90results about How to "High acceptability" patented technology

The invention relates to a business credit evaluation and supervision method based on a multi-modal coevolution algorithm, and the method comprises the steps: collecting and cleaning multi-modal data, guaranteeing the data quality, uniformly storing the multi-modal data as a structural database, extracting features through cross-modal comparative learning, and enabling the features to be embedded into a dynamic multi-modal knowledge graph, a modal sharing network is used to extract and fuse modal sharing and specific features, consistency of modal feature distribution is optimized through adversarial learning, a global co-evolution credit scoring model is initialized, a dynamic multi-objective algorithm is used to optimize accuracy, robustness and interpretability of the model, and a credit scoring result is obtained. A causal reasoning model is introduced to analyze driving factors of enterprise credit changes, a causal relationship is established, a closed-loop feedback system is designed, a credit evaluation model is updated, adaptability is enhanced, an interpretable credit evaluation report is generated based on a generative adversarial network, and transparency and credibility are enhanced. According to the method, the accuracy and adaptability of credit assessment are improved, and the robustness and interpretability of an assessment result are ensured.

The invention discloses an electronic contract sharing and management system based on a block chain, and relates to the field of block chain technology application. A contract management module; the front-end unit provides a user interaction interface, and the rear-end unit encapsulates a service function and interacts with the intelligent contract module; the file identification module is used for realizing process automation of the existing paper contract; the intelligent contract module is used for participating in a business process; the alliance chain bottom layer module is used for providing CA service and ensuring transaction consistency on an alliance block chain by improving a PBFT consensus algorithm; and the distributed storage module is used for storing on-chain data and off-chain data of the block chain. According to the method, an improved PBFT consensus algorithm is designed, a reputation scoring mechanism and a grouping mechanism are introduced, a main node selection strategy based on a VRF algorithm is used, consensus steps are optimized, the number of nodes participating in consensus can be dynamically adjusted, the communication frequency and response delay between the nodes are reduced, and the throughput is improved.

The invention relates to a deep neural network anti-attack method based on an attack space GAN, belongs to the technical field of machine learning and deep learning security, and aims to solve the problem that an anti-attack sample generated by a single-step attack and iterative attack method lacks attack validity and concealment. Meanwhile, a feature map generated by an encoder in a generator at a patent layer is utilized, after processing is conducted through a convolutional layer and a ReLU layer, attack space is generated, and disturbance and attack space are superposed to obtain an adversarial sample; a structural similarity loss function and a feature loss function are introduced, game training between a generator and a discriminator is carried out, the trained generator can generate an effective adversarial sample, the invention provides an efficient adversarial attack method, the adversarial sample capable of misleading a target learning model is generated, and the target learning efficiency is improved. And the robustness test of the deep neural network model is enhanced.

The invention discloses a mixed mode anti-attack method and system based on a laser radar point cloud. The method comprises the following steps: acquiring an original point cloud; sequentially performing frequency domain transformation, disturbance and inverse transformation processing on the original point cloud to generate a disturbance point cloud; generating an initial antagonistic point cloud based on the disturbance point cloud; optimizing the initial antagonistic point cloud to obtain first antagonistic disturbance, wherein the first antagonistic disturbance comprises the following steps: constructing a target function based on a Hausdorff distance and a chamfering distance between the antagonistic point cloud and the original point cloud; obtaining a first antagonistic disturbance by minimizing the objective function, including: calculating gradient information in the current iteration; the step length is adjusted according to gradient information in the current iteration, the antagonistic disturbance in the next round of iteration is determined, and the first antagonistic disturbance is output after iteration is conducted for the preset number of times; and processing the original point cloud and the first adversarial disturbance based on shape prior guidance to generate an optimal adversarial point cloud so as to carry out adversarial attack. According to the method, the attack resisting effect and robustness are improved.

The invention provides application of mitochondrial acid 5 in preparation of a medicine for treating reproductive organ injury caused by diabetes mellitus, and relates to the technical field of biological medicine. Experiments prove that as an artificially synthesized indole-3-acetic acid derivative, MA-5 provides a brand new treatment thought for testis injury caused by diabetes mellitus, not only is beneficial to improvement of reproductive function, but also possibly provides a new strategy for overall treatment of diabetes mellitus. Besides, as a natural plant hormone, MA-5 has relatively high safety and acceptability, and possibly becomes a new alternative therapy with a clinical application prospect. Although the long-term administration of the MA-5 does not significantly influence the blood glucose level, the alleviation effect of the MA-5 on testis injury shows that the MA-5 as a treatment means for long-term use can continuously improve reproductive dysfunction caused by diabetes, and has potential clinical advantages.

