53 results about "TRADACOMS" patented technology

An improved system implements Fitness Gradient Consensus including hash distance and bucket consensus variations within a digital blockchain by calculating the highest fitness value competing blocks to resolve conflicts and allocate the rewards associated with building new blocks. The consensus system applies conflict resolution formulas to incentivize block-building nodes to share blocks generated, as it completes construction, to improve chances of a reward, resulting in enhanced speed and security of blockchain.The hash distance consensus utilizes a hash distance scalar value as part of its fitness metric, and the bucket consensus assigns tokens to buckets and calculates an aggregate value of the assigned tokens. A trust-but-verify variant increases transactional throughput and reduces linearity and computational constraints.The system also utilizes novel record types, such as token genesis, transfer, transaction, trade order, settlement, proposition, determination, and pattern linkage records to facilitate the automation of financial, commercial and legal processes.

Methods and systems for monitoring employee-customer conversations in commercial settings to identify participants, detect key events, and generate actionable insights into employee performance, customer sentiment, and operational efficiency are described. In some instances, for example the disclosed methods comprise capturing audio data for a transaction conversation at a transaction location within a commercial setting using at least one microphone positioned at the transaction location; generating a transaction conversation record based on the captured audio data; and processing the transaction conversation record using at least one machine learning model, where the at least one machine learning model is configured to process the transaction conversation record and detect a transaction event.

An improved system implements Fitness Gradient Consensus including hash distance and bucket consensus variations within a digital blockchain by calculating the highest fitness value competing blocks to resolve conflicts and allocate the rewards associated with building new blocks. The consensus system applies conflict resolution formulas to incentivize block-building nodes to share blocks generated, as it completes construction, to improve chances of a reward, resulting in enhanced speed and security of blockchain.The hash distance consensus utilizes a hash distance scalar value as part of its fitness metric, and the bucket consensus assigns tokens to buckets and calculates an aggregate value of the assigned tokens. A trust-but-verify variant increases transactional throughput and reduces linearity and computational constraints.The system also utilizes novel record types, such as token genesis, transfer, transaction, trade order, settlement, proposition, determination, and pattern linkage records to facilitate the automation of financial, commercial and legal processes.

The invention relates to the technical field of data backup and storage, and discloses a universal chatting record backup and storage method and system.The universal chatting record backup and storage system comprises a multi-source data acquisition unit, an information storage unit, an operation recording unit and a supplementary acquisition unit. One-stop efficient acquisition is realized, and the data processing efficiency is improved; classified storage and structured processing are carried out according to data characteristics, original data storage and efficient query analysis are considered, and data structure changes are flexibly coped with; the operation recording unit completely records the whole operation process by using a screen recording and Hash algorithm, ensures that the operation record is tamper-proof, and provides authenticity guarantee for the chat record as evidence in scenes such as commercial disputes and lawsuit; the supplementary acquisition unit breaks through the limitation of a data interface by means of technologies such as screenshot and optical character recognition, realizes complete acquisition of chat records of a complex communication platform, and enhances the universality and adaptability of the system.

The invention discloses a method for constructing vTEE and certification in an AMD SEV environment, provides a refined communication and fusing sequence diagram for the vTEE for the first time, and defines a module interaction sequence under two scenes of normal task execution and anomaly detection. According to the method, a trusted cloud security management platform initiates a request, a protection component coordinates a calculation component to collect an SEV-SNP report and vTEE key data, signature combination and uploading verification are carried out, and finally, the platform compares with a reference value to determine whether the vTEE is trusted or not. According to the method, a double-layer certification mechanism of SEV hardware certification and vTEE equipment measurement is adopted, an SEV-SNP certification report proves that a hardware environment, a VM mirror image and a vTEE operation environment are not tampered, vTEE key data measurement supports complete trust chain verification of equipment firmware, instruction streams and strategy states, and end-to-end certification is achieved. Equipment-level measurement, strategy issuing, abnormal fusing and remote certification are realized through an external protection part, and the system has important commercial landing value and strong system expandability.

