AI Applications to Metal Stamping Die Design– A Review

Metal stamping die design is a complex, experiencebased and time-consuming task. Various artificial intelligence (AI) techniques are being used by worldwide researchers for stamping die design to reduce complexity, dependence on human expertise and time taken in design process as well as to improve design efficiency. In this paper a comprehensive review of applications of AI techniques in manufacturability evaluation of sheet metal parts, die design and process planning of metal stamping die is presented. Further the salient features of major research work published in the area of metal stamping are presented in tabular form and scope of future research work is identified.

Edit Distance Algorithm to Increase Storage Efficiency of Javanese Corpora

Since the one-to-one word translator does not have the facility to translate pragmatic aspects of Javanese, the parallel text alignment model described uses a phrase pair combination. The algorithm aligns the parallel text automatically from the beginning to the end of each sentence. Even though the results of the phrase pair combination outperform the previous algorithm, it is still inefficient. Recording all possible combinations consume more space in the database and time consuming. The original algorithm is modified by applying the edit distance coefficient to improve the data-storage efficiency. As a result, the data-storage consumption is 90% reduced as well as its learning period (42s).

Organizational De-Evolution; the Small Group or Single Actor Terrorist

Traditionally, terror groups have been formed by ideologically aligned actors who perceive a lack of options for achieving political or social change. However, terrorist attacks have been increasingly carried out by small groups of actors or lone individuals who may be only ideologically affiliated with larger, formal terrorist organizations. The formation of these groups represents the inverse of traditional organizational growth, whereby structural de-evolution within issue-based organizations leads to the formation of small, independent terror cells. Ideological franchising – the bypassing of formal affiliation to the “parent" organization – represents the de-evolution of traditional concepts of organizational structure in favor of an organic, independent, and focused unit. Traditional definitions of dark networks that are issue-based include focus on an identified goal, commitment to achieving this goal through unrestrained actions, and selection of symbolic targets. The next step in the de-evolution of small dark networks is the miniorganization, consisting of only a handful of actors working toward a common, violent goal. Information-sharing through social media platforms, coupled with civil liberties of democratic nations, provide the communication systems, access to information, and freedom of movement necessary for small dark networks to flourish without the aid of a parent organization. As attacks such as the 7/7 bombings demonstrate the effectiveness of small dark networks, terrorist actors will feel increasingly comfortable aligning with an ideology only, without formally organizing. The natural result of this de-evolving organization is the single actor event, where an individual seems to subscribe to a larger organization-s violent ideology with little or no formal ties.

Reconstitute Information about Discontinued Water Quality Variables in the Nile Delta Monitoring Network Using Two Record Extension Techniques

The world economic crises and budget constraints have caused authorities, especially those in developing countries, to rationalize water quality monitoring activities. Rationalization consists of reducing the number of monitoring sites, the number of samples, and/or the number of water quality variables measured. The reduction in water quality variables is usually based on correlation. If two variables exhibit high correlation, it is an indication that some of the information produced may be redundant. Consequently, one variable can be discontinued, and the other continues to be measured. Later, the ordinary least squares (OLS) regression technique is employed to reconstitute information about discontinued variable by using the continuously measured one as an explanatory variable. In this paper, two record extension techniques are employed to reconstitute information about discontinued water quality variables, the OLS and the Line of Organic Correlation (LOC). An empirical experiment is conducted using water quality records from the Nile Delta water quality monitoring network in Egypt. The record extension techniques are compared for their ability to predict different statistical parameters of the discontinued variables. Results show that the OLS is better at estimating individual water quality records. However, results indicate an underestimation of the variance in the extended records. The LOC technique is superior in preserving characteristics of the entire distribution and avoids underestimation of the variance. It is concluded from this study that the OLS can be used for the substitution of missing values, while LOC is preferable for inferring statements about the probability distribution.

Device for 3D Analysis of Basic Movements of the Lower Extremity

This document details the process of developing a wireless device that captures the basic movements of the foot (plantar flexion, dorsal flexion, abduction, adduction.), and the knee movement (flexion). It implements a motion capture system by using a hardware based on optical fiber sensors, due to the advantages in terms of scope, noise immunity and speed of data transmission and reception. The operating principle used by this system is the detection and transmission of joint movement by mechanical elements and their respective measurement by optical ones (in this case infrared). Likewise, Visual Basic software is used for reception, analysis and signal processing of data acquired by the device, generating a 3D graphical representation in real time of each movement. The result is a boot in charge of capturing the movement, a transmission module (Implementing Xbee Technology) and a receiver module for receiving information and sending it to the PC for their respective processing. The main idea with this device is to help on topics such as bioengineering and medicine, by helping to improve the quality of life and movement analysis.

