Complete Performance Evaluation Research Articles

Emergency callback prioritize

The need for performance evaluation of Electric Power Distributors by the National Electric Energy Agency (ANEEL), focusing on service quality, measured through the percentage of emergency occurrences with Power Interruption (PNIE). In response to the challenges faced by distributors in efficiently managing emergency complaints, with attention to reducing services without power interruption. The main objective is to develop an advanced system that optimizes service, establishes precise performance metrics, and reduces operational costs. We have a system that enables analysis, identification, prioritization, and forwarding of occurrences to the teams. Done through the mobile dispatch system, which streamlines communication between operations center operators and field teams. Once the service is completed, it becomes available for the next processing stage, where the data is analyzed and transformed into continuity indicators, providing a detailed view of service performance. Performance evaluation was conducted through meticulously selected metrics, allowing comprehensive analysis of Fuzzy logic, considering the diffuse and uncertain nature of the data. Among these metrics, calculation of the average degree of relevance, analysis of degree of relevance variation, and identification of minimum and maximum relevance stand out, providing a complete and detailed evaluation of model performance. After the initial tool implementation, it was observed that the percentage of unproductive displacement remained on average 40.64% over 12 months. Additionally, a significant increase of 18% in the entry of emergency occurrences was noted, indicating satisfactory initial effectiveness of the tool. Although there is room for additional improvements, these results suggest that we are on the right track in our pursuit of service optimization and continuous process improvement. Finally, the first round of model testing and validation has already shown promising results, indicating significant potential to reduce the percentage of unproductive displacements in the company. Based on solid foundations and previous analyses, it is expected that the model will positively contribute to operational efficiency, being considered a strategy to optimize operations. We are committed to closely monitoring the results to make continuous adjustments and improvements to the