50 results about "Stimulus detection" patented technology

Electronic toy receives control information via an input interface and stores the received control information in memory. The electronic toy includes at least one sensor for detecting an external stimulus applied to the toy, and control information is read out from the memory in response to an external stimulus detection signal generated by the sensor so that the electronic toy is controlled to perform a predetermined operation in accordance with the read-out control information. It is possible to readily renew operations that can be performed by the electronic toy, by, for example, downloading desired control information from a server via a communication line and then storing the desired control information in an internal memory of the toy.

The invention discloses an inspection and detection intelligent laboratory quality supervision management system. The system comprises a sample collection and circulation standard management system, adetection item, inspection standard, reagent and instrument equipment intelligent matching system, a laboratory environment condition monitoring and automatic adjustment system, an inspection and detection process video monitoring and identification comparison system, an inspection and detection theory and operation online training system, an inspection and detection data information collection study judgment system, an inspection report generation and transmission system, and an interactive inspection and detection information management system. The comprehensive supervision of a food detection process is realized; a management tool is provided for laboratory managers and national supervision departments; real-time online guidance and training are provided for detection personnel; and detection laboratories are prevented from issuing false reports. The vulnerabilities and deficiencies of an existing food quality safety inspection and detection monitoring system are overcome; and an efficient, intelligent and comprehensive information technology means is provided for food quality safety inspection and detection laboratory quality supervision management.

The invention relates to a method for detecting the total number of bacteria based on the fluorescent method of NADH, in particular to a novel method for rapidly detecting the total number of colon bacteria based on the fluorescent characteristic of the NADH in a colon bacteria cell and the stable-content characteristic of the NADH in the colon bacteria cell, which comprises the processes of extracting NADH in the colon bacteria cell, detecting the content of the NADH in the colon bacteria cell, detecting the fluorescent intensity of the NADH in the colon bacteria cell with a fluorescent spectrophotometer and rapidly detecting the total number of bacteria. The fluorescent detection limit of the NADH is 1 nM, and the content of the NADH ranges from 10 nM to 80 microns and keeps a favorable liner relationship (R = 0.9905) with the fluorescent intensity. The colon bacterial cell is obtained in a decentering way, the NADH in the colon bacteria cell is extracted in a Tris-HCl method, the fluorescent intensity of extracting solution of the NADH is extracted with the excitation wavelength of 342 nm and the emission wavelength of 461 nm, and the colon bacteria of 10 cfu / mL can be detected in one hour. The method adopts novel detection theory, has rapid detection speed and good repeatability, is sensitive and easy, is suitable for quantitatively detecting the number of colon bacteria in the fields of food sanitation and safety, environment detection, and the like, and can replace the traditional method for detecting the number of living cells.

A low-rate denial of service (LDoS) attack flow has an obvious periodical small-signal characteristic. By means of a small-signal detection theory, the invention provides an LDoS attack detection method based on a small-signal model. According to the LDoS attack detection method, the number of data packages reaching in certain time is counted through a structural characteristic value estimating matrix, the attack cycle of the LDoS is estimated, a statistic value is compared with a preset judgment characteristic value threshold for indicate differences between normal flow rate and mixed flow rate which includes the LDoS attack, and the differences serve as a basis for judging whether the LDoS attack exists or not. If the LDoS attack is judged to exist, the cycle value of the LDoS attack can be accurately calculated through the structural characteristic value estimating matrix. By means of the technical scheme, the LDoS attack can be effectively detected.

The invention belongs to the field of reverse engineering, in particular to a method for measuring a key point of a car frame based on coding points and computer vision. The method comprises the following steps of: sticking a digital three-dimensional coding mark point to a key position of the car frame, placing a cross target and a scale stuck with coding mark points near an object, and firstly acquiring pictures of the object to be measured in different directions by using a high-precision digital camera; calculating three-dimensional coordinates corresponding to certain pixel points of the mark point through the acquired pictures; and acquiring the coordinate information of the key point of the car frame by combining an algorithm through the acquired pictures and the three-dimensional coordinate information of the marker point so as to provide data basis for subsequent car frame matching. The method for measuring the key point of the car frame enriches the three-dimensional vision measurement basic theory, lays the foundation for the reverse engineering and the three-dimensional vision detection theory, and improves the manufacture level in China.