The invention discloses a block chain digital right management method and system, and the method and system achieve the efficient and safe circulation of polymorphic values through the construction of a dynamic anchoring engine and a space-time verification network. A legal clause coding technology is innovatively adopted, and laws and regulations such as a payment settlement method are embedded into an intelligent contract, so that the compliance is ensured while the commercial efficiency is improved. Through test verification, the system realizes 2000 + transaction processing capacity per second under a million-level user scale, and the abnormal transaction identification accuracy rate reaches 98.7%.

A fleet of all-electric, battery powered industrial or commercial mobile power units (MPUs) or equipment is provided. Systems and methods for managing the fleet of equipment is also provided. Observable data, such as i) equipment performance and health data, ii) electricity cost data, iii) telematic data, and iv) scheduling data, can be used by machine learning models to optimize fleet management and decision making. The machine learning model can be configured to generate suggested actions, commands, or decisions which are transmitted to fleet managers who are responsible for activities such as i) equipment charging and maintenance, ii) equipment delivery logistics, and iii) rental pricing strategy. Feedback data from the outcome of these decisions, or the completion of the related activities, can tracked and used to update the machine learning model. Interactive portals may also be utilized by customers to make reservations and managers to manage reservations, monitor the fleet of equipment and provide support to MPUs across the product lifecycle.

A dialogue-based artificial intelligence system for interaction management in digital commerce, consisting of: a housing that encloses an arrangement of interconnected printed circuit boards; a conversation processing unit arranged on a first circuit board, comprising a syntactic parsing processor for generating hierarchical parse structures from user input texts, a semantic embedding processor for generating high-dimensional semantic vectors from the parsed structures, and a dialogue state calculation circuit for managing a multi-level conversation memory using clocked recurrent memory buffers; a retrieval augmentation unit arranged on a second circuit board, comprising a vector indexing processor for storing and retrieving domain-specific embedding vectors, a similarity calculation processor for calculating cosine-based semantic distances between the semantic vectors and vectors stored in a knowledge store, and a document reconstruction structure for merging retrieved text segments into a unified context representation; a generative response unit arranged on a third circuit board, comprising a transformer execution processor for executing a quantized transformer architecture for natural language generation, a context fusion circuit for merging the unified context representation with the semantic vectors to generate response conditioning data, and a hallucination suppression circuit for comparing the generated text with retrieved text segments and attenuating content divergence beyond a predetermined semantic threshold; a domain integrity check unit that is communicatively connected to the generative response unit, wherein the domain integrity check unit includes a regulatory restriction store that stores domain-driven rules, and a conformance assessment processor configured to check generated responses for conformance with the domain-driven rules, blocking non-conforming segments or replacing them using verified text content from the retrieval extension unit; a knowledge storage array comprising at least one static domain repository for storing commercial specifications, regulatory guidelines, product descriptions, and domain documents, a dynamic interaction buffer for storing anonymized conversation state data, and a vector storage partition for storing embedding vectors that can be retrieved by the vector indexing processor; and a multi-interaction device consisting of a touchscreen panel, an array microphone, a speaker structure and a contactless communication interface, each configured to receive multimodal user inputs or generate multimodal system outputs.

The invention provides a commercial satellite-oriented intelligent measurement and control responder and a multi-frequency-band measurement and control method thereof in order to solve the problems that a current measurement and control responder can only support a measurement and control task of a corresponding frequency band, so that frequency band selection flexibility is poor, and flexible measurement and control requirements cannot be met, and belongs to the technical field of spaceflight measurement and control. According to the invention, the architecture of the basic function module, the multi-band radio frequency front-end module and the multi-band measurement and control antenna is adopted, and the basic function module is integrated into a sharing platform with core functions of baseband processing, modulation and demodulation, intermediate frequency conversion and the like, so that an independent complete transceiving channel is prevented from being repeatedly designed for each band. Meanwhile, radio frequency front ends and antennas of multiple frequency bands such as KA, S and X are integrated, and the limitation that a traditional responder can only work in a single frequency band is broken through. An independent S frequency band measurement and control mode, an S + KA frequency band measurement and control mode, an S + X frequency band measurement and control mode and a KA + X frequency band measurement and control mode can be realized. The method is suitable for design of the measurement and control responder in aerospace constellation networking.

