Abstract: Using training data, machine learning is performed to construct a learning model which is a non-linear function for discrimination or regression analysis (S2). A degree of contribution of each input dimension is calculated from a partial differential value of that function. Input dimensions to be invalidated are determined using a threshold defined by a Gaussian distribution function based on the degrees of contribution (S3-S5). Machine learning is once more performed using the training data with the partially-invalidated input dimensions (S6). A new value of the degree of contribution of each input dimension is determined from the obtained learning model, and the degree of contribution is updated using the old and new values (S7-S8). After the processes of Steps S5-S8 are iterated a specified number of times (S9), useful dimensions are determined based on the finally obtained degrees of contribution, and the machine-learning model is constructed (S10).

Abstract: Provided is a CdZnTe monocrystalline substrate which has a small leakage current even when a voltage is applied from a low voltage to a high voltage, and which has a lower variation in resistivity with respect to applied voltage changes from 0 to 900 V, and which can maintain a stable resistivity. A semiconductor wafer comprising a cadmium zinc telluride monocrystal having a zinc concentration of 4.0 at % or more and 6.5 at % or less and a chlorine concentration of 0.1 ppm by weight or more and 5.0 ppm by weight or less, wherein when a voltage is applied in a range of from 0 to 900 V, the semiconductor wafer has a resistivity for each applied voltage value of 1.0×107 ?cm or more and 7.0×108 ?cm or less, and wherein a relative variation coefficient of each resistivity to the applied voltages in a range of from 0 to 900 V is 100% or less.

Abstract: A sample measurement device includes a measurement unit (1) configured to measure a sample, and a controller (2) configured to analyze a measurement result of the measurement unit. The controller (2) is configured to estimate and acquire a measurement result under another measurement condition using a model formula based on measurement results under a plurality of measurement conditions with different measurement parameter conditions, and estimate a distribution of a measurement quality indicator with respect to a measurement parameter based on the estimated measurement result.

Abstract: In this photoelectric conversion element wherein group III-IV compound semiconductor single crystals containing zinc as an impurity are used as a substrate, the substrate is increased in size without lowering conversion efficiency. A heat-resistant crucible is filled with raw material and a sealant, and the raw material and sealant are heated, thereby melting the raw material into a melt, softening the encapsulant, and covering the melt from the top with the encapsulant. The temperature inside the crucible is controlled such that the temperature of the top of the encapsulant relative to the bottom of the encapsulant becomes higher in a range that not equal or exceed the temperature of bottom of the encapsulant, and seed crystal is dipped in the melt and pulled upward with respect to the melt, thereby growing single crystals from the seed crystal.

Abstract: A series of processes of dividing given labeled teacher data into model construction data and model verification data, constructing a machine learning model using the model construction data, and applying the model to the model verification data to identify (label) a sample is repeated multiple times (S2 to S5). Although the machine learning model to be constructed changes when the model construction data changes, an accurate identification can be made with a high probability. Thus, there is a high possibility that an original label and an identification result do not coincide in a mislabeled sample, resulting in misidentification. If the number of misidentifications is counted for each sample to obtain a misidentification rate, the mislabeled sample is identified based on the misidentification rate since the misidentification rate is relatively high in the mislabeled sample (S6 to S7).

Abstract: The present disclosure provides methods for analyzing data to be analyzed by an analysis program using an analysis parameter.

Abstract: Provided is a large diameter InP single crystal substrate having a diameter of 75 mm or more, which can achieve a high electrical activation rate of Zn over a main surface of the substrate even in a highly doped region having a Zn concentration of 5×1018 cm?3 or more; and a method for producing the same. An InP single crystal ingot is cooled such that a temperature difference of 200° C. is decreased for 2 to 7.5 minutes, while rotating the InP single crystal ingot at a rotation speed of 10 rpm or less, and the cooled InP single crystal ingot is cut into a thin plate, thereby allowing production of the InP single crystal substrate having an electrical activation rate of Zn of more than 85% over the main surface of the substrate even in a highly doped region having a Zn concentration of 5×1018 cm?3 or more.

