810results about How to "Improve response speed" patented technology

The invention relates to the technical field of PCIe (Peripheral Component Interconnect Express), in particular to a PCIe dynamic degradation type link resetting method and system. Comprising the following steps: S1, continuously reading the LTSSM state of a PCIe link, recording the duration of an abnormal state, and when the duration exceeds a preset threshold value, judging that timeout abnormity exists; s2, after the abnormal early warning is received, a dynamic degradation reset instruction for the NVMe controller is initiated; s3, the state machine control unit takes over the reset link initialization process and follows the physical layer priority gt; the link layer is preferentially gt; a priority strategy is simplified by a transaction layer, and a centralized resource guide link rapidly completes training and enters an L0 state. Compared with the prior art, the method has strict protocol compliance, the reset efficiency is improved, and the overall stability and performance of the system are optimized.

The intelligent sensing and pressure self-adaption support pile system comprises a plurality of support pile bodies, a sensor network, a hydraulic servo adjusting system and an intelligent control unit. The support pile body is of a conventional foundation pit support pile structure, is prefabricated by reinforced concrete or is formed by cast-in-place, provides a basic support function and resists soil pressure; the sensor network is embedded into the support pile body and monitors the strain condition of each pile body in real time; the intelligent control unit calculates support parameters according to monitoring data of the sensor network and outputs a control instruction; and the hydraulic servo adjusting system automatically adjusts the contact pressure between the pile and the soil according to the control instruction. The system can monitor the stress state of a pile body in real time and automatically adjust supporting parameters through the hydraulic servo system, so that the safety and reliability of foundation pit engineering are remarkably improved.

The invention provides a business process intelligent configuration and security execution method, system and device, and the method comprises the steps: converting a natural language demand into a BPMN 2.0 process model based on a large language model and an enterprise knowledge base; the service rule description is converted into a Grouping script through multi-level security compiling; the process and the script are executed in the Flowable process engine integrated with the security sandbox, and execution data are collected; and calculating a process health score based on the data, generating and implementing an optimization suggestion, and feeding back a result to the knowledge base. The problems that a traditional process system depends on manual coding, the script safety is poor, and continuous optimization is lacked can be solved. The full-link automation and intelligentization of the business process from design, execution to optimization can be realized, the development efficiency and the system security are greatly improved, and the process has the self-evolution capability through closed-loop feedback.

The invention provides an NoC low-delay data transmission method based on a dynamic routing algorithm, relates to the technical field of data transmission, and aims to solve the technical problems that an existing NoC routing algorithm cannot adapt to a link dynamic load, is lack of congestion trend prejudgment, is slow in path search convergence and is insufficient in QoS differential scheduling. The method comprises the following steps: constructing a dynamic sensing module containing a double-branch LSTM time sequence prediction model, collecting states such as link bandwidth and queue length in real time, and predicting a congestion trend in 50-100ms in the future; constructing a multi-objective evaluation function taking delay as a core, and dynamically adjusting the weight according to the QoS level; solving an optimal path by adopting an improved ant colony algorithm which introduces a congestion penalty and pruning strategy; during transmission, dynamic reselection is triggered through a pre-calculation + fast matching mechanism; and iteratively optimizing the prediction model based on incremental learning. According to the method, congestion is avoided in advance, the path search efficiency and the transmission reliability are improved, the delay is remarkably reduced compared with a traditional algorithm, and the method is adaptive to delay sensitive scenes such as a high-performance processor and an AI chip.

The invention provides a unified context and multi-level memory cooperation system and method for an LLM agent, and belongs to the field of artificial intelligence. The system comprises a unified context module which is used for aggregating and structuring all input information required for organizing agent operation, and providing an integrated context view for an LLM agent core; the LLM agent core is used for executing task planning, tool calling, result evaluation and response generation based on the context provided by the unified context module; and the multi-level memory system is connected with the unified context module and the LLM agent core and is used for hierarchically storing, managing and feeding back experience and knowledge of the agents. According to the method, the problems that an existing LLM intelligent agent is limited in context, low in memory efficiency and lack of self-correction capacity are solved, and the intelligent level and reliability of complex task processing are remarkably improved.

