Electromagnetic Scan Research Articles

AYARLANABİLİR RADYO FREKANS (RF) ALICI (RX) ENTEGRE DEVRE (IC)

In this work tunable radio frequency (RF) receiver (Rx) integrated circuit (IC) was demonstrated. TSMC 65 nm technology node was selected to implement IC. RF technique has some advantages over biomedical optic molecule investigation methods since it is easy to design, implement. Experimental measurement on live tissue is much easier than optic methods. Nanoscopic creatures have specific binding structures. Their elements construct their shapes and neighborhood conformation between their own atoms. Based on this work differential RF waves will be used to investigate the nanoscopic creatures. Since the investigation of nanoscopic creatures will require to use electromagnetic wave phase shift and scan of different RF frequencies, ultra-wide band (UWB) tunable receiver circuit topology was designed and simulated. For this purpose, Rx block was designed, and simulation work was demonstrated here. In the circuit simulations, off-chip antenna was connected to the low-noise amplifier (LNA) circuit. Specific frequency was around 30 GHz. Frequency tuning was adjusted by changing the source and bias voltages at the active inductor voltage-controlled oscillator (VCO) circuit block. The same VCO block was also used at the Tx circuit before. Antenna signal was modeled by using 33 GHz alternative sinusoidal signal. Antenna signal and 30 GHz active-inductor VCO voltage output were mixed at the mixer circuit block, 3 GHz envelope signal was extracted in this work. Layout implementation of Rx receiver IC was demonstrated.

EMI Prediction of Slew-Rate Controlled I/O Buffers by Full-Wave and Circuit Co-Simulation

In this paper, a modeling and co-simulation methodology is proposed to predict the radiated electromagnetic interference (EMI) from on-chip switching I/O buffers. The output waveforms of I/O buffers are simulated including the on-chip I/O buffer circuit and the RC extracted on-chip interconnect netlist, package, and printed circuit board (PCB). In order to accurately estimate the EMI, a full-wave 3D simulation is performed including the measurement environment. The simulation results are compared with near-field electromagnetic scan results and farfield measurements from an anechoic chamber, and the sources of emission peaks were analyzed. For accurate far-field EMI simulation, PCB power trace models considering IC switching current paths and external power cable models must be considered for accurate EMI prediction. With the proposed EMI simulation model and flow, the electromagnetic compatibility can be tested even before the IC is

A New Circuit Detection Method and an Anomalous Frequency Recognition Algorithm

The characteristics of the high-density circuits are high assembly density of the components and complex functions. It is difficult to detect the electrical defects by the existing optical techniques. The Electromagnetic Scan (EMScan) technology as a new detection method was introduced into the high-density circuit detection. For the new approach, the EMScan process was designed and its key techniques were analyzed. Meanwhile the corresponding recognition algorithm was given toward one of the key techniques determining the anomalous frequencies. The spectrums of the circuit board were transformed into a series of strings. Then according to the string comparison algorithm, the anomalous frequencies were determined. The experimental results show that it is feasible to apply the EMScan into the high-density circuit detection. The recognition algorithm is effective and can determine the anomalous frequencies accurately by this way.

Diagnosis of Bladder Cancer at 465 MHz

Current methods for bladder cancer investigation involve cystoscopy, ultrasound scanning, and contrast urography, with additional information provided by cytology. These methods, although having a high detection rate, are expensive, time-consuming, invasive, and uncomfortable. Therefore, there is a need for an inexpensive, non invasive, quick, and simple investigation with a high sensitivity and specificity. In this study we evaluate the use of an in vivo electromagnetic (EM) interaction as a non invasive method for detecting cancer. A clinical trial was designed and completed. The main trial target was the feasibility assessment of the novel method by comparing its results with standard cystoscopy. A physical discussion of the EM interaction with bladder cancer tissue is presented. One hundred and fourteen patients referred for cystoscopy by microscopic or gross haematuria, irritative voiding symptoms, or suspected bladder tumor at ultrasound were first submitted to EM scan by means of the TRIMprob™ system. Cystoscopy was performed on each patient after the TRIMprob™ examination. Comparison between EM and cystoscopy results provides a high level of agreement (Cohen's K = 0.77, p < 0.001). The TRIMprob™ performance in malignant cancer cells detection suggests that this in vivo EM waves method is also worth investigating for routine diagnostic procedures.

