Straight Line Defect Detection with Feed Forward Neural Network

Nowadays, hard disk is one of the most popular storage components. In hard disk industry, the hard disk drive must pass various complex processes and tested systems. In each step, there are some failures. To reduce waste from these failures, we must find the root cause of those failures. Conventionall data analysis method is not effective enough to analyze the large capacity of data. In this paper, we proposed the Hough method for straight line detection that helps to detect straight line defect patterns that occurs in hard disk drive. The proposed method will help to increase more speed and accuracy in failure analysis.

The Negative Effect of Traditional Loops Style on the Performance of Algorithms

A new algorithm called Character-Comparison to Character-Access (CCCA) is developed to test the effect of both: 1) converting character-comparison and number-comparison into character-access and 2) the starting point of checking on the performance of the checking operation in string searching. An experiment is performed using both English text and DNA text with different sizes. The results are compared with five algorithms, namely, Naive, BM, Inf_Suf_Pref, Raita, and Cycle. With the CCCA algorithm, the results suggest that the evaluation criteria of the average number of total comparisons are improved up to 35%. Furthermore, the results suggest that the clock time required by the other algorithms is improved in range from 22.13% to 42.33% by the new CCCA algorithm.

Design of an M-Channel Cosine Modulated Filter Bank by New Cosh Window Based FIR Filters

In this paper newly reported Cosh window function is used in the design of prototype filter for M-channel Near Perfect Reconstruction (NPR) Cosine Modulated Filter Bank (CMFB). Local search optimization algorithm is used for minimization of distortion parameters by optimizing the filter coefficients of prototype filter. Design examples are presented and comparison has been made with Kaiser window based filterbank design of recently reported work. The result shows that the proposed design approach provides lower distortion parameters and improved far-end suppression than the Kaiser window based design of recent reported work.

A Survey: Clustering Ensembles Techniques

The clustering ensembles combine multiple partitions generated by different clustering algorithms into a single clustering solution. Clustering ensembles have emerged as a prominent method for improving robustness, stability and accuracy of unsupervised classification solutions. So far, many contributions have been done to find consensus clustering. One of the major problems in clustering ensembles is the consensus function. In this paper, firstly, we introduce clustering ensembles, representation of multiple partitions, its challenges and present taxonomy of combination algorithms. Secondly, we describe consensus functions in clustering ensembles including Hypergraph partitioning, Voting approach, Mutual information, Co-association based functions and Finite mixture model, and next explain their advantages, disadvantages and computational complexity. Finally, we compare the characteristics of clustering ensembles algorithms such as computational complexity, robustness, simplicity and accuracy on different datasets in previous techniques.

Novel Dual Stage Membrane Bioreactor for the Continuous Remediation of Electroplating Wastewater

In this study, the designed dual stage membrane bioreactor (MBR) system was conceptualized for the treatment of cyanide and heavy metals in electroplating wastewater. The design consisted of a primary treatment stage to reduce the impact of fluctuations and the secondary treatment stage to remove the residual cyanide and heavy metal contaminants in the wastewater under alkaline pH conditions. The primary treatment stage contained hydrolyzed Citrus sinensis (C. sinensis) pomace and the secondary treatment stage contained active Aspergillus awamori (A. awamori) biomass, supplemented solely with C. sinensis pomace extract from the hydrolysis process. An average of 76.37%, 95.37%, 93.26 and 94.76% and 99.55%, 99.91%, 99.92% and 99.92% degradation efficiency for total cyanide (T-CN), including the sorption of nickel (Ni), zinc (Zn) and copper (Cu) were observed after the first and second treatment stages, respectively. Furthermore, cyanide conversion by-products degradation was 99.81% and 99.75 for both formate (CHOO-) and ammonium (NH4 +) after the second treatment stage. After the first, second and third regeneration cycles of the C. sinensis pomace in the first treatment stage, Ni, Zn and Cu removal achieved was 99.13%, 99.12% and 99.04% (first regeneration cycle), 98.94%, 98.92% and 98.41% (second regeneration cycle) and 98.46 %, 98.44% and 97.91% (third regeneration cycle), respectively. There was relatively insignificant standard deviation detected in all the measured parameters in the system which indicated reproducibility of the remediation efficiency in this continuous system.