The invention discloses a power grid monitoring alarm event handling method and system based on a large model, and relates to the technical field of power systems, and the method comprises the steps: obtaining a historical sample of a power grid monitoring alarm event, and carrying out the preprocessing; constructing a balance training sample set based on a first large language model and resampling combined sample enhancement method; based on the pre-training language model, utilizing the balance training sample set to carry out fine tuning training, and constructing a power grid monitoring alarm event diagnosis model; on the basis of a second large language model, a power grid monitoring alarm event disposal model is constructed, and the disposal model is used for retrieving reference information from a historical disposal knowledge base in combination with an event type diagnosis result output by the diagnosis model and generating an auxiliary disposal suggestion for an input alarm event text; and integrating the diagnosis model and the disposal model to form a power grid monitoring alarm event disposal framework. According to the invention, intelligent diagnosis and auxiliary disposal of the power grid monitoring alarm are realized, and the diagnosis accuracy and the disposal efficiency are improved.

The invention provides video processing equipment and a video processing method. The video processing device comprises a multi-core processor, a task scheduling module, a visual processing unit and a cooperative control module, and the multi-core processor is used for sending a task queue corresponding to a video stream to the task scheduling module; the task queue comprises a plurality of to-be-processed tasks and real-time levels corresponding to the tasks; the cooperative control module is used for monitoring the states of the visual processing unit and the multi-core processor to obtain state information and sending the state information to the task scheduling module; the task scheduling module is used for dynamically distributing each task to a target processing component corresponding to each task according to the real-time level and state information corresponding to each task, and each target processing component comprises a multi-core processor and a visual processing unit for processing; the target processing component is used for processing each task to obtain an output result corresponding to the video stream; and the multi-core processor is used for outputting an output result corresponding to the video stream.

The invention relates to a multi-factor dynamic correction investment benefit intelligent evaluation system, in particular to the field of investment evaluation, and aims to capture macroscopic event and project risk index impact in real time and dynamically generate factor impact coefficients through an event-driven factor correction module, so that the response speed and sensitivity of a model to project sudden change are remarkably improved, and the evaluation efficiency is improved. The self-adaptive weight optimization module utilizes a deep reinforcement learning framework to continuously optimize factor weight distribution based on revenue after risk adjustment in a rolling time window so as to realize self-adaptive adjustment of an investment strategy and optimization of a revenue-risk ratio, and the abnormal conduction early warning module constructs a dynamic directed graph and combines a graph neural network technology to realize early warning of the abnormal conduction. According to the method, abnormal factor conduction paths can be perspectively recognized, systematic engineering risks can be effectively warned, a strategy execution module fuses weight optimization results and risk warning signals, rebalance is executed under the condition that investment cost and risk control constraints are strictly met, and finally a project configuration scheme giving consideration to revenue, robustness and real-time performance is generated.

The invention relates to the technical field of block chains, and discloses a block chain data encryption query method, device, equipment and medium, the method comprises the following steps: extracting data content information of to-be-chained data, using a homomorphic encryption algorithm to encrypt the data content information to obtain ciphertext content information; taking the ciphertext content information and the corresponding ciphertext hash value as on-chain evidence storage data to be stored in a block chain in a chaining manner; performing association mapping on the on-chain evidence storage data and the ciphertext access rule through the smart contract to generate an authority association rule corresponding to the on-chain evidence storage data; performing permission verification on the access permission in the data query request based on a permission association rule; after the permission verification is passed, querying the on-chain evidence storage data in a homomorphic encryption state according to the data query request to obtain an encrypted query result; and decrypting the encrypted query result to obtain target plaintext query data. The reliability of data encryption query can be improved.

The embodiment of the invention discloses a long-term ownership task planning method and device based on a large model, a robot and a storage medium. The method comprises the following steps: acquiring working environment information of a robot through multi-modal sensing equipment, and constructing a semantic scene graph; a natural language instruction is received, a scene graph is combined to input a task planning large language model to generate an initial task decision tree, nodes represent atomic actions, and branches correspond to different execution results; starting from the root node, matching branches based on node execution results in sequence and executing corresponding atomic actions; for any current tail end node in the decision-making tree, calling the large language model in parallel to infer different execution results and corresponding subsequent actions, and dynamically updating and expanding the decision-making tree; and after the execution of the current node is completed, matching the actual result of the current node with the corresponding branch in the decision tree: if the matching is successful, determining the next to-be-executed sub-node according to the matched branch, and pruning the decision tree to reserve the sub-tree corresponding to the branch.