The invention relates to a ganoderma lucidum beverage and a making process thereof, and belongs to the technical field of drinks, the making process comprises the following steps: uniformly mixing lactobacillus acidophilus and bifidobacterium bifidum to obtain a mixed bacteria solution; inoculating the mixed bacterial liquid into a culture medium for culturing, and then mixing with a lucid ganoderma extract to obtain a lucid ganoderma active substance; packaging the lucid ganoderma active substance with maltodextrin and beta-lactoglobulin to obtain a lucid ganoderma encapsulated substance; and mixing the ganoderma lucidum encapsulation material, a sweetening agent, a thickening agent and water, homogenizing, sterilizing, cooling and aseptically filling to obtain the ganoderma lucidum beverage. According to the technical scheme, the two probiotics are mixed according to a certain volume ratio, intestinal flora balance can be effectively adjusted, proliferation of bad microorganisms in the intestinal tract can be inhibited, the probiotics and the ganoderma lucidum extract are jointly packaged in a microcapsule system formed by the maltodextrin and the beta-lactoglobulin, the stability of the microcapsule is improved, and the preparation process is simple and convenient. And the prepared ganoderma lucidum beverage has relatively good mouth feel and flavor.

The invention provides an OPC UA information model automatic construction method based on a knowledge graph and a large language model. The method comprises the steps of obtaining an unstructured industrial text, performing semantic analysis on the unstructured industrial text, and extracting a main body entity, an object entity, a method entity and attribute information thereof according to a predefined hierarchical tuple structure; calling an industrial field knowledge graph in real time to perform semantic enhancement on an extraction result; performing similarity calculation and evaluation on an enhanced result, and performing information fusion and duplicate removal based on a similarity evaluation result to obtain an entity-attribute set; generating a tree-shaped hierarchical structure framework by using a large language model, and calling a knowledge graph to perform structural integrity verification; semantic association between the entity-attribute set and the tree structure framework is analyzed, attributes and methods are mapped to corresponding structure nodes, and a mapping reasoning process is output in a natural language form; converting the mapped model structure into a format of XML (Extensive Makeup Language) grammar, and executing automatic compliance check and repair; by designing a progressive task chain of information extraction, semantic fusion, model construction, interpretable mapping and standardized output, a set of complete understanding-enhancement-construction-verification automation system is constructed.

The invention provides an operator fatigue monitoring method and device based on machine vision, and the method comprises the steps: carrying out the preprocessing of the obtained operation live data of an operator, and obtaining a preprocessing result; detecting and positioning the eye region by using a gradient weighted generalized Hough transform algorithm according to the preprocessing result to obtain the eye region; according to the eye region, extracting the eyelid closing frequency of the operator as a fatigue feature; and performing fatigue evaluation based on the fatigue characteristics, and performing early warning and / or suggestion according to an evaluation result. According to the invention, a non-contact machine vision technology is adopted, fatigue monitoring is carried out on an operator through operation real-time data, the fatigue state of the operator is monitored in real time according to the operation real-time data, especially the eye area with asthenopia is monitored, a de-identification technology is adopted in the monitoring process, personal identity and sensitive information are protected, and the safety of the operator is improved. And meanwhile, personalized early warning and suggestions can be provided according to individual differences, and the universality is good.

The present application relates to the technical field of short-circuit current calculation, and particularly relates to a flexible DC system short-circuit current calculation method based on a physical information neural network, comprising: setting a model input feature vector, the model input feature vector being used to represent a system operating state before a fault and fault information, and performing data preprocessing on the model input feature vector; constructing a hybrid driving calculation model, the hybrid driving calculation model comprising a physical calculation module and a neural network module, and being coupled based on a preset fusion architecture; performing end-to-end training and optimization on the hybrid driving calculation model by using a preset composite loss function; and performing flexible DC system short-circuit current calculation based on the optimized hybrid driving calculation model, so that the problems of poor precision, speed and convergence, poor interpretability and weak generalization ability in the prior art are solved.