SLM Using Riemann Sequence Combined with DCT Transform for PAPR Reduction in OFDM Communication Systems

Orthogonal Frequency Division Multiplexing (OFDM) is an efficient method of data transmission for high speed communication systems. However, the main drawback of OFDM systems is that, it suffers from the problem of high Peak-to-Average Power Ratio (PAPR) which causes inefficient use of the High Power Amplifier and could limit transmission efficiency. OFDM consist of large number of independent subcarriers, as a result of which the amplitude of such a signal can have high peak values. In this paper, we propose an effective reduction scheme that combines DCT and SLM techniques. The scheme is composed of the DCT followed by the SLM using the Riemann matrix to obtain phase sequences for the SLM technique. The simulation results show PAPR can be greatly reduced by applying the proposed scheme. In comparison with OFDM, while OFDM had high values of PAPR –about 10.4dB our proposed method achieved about 4.7dB reduction of the PAPR with low complexities computation. This approach also avoids randomness in phase sequence selection, which makes it simpler to decode at the receiver. As an added benefit, the matrices can be generated at the receiver end to obtain the data signal and hence it is not required to transmit side information (SI).

Pyrolysis of Rice Husk in a Fixed Bed Reactor

Fixed-bed slow pyrolysis experiments of rice husk have been conducted to determine the effect of pyrolysis temperature, heating rate, particle size and reactor length on the pyrolysis product yields. Pyrolysis experiments were performed at pyrolysis temperature between 400 and 600°C with a constant heating rate of 60°C/min and particle sizes of 0.60-1.18 mm. The optimum process conditions for maximum liquid yield from the rice husk pyrolysis in a fixed bed reactor were also identified. The highest liquid yield was obtained at a pyrolysis temperature of 500°C, particle size of 1.18-1.80 mm, with a heating rate of 60°C/min in a 300 mm length reactor. The obtained yield of, liquid, gas and solid were found be in the range of 22.57-31.78 %, 27.75-42.26 % and 34.17-42.52 % (all weight basics) respectively at different pyrolysis conditions. The results indicate that the effects of pyrolysis temperature and particle size on the pyrolysis yield are more significant than that of heating rate and reactor length. The functional groups and chemical compositions present in the liquid obtained at optimum conditions were identified by Fourier Transform-Infrared (FT-IR) spectroscopy and Gas Chromatography/ Mass Spectroscopy (GC/MS) analysis respectively.

An Investigation of the Effect of the Different Mix Constituents on Concrete Electric Resistivity

Steel corrosion in concrete is considered as a main engineering problems for many countries and lots of expenses has been paid for their repair and maintenance annually. This problem may occur in all engineering structures whether in coastal and offshore or other areas. Hence, concrete structures should be able to withstand corrosion factors existing in water or soil. Reinforcing steel corrosion enhancement can be measured by use of concrete electrical resistance; and maintaining high electric resistivity in concrete is necessary for steel corrosion prevention. Lots of studies devoted to different aspects of the subjects worldwide. In this paper, an evaluation of the effects of W/C ratio, cementitious materials, and percent increase in silica fume were investigated on electric resistivity of high strength concrete. To do that, sixteen mix design with one aggregate grading was planned. Five of them had varying amount of W/C ratio and other eleven mixes was prepared with constant W/C ratio but different amount of cementitious materials. Silica fume and super plasticizer were used with different proportions in all specimens. Specimens were tested after moist curing for 28 days. A total of 80 cube specimens (50 mm) were tested for concrete electrical resistance. Results show that concrete electric resistivity can be increased with increasing amount of cementitious materials and silica fume.