The invention relates to a code point and computer vision based method for measuring key points of a vehicle frame, belonging to the field of reverse engineering. The method comprises the steps of: pasting digital stereoscopic coding mark points to key positions of the vehicle frame, and placing a cross target pasted with the code mark points and a ruler near an object, wherein a high-precision digital camera is adopted; firstly, carrying out image acquisition on different directions of the objected to be measured; resolving the three-dimensional coordinates of certain pixel points of the mark points through the acquired images; and further obtaining the coordinate information of the key point of the vehicle frame though the acquired images and the three-dimensional coordinate information of the mark points by combining with an algorithm so as to provide data base for the subsequent vehicle frame matching. The algorithm provided by the invention for resolving the key points of the vehicle frame enriches the basic theory of three-dimensional vision measurement, provides a foundation for the reverse engineering and the three-dimensional vision detection theory and improves the level of the manufacture industry in China.

The invention discloses a method for detecting a transverse magnetic polarized field with multi-wire sources and transient electromagnetism. The method comprises the following steps: laying one or more pairs of grounding conductive wire sources on the ground, and emitting a bipolar step current with an opposite direction to the underground through three grounding electrodes by each pair of conductive wire sources. The electromagnetic field observation can be performed on an apparatus with a pair of grounding conductive wire sources in the axial and equatorial directions. The electromagnetic field observation can be performed on an apparatus with multiple pairs of grounding conductive wire sources radially. The space structure of the underground electrical target body is obtained by performing inversion interpretation on the measured data. According to the method for detecting the transverse magnetic polarized field with the multi-wire sources and the transient electromagnetism, important pushing effect on improving the detection theory of a transient electromagnetism multi-polarized field and the detection ability of the transient electromagnetism on a high-resistance target body is realized, and a solid foundation for achieving fine detection of mineral resources, oil and gas resources in a second deep space is laid.

Described is a system for improved electroencephalograph (EEG) rapid serial visual presentation (RSVP) target stimuli detection through visual attention distractor insertion. A first RSVP sequence is created comprising a set of image chips. The image chips are a combination of target images containing target events and non-target images containing comment events. A number of visual attention distractors to optimize target event detection is determined, and the determined number of visual attention distractors is inserted into the first RSVP sequence to generate a second RSVP sequence. The second RSVP sequence is reordered to generate a third RSVP sequence. The third RSVP sequence is presented to a user, and an EEG signal is received from the user. Finally, the EEG signal is decoded to identify a true target event via a P300 detection in the EEG signal.

The invention relates to the technical field of pipeline detection, and particularly relates to an experimental platform of a pipeline magnetic flux leakage detection theory. The experimental platform of the pipeline magnetic flux leakage detection theory comprises a bracket, a driving device, a travelling crane device and a magnetic flux leakage detection module, wherein the travelling crane device is driven to move along the bracket by the driving device, and the moving speed of the travelling crane device under the driving of the driving device can be adjusted; the magnetic flux leakage detection module is arranged on the travelling crane device, and the position of the magnetic flux leakage detection module relative to the travelling crane device can be adjusted; a to-be-tested piece placing space is formed on the bracket and below a moving area of the travelling crane device. According to the testing platform provided by the invention, the running speed and position of the travelling crane device can be precisely controlled, magnetic flux leakage signals are collected by the magnetic flux leakage detection module which is arranged on the travelling crane device, and collected data are used for analyzing and researching the relation between leakage magnetic field signals and defect sizes and assisting the development of an in-pipeline magnetic flux leakage detector.

The embodiment of the invention discloses an advanced detection method for a water-containing geologic structure of a tunnel, and relates to the technical field of tunnel engineering construction. Themethod can be used for detection theory study and engineering practice of the water-containing geologic structure of the tunnel to guide construction of the tunnel. The method comprises the steps ofconstructing a geologic model according to the specific variety of the water-containing geologic structure; arranging a laying-off circuit on the geologic model; receiving different geologic model condition parameters input by a user, and simulating different water-containing geologic structures; utilizing the laying-off circuit for laying off apparent resistivity values of the water-containing geologic structures under different condition parameters; drawing an apparent resistivity curve chart under the condition according to the apparent resistivity values; determining whether or not water is contained in a place in front of a working area of the tunnel according to the apparent resistivity curve chart. The method is suitable for detection forecasting and theory study analysis on the water-containing geologic structure of the place in front of the working area of the tunnel.