The invention relates to a sleep staging method, device and equipment and a storage medium. The sleep staging method comprises the following steps: acquiring a low-load physiological signal of a target user; carrying out beat-by-beat interval heartbeat feature extraction on the physiological signal to obtain a beat-by-beat interval sequence; wherein the beat-by-beat interval refers to a time interval between two adjacent heartbeats; analyzing heart rate variability according to the beat-by-beat interval sequence, and extracting physiological features of the target user from multiple angles; and classifying the physiological features through a pre-trained machine learning model, and determining a sleep staging result of the target user. According to the method provided by the invention, the accuracy and acceptability of sleep staging of children are improved.

The invention discloses a water area resource utilization grading and pricing method based on spatial heterogeneity correction. The method comprises the following steps: S1, evaluating the service value of a water area ecosystem; s2, determining a water area resource utilization standard price; s3, dividing water area space levels; and S4, correcting the water area resource utilization standard price. According to the method, the water area resource utilization standard price is determined by quantifying the influence of water area resource utilization on the ecological system service value, the hierarchical water area resource utilization coefficient reflecting spatial heterogeneity is introduced for spatial correction, and finally the water area resource utilization hierarchical guidance price is formed. According to the method, a complete technical process from ecological system service value profit and loss quantification to space differentiation pricing is constructed, the water area resource utilization grading guidance price is determined, the technical blank in the field is filled, a scientific basis is provided for a water area resource management decision, and the economic benefit of the water area resource management decision is improved. The method has good operability, acceptability and popularization and application prospects, and ecological protection and sustainable utilization of water resources can be promoted.

The present invention discloses a medicine composition for clearing away heat and removing dampness, and a preparation and application thereof. The medicine composition for clearing away heat and removing dampness is composed of Polygonum cuspidatum, Verbena officinalis, Gypsum, Talcum, Bupleurum, Scutellaria baicalensis, Artemisia annua, Capillaris, Pinellia ternata, Magnolia officinalis, Patchouli, Amomum villosum, Spider fragrance, Pseudostellaria chinensis, Chao Shenqu, Honeysuckle, Forsythia suspensa, Ginger, and Licorice. The medicine composition for clearing away heat and removing dampness is added with pharmaceutically acceptable excipients to prepare a preparation. The medicine composition for clearing away heat and removing dampness and its preparation can be used to prepare a medicine for treating internal damp-heat syndrome.

The invention belongs to the technical field of gas emission of terrestrial ecosystems, and particularly discloses a method for measuring respiration and nitrous oxide emission of a facility greenhouse ecosystem, which comprises the following steps: selecting a sampling point at the middle position in a facility greenhouse according to the layout and structural characteristics of the facility greenhouse; a ventilation opening of the facility greenhouse is closed and covered with a heat preservation cotton quilt, so that the facility greenhouse is in a dark closed environment, and gas in the greenhouse is collected through an injector and then stored through a gas bag; collecting the gas sample for multiple times within several hours to form a time gradient; measuring the concentration of carbon dioxide and the concentration of nitrous oxide in the gas sample to obtain gas concentration data, and recording the gas concentration data; according to the gas concentration data and the environment information of the facility greenhouse, the ecological system respiration and nitrous oxide emission rate of the facility greenhouse are determined. The method is suitable for measuring the respiration rate and the nitrous oxide emission rate of the ecological system in the facility greenhouse, the operation is simple and convenient, and the accuracy of obtained data is relatively high.

The invention relates to a parking lot pricing prediction system and method based on artificial intelligence and big data, and belongs to the technical field of big data analysis. The system comprises a three-layer state sensing and coding module, wherein a graph loop fusion network, an attention scoring model and a user clustering model are arranged in the three-layer state sensing and coding module; the graph loop fusion network is used for encoding the network game layer data into graph embedding vectors; the attention scoring model is used for carrying out dynamic weight distribution and fusion according to the importance of the influence of the current moment on the parking demand; the user clustering model is used for clustering individual heterogeneous layer data into a plurality of typical user groups, and extracting group features to obtain user heterogeneous state vectors. According to the method, a'three-layer perception-collaborative game 'framework is constructed, a regional Pareto improved pricing strategy is generated by utilizing a multi-agent dynamic game, meanwhile, the method has real-time response and decision interpretation capabilities, and social benefits and collaborative commercial and public benefits are embedded in a reward function of the method.