Abstract: Provided is a radiation detection element, including: a plurality of electrode portions on a surface of a substrate; and an insulating portion between the electrode portions, the substrate being made of a compound semiconductor crystal containing cadmium telluride or cadmium zinc telluride, wherein an intermediate layer containing tellurium oxide is present between each of the electrode portions and the substrate, and wherein the tellurium oxide layer has a thickness of 100 nm or less on a 500 nm inner side from an end portion of the insulating portion between the electrode portions. The radiation detection element has higher adhesion of the electrodes, and does not result in an element performance defect caused by insufficient insulation between the electrodes, even if the radiation detection element has a narrower distance between the electrode portions in order to obtain a high-definition radiographic image.

Abstract: Wavelength spectrums of peaks detected on a chromatogram based on observation data to be processed are extracted to create a spectrum set {Sn?} in which the intensity values of the spectrums are normalized (S10, S11). One wavelength spectrum is selected from the set, and a vector of the wavelength spectrum at each point in time of measurement based on the observation data is projected so as to be perpendicular to the vector of the selected spectrum (S12 to S14). The vectors of the wavelength spectrums in the set {Sn? } are also similarly projected (S15). Consequently, the selected spectrum is erased from the set {Sn?}. The processes from S12 to S16 are repeated until the set {Sn? } does not include a spectrum, and the obtained signals are added (S17). The signal resulting from the addition is a signal indicating the waveform shape of an unknown baseline.

Abstract: Provided is a pump monitoring device for detecting abnormalities of multiple vacuum pumps connected to the same chamber, the pump monitoring device being configured to estimate occurrence of the abnormality at any of the multiple vacuum pumps based on a comparison result of signals indicating rotation states of pump rotors of the multiple vacuum pumps.

Abstract: Provided are a high resistance CdTe-based compound single crystal with miniaturized Te precipitates and a method for producing the same. According to one embodiment of the present invention, a CdTe based compound single crystal is provided including a precipitate having a particle size of less than 0.1 ?m obtained from an analysis by a light scattering tomography method. In the CdTe based compound single crystal, resistivity may be 1×107 ?cm or more. In addition, in the CdTe based compound single crystal, a precipitate having a particle size of 0.1 ?m or more obtained from the analysis by the light scattering tomography method is not detected. In the CdTe based compound single crystal, the precipitate may be a Te precipitate.

Abstract: For vector A which expresses an absorption spectrum of a target component, vector F orthogonal to vector A is designated as a filter for extracting an impurity superposed on the target component on a chromatogram. For vector I which expresses a measured spectrum obtained by a chromatographic analysis performed on a sample, the inner product of vectors I and F is defined as an index value u of the amount of impurity. If an impurity is present, a peak-like waveform appears on a graph which shows a temporal change in the index value u for the measured spectrum obtained at each point in time of the measurement. By detecting this waveform, the presence or absence of the impurity can be correctly determined. The direction of vector F may be determined so that, when vector B which expresses a spectrum of the impurity is decomposed into vector Ba parallel to vector A and vector Bo orthogonal to vector A, vector F becomes nearly parallel to vector Bo (i.e. the cosine similarity index is maximized).

Abstract: The EM algorithm for a Gaussian mixture model is applied to the separation of peaks that overlap one another on a chromatogram. However, the number of overlapping components is unknown. Thus, a suitable number of models is set, and the fitting of model parameters is performed while an actually measured signal is appropriately divided for each model by the EM algorithm. Then, when a solution converges, a determination is made as to whether a peak-like waveform is present in a residue signal that is not divided. When the peak-like waveform is present, a peak model is added. The EM algorithm is executed again. In the M step, optimization is performed using, not only a simple Gaussian function, but also a modified Gaussian function assuming a tailing. In the M step, the estimation of a spectrum assuming a chromatogram and the estimation of a chromatogram assuming a spectrum are repeatedly performed.