Digital Power Management Hardware Realization Using FPGA

This paper describes design of a digital feedback loop for a low switching frequency dc-dc switching converters. Low switching frequencies were selected in this design. A look up table for the digital PID (proportional integrator differentiator) compensator was implemented using Altera Stratix II with built-in ADC (analog-to-digital converter) to achieve this hardware realization. Design guidelines are given for the PID compensator, high frequency DPWM (digital pulse width modulator) and moving average filter.

Assessing Nutrient Concentration and Trophic Status of Brahma Sarover at Kurukshetra, India

Eutrophication of surface water is one of the most widespread environmental problems at present. Large number of pilgrims and tourists visit sacred artificial tank known as “Brahma Sarover” located at Kurukshetra, India to take holy dip and perform religious ceremonies. The sources of pollutants include impurities in feed water, mass bathing, religious offerings and windblown particulate matter. Studies so far have focused mainly on assessing water quality for bathing purpose by using physico-chemical and bacteriological parameters. No effort has been made to assess nutrient concentration and trophic status of the tank to take more appropriate measures for improving water quality on long term basis. In the present study, total nitrogen, total phosphorous and chlorophyll a measurements have been done to assess the nutrient level and trophic status of the tank. The results show presence of high concentration of nutrients and Chlorophyll a indicating mesotrophic and eutrophic state of the tank. Phosphorous has been observed as limiting nutrient in the tank water.

On-Line Geometrical Identification of Reconfigurable Machine Tool using Virtual Machining

One of the main research directions in CAD/CAM machining area is the reducing of machining time. The feedrate scheduling is one of the advanced techniques that allows keeping constant the uncut chip area and as sequel to keep constant the main cutting force. They are two main ways for feedrate optimization. The first consists in the cutting force monitoring, which presumes to use complex equipment for the force measurement and after this, to set the feedrate regarding the cutting force variation. The second way is to optimize the feedrate by keeping constant the material removal rate regarding the cutting conditions. In this paper there is proposed a new approach using an extended database that replaces the system model. The feedrate scheduling is determined based on the identification of the reconfigurable machine tool, and the feed value determination regarding the uncut chip section area, the contact length between tool and blank and also regarding the geometrical roughness. The first stage consists in the blank and tool monitoring for the determination of actual profiles. The next stage is the determination of programmed tool path that allows obtaining the piece target profile. The graphic representation environment models the tool and blank regions and, after this, the tool model is positioned regarding the blank model according to the programmed tool path. For each of these positions the geometrical roughness value, the uncut chip area and the contact length between tool and blank are calculated. Each of these parameters are compared with the admissible values and according to the result the feed value is established. We can consider that this approach has the following advantages: in case of complex cutting processes the prediction of cutting force is possible; there is considered the real cutting profile which has deviations from the theoretical profile; the blank-tool contact length limitation is possible; it is possible to correct the programmed tool path so that the target profile can be obtained. Applying this method, there are obtained data sets which allow the feedrate scheduling so that the uncut chip area is constant and, as a result, the cutting force is constant, which allows to use more efficiently the machine tool and to obtain the reduction of machining time.

Improving the Effectiveness of Software Testing through Test Case Reduction

This paper proposes a new technique for improving the efficiency of software testing, which is based on a conventional attempt to reduce test cases that have to be tested for any given software. The approach utilizes the advantage of Regression Testing where fewer test cases would lessen time consumption of the testing as a whole. The technique also offers a means to perform test case generation automatically. Compared to one of the techniques in the literature where the tester has no option but to perform the test case generation manually, the proposed technique provides a better option. As for the test cases reduction, the technique uses simple algebraic conditions to assign fixed values to variables (Maximum, minimum and constant variables). By doing this, the variables values would be limited within a definite range, resulting in fewer numbers of possible test cases to process. The technique can also be used in program loops and arrays.