Pork carcass composition derived from a neural network model of electromagnetic scans.

We used an advanced computer logic system (NETS 3.0) to decipher electromagnetic (EM) scans in lieu of traditional linear regression for estimation of pork carcass composition. Fifty EM scans of pork carcasses were obtained on-line (prerigor) at a swine slaughter facility. Right sides were cut into wholesale parts and dissected into fat, lean, and bone to obtain total dissected carcass and primal cut lean. In this study, the input layer consisted of 81 nodes (80-point EM scan curve and warm carcass weight), one hidden layer of 42 nodes, and an output layer consisting of one node, which were run separately for outputs of ham, loin, or shoulder lean. The hidden layer connected to the output of total lean contained 50 nodes. Thirty-five scans were used for training of the network. The new network was then tested with 15 previously unseen input/output pairs. Separate neural networks were developed for the estimation of dissected total carcass, ham, loin, and shoulder lean. The NETS configuration improved on linear regression equations for estimation of total carcass lean by .31 kg, ham lean by .284 kg, and shoulder lean by .148 kg. Our results show that advanced computer logic systems have the capacity to improve upon traditional linear regression equations for prediction of pork carcass composition.

Prediction of live lamb chemical composition utilizing electromagnetic scanning (ToBEC).

Electromagnetic scanning was investigated to determine its accuracy in predicting chemical composition in live lambs. Forty-seven Rambouillet wether lambs were scanned with an electromagnetic instrument (ToBEC Model HA-2). Lambs were serially scanned and slaughtered over the weight range of 29.5 to 63.5 kg. Each lamb was scanned twice: before and immediately after 24 h of food deprivation. Chemical composition was determined from whole-animal ground samples by AOAC methods for percentage of DM, CP, ether extract (EE), and Ash. Percentage of fat-free mass (FFM) was calculated from the percentage of moisture and CP. Correlation and stepwise regression procedures were used to identify the most reliable independent variables for predicting chemical composition. Independent variables included electromagnetic scan data and live animal measures for weight, body length, and chest girth circumference. Electromagnetic data included the average scan response curve (PH0) and Fourier transformations (P1T, P1R, P2T, and P2R). Repeatability of the HA-2 model was extremely high (r = .98). Reliable prediction equations were obtained for DM, CP, EE, and FFM (R2 > .66). The percentage of ash could not be predicted from the independent variables. Electromagnetic scan responses contributed little to the model sum of squares. Body weight accounted for the majority of the model sum of squares. Depriving lambs of food for 24 h slightly improved the R2 value and significantly decreased scan responses (P < .01). Body weight was a better predictor of chemical composition over a large weight range than any of the scan responses. Further investigation of the HA-2 is needed to determine whether it is effective in determining differences in live body composition between animals of equal weight.

Electromagnetic scanning of beef quarters to predict carcass and primal lean content.

To study the use of electromagnetic scanning in prediction of lean content in beef carcasses and cuts, 100 beef cattle (60 steers and 40 heifers), representing a broad range in external fat thickness (.1 to 2.9 cm) and live weight (414 to 742 kg), were selected. Chilled right sides were divided into streamlined (foreshank, brisket, and ventral plate removed) forequarters (FQ) and full hindquarters (HQ) and scanned. Primal rounds, loins, ribs, and chucks were fabricated from the right side, scanned, and physically separated into lean, fat, and bone. Prediction equations for dissected lean content and percentage of lean included the peak of the electromagnetic scan response curve (obtained from scanning the HQ or FQ), length, temperature and weight of the scanned cut, and fat thickness at the 12th rib. Using the coefficient of determination, root mean square error, and Mallows' Cp statistic, the best model for each dependent variable (weight and percentage of lean) that included up to five independent variables was selected. Prediction equations for the HQ or FQ of steers accounted for 84 to 93% of the variation in lean weight of beef sides and quarters and 71 to 93% of primals. Sixty-one to 75% of the variation in percentage of lean in sides and quarters and 48 to 65% of primals was also explained. Similar results were obtained for heifer carcasses. Predicting percentage of lean in any scanned cut, rather than weight of lean, accounted for less of the variation. Weight and fat thickness contributed significantly when predicting percentage of lean.(ABSTRACT TRUNCATED AT 250 WORDS)