The invention relates to computer-implemented systems and methods for identifying and further preventing commercial or contract leakage across multiple different procurement relationships. This may involve ingesting a contract extracting commercial terms, such as price, rates, etc. Invoices may be similarly ingested and commercial terms may be extracted on a line item basis. An embodiment of the present invention may identify various types of commercial leakage, such as rate / price discrepancies, full / partial duplication, unrealized discounts, unrealized rebates, disallowance of charges (travel expenses), etc.

Assessments of guardrails of LLMs, whether used by an application or within an AI / LM stack, must be dynamic to protect against the ongoing engineering of jailbreaking prompts. An assessment framework has been created that facilitates assessment of language model guardrails. The assessment framework includes a prompt generator and has access to sensitive data (e.g., source code, trade secret, confidential documents, etc.) that occurs in training data of a model being assessed. The framework provides the prompt generator jailbreaking strategies and categories of the sensitive data (e.g., program code, trade secret, confidential document.). With the data categories and the strategies, the prompt generator generates different prompts and submits them to the AI-powered application or LM stack being assessed. The assessment framework then analyzes the outputs / responses from the AI-powered application or LM stack to determine whether guardrails have been subverted and any of the sensitive data has been exfiltrated.

The application relates to the technical field of sentiment analysis of mixed language reviews, and discloses a sentiment analysis method and device for mixed language reviews, electronic equipment and a medium, wherein the method comprises the following steps: through a multilingual pre-training model and an attention mechanism, accurate analysis of mixed language reviews is realized, different language segments are fused and understood in a preset semantic space, the sentiment recognition accuracy of mixed sentences is improved, and further through dynamic calling of a target language dictionary based on a language label, the sentiment weight of slang is corrected in a targeted manner, the sentiment polarity reversal is effectively avoided, and the misjudgment rate of regional market reviews is reduced.The application has the beneficial effects that while maintaining the processing efficiency, a high-accuracy and high-adaptability sentiment analysis solution is provided for application scenarios such as cross-border e-commerce and social media monitoring, and the accuracy and automation level of business decision-making are improved.

The invention relates to the technical field of information and communication suitable for supervision, in particular to a block chain-based transformer operation and maintenance data management system, which comprises the following steps of: analyzing a service level protocol into automatically executable commercial contract terms deployed on a chain in a smart contract form through a protocol analyzer; the commercial contract terms are automatically triggered to generate an operation and maintenance work order based on transformer real-time data monitored by an oracle machine; receiving and verifying a completion report, driving a multi-party collaborative acceptance process through commercial contract terms, and finally generating an acceptance voucher containing multi-party digital signatures; generating a verifiable digital certificate for the digital identity of the transformer according to the acceptance certificate, taking the verifiable digital certificate as a non-tampering historical record, and solidifying the verifiable digital certificate in a distributed ledger; according to the invention, high-credibility transformer operation and maintenance management is realized based on the block chain technology, and intelligentization of transformer operation and maintenance management is realized through the chain contract which can be automatically executed.

The invention discloses a trusted data circulation method and system based on a security sandbox in a trusted data space. According to the method, a security sandbox data controllable encryption mechanism is constructed, so that'available and invisible 'type sharing of power consumption data is realized. The method specifically comprises the steps of power utilization data encryption synchronization, data use application based on zero-trust dynamic multi-factor authentication, intelligent contract automatic approval, environment perception strategy execution, model training based on noise addition and homomorphic encryption, loan limit prediction and verification and the like. According to the method, a decentralized architecture, an integrated block chain, homomorphic encryption, noise addition, proxy re-encryption and other technologies are adopted, and it is ensured that data are encrypted in the whole process in the circulation process, the authority is controllable, and the process is traceable. According to the invention, the problems of privacy disclosure and commercial confidential protection when the power consumption data of the power enterprise is shared in a financial scene are effectively solved, and the security and credibility of data circulation are improved.

The invention provides a super high-rise commercial user-oriented power transaction scheduling device and method and a storage medium, and relates to the technical field of power transaction scheduling processing. According to the super high-rise commercial user-oriented power transaction scheduling device, the basic data layer collects equipment parameters to extract the total load response capability, and the circuit loss is combined to obtain the preliminary net load; the transaction data screening layer screens out tradable net loads according to user signing states and comfort constraints, the transaction decision-making layer calculates the operation and maintenance cost of a signing area and determines the optimal quotation, and the value distribution layer determines income distribution based on the optimal quotation and clarifies settlement results of cold overflow and hot overflow scenes. The method has the advantages that the decentralized function is modularly integrated, the problems of fuzzy load boundary and extensive scheduling of a traditional system are solved, link logic coherence is preserved by means of interlayer data linkage, a super high-rise complex scene is adapted, a clear framework is provided, and the overall collaboration and operability are improved.