Compensation–Based Current Decomposition

This paper deals with the current space-vector decomposition in three-phase, three-wire systems on the basis of some case studies. We propose four components of the current spacevector in terms of DC and AC components of the instantaneous active and reactive powers. The term of supplementary useless current vector is also pointed out. The analysis shows that the current decomposition which respects the definition of the instantaneous apparent power vector is useful for compensation reasons only if the supply voltages are sinusoidal. A modified definition of the components of the current is proposed for the operation under nonsinusoidal voltage conditions.

Hopfield Network as Associative Memory with Multiple Reference Points

Hopfield model of associative memory is studied in this work. In particular, two main problems that it possesses: the apparition of spurious patterns in the learning phase, implying the well-known effect of storing the opposite pattern, and the problem of its reduced capacity, meaning that it is not possible to store a great amount of patterns without increasing the error probability in the retrieving phase. In this paper, a method to avoid spurious patterns is presented and studied, and an explanation of the previously mentioned effect is given. Another technique to increase the capacity of a network is proposed here, based on the idea of using several reference points when storing patterns. It is studied in depth, and an explicit formula for the capacity of the network with this technique is provided.

A Reconfigurable Processing Element Implementation for Matrix Inversion Using Cholesky Decomposition

Fixed-point simulation results are used for the performance measure of inverting matrices using a reconfigurable processing element. Matrices are inverted using the Cholesky decomposition algorithm. The reconfigurable processing element is capable of all required mathematical operations. The fixed-point word length analysis is based on simulations of different condition numbers and different matrix sizes.

On-line Image Mosaicing of Live Stem Cells

Image mosaicing is a technique that permits to enlarge the field of view of a camera. For instance, it is employed to achieve panoramas with common cameras or even in scientific applications, to achieve the image of a whole culture in microscopical imaging. Usually, a mosaic of cell cultures is achieved through using automated microscopes. However, this is often performed in batch, through CPU intensive minimization algorithms. In addition, live stem cells are studied in phase contrast, showing a low contrast that cannot be improved further. We present a method to study the flat field from live stem cells images even in case of 100% confluence, this permitting to build accurate mosaics on-line using high performance algorithms.

Thermal Analysis of a Sliding Electric Contact System Using Finite Element Method

In this paper a three dimensional thermal model of a sliding contact system is proposed for both steady-state or transient conditions. The influence of contact force, electric current and ambient temperature on the temperature distribution, has been investigated. A thermal analysis of the different type of the graphite material of fixed electric contact and its influence on contact system temperature rise, has been performed. To validate the three dimensional thermal model, some experimental tests have been done. There is a good correlation between experimental and simulation results.

Application of Femtosecond Laser pulses for Nanometer Accuracy Profiling of Quartz and Diamond Substrates and for Multi-Layered Targets and Thin-Film Conductors Processing

Research results and optimal parameters investigation of laser cut and profiling of diamond and quartz substrates by femtosecond laser pulses are presented. Profiles 10 μm in width, ~25 μm in depth and several millimeters long were made. Investigation of boundaries quality has been carried out with the use of AFM «Vecco». Possibility of technological formation of profiles and micro-holes in diamond and quartz substrates with nanometer-scale boundaries is shown. Experimental results of multilayer dielectric cover treatment are also presented. Possibility of precise upper layer (thickness of 70–140 nm) removal is demonstrated. Processes of thin metal film (60 nm and 350 nm thick) treatment are considered. Isolation tracks (conductance ~ 10-11 S) 1.6–2.5 μm in width in conductive metal layers are formed.

Efficient STAKCERT KDD Processes in Worm Detection

This paper presents a new STAKCERT KDD processes for worm detection. The enhancement introduced in the data-preprocessing resulted in the formation of a new STAKCERT model for worm detection. In this paper we explained in detail how all the processes involved in the STAKCERT KDD processes are applied within the STAKCERT model for worm detection. Based on the experiment conducted, the STAKCERT model yielded a 98.13% accuracy rate for worm detection by integrating the STAKCERT KDD processes.

Finding a Solution, all Solutions, or the Most Probable Solution to a Temporal Interval Algebra Network

Over the years, many implementations have been proposed for solving IA networks. These implementations are concerned with finding a solution efficiently. The primary goal of our implementation is simplicity and ease of use. We present an IA network implementation based on finite domain non-binary CSPs, and constraint logic programming. The implementation has a GUI which permits the drawing of arbitrary IA networks. We then show how the implementation can be extended to find all the solutions to an IA network. One application of finding all the solutions, is solving probabilistic IA networks.