The present application relates to the biological field, and particularly to a weak acid buffer and its use in an immunopeptidome separation reagent, the weak acid buffer comprising amino acids and / or polypeptides, the mass-to-charge ratio of the amino acids and / or polypeptides being theoretically predictable and experimentally reproducible, or the mass-to-charge ratio being beyond the preset acquisition range of a mass spectrometer; the weak acid buffer further comprising a volatile acid, the volume concentration of the volatile acid being 0.01% to 10%; and the pH of the weak acid buffer being 3.0 to 3.5. The weak acid buffer of the present application has high compatibility, can maximally avoid pollution and signal interference to an analysis system, has a simple experimental procedure, and the overall operation can be completed within tens of minutes, thus having low technical threshold and high acceptability; can improve the number of immunopeptide groups identified, thus improving the efficiency of the experiment; and the reagent is cheap and easy to obtain, thus the method has low cost, is suitable for large-scale or even industrial use, has high universality, and the like.

The invention discloses a wristwatch type personal radiation monitor based on a plastic scintillator. The wristwatch type personal radiation monitor comprises a dial plate and a watchband, the scintillator is used for generating an optical signal when receiving radiation rays of the radiation source; the photomultiplier is used for converting the optical signal generated by the scintillator into an electric pulse signal; the radiation calculation module is used for calculating a corresponding radiation intensity value according to the electric pulse signal; the health data acquisition module is used for acquiring health condition data of the user; the historical radiation recording module is used for acquiring a historical radiation exposure condition of the user; the personalized threshold value generation module is used for generating a personalized alarm threshold value of the user according to the health condition data and the historical radiation exposure condition of the user; and the safety alarm module is used for comparing the radiation intensity value with an alarm threshold value, and sending out a safety alarm signal when the radiation intensity value exceeds the personalized alarm threshold value of the user. The health of the user can be protected, and the pertinence and flexibility of radiation monitoring are improved.

The present invention discloses a ramp collaborative control system and method based on driving style, including: an on-board control subsystem, a vehicle-to-vehicle communication subsystem, and a collaborative decision-making subsystem based on driving style; the present invention fully considers the state and reaction decision of competing vehicles in the merging process, establishes a ramp collaborative merging interactive decision-making model, and designs a framework for multi-vehicle deep reinforcement learning; in order to consider the impact of random driving style on the decision-making process, the optimal merging strategy is defined based on Bayesian Nash equilibrium, and an experience pool is established through interactive learning with the environment to train and learn the optimal merging strategy. The method of the present invention can adjust the driving performance weights such as safety and efficiency based on driving style to achieve personalized driving and improve the acceptability of autonomous driving vehicles; the decision-making strategy is learned through interactive learning with the environment to improve the adaptability of the decision-making algorithm to dynamic scenarios.

The invention belongs to the technical field of biological information processing, and particularly relates to a method and system for constructing a risk prediction model from Kawasaki disease to huge coronary artery tumor. The invention provides a Kawasaki disease MGCAA risk prediction model construction method and system, and the method comprises the steps: building a prediction model based on six conventional clinical variables through employing a random forest (RF ranger) algorithm; an SHAP explanation mechanism is introduced, so that the contribution of each variable to a prediction result can be visually displayed in global and individual levels, and the transparency and clinical interpretability of the model are improved; through external verification and intercept-only recalibration, the reliability and the applicability of the model in different groups of people can be ensured; according to the method, an online webpage tool (Shiny App) is deployed, and a doctor can input clinical data of a patient in real time and immediately obtain individualized risk prediction and explanation, so that clinical early recognition of an MGCAA high-risk child patient is realized, and formulation of an individualized treatment scheme and early intervention measures is assisted.

The present invention relates to a sleep staging method, device, equipment and storage medium. The sleep staging method comprises: obtaining a low-load physiological signal of a target user; extracting the heartbeat features of the beat-by-beat interval of the physiological signal to obtain a beat-by-beat interval sequence; wherein the beat-by-beat interval refers to the time interval between two adjacent heartbeats; analyzing the heart rate variability according to the beat-by-beat interval sequence, and extracting the physiological features of the target user from multiple angles; classifying the physiological features through a pre-trained machine learning model to determine the sleep staging result of the target user. The method provided by the present application improves the accuracy and acceptability of sleep staging for children.