Wind-tunnel Measurement of the Drag-reducing Effect of Compliant Coating

A specially designed flat plate was mounted vertically over the axial line in the wind tunnel of the Aerospace Department of the Pusan National University. The plate is 2 m long, 0.8 m high and 8 cm thick. The measurements were performed in velocity range from 15 to 60 m/s. A sand paper turbulizer was placed close to the plate nose to provide fully developed turbulent boundary layer over the most part of the plate. Strain balances were mounted in the trailing part of the plate to measure the skin friction drag over removable insertions of 0.55×0.25m2 size. A set of the insertions was designed and manufactured: 3mm thick polished metal surface and three compliant surfaces. The compliant surfaces were manufactured of a silicone rubber Silastic® S2 (Dow Corning company). To modify the viscoelastic properties of the rubber, its composition was varied: 90% of the rubber + 10% catalyst (standard), 92.5% + 7.5% (weak), 85% + 15% (strong). Modulus of elasticity and the loss tangent were measured accurately for these materials in the frequency range from 40 Hz to 3 KHz using the unique proposed technique.

Identifying an Unknown Source in the Poisson Equation by a Modified Tikhonov Regularization Method

In this paper, we consider the problem for identifying the unknown source in the Poisson equation. A modified Tikhonov regularization method is presented to deal with illposedness of the problem and error estimates are obtained with an a priori strategy and an a posteriori choice rule to find the regularization parameter. Numerical examples show that the proposed method is effective and stable.

A New Evolutionary Algorithm for Cluster Analysis

Clustering is a very well known technique in data mining. One of the most widely used clustering techniques is the kmeans algorithm. Solutions obtained from this technique depend on the initialization of cluster centers and the final solution converges to local minima. In order to overcome K-means algorithm shortcomings, this paper proposes a hybrid evolutionary algorithm based on the combination of PSO, SA and K-means algorithms, called PSO-SA-K, which can find better cluster partition. The performance is evaluated through several benchmark data sets. The simulation results show that the proposed algorithm outperforms previous approaches, such as PSO, SA and K-means for partitional clustering problem.

Extracting Road Signs using the Color Information

In this paper, we propose a method to extract the road signs. Firstly, the grabbed image is converted into the HSV color space to detect the road signs. Secondly, the morphological operations are used to reduce noise. Finally, extract the road sign using the geometric property. The feature extraction of road sign is done by using the color information. The proposed method has been tested for the real situations. From the experimental results, it is seen that the proposed method can extract the road sign features effectively.

Optimization of Petroleum Refinery Configuration Design with Logic Propositions

This work concerns the topological optimization problem for determining the optimal petroleum refinery configuration. We are interested in further investigating and hopefully advancing the existing optimization approaches and strategies employing logic propositions to conceptual process synthesis problems. In particular, we seek to contribute to this increasingly exciting area of chemical process modeling by addressing the following potentially important issues: (a) how the formulation of design specifications in a mixed-logical-and-integer optimization model can be employed in a synthesis problem to enrich the problem representation by incorporating past design experience, engineering knowledge, and heuristics; and (b) how structural specifications on the interconnectivity relationships by space (states) and by function (tasks) in a superstructure should be properly formulated within a mixed-integer linear programming (MILP) model. The proposed modeling technique is illustrated on a case study involving the alternative processing routes of naphtha, in which significant improvement in the solution quality is obtained.

Toward Integrative Stormwater Design in Urban Spaces

The design requirements for successful human accommodation in urban spaces are well known; and the range of facilities available for meeting urban water quality and quantity requirements is also well established. Their competing requirements must be reconciled in order for urban spaces to be successful for both. This paper outlines the separate human and water imperatives and their interactions in urban spaces. Stormwater management facilities- relative potential contributions to urban spaces are contrasted, and design choices for achieving those potentials are described. This study uses human success of urban space as the evaluative criterion of stormwater amenity: human values call on stormwater facilities to contribute to successful human spaces. Placing water-s contribution under the overall idea of successful urban space is an evolution from previous subjective evaluations. The information is based on photographs and notes from approximately 1,000 stormwater facilities and urban sites collected during the last 35 years in North America and overseas, and the author-s experience on multi-disciplinary design teams. This conceptual study combines the disciplinary roles of engineering, landscape architecture, and sociology in effecting successful urban design.