Electromagnetic scanning of pork carcasses in an on-line industrial configuration.

The objective of this study was to test and validate electromagnetic scanning of whole pork carcasses in an on-line, integrated, industrial configuration. The electromagnetic (EM) scanner was installed in two pork processing facilities (Plant A and Plant B). Plant A was a small pork fabrication plant that further processed chilled pork carcasses. Carcasses were delivered to Plant A by refrigerated trucks. The amount of EM energy absorbed by the carcasses was recorded as they were conveyed through the EM field. A plot of the absorption units over time (EM scan curve) was used to obtain predictive variables for estimating carcass and primal cut composition. Forty-eight whole, chilled carcasses (Group A) were electromagnetically scanned and conveyed onto the fabrication line. The average percentage carcass lean for Group A was 49.1% (range = 36.5 to 59.5%). Right carcass sides were removed from the processing line, fabricated into primal cuts, and dissected into fat, lean, and bone. Prediction equations were developed from EM scans for weight of total dissected carcass lean (R2 = .830; root mean square error = 1.80 kg), percentage of carcass lean (R2 = .820; root mean square error = 2.29%), and weight of dissected ham, longissimus muscle, and shoulder lean. In Plant B, the electromagnetic scanner was installed at the end of a pork slaughter line to ensure carcass scanning at a consistent carcass temperature. Fifty whole, pre-rigor eviscerated carcasses (Group B) were electromagnetically scanned before entering the chill cooler where fat and loin tissue depths were obtained by an optical grading probe. The average percentage carcass lean for Group B was 46.7% (range = 30.1 to 57.3%). Prediction equations were developed from EM scans for weight of total dissected carcass lean (R2 = .904; root mean square error = 1.59 kg), percentage of carcass lean (R2 = .863; root mean square error = 2.05%), and weight of dissected ham, loin, and shoulder lean. Statistical equations developed for the prediction of dissected primal cut lean were superior from EM scans of Group B (prerigor) carcasses. Electromagnetic scanning proved more statistically efficient than optical probes for predicting weight of dissected carcass lean and percentage of carcass lean. Statistical comparison of EM scan equations from Groups A and B are not completely valid because two different populations of carcasses were tested at different times of the year. The results of this study show that EM scanning has the potential to accurately predict pork carcass composition in a fully automated, on-line industrial configuration.

Analysis of environmental samples by spark source mass spectrometry—I. Trace elements in water

Spark source mass spectrometry is ideally suited to the determination of trace elements in natural waters. In the work described, almost all of the elements present in lake or river waters at concentrations of one part in 1011 parts of water and higher were routinely determined. In the particular waters investigated 30 or more elements were found in each sample.The main features of the procedure were freeze-drying for sample preconcentration, low temperature oxygen plasma ashing to eliminate organic ion interferences, sample presentation to the mass spectrometer in counter-electrodes tipped with a homogeneous conducting ashcarbon mixture, and newly-perfected electrical detection and measurement of the mass-resolved ion beams.Precisions achieved for individual elements in a rapid 10 min electromagnetic scan from mass number 238 down to mass number 7 averaged ± 30 per cent. Using the electrostatic peak switching mode and the expenditure of considerably more time, precisions of better than 5% were possible. Accuracy is dependent upon the availability of suitable calibration standards and upon the concentration range of the particular elements determined.