The invention relates to a simulated deep sea comprehensive experiment table provided with a bubble generator and a use method of the simulated deep sea comprehensive experiment table provided with the bubble generator. The simulated deep sea comprehensive experiment table provided with the bubble generator comprises a water tank system, a pressure-adjusting and pressure-maintaining system, a bubble generating system and a water tank pressure protecting system. The pressure-adjusting and pressure-maintaining system, the bubble generating system and the water tank pressure protecting system are not connected with each other and are all connected with the water tank system. The intensity of pressure in a water tank is adjusted to a set value by the pressure-adjusting and pressure-maintaining system, real-time adjustment is conducted, and long-time pressure maintenance is achieved; bubbles can be generated by the bubble generating system, wherein the size, the moving speed, the contained chemical components and the like of the bubbles are all controllable; the pressure of the water tank is controlled in a specialized range by the water tank pressure protecting system and the function of protection can be achieved. The simulated deep sea comprehensive experiment table provided with the bubble generator is mainly used for scientific research, the deep sea environment is simulated in a laboratory, pressure adjustment and pressure maintenance are achieved in real time, and the intensity of pressure at any depth in the deep sea can be simulated in the specialized range; meanwhile, the generated bubbles can simulate truly discharged bubbles at the bottom of the deep sea, and therefore the deep sea mine detection theory can be simulated in the laboratory.

The invention provides an electroencephalogram signal feature detection method based on hidden behaviors of consciousness conflicts and a system thereof. The method is based on a conflict monitoring theory in cognitive psychology, and because a conflict exists between hidden active consciousness and individual subconsciousness to irritants, activation of a cognitive conflict monitoring brain areais initiated, so that related electroencephalogram signal characteristics are generated. The method comprises the following steps: providing a psychological test stimulation material based on the conflict detection theory and a special operation reaction of the psychological test stimulation material; enhancing memory through target stimulation; constructing a guide language or a guide scene; testing a testee to obtain an electroencephalogram signal of the testee; performing multiple processing on electroencephalogram signals, extracting an event-related electroencephalogram feature map of thehidden behaviors, screening out electroencephalogram feature indexes of the hidden behaviors, and automatically identifying the hidden behaviors by applying a machine learning and mode identificationmethod based on the features. According to the method, the electroencephalogram characteristics of the hidden behaviors can be quickly and effectively recognized, the credibility of the answering result of the testee is evaluated, the application range is wide, and the applicability is high.

The invention discloses a directive bunching detection method aiming at specific regions. Signal detection probability can be calculated by adopting an F detection theory, and an array is guaranteed only to be sensitive to some seismic phases in the specific regions by designating array signal bunching processing of slowness vectors, and then the detection of other seismic phases from other regions or the signals in other regions can be filtered. When the signal detection probability P is greater than the set detection threshold, the result of the nuclear earthquake events in the specific regions can be given, and therefore the detection efficiency is higher. The directive bunching detection method is advantageous in that the directivity is strong, the detection sensitivity is high, the flow is concise, the calculation quantity is small, and the realization is convenient.

The invention discloses a fire power station boiler four-pipe preliminary leakage weak signal online detecting method, and belongs to the field of power station boiler pressure pipeline preliminary leakage weak signal detection. The weak signal detection theory is introduced to furnace pressure pipeline weak leakage signal detection, EMD is combined with a self-correlation differential duffing vibrator method for detection, EMD is carried out on collected signals, a background noise and leakage signal database is built for primary screening, an IMF corresponding to a characteristic frequency band is selected for reconstitution, self-correlation processing is carried out on reconstitution signals, the signals obtained through processing are input into a differential duffing vibrator based an adjustable time domain, differential signals are output for judgment, the detecting signal to noise ratio is low, and the real-time performance is good.

The invention discloses a state index evaluation and optimization method based on signal detection and ROC analysis. The method comprises a step of determining a target moving component and a failuremode and preparing monitoring signals of the moving component in a healthy state and the failure mode, a step of combing state indexes and extracting the state indexes from a healthy signal and a failure signal, and establishing a state index set, a step of estimating probability density functions of state indexes in a healthy state and a failure state, a step of calculating a state index discrimination index based on the signal detection theory and carrying out state index estimation, a step of solving an ROC curve, a step of constructing an optimization target function based on the ROC curve, and a step of solving an equation, obtaining an optimization target function minimum point, and thus obtaining a state index optimal threshold. The method provided by the invention has the advantages of a simple principle, simple operation and high stability and reliability and is applicable to the state index evaluation and optimization of various rotating machinery state monitoring and fault diagnosis.