The invention discloses an AI intention shunting recommendation method and system based on user re-purchase behavior recognition, and is applied to a take-out service platform. According to the method, a re-purchase frequency N is established by tracking historical order placing times of a user to a service provider, and a page type currently accessed by the user is combined as a technical signal to judge whether the user is in an efficiency scene or an exploration scene. In an efficiency scene, the system generates a service list arranged in a descending order according to a re-purchase frequency, and provides a quick entry of'one-order-again '; in an exploration scene, the system generates an initial candidate set based on multi-dimensional behavior preference, and applies negative weight adjustment to a high-frequency re-purchase service provider according to a re-purchase frequency N or a time-weighted re-purchase frequency N ', a weight reduction coefficient alpha = max (0, 1-k. (N-1)) or alpha = max (0, 1-k. (N'-1)), and when N is greater than or equal to S, direct shielding is performed. And after adjustment, performing diversity filtering, and setting a commercial cooperation weight factor to zero to generate a pure exploration recommendation list. According to the invention, through a set of quantitative AI-driven shunting and counterbalance mechanism, two opposite demands of exploration and re-purchase are met. An A / B test verifies that the exposure click rate of a new service provider in an exploration scene is increased by about 25%, and the average operation path of a user in a re-purchase scene is shortened to about two times of click.

The application discloses a social media tag multi-target combination recommendation method and system, and relates to the technical field of data processing.The video record including the parent tag, the sub-tag and the video attribute data is read, the video record is divided according to the parent tag to obtain an analysis unit, the affinity degree of the parent tag and the sub-tag in the analysis unit is statistically analyzed, and the affinity level is generated, the sub-tags in the same analysis unit are combined two by two, the co-occurrence number of the tags and the appearance number of the single tag are counted, the tag correlation weight is calculated, and the tag correlation matrix is constructed; the trend intensity, the commercial concentration and the stability of the play quantity of the sub-tag are calculated according to the video attribute data, the comprehensive recommendation score is obtained in combination with the affinity score; the number of the recommended tags, the grade ratio constraint, the internal correlation constraint and the approximate tag constraint are set, the candidate sub-tags are selected according to the comprehensive recommendation score, and the candidate sub-tags meeting the constraint are taken as the recommended tags, so that the accuracy and the applicability of the tag combination recommendation are improved.

A computer-implemented innovation automation and education platform comprises a multi-stage processing system managing innovation workflows from idea input through deliverable output. The platform includes a collation stage receiving multimodal input data via customizable forms, automatically parsing uploaded documents to extract relevant information fields, validating data integrity and completeness, and normalizing diverse input types into canonical representations with policy-aware routing capabilities. An intelligence layer implements claim-aware option generation, producing constrained and unconstrained idea variants while evaluating patentability and freedom-to- operate considerations through analogical mapping and recombination engines. The system incorporates an innovation corridor with policy -contract compilation that automatically translates organizational policies into executable contract representations, implements programmable royalty frameworks for automated revenue sharing, and processes settlements based on verified commercial outcomes. An agentic coaching module provides Al-driven learning task recommendations with cryptographic audit trails and human mentor escalation capabilities, enabling organizations to systematically process innovations while maintaining comprehensive compliance verification.

Methods and systems including one or more entropically configured distinct physical features (an “identropy”) that serve as unique identifiers for a physical item, such as a product or device, particularly products and / or devices in commerce, documents, packaging, etc. are described herein. The identropy makes it possible to uniquely distinguish one item from the other. In one embodiment, the identropy needs to be converted into a digital entity which can be done through a challenge-response interaction, in which a physical challenge acts upon the identropy, and in which the identropy as a reaction to the challenge will provide a physical response. In some embodiments, the response(s) described above is encrypted. In some embodiments, the resulting decrypted and optionally decompressed code can be compared to the digital response that was retrieved upon the challenge by the authentication device to estimate a trust score, such as a trust quotient.