The invention discloses an unmanned aerial vehicle patrol and security monitoring linkage management method. According to the system, urban geographic information data and key monitoring area coordinates are acquired, hierarchical grid division is realized by using a quadtree spatial index algorithm, and a patrol task distribution basic data structure is established; solving an approximate optimal solution of the patrol path of the unmanned aerial vehicle by adopting an improved greedy strategy, and performing optimization adjustment according to technical parameters and weather conditions of the unmanned aerial vehicle; the unmanned aerial vehicle collects video data in real time through high-definition camera equipment in the patrol process, target detection is conducted through a deep learning model, and potential safety hazards such as personnel gathering and vehicle abnormity are recognized; detecting violent conflicts and illegal intrusion behaviors in combination with a time sequence analysis algorithm, and generating an abnormal event report; cooperative work of the unmanned aerial vehicle, the ground robot and the command center is realized; and a patrol scheme is dynamically adjusted according to meteorological conditions, and robot scheduling is optimized through energy consumption management.

The invention provides a real-time disaster situation multi-dimensional verification alarm method and system based on a large model, and relates to the technical field of disaster situation response, and the method comprises the steps: carrying out the backtracking and calling of multi-source disaster situation associated data after a disaster situation early warning signal is received, and obtaining a heterogeneous disaster situation data set; starting a dynamic task chain scheduling mechanism, executing multi-priority thread trend analysis, and outputting a multi-dimensional index analysis result; executing multi-dimensional index cross verification, and outputting a disaster verification conclusion; disaster decision making is carried out, and a disaster decision instruction is generated; carrying out township-level disaster situation grid positioning, and outputting a disaster boundary coordinate set; after the thermal rescue target spot is framed, geological disaster avoidance analysis is carried out, and a safety buffer area is positioned; and executing an alarm verification response. The technical problems that in the prior art, a disaster monitoring and early warning system mainly depends on a step-by-step reporting mechanism, so that disaster information transmission is lagged, accuracy is lost, and timeliness and accuracy of post-disaster rescue work are affected are solved.

The invention discloses an automobile part intelligent production control and quality early warning system based on an AI model. Comprising a data acquisition module, a production process monitoring module, an AI analysis engine module, an adaptive control module, a quality early warning module, an equipment collaborative scheduling module, a data governance and model training module, a user permission and audit module and a remote operation and maintenance and knowledge precipitation module. According to the system and the method, an artificial intelligence algorithm and an industrial automation control technology are fused, and deep perception, dynamic regulation and control and defect pre-recognition of a production process are realized. The prediction precision of the method is superior to that of a traditional statistical process control method in a plurality of actual production scenes.

The invention relates to the technical field of information management, in particular to a material digital management system and method based on a cloud platform. The method comprises the following steps: acquiring material data; distributing a material storage space by using the material data; receiving an operation message of the storage space, and pushing the operation message to an inventory database; creating a circulation record table and an inventory state table; using the operation message in the inventory database to update a circulation record table, and recording circulation data; automatically updating an inventory state table according to the circulation data so as to determine the material inventory capacity; when the material inventory capacity is lower than or equal to a preset safety inventory threshold value, management early warning information is generated; and when the material inventory capacity is higher than a preset safety inventory threshold value, updating the management safety field of the inventory state table. The material inventory is monitored in real time based on the information management technology, the replenishment information is intelligently generated, inventory dynamic management is achieved, and the material management efficiency is improved.

The utility model provides a kind of light six-axis robot belongs to mechanical hand technical field.It solves the problem of slow start, brake and low response speed of six-axis robot in prior art due to its heavy weight.The utility model includes turbine box, driving arm seat, light driving arm, connecting rod, intermediate seat, driving wrist and forepaw assembly, turbine flange is installed at the top of turbine box, driving arm seat is connected and fixed with turbine box by turbine flange, the inside of light driving arm is hollow structure and the both ends of light driving arm are formed with large connecting seat and small connecting seat respectively, large connecting seat is connected with driving arm seat, the both ends of driving arm seat are fixedly connected with cycloidal reducer and servo motor, servo motor extends motor shaft, and motor shaft is connected with connecting rod transmission shaft, connecting rod lower end is connected with connecting rod transmission shaft, connecting rod is set along the direction of light driving arm, and the other end of connecting rod is connected with the bottom of intermediate seat, side plate is formed on the both sides of intermediate seat, and small connecting seat is connected with side plate.The utility model has the advantages of light weight and compact structure.