Belonging to the technical field of visibility detection, the invention discloses a trace norm based road visibility detection method. The method includes: firstly conducting camera calibration on acquired video images, and determining the vertical distance from a point on an actual road surface to a camera coordinate system; according to the existing visibility detection theory and actual visibility data, regarding the extinction coefficient k as the function k(t) of time t, and assuming the extinction coefficient function k(t) as a constant near the moment t0, based on the trace norm, utilizing the visibility monitoring image frame at the t0 moment for curve fitting, and when the fitted curve is close to an actual brightness curve, acquiring the extinction coefficient of the moment; forthe continuous several frames nearby the t0 moment, working out the extinction coefficients of the frames respectively and taking the average, thus obtaining an extinction coefficient value nearby thet0 moment; and carrying out solving repeatedly to obtain extinction coefficient values of several moments, and finally working out the visibility values of different moments. The detection method provided by the invention has the characteristics of good robustness, high accuracy, compatibility with high-speed road condition video monitoring system, practicability and universality.

The invention discloses a textural coarseness quantitative evaluation method based on a signal detection theory. The textural coarseness quantitative evaluation method comprises the steps that a textural coarseness perception experiment is carried out, the identifying results of perceiving different texture samples of a tester are recorded, the identifying results are contrasted with a normal distribution table to obtain the probability of texture false reporting after perception and the probability of correct texture answering after perception, and the coarseness discriminability index is calculated by combining the objective texture parameters of different texture samples; according to the correlation, the objective texture parameters serve as input, the quantized value of the texture coarseness based on the signal detection theory serve as output, a textural coarseness perception evaluation model is established, and the weight of the objective texture parameter in the model is acquired through nonlinear least squares fitting; and the objective texture parameters to be evaluated are substituted into the model and then output to obtain the corresponding textural coarseness quantized value. According to the textural coarseness quantitative evaluation method based on the signal detection theory, the stability of subjective perception results under the condition of limited experimental subjects is effectively improved, the accuracy of evaluation is improved, and the method can be widely applied to predicting of textural coarseness perception of mechanical arms.

The invention discloses a greedy algorithm-based self-adapting compression perception signal restoring method. On the basis of an OMP (Orthogonal Matching Pursuit) algorithm, a detector used for judging whether a signal component exists in residual vector or not is designed, the detector is obtained through a hypothesis test model in the signal detection theory, the threshold of the detector is given through preset false alarm probability, when the threshold of the detector is smaller than the given threshold, the state that the signal component does not exist in residual vector can be judged, at the moment, iteration is stopped in the algorithm and restoring value of the signal is obtained, otherwise, iteration is continued. According to the method, the greedy algorithm serves as a channel estimation method without depending on the multipath number of a channel; compared with the MDL (Minimum Description Length), the method has the advantage that communication resources are saved due to the fact that observation for multiple times is not required; the method has the advantage of smaller calculation amount of the greedy algorithm, the problem that the requirement of the greedy algorithm on the real-time capability of sparse signal restoration is relatively high is solved, and the method can be applied to the condition that the signal sparsity is unknown.

The invention relates a method for detection of key parameters such as an electrode end position, an arc length and a molten pool liquid level position in a production technology course of submerged arc furnace smelting and specifically relates to a new method for detection of the key parameters of the submerged arc furnace smelting, namely the magnetic field detection method. The magnetic field detection method comprises the steps that firstly, an internal circuit model of a submerged arc furnace is established; secondly, a magnetic field radiation model of the submerged arc furnace is established according to electromagnetic field theories, and two measurement origin points including (i)P( / i)1 and (i)P( / i)2 in the furnace are selected; and thirdly, the measurement origin point (i)P( / i)1 is taken as the origin point (i)O( / i), multiple points on the origin point axis (i)z( / i) are extracted as detection points, a magnetic induction intensity curve is obtained according to magnetic induction intensities at each detection point, and the molten pool liquid level position, the electrode end position and the arc length parameter can be obtained according to the magnetic induction intensity curve. The invention discloses the non-contact magnetic field detection method based on an electromagnetism theory for the first time. The detection theory is characterized in that a corresponding electromagnetic field model is established, so that the electrode end position, the arc length and the molten pool liquid level position in the submerged arc furnace can be determined effectively.