The invention provides a three-party data automatic charging method and system based on a large model and electronic equipment, and the method comprises the steps: automatically reading and understanding charging rules and terms in a contract, and converting the charging rules and terms in the contract into structured data, including: cleaning contract documents and transaction data; training an NLP model by using the labeled contract data set, so that the NLP model can understand contract terms; calculating cost according to contract rules, and dynamically adjusting a charging strategy; recording the detailed process and basis of each charging, and providing a report; providing an interface to monitor a charging state, adjusting a charging rule, and checking a charging result; multiple layers of security measures including data encryption, access control and anomaly detection are implemented, security of sensitive data is ensured, and unauthorized access and data are prevented. According to the invention, an advanced artificial intelligence technology, especially a large-scale language model, is utilized to process and analyze a complex commercial contract text, so that charging rules are automatically identified and applied to third-party data.

This invention belongs to the interdisciplinary field of information technology, fintech, and distributed systems, specifically relating to a privacy-preserving multi-party collaborative reconciliation method and system based on value codes. More specifically, this invention relates to a trusted reconciliation scheme that utilizes programmable "value codes" as the core reconciliation carrier. It aims to solve problems such as inconsistencies in transaction records among multiple participants, cumbersome reconciliation processes, excessive manual intervention, difficulties in dispute resolution, and data privacy leaks by constructing a distributed, auditable, highly transparent, and privacy-preserving reconciliation infrastructure. This solution is applicable to various business scenarios requiring efficient, accurate, and trusted reconciliation, such as cross-institutional transaction clearing, supply chain collaborative reconciliation, multi-party profit sharing verification in platform-based economies, and cross-border business transaction reconciliation. This invention breaks through the limitations of traditional ledgers, inventing value codes as a measure of human value, and constructing a trusted reconciliation axiomatic system based on information economics and game theory. The core algorithm of the system integrates: a transaction energy level mapping operator based on log-normal distribution, a reconciliation utility evaluation model based on Milgrom's information value equation, and a non-cooperative game-theoretic collaborative engine based on Nash algorithm.

The present invention discloses a system, method and equipment for constructing trusted data resources and tradable data assets, and relates to the fields of data elements and data governance technology. The construction system includes a network communication module, a digital rights certification module, a data policy module and a data evidence module; the data policy module includes a permission allocator, a policy configurator and a data encapsulator; the data evidence module includes a workspace, an evidence bucket, an asset bucket and a transaction bucket; the permission allocator, the policy configurator and the data encapsulator are respectively connected to the data policy module; the workspace, the evidence bucket, the asset bucket and the transaction bucket are respectively connected to the data evidence module; the benefits are that users remotely collect business data, automatically store data resources, independently construct data assets, and connect to various forensic platforms and commercial service platforms in the national data governance system, so as to achieve five basic standards such as data security and anti-tampering, traceable data source, complete and credible evidence, circulated packaging specifications, and clear and verifiable digital rights.

The invention provides a method for native compilation and deployment of a time sequence interference radar processing tool chain ISCE2 and MintPy on a domestic ARM architecture. Aiming at three bottlenecks of poor compilation compatibility, difficulty in dependency library collaboration and huge virtualization computing power loss faced by migration from x86 to ARM architecture, the method eliminates nonstandard path hard coding errors through a dynamic path repair mechanism, establishes a hybrid dependency scheduling system, solves symbol conflicts and ABI incompatibility, and deeply optimizes an instruction set to realize performance maximization. Through strict verification, the compiling success rate is remarkably improved to 100% from less than 50%, the computing power utilization rate reaches 100%, the global first set of full-function ARM time sequence InSAR processing system is successfully constructed, and the performance approaches or even exceeds that of an x86 platform under the same hardware scale. The method is completely based on an open source scientific calculation library, the commercial authorization cost is avoided, a full-stack localization technical chain from a chip, an operating system to application software is realized, and important localization technical support and diversified selection are provided for satellite remote sensing deformation monitoring and geological disaster early warning.