The invention discloses an image generation model-oriented watermark generation and detection method and system, and the method comprises the steps: a model provider pre-embeds an invisible watermark in a diffusion model, and provides a high-quality non-perception image generation service for a legal user; when a malicious user generates and propagates illegal or harmful images by using an API, a detection request can be provided to a model party through a supervision party, and a model provider performs watermark detection on suspicious images; and the model provider extracts watermark information from the suspicious image, judges whether the watermark information is generated by the model or not, and submits a detection result to the supervisor to judge whether the watermark information is legal or not. According to the method, a watermarking mechanism which is only used for'detection 'instead of'traceability' is designed, the speech freedom and privacy of legal users are protected while the identifiability requirement of supervision on AI generation content is met, direct tracking of user identities is avoided, and therefore effective balance between content safety guarantee and user right maintenance is achieved, and user experience is improved. And the fairness and acceptability of AI content governance are obviously improved.

The invention belongs to the technical field of food preparation, and particularly relates to a Maillard reaction product and application thereof in instant noodles. Different from the traditional research and development thought of adding dietary fibers and other raw materials for promoting digestion, the Maillard reaction product is applied to the instant noodle soup base, and the free radical scavenging capacity of the Maillard reaction product can be used for correcting metabolic health and indirectly adjusting signals of hunger and abdominal distension, so that the taste of the instant noodle soup base is improved. Therefore, the symptoms of gastrointestinal discomfort such as abdominal distension caused by intake of the instant noodles are effectively relieved. Sensory experiments show that the instant noodles added with the Maillard reaction product are obviously lower in abdominal distension feeling and higher in acceptability when being eaten at the same amount. On the basis of traditional instant noodles, the Maillard reaction product is added, so that the flavor of the instant noodles is further increased, sensory evaluation shows that the flavor of the instant noodles is basically close to full, and the flavor of the instant noodles is greatly different from that of the traditional instant noodles, so that the flavor of the instant noodles is good.

The invention relates to poria cocos fresh and wet noodles and a preparation method thereof, the poria cocos fresh and wet noodles comprise poria cocos powder and wheat flour, and the mass of the poria cocos powder accounts for 15-25% of the total mass of the poria cocos powder and the wheat flour; the average particle size of the poria cocos powder is 50-180 microns; the average particle size of the wheat flour is less than 90 [mu] m. The invention also discloses a preparation method of the fresh and wet poria cocos noodles. Compared with common fresh and wet noodles, the poria cocos fresh and wet noodles disclosed by the invention are better in quality and higher in content of health-care functional components; the product has good taste, mouthfeel and surface state, has good flavor, has high acceptability of sensory evaluation, and has better processing stability and storage stability.

The utility model relates to the technical field of medical instruments, and discloses a multifunctional lower limb rehabilitation training support which comprises a shell, a driving mechanism is arranged on the lower portion of the shell, a lifting mechanism is arranged on the upper portion of the shell, and the upper portion of the driving mechanism makes contact with the lower portion of the lifting mechanism. According to the multifunctional lower limb rehabilitation training support, a driving gear motor drives a transmission shaft to rotate through a belt wheel and a belt, then cams are driven to rotate, accordingly, through jacking of the cams, a lifting rod drives a supporting block to move upwards through a limiting column, the supporting block supports the legs of a patient, every three adjacent cams form a group, and the supporting block is driven to move upwards; the three cams in each group are fixed on the periphery of the transmission shaft in a circumferential array, so that when the transmission shaft is driven by the gear motor to rotate by a certain angle, different supporting blocks are jacked up, muscles of the lower limbs are moved, blood circulation is promoted, and diseases such as pressure sores can be effectively prevented.

According to the multi-label automatic diagnosis and evaluation system and method for ankylosing spondylitis, pelvic X-ray film images and clinical data are combined, automatic diagnosis of ankylosing spondylitis is achieved through a multi-label classification model, and the severity degree of injury of sacroiliac joints and hip joints is evaluated. The system adopts a prior attention mechanism, can automatically focus a key area in an image, and further improves the diagnosis efficiency. Experimental results show that the system still has relatively high diagnosis accuracy in an environment with limited resources, and can be comparable with diagnosis results of experienced doctors. The multi-label classification model with the priori attention mechanism provided by the invention provides a promising and cost-effective tool for diagnosis and evaluation of ankylosing spondylitis, and has important practical application value.