The application provides an environment simulation air extraction device cooperative optimization control method and system based on cooperative differential game, comprising the following steps: step 1, a dynamic model of the air extraction device is established. Step 2, the air supplement valve and the plurality of inlet valves are regarded as game participants, and a pressure-pressure ratio multi-objective optimization model based on cooperative differential game is constructed. Step 3, an approximate dynamic programming algorithm-critical neural network is combined to obtain an approximate Pareto optimal solution of the established game optimization model. Step 4, a cooperative optimization controller is designed: the inlet valve adopts PI control combined with a filter and an optimization item to realize cooperative control of pressure and pressure ratio. Step 5, on a multi-compressor parallel simulation platform, various complex working conditions such as valve leakage and compressor failure are set to verify the robustness and superiority of the algorithm. After the application of the technical scheme, the speed, robustness and anti-interference ability of the system based on the cooperative differential game cooperative optimization control algorithm are significantly improved.

The invention discloses a fruit conveying anti-blocking mechanism based on a neural network and a control method. The mechanism comprises a conveying channel, a disturbance disc connected with a motor through a universal joint, a touch sensing array and a gravity self-adaptive floating assembly. According to the mechanism, pressure data of a tactile sensing array on the surface of a disturbance disc are collected through Jetson, and the blockage state is judged in real time through a full-connection neural network; when blockage occurs, the Jetson directly controls the servo motor to change speed, the alternating inertia moment is matched with the gravity of fruits to overcome the resistance of the spring, and the disturbance disc is forced to passively incline around the center of the universal joint, so that the blockage is relieved. By means of the mode of combining motor rotating speed control and mechanical passive inclination, blockage caused by fruit accumulation is effectively damaged, and fruit damage is reduced while rapid dredging is achieved.

This invention provides a method and system for intelligent load control in ammonia synthesis production based on wind and solar forecasting, relating to the fields of energy and chemical production technology. The method includes collecting wind and solar data and ammonia synthesis process data; using a dual-current variational autoencoder combined with a residual connection mechanism to predict power generation curves and process parameter trends; determining process parameter constraints and safety boundaries; establishing a process parameter safety constraint model; obtaining the load adjustment space; generating optimal load commands based on optimization algorithms; and achieving intelligent load control through cascaded PID control. This invention achieves precise dynamic control of the load on ammonia synthesis units, improving wind and solar energy absorption capacity and production efficiency.

The invention provides a drilling machine fault diagnosis, alarm and processing method and device.The method comprises the steps that operation data and logging data of a target drilling machine are obtained, and the operation data comprise at least one of motor torque, motor rotating speed, motor power and motor temperature; the logging data comprises at least one of bit pressure, rotating speed, pumping pressure, well depth and torque; performing timestamp alignment, data normalization, feature cleaning and missing compensation on the operation data and the logging data to construct a unified time sequence multi-modal feature set; and inputting the unified time sequence multi-modal feature set into a pre-trained large language model, performing anomaly diagnosis on the target drilling machine, and outputting an improvement suggestion. According to the scheme, the technical problem that existing drilling machine fault diagnosis is low in efficiency and accuracy is solved, and the technical effect of improving the accuracy, generalization and response speed of drilling machine fault diagnosis is achieved.

The utility model discloses a monitoring device for industrial automation equipment, and belongs to the technical field of monitoring of the industrial automation equipment. The monitoring device for the industrial automation equipment has the advantages of being rapid in disassembly, improving the maintenance efficiency and simplifying the operation process, the connecting plate and the monitoring equipment body can be disassembled by pulling the U-shaped grip towards one side, rapid disassembly and assembly can be achieved without using bolts or tools, the maintenance time is greatly shortened, and the maintenance efficiency is improved. When the monitoring equipment body is overhauled or replaced, an operator can quickly complete the loading and unloading operation, the response speed and the maintenance efficiency of a production line are improved, the loss caused by shutdown maintenance is reduced, and a traditional bolt fixing mode is tedious in operation and needs to be disassembled and assembled with the help of a tool. Therefore, the fixing and releasing of the monitoring equipment body can be completed, the operation is more convenient, and an operator can complete the replacement or maintenance work without professional skills.