Abstract: A method for setting, within an observed image of a sample, an analysis target region that is a region on which an analysis is to be performed by an analyzer, the method including displaying the observed image of the sample on the display, dividing the observed image into a plurality of divisional areas, calculating a predetermined image characteristic quantity in each of the plurality of divisional areas, designating at least two of the divisional areas of the observed image displayed on the display, calculating a distribution of the values of the image characteristic quantity of the designated divisional areas, determining a value range of the image characteristic quantity for the divisional areas to be extracted as the analysis target region, based on the calculated distribution, and extracting from the observed image each of the plurality of divisional areas having a value of the image characteristic quantity within the value range.

Abstract: An analysis data processing method for processing analysis data collected with an analyzing device for each of a plurality of samples, by applying an analytical technique using statistical machine learning to multidimensional analysis data formed by output values obtained from a plurality of channels of a multichannel detector provided in the analyzing device, the method including: acquiring a non-linear regression or non-linear discrimination function expressing analysis data obtained for known samples; calculating a contribution value of each of the output values obtained from the plurality of channels forming the analysis data of the known samples, to the acquired non-linear regression or non-linear discrimination function, based on a differential value of the non-linear regression function or non-linear discrimination function; and identifying one or more of the plurality of channels of the detector, which are to be used for processing analysis data obtained for an unknown sample, based on the contributio

Abstract: An upsampler 22 performs upsampling based on actual measurement data forming a profile spectrum obtained with a time-of-flight mass spectrometer 1, to insert interpolation data between the temporally adjacent actual measurement data and make the waveform smoother. Subsequently, a peak waveform processor 23 determines the centroid position, peak area or other relevant values by performing centroid processing which employs trapezoidal approximation or similar technique. The smoothing of the waveform between adjacent measurement data improves the accuracy of the centroid processing, whereby a systematic error in the estimation of the centroid position or calculation of the peak area is reduced. Therefore, even when the number of data points forming one peak on a measured waveform is small, the centroid position and other kinds of peak information can be obtained with a high level of accuracy, and the performance of qualitative or quantitative determination is thereby improved.

Abstract: For a signal waveform to be processed, the continuous wavelet transform is performed with various scale factors, and a wavelet coefficient at each point in time is calculated. On an image showing the strength of the wavelet coefficient with respect to the scale factor and time, ridge lines are detected, and based on these ridge lines, positive and negative peak candidates are extracted, after which an error in the position and width of the peak due to the influence of a neighboring peak is corrected. Subsequently, the degree of non-symmetry of the peak shape or other features are examined to remove false negative peaks due to negative peak artifacts. Subsequently, a true peak cluster, a false peak cluster resulting from the removal of high-frequency components of a high-frequency noise or other causes, and other kinds of peaks are identified, and the obtained result is used to remove false peaks.

Abstract: An UBM electrode structure body for a radiation detector and a radiation detector arranged with the UBM electrode structure body are provided for suppressing peeling and having high electrode adhesion. In addition, a manufacturing method of an UBM electrode structure body for a radiation detector and a manufacturing method of a radiation detector using the UBM electrode structure body are provided in which peeling does not occur during UBM structure formation, a solder bonding process or bonding of a signal line to a Pt layer. The UBM electrode structure body for a radiation detector of the present invention is arranged with a CdTe substrate or CdZnTe substrate and a Pt electrode layer arranged on the CdTe substrate or CdZnTe substrate, adhesion of the Pt electrode layer with respect to the CdTe substrate or the CdZnTe substrate being 0.5 N/cm or more.

Abstract: Wavelength spectrums of peaks detected on a chromatogram based on observation data to be processed are extracted to create a spectrum set in which the intensity values of the spectrums are normalized. One wavelength spectrum is selected from the set, and a vector of the wavelength spectrum at each point in time of measurement based on the observation data is projected so as to be perpendicular to the vector of the selected spectrum. The vectors of the wavelength spectrums in the set are also similarly projected. Consequently, the selected spectrum is erased from the set. The processes are repeated until the set does not include a spectrum, and the obtained signals are added. The signal resulting from the addition is a signal indicating the waveform shape of an unknown baseline.

Abstract: In a spectrum analysis apparatus, a controller controls selection of an adequate the correction device based on a plurality of corrected absorption spectra corrected by a plurality of correction devices acquired in advance for eliminating an effect of stray light.