forged emails based on Random Forests and Naïve Bays classifiers. Instead of investigating the email headers, we use the body content to extract a unique writing style for all the possible suspects. Our approach consists of four main steps: (1) The cybercrime investigator extract different effective features including structural, lexical, linguistic, and syntactic evidence from previous emails for all the possible suspects, (2) The extracted features vectors are normalized to increase the accuracy rate. (3) The normalized features are then used to train the learning engine, (4) upon receiving the anonymous email (M); we apply the feature extraction process to produce a feature vector. Finally, using the machine learning classifiers the email is assigned to one of the suspects- whose writing style closely matches M. Experimental results on real data sets show the improved performance of the proposed method and the ability of identifying the authors with a very limited number of features.

Choosing Search Algorithms in Bayesian Optimization Algorithm

The Bayesian Optimization Algorithm (BOA) is an algorithm based on the estimation of distributions. It uses techniques from modeling data by Bayesian networks to estimating the joint distribution of promising solutions. To obtain the structure of Bayesian network, different search algorithms can be used. The key point that BOA addresses is whether the constructed Bayesian network could generate new and useful solutions (strings), which could lead the algorithm in the right direction to solve the problem. Undoubtedly, this ability is a crucial factor of the efficiency of BOA. Varied search algorithms can be used in BOA, but their performances are different. For choosing better ones, certain suitable method to present their ability difference is needed. In this paper, a greedy search algorithm and a stochastic search algorithm are used in BOA to solve certain optimization problem. A method using Kullback-Leibler (KL) Divergence to reflect their difference is described.

A Visual Control Flow Language and Its Termination Properties

This paper presents the visual control flow support of Visual Modeling and Transformation System (VMTS), which facilitates composing complex model transformations out of simple transformation steps and executing them. The VMTS Visual Control Flow Language (VCFL) uses stereotyped activity diagrams to specify control flow structures and OCL constraints to choose between different control flow branches. This work discusses the termination properties of VCFL and provides an algorithm to support the termination analysis of VCFL transformations.

Climatic Change, Drought and Dust Crisis in Iran

Drought is a phenomenon caused by environmental and climatic changes. This phenomenon is affected by shortage of rainfall and temperature. Dust is one of important environmental problems caused by climate change and drought. With recent multi-year drought, many environmental crises caused by dust in Iran and Middle East. Dust in the vast areas of the provinces occurs with high frequency. By dust affecting many problems created in terms of health, social and economic. In this study, we tried to study the most important factors causing dust. In this way we have used the satellite images and meteorological data. Finally, strategies to deal with the dust will be mentioned.