The invention discloses a signal detection method based on error decision multi-model hypothesis test. The method comprises the following steps: 1, selecting a non-signal model set and a signal model set for signal features, and describing an original signal detection problem based on model as a binary composite hypothesis verification mode; 2, calculating the likelihood of the non-signal model set; 3, calculating the likelihood of the signal model set according to a multi-model algorithm; 4, calculating the likelihood of an intermediate signal model of the non-signal model set and the signal model set; and 5, calculating the test statistics of a 2-SPRT decision rule, and comparing the test statistics with a threshold t obtain an asymptotically optimal detection results. The method disclosed by the invention is simple in steps, is convenient to implement, solves the problems of wrong judgment and no upper limit of stop time in the existing method, can obtain a detection result with a proper average sample amount and an error probability, and can provide a new idea for the development of the detection theory in the future, is high in practicability and is convenient to promote and use.

The invention belongs to the technical field of e-commerce, and discloses an online commodity reputation value calculation method, a network transaction platform and a computer. The method comprises the steps of malicious evaluation detection, user interestingness evaluation and reputation value calculation. By utilizing a two-phase detection theory, slight change of an evaluation model is detected, so that the conditions when malicious users carry out malicious evaluation on all the commodities can be processed, and the conditions when malicious users only carry out malicious evaluation on target commodities also can be processed. According to the method, weights of different user evaluations are determined through comparing similarities between target items and user evaluation items, sothat the interestingness, to target commodities, of users and reliability of the users can be reflected more correctly.

The invention relates to a verifying unit for a medium-voltage switchgear insulated detector. The verifying unit for the medium-voltage switchgear insulated detector is composed of an electromagnetic wave signal generator, an insulated supporting member, a metal outer shell provided with a gap and an insulating spacer, wherein the electromagnetic wave signal generator is fixed inside the metal outer shell provided with the gap through the insulation supporting member, and the insulating spacer is fixed in the gap of the metal outer shell provided with the gap. The verifying unit for the medium-voltage switchgear insulated detector fills the blank of verifying unit of the insulated detector, and provides a verifying device for the insulated detector based on the transient-state ground voltage. Based on the detection theory of the transient-state ground voltage, the verifying unit for the medium-voltage switchgear insulated detector simulates generated electric-discharge signals, simulates the transmission and leakage paths of electromagnetic waves in a switch cabinet, and achieves verification of the transient-state ground voltage detector. The verifying unit for the switchgear medium-voltage insulated detector has the advantages of being ingenious in design, reasonable in structure, and quite suitable for verification and popularization of insulated detectors of medium-voltage switchgears in an electric power system.

Systems and methods for dynamically optimizing models used for sensor data analytics. An action is taken based on an analytics determination by systematically varying parameters of the analytical model using actions taken based on the analytics to determine the relative frequencies of hits, misses, false alarms, and correct rejections for particular model parameters. The model parameters for localanalytics are selected based upon on signal detection theory analysis and the value or cost of each hit, miss, false alarm, or correct rejection.

The invention discloses a method for detecting internal damage of a pavement based on passive source random excitation, which comprises the following steps: firstly, an acceleration sensor is arrangedon the pavement surface to form a detection table array; Then, the sensor collects the vibration signal of the pavement surface and transmits it to the computer by using the environmental micro-action as the excitation source. Secondly, the computer pretreats the collected vibration data of each sensor. Thirdly, the phase velocity of the surface wave is obtained by using the spatial autocorrelation method, and the dispersion curve of the surface wave is extracted. Finally, according to the depth of the surface wave- Phase velocity curve to determine whether there is damage inside the pavement. The invention uses the passive source surface wave detection theory to diagnose the damage position and degree of the pavement, scientifically evaluates the service condition and the damage condition of the pavement and the bearing capacity of the pavement, and provides a new method for solving the internal nondestructive detection of the pavement.