The utility model discloses an external wheel forming die's correction mechanism, including base and support column, the support column symmetry fixed junction in base both sides to set up the correction subassembly in the base upper portion, the correction subassembly is used for heating correction to the external wheel, still include the rotating subassembly of setting up between the support column, the rotating subassembly is used for driving the external wheel and carries out the clamping rotation. The utility model belongs to external wheel forming die technical field, and specifically is the correction mechanism of automatic external wheel forming die of real -time monitoring the deviation situation of external wheel and automatic control correction accuracy.

The present application belongs to the technical field of data analysis, and particularly relates to a high-throughput biosensing system for early warning of algal blooms and pathogens, which comprises multiple sampling units, a microfluidic chip with a multi-channel structure, and a high-throughput surface-enhanced Raman detection unit with an integrated metal nanostructure surface, and obtains the original surface-enhanced Raman spectrum of the water sample through a Raman spectrum acquisition mechanism. The system uses compressed spectrum sampling and sparse reconstruction methods to reduce the data volume and maintain the integrity of the spectrum information, constructs a pathogen Raman fingerprint dictionary through a dictionary learning method, and realizes the identification of different algal metabolites, algal toxins and pathogen-related molecular components and the concentration interval judgment thereof in combination with a sparse representation classification mechanism. Based on the type and concentration interval of the pathogens, the system further generates algal bloom risk warning and pathogen risk warning, and realizes early discovery of abnormal changes in the water body. The present application has significant advantages in stability, sensitivity, throughput and real-time performance.

This invention discloses a knowledge- and data-driven time series forecasting method and system, belonging to the field of industrial time series forecasting technology. To address the technical problems of existing technologies when processing strongly non-stationary data, such as key signal attention dilution, systematic underestimation of peak amplitude, incomplete capture of multi-scale dynamic patterns, and difficulty in embedding physical domain knowledge, this invention constructs standardized multi-dimensional time series data, performs heterogeneous feature grouping and parallel encoding to obtain multiple sets of feature representations, then extracts and integrates features from multiple sources to obtain intermediate state features, and finally performs multi-branch prediction and adaptive weighted fusion based on the intermediate state features to obtain the final time series forecast result. This invention can achieve active focusing on abrupt events in industrial sequences and accurate characterization of extreme value amplitudes, significantly improving prediction accuracy, physical consistency, and robustness to extreme conditions.

The utility model discloses a silkworm breeding device capable of automatically controlling temperature and humidity. The silkworm breeding device comprises a silkworm information acquisition device, a data processing module, a data storage module, a display module, a temperature and humidity control module, an environment data acquisition device, a power supply module, an alarm module and a communication module, the silkworm information acquisition device, the data storage module, the display module, the temperature and humidity control module, the environment data acquisition device, the power supply module, the alarm module and the communication module are respectively connected with the data processing module. Through the integrated silkworm information collecting and processing system, the growth stage of silkworms can be automatically recognized, the temperature and humidity are automatically adjusted according to preset parameters, manual intervention is reduced, and the breeding efficiency is improved.

The application provides a kind of operation and maintenance scene visualization report generation method and system based on natural language question and answer, belongs to intelligent operation and maintenance technical field, method includes: receiving the natural language query input by user;Through the pre-training of large language model and the preset operation and maintenance terminology dictionary, the natural language query is parsed and entity is extracted, and the entity-field association table containing demand type is generated;According to demand type and semantic feature, the query type is judged to be data query or visual query;Based on the judgment result, generate structured query language sentence or visual instruction;Query is executed to the interface business database to obtain raw data;Raw data is processed and analyzed to obtain analysis result data;Call data feature adaptation algorithm to match chart type, generate and output visual report.The application realizes the full-link automation from natural language input to visual report output, reduces the operation and maintenance data interaction threshold, improves the operation and maintenance data processing efficiency and accuracy.