Factors Influence Depositors- Withdrawal Behavior in Islamic Banks: A Theory of Reasoned Action

Unlike its conventional counterpart, Islamic principles forbid Islamic banks to take any interest-related income and thus makes deposits from depositors as an important source of fund for its operational and financing. Consequently, the risk of deposit withdrawal by depositors is an important aspect that should be wellmanaged in Islamic banking. This paper aims to investigate factors that influence depositors- withdrawal behavior in Islamic banks, particularly in Malaysia, using the framework of theory of reasoned action. A total of 368 respondents from Klang valley are involved in the analysis. The paper finds that all the constructs variable i.e. normative beliefs, subjective norms, behavioral beliefs, and attitude towards behavior are perceived to be distinct by the respondents. In addition, the structural equation model is able to verify the structural relationships between subjective norms, attitude towards behavior and behavioral intention. Subjective norms gives more influence to depositors- decision on deposit withdrawal compared to attitude towards behavior.

Multi-board Run-time Reconfigurable Implementation of Intrinsic Evolvable Hardware

A multi-board run-time reconfigurable (MRTR) system for evolvable hardware (EHW) is introduced with the aim to implement on hardware the bidirectional incremental evolution (BIE) method. The main features of this digital intrinsic EHW solution rely on the multi-board approach, the variable chromosome length management and the partial configuration of the reconfigurable circuit. These three features provide a high scalability to the solution. The design has been written in VHDL with the concern of not being platform dependant in order to keep a flexibility factor as high as possible. This solution helps tackling the problem of evolving complex task on digital configurable support.

Comparative Study of Fault Identification and Classification on EHV Lines Using Discrete Wavelet Transform and Fourier Transform Based ANN

An appropriate method for fault identification and classification on extra high voltage transmission line using discrete wavelet transform is proposed in this paper. The sharp variations of the generated short circuit transient signals which are recorded at the sending end of the transmission line are adopted to identify the fault. The threshold values involve fault classification and these are done on the basis of the multiresolution analysis. A comparative study of the performance is also presented for Discrete Fourier Transform (DFT) based Artificial Neural Network (ANN) and Discrete Wavelet Transform (DWT). The results prove that the proposed method is an effective and efficient one in obtaining the accurate result within short duration of time by using Daubechies 4 and 9. Simulation of the power system is done using MATLAB.

Strong Limit Theorems for Dependent Random Variables

In This Article We establish moment inequality of dependent random variables,furthermore some theorems of strong law of large numbers and complete convergence for sequences of dependent random variables. In particular, independent and identically distributed Marcinkiewicz Law of large numbers are generalized to the case of m0-dependent sequences.

FPGA Implementation of a Vision-Based Blind Spot Warning System

Vision-based intelligent vehicle applications often require large amounts of memory to handle video streaming and image processing, which in turn increases complexity of hardware and software. This paper presents an FPGA implement of a vision-based blind spot warning system. Using video frames, the information of the blind spot area turns into one-dimensional information. Analysis of the estimated entropy of image allows the detection of an object in time. This idea has been implemented in the XtremeDSP video starter kit. The blind spot warning system uses only 13% of its logic resources and 95k bits block memory, and its frame rate is over 30 frames per sec (fps).

Resource Discovery in Web-Services Based Grids

A Web-services based grid infrastructure is evolving to be readily available in the near future. In this approach, the Web services are inherited (encapsulated or functioned) into the same existing Grid services class. In practice there is not much difference between the existing Web and grid infrastructure. Grid services emerged as stateful web services. In this paper, we present the key components of web-services based grid and also how the resource discovery is performed on web-services based grid considering resource discovery, as a critical service, to be provided by any type of grid.