The invention discloses an intrusion detection method based on the tripling real value negative selection and belongs to the field of network information security. The method includes simulating the immune mechanism of an organism, and adopting own normal behavior data as an tautological set; firstly, matching alternate detectors and individuals of a mature detector set, if the matching fails, determining the alternate detectors as shortlisted ones; secondly, detecting the alternate detectors through the trained tautological set, and determining the shortlisted detectors disjointed to the trained tautological set to be elements of the mature detector set; finally, integrating and optimizing the elements of the mature detector set. By the aid of the method, the problems that in the current intrusion detecting process, the number of black holes is large, the mature detector set is large in scale and the detecting efficiency is low are solved, the mature detector set scale can be compacted, the detecting capability is improved, the theory development of the intrusion detection can be promoted, and the high application value is provided.

The invention belongs to the technical field of biometric authentication, and aims to improve the reliability of a face living body detection system in coping with samples of different attack modes. According to a binary signal detection theory, parameters of a classifier are adjusted, the practicability of the face living body detection system is improved, the safety of the face living body detection system is improved, and the efficient and accurate face living body detection method is established, so that the face detection system has higher practicability, and the development of the face living body detection system is promoted. A face living body detection method for removing highlight features and direction gradient histograms comprises the steps that firstly, a highlight removing method HRM is used for preprocessing a to-be-detected picture, then a gradient histogram HOG is used for texture feature extraction and feature processing, and the texture features are used for distinguishing face pictures collected primarily and face pictures collected secondarily; and finally, parameter adjustment is made on the classifier to finally realize accurate detection of the face living body. The invention is mainly applied to biometric authentication occasions.

An ultrasonic flaw detection method for identifying a hollow-bead defect of a submerged arc welded pipe is disclosed. Through metallographic phase anatomy on hollow beads and gas pore defects in welding seams in an actual checkout procedure in a production site, morphologies and characteristics of the defects are acquired, the defects are initially confirmed according to a waveform and position ofrefection wave at a submerged arc welding toe, and relative positions of the probe and the defects on the basis of an ultrasonic flaw detection theory, and are finally confirmed by a high-precision longitudinal wave probe. Through the method, a determination error can be avoided to the greatest extent, thereby saving a part of the degradation and head-cut tubes, avoiding the risk of leakage of the hollow bead defect, and saving a large number of tubes which originally need to be degraded.

The invention discloses a state index evaluation and optimization method based on signal detection and ROC analysis. The method comprises a step of determining a target moving component and a failuremode and preparing monitoring signals of the moving component in a healthy state and the failure mode, a step of combing state indexes and extracting the state indexes from a healthy signal and a failure signal, and establishing a state index set, a step of estimating probability density functions of state indexes in a healthy state and a failure state, a step of calculating a state index discrimination index based on the signal detection theory and carrying out state index estimation, a step of solving an ROC curve, a step of constructing an optimization target function based on the ROC curve, and a step of solving an equation, obtaining an optimization target function minimum point, and thus obtaining a state index optimal threshold. The method provided by the invention has the advantages of a simple principle, simple operation and high stability and reliability and is applicable to the state index evaluation and optimization of various rotating machinery state monitoring and fault diagnosis.

The present invention provides a behavior detection device for overall perception, comprising: an open field, which is a box structure with an open top, and the open field is surrounded by a bottom plate and a plurality of side plates connected end to end; a display screen, It is arranged on the top of the open field, the display surface of the display screen faces the bottom plate surface of the open field, and a dynamic approaching image is displayed on the display screen, and the dynamic approaching image includes an image maintaining topological properties and transforming topological properties at least one of the images; the shielding part is arranged on the bottom plate surface of the open field, and the shielding part is provided with a shielding space; the camera part is arranged on the open field for real-time monitoring of the open field Dynamic. The behavior detection device is a subconscious visual stimulus detection device, which can be used to test the influence of subconscious topology perception on animal behavior, and can reflect the correlation between animal behavior and overall attribute perception to a certain extent. The invention also provides a method for testing animal cognitive behavior.

A device comprising an adaptive acoustic detection circuit and an acoustic sensor device, such as a microphone, is described. In addition to the sensor, the apparatus includes circuitry configured to detect when an input stimulus of the sensor satisfies an adaptive threshold, and to generate, upon detection, a signal that causes a performance adjustment of the apparatus, wherein the adaptive threshold is a threshold that varies over time as a function of a detected change in the sound of the environment in which the device is located.