This utility model discloses an integrated transition yaw connection system for wind turbines, belonging to the technical field of wind power generation equipment. The system includes a wind turbine tower, a slewing bearing, a short-section cylinder, and a lower platform. The wind turbine tower has a truss-type hollow structure. The short-section cylinder is vertically arranged and its top is welded to the lower platform as a whole. Its bottom is connected to the top of the tower through the slewing bearing. This utility model uses a hierarchical structure of truss tower-slewing bearing-short-section cylinder-platform. It utilizes the short-section cylinder to distribute the nacelle load and compensate for installation errors. Combined with the slewing bearing, it achieves low-friction and stable yaw. This structure effectively solves the problems of heavy self-weight, obvious yaw vibration, complex assembly, and easy wear of connection parts of traditional wind turbine towers. It has the advantages of lightweight, stable yaw, convenient installation, and long service life.

The application discloses a quick-mounting temperature sensor, relates to the technical field of temperature sensors, and comprises a temperature sensor main body, a mounting block integrally connected to the top end of the temperature sensor main body and a plug-in part, the plug-in part is arranged above the mounting block, one side of the mounting block is provided with an arc-shaped mounting groove, both ends of the mounting block are provided with rotating holes, one end of a first connecting rod is rotationally connected to the inside of one of the rotating holes, a fixing piece is fixedly connected to one end of the first connecting rod, the periphery of one of the rotating holes is fixedly connected with a first limiting clamping tooth piece, and a fixing hole is formed in the other end of the first connecting rod. The application can flexibly adjust the mounting angle of the quick-mounting temperature sensor, is suitable for the inclined mounting surface which is not horizontal or vertical, improves the compatibility of mounting, ensures that the temperature sensing end of the sensor always contacts the measured medium at the best angle, and improves the temperature measurement accuracy and response speed.

This application discloses a method, apparatus, storage medium, and product for controlling the current of a charge-and-discharge power supply. The method includes acquiring a target adjustment command, which includes a target current increment. This target current increment is the difference between a first preset current and a second preset current. The first preset current is the target current of the previous adjustment cycle, and the second preset current is the target current of the current adjustment cycle. The method also includes acquiring a voltage increment based on multiple target parameters and the target current increment. These multiple target parameters include the battery electromotive force, battery internal resistance, and line impedance of the charge-and-discharge power supply when it was in a stable state in the previous adjustment cycle. Finally, the method includes acquiring an adjustment amount based on the voltage increment and adjusting the output current of the charge-and-discharge power supply based on the adjustment amount. This method can improve the response speed while ensuring the stability of the output current of the charge-and-discharge power supply.

The application discloses an electric-thermal comprehensive energy system collaborative frequency modulation method and system, the method comprising: obtaining a frequency deviation parameter in an electric power subsystem and a thermal energy storage state parameter in a thermal power subsystem as a real-time frequency modulation parameter; calculating a frequency deviation change rate and combining the real-time frequency modulation parameter to evaluate a thermal energy storage capacity margin value, generating a composite frequency modulation demand index; generating a multi-time scale frequency modulation task; based on the multi-time scale frequency modulation task, generating an electric-thermal weight distribution value by fusing the frequency deviation change rate and the thermal energy storage capacity margin value; generating an electric-thermal collaborative frequency modulation instruction according to the electric-thermal weight distribution value; and executing the electric-thermal collaborative frequency modulation instruction to control frequency modulation devices in the electric power subsystem and the thermal power subsystem. The application adopts a multi-time scale task decomposition and dynamic weight distribution strategy based on a composite frequency modulation demand index, can realize deep collaboration and optimized control of electric-thermal resources, and improves the frequency modulation performance and operation economy of the comprehensive energy system.

The utility model relates to cable production technical field especially is a kind of cable straightening equipment, including mounting plate, mounting plate is provided with two and is symmetrically distributed before and after, the four corners of two mounting plates are all provided with mounting hole, the opposite end of two mounting plates is all fixedly connected with slide rail, straightening mechanism is slidably connected between two mounting plates, two stands are symmetrically fixedly installed in the upper end of the mounting plate located rear part, one end of a stand is fixedly installed with one positive and negative motor, the output of one positive and negative motor is fixedly connected with ball screw, ball screw is screw-connected with the rear part of straightening mechanism. The utility model discloses a kind of cable straightening equipment, reciprocating motion is driven by ball screw straightening mechanism, realize the stable feeding of cable and continuous straightening;While using the multiple straightening wheels of annular distribution, realize automatic adaptation different diameter cable with adjusting disc cooperation, improve straightening efficiency and versatility, applicable to the efficient processing and automatic production of multiple specifications cable.