The invention relates to the technical field of natural language processing, in particular to an intention recognition method and system in an operator OLT fault processing scene, and the method comprises the following steps: data cleaning and de-duplication verification, full intention library construction and intention matching classification, and domain knowledge fusion and dynamic intention optimization. The method has the beneficial effects that natural language dialogues are converted into executable operation and maintenance actions through a domain-enhanced intention recognition technology, the core pain points of slow response, more misjudgments and high cost in traditional OLT fault processing are solved, and transformation from'artificial experience driving 'to'intelligent decision driving' is realized. The application value of the method not only is reflected in quantitative improvement of efficiency and precision, but also provides long-term support for the network stability of operators, the satisfaction degree of users and the commercial competitiveness through a standardized process and preventive operation and maintenance capability.

A system (100) for automated account, call and sample reconciliation in commercial life sciences operations, the system comprising: an agent-based AI orchestration engine (1) configured to independently initiate, sequence, and manage voting workflows across multiple data sources; a relational data warehousing and lineage layer (2) configured to ingest, normalize, correlate and store structured operational data associated with accounts, calls and samples; an MDM synchronization and golden record management module (3) configured to synchronize master data entities and generate consistent golden records across different platforms; an engine for reconciling accounts, calls and samples (4) configured to compare related records across the synchronized records and to identify mismatches, missing links, duplicate records and transaction inconsistencies; a module for compliance rules, exception notifications and policy validation (5) that is configured to validate reconciled data against predefined business, regulatory and sample responsibility rules; a human-in-the-loop workflow, recommendation, and resolution console (6) configured to present detected exceptions along with corrective suggestions and to enable user-assisted or automated resolution; and a module (7) for audit analysis, continuous learning and reporting, configured to generate audit trails, reconciliation summaries, performance analyses and adaptive learning updates based on historical exception resolution results.

The application discloses a kind of contract and commercial text's auditing method and system based on multi-model fusion, it is related to computer information processing technical field, it solves the problems that only risk can be identified in prior art, cannot provide correction suggestion, poor multi-scene adaptability, auditing rule timeliness is insufficient and lack of traceability capability, the method comprises: constructing compliance risk atlas and knowledge base and updating data in real time, pre-processing is carried out on the file to be audited, multi-model fusion strategy is used to analyze the pre-processed file to be audited to obtain text analysis result, multi-dimensional auditing and risk determination are carried out on text analysis result to obtain auditing result and risk point and its corresponding risk level, based on compliance risk atlas and knowledge base, generate the auditing report containing legal basis and correction suggestion, can greatly improve auditing efficiency and risk identification accuracy, realize whole-process closed loop, compliance risk caused by rule lag is avoided simultaneously.

The present application provides a conflict and dispute incident early warning method, system, program product and storage medium, and relates to the field of information and communication technology specifically suitable for administrative, commercial, financial, management or supervisory purposes. The first feature data related to the subject information is extracted in the event structure tree using feature extraction rules, so that the key features of the event can be clearly presented. For personnel data, after constructing the personnel structure tree by word segmentation and part-of-speech tagging, the extracted words are subjected to sentiment tendency analysis, and negative sentiment words are marked, so as to facilitate subsequent judgment of the conflict and dispute incidents. The subject information and personnel are clustered according to the first feature data and the second feature data. The personnel carry the marked words during the clustering process, so that the event is closely associated with the relevant personnel, and the deep integration of data is realized. The problem of data confusion and mismatch is solved, so as to judge the real situation and development trend of the conflict and dispute incidents and improve the accuracy of the early warning.

The invention belongs to the field of alliance chains, and particularly relates to an efficient alliance chain method and system based on an improved consensus mechanism, and the method comprises the following steps: S1, a node is added into a network, the node is added into an alliance chain network, and when the node is added into the alliance chain network, the node passes through an identity verification and node reputation initialization program to ensure that the node meets the security requirement of the network; s2, node reputation evaluation and role allocation: the reputation value of each node in the network is evaluated regularly, different roles are allocated to the nodes based on evaluation, and role allocation is dynamically adjusted according to the reputation of the nodes, the payment and settlement efficiency can be effectively improved, the confirmation delay of large-scale financial transactions is reduced, and the payment and settlement efficiency is improved. And meanwhile, the privacy of sensitive data can be ensured, the leakage of commercial confidentials is avoided, the traceability and compliance of transactions in the supply chain are ensured, and the problems of interoperability and data consistency in cross-chain collaboration in the prior art can be solved.