This invention discloses a process optimization method, system, and equipment for a large-scale bio-fermentation model, applicable to pipeline network anomaly detection. The method includes: acquiring multi-source heterogeneous raw fermentation data; standardizing the multi-source heterogeneous raw fermentation data to obtain standardized data; constructing a cross-domain fermentation knowledge base based on the standardized data and publicly available industry information, wherein the cross-domain fermentation knowledge base includes constraint rules for at least one of four major domains: traditional Chinese medicine, food, pet food, and cosmetics; and constructing a fermentation domain knowledge graph based on the standardized data and the cross-domain fermentation knowledge base. Beneficial effects: By embedding prior knowledge from the fermentation knowledge base and knowledge graph into the model through a domain knowledge embedding layer, the model acquires professional domain reasoning capabilities.

The present application discloses a method for establishing a PAYG‑ID payment code for a pay-as-you-go product, wherein the PAYG‑ID includes a Q‑ID function code, a PAY‑ID function code, and a SecretKey function code; the Q‑ID function code is used for internal hierarchical management of different regions where different models of products are sold; the PAY‑ID function code is a product identification code that users can directly view on the product packaging shell or the product UI interface, i.e., a plain code; the SecretKey function code is an internal management password for the product, i.e., a cipher code. The PAYG‑ID established in the present application achieves precise management of products in the background by establishing a connection between product codes and sales areas and encrypting and managing the codes, and the related ID is not easy to crack after encryption, and has the characteristics of convenient management and strong anti-tampering ability. It is applied to the field of offline installment payment, which is conducive to the promotion of offline installment payment methods.

The invention discloses a depression detection method based on a face video, belongs to the technical field of depression detection, and can solve the problems of invasive equipment, long detection time, unreliable detection effect, high cost and possible physiological and psychological discomfort to a patient in the existing detection method. The method comprises the following steps: S1, determining a facial feature set of each subject according to a facial action video of each subject in a plurality of subjects; s2, training a classifier according to the facial feature set of all subjects and the depression degree label of each subject to obtain a classification model and an optimal feature subset; s3, the facial feature set of the to-be-tested person corresponds to the features of the optimal feature subset and then is input into the classification model, and a depression prediction result of the to-be-tested person is obtained. The method is used for detecting depression.

The invention provides a pilose antler mushroom and pork emulsified sausage and a preparation method thereof, and relates to the technical field of food processing. In the invention, the antler mushroom and pork emulsified sausage is prepared from the following components by taking the mass of lean pork as a standard: 9-15% of baked antler mushroom powder, 24-26% of fat pork, 0.5-1.5% of table salt, 5-7% of cooking wine, 6-8% of starch and 37-39% of ice water. Under the condition that no other redundant seasoning is added, the pilose antler mushroom is used as an auxiliary material, and the roasted pilose antler mushroom powder is added in the sausage preparation process, so that the quality of the pilose antler mushroom and pork emulsified sausage is improved, the forming effect and texture characteristics of the sausage are specifically improved, and the cooking loss rate is reduced; the sausage prepared from the baked pilose antler mushroom powder is good in color, smell, texture, taste and overall acceptability, and a basis is provided for development of novel edible mushroom meat products.

This invention provides a multi-agent traceable decision-making system and method for environmental data mining, belonging to the interdisciplinary field of artificial intelligence and environmental informatics. The system includes: a task complexity assessment module, a multi-agent conditional collaboration module, an arbitrator triggering and adjudication module, an environmental knowledge graph module, a feedback learning optimization module, and a decision tracing and visualization module. The method includes the following steps: Step 1: Task complexity assessment and collaboration mode allocation; Step 2: Parallel processing and dynamic collaboration of two intelligent analysts; Step 3: Consistency check and arbitration triggering; Step 4: Arbitrator adjudication and weight integration; Step 5: Human expert correction and weight optimization feedback; Step 6: Decision tracing and weight visualization. This invention enables more accurate decision optimization, significantly improves the professionalism and accuracy of decision-making, and possesses the ability to proactively identify and prevent potential problems.

The invention is suitable for the field of defect detection, and provides a cable defect detection method and device, electronic equipment and a computer program product, and the method comprises the steps: determining the detection point coordinate of at least one target detection point located on the surface of an armor layer of a cable; based on cable parameters, detection wave emission equipment parameters and the detection point coordinates of each target detection point, the incident coordinates and incident angles of to-be-emitted detection waves corresponding to each target detection point are calculated; emitting a detection wave based on the incident coordinate and the incident angle corresponding to each target detection point to obtain a target reflection echo of each target detection point; and determining a defect detection result of each target detection point on the surface of the armor layer based on the target reflection echo. According to the scheme, the receivability of reflection echoes and the defect detection efficiency of the cable are improved.