Synthesis and Fluorescence Spectroscopy of Sulphonic Acid-Doped Polyaniline When Exposed to Oxygen Gas

Three sulphonic acid-doped polyanilines were synthesized through chemical oxidation at low temperature (0-5 oC) and potential of these polymers as sensing agent for O2 gas detection in terms of fluorescence quenching was studied. Sulphuric acid, dodecylbenzene sulphonic acid (DBSA) and camphor sulphonic acid (CSA) were used as doping agents. All polymers obtained were dark green powder. Polymers obtained were characterized by Fourier transform infrared spectroscopy, ultraviolet-visible absorption spectroscopy, thermogravimetry analysis, elemental analysis, differential scanning calorimeter and gel permeation chromatography. Characterizations carried out showed that polymers were successfully synthesized with mass recovery for sulphuric aciddoped polyaniline (SPAN), DBSA-doped polyaniline (DBSA-doped PANI) and CSA-doped polyaniline (CSA-doped PANI) of 71.40%, 75.00% and 39.96%, respectively. Doping level of SPAN, DBSAdoped PANI and CSA-doped PANI were 32.86%, 33.13% and 53.96%, respectively as determined based on elemental analysis. Sensing test was carried out on polymer sample in the form of solution and film by using fluorescence spectrophotometer. Samples of polymer solution and polymer film showed positive response towards O2 exposure. All polymer solutions and films were fully regenerated by using N2 gas within 1 hour period. Photostability study showed that all samples of polymer solutions and films were stable towards light when continuously exposed to xenon lamp for 9 hours. The relative standard deviation (RSD) values for SPAN solution, DBSA-doped PANI solution and CSA-doped PANI solution for repeatability were 0.23%, 0.64% and 0.76%, respectively. Meanwhile RSD values for reproducibility were 2.36%, 6.98% and 1.27%, respectively. Results for SPAN film, DBSAdoped PANI film and CSA-doped PANI film showed the same pattern with RSD values for repeatability of 0.52%, 4.05% and 0.90%, respectively. Meanwhile RSD values for reproducibility were 2.91%, 10.05% and 7.42%, respectively. The study on effect of the flow rate on response time was carried out using 3 different rates which were 0.25 mL/s, 1.00 mL/s and 2.00 mL/s. Results obtained showed that the higher the flow rate, the shorter the response time.

A Double Referenced Contrast for Blind Source Separation

This paper addresses the problem of blind source separation (BSS). To recover original signals, from linear instantaneous mixtures, we propose a new contrast function based on the use of a double referenced system. Our approach assumes statistical independence sources. The reference vectors will be incrusted in the cumulant to evaluate the independence. The estimation of the separating matrix will be performed in two steps: whitening observations and joint diagonalization of a set of referenced cumulant matrices. Computer simulations are presented to demonstrate the effectiveness of the suggested approach.

Prediction of Optimum Cutting Parameters to obtain Desired Surface in Finish Pass end Milling of Aluminium Alloy with Carbide Tool using Artificial Neural Network

End milling process is one of the common metal cutting operations used for machining parts in manufacturing industry. It is usually performed at the final stage in manufacturing a product and surface roughness of the produced job plays an important role. In general, the surface roughness affects wear resistance, ductility, tensile, fatigue strength, etc., for machined parts and cannot be neglected in design. In the present work an experimental investigation of end milling of aluminium alloy with carbide tool is carried out and the effect of different cutting parameters on the response are studied with three-dimensional surface plots. An artificial neural network (ANN) is used to establish the relationship between the surface roughness and the input cutting parameters (i.e., spindle speed, feed, and depth of cut). The Matlab ANN toolbox works on feed forward back propagation algorithm is used for modeling purpose. 3-12-1 network structure having minimum average prediction error found as best network architecture for predicting surface roughness value. The network predicts surface roughness for unseen data and found that the result/prediction is better. For desired surface finish of the component to be produced there are many different combination of cutting parameters are available. The optimum cutting parameter for obtaining desired surface finish, to maximize tool life is predicted. The methodology is demonstrated, number of problems are solved and algorithm is coded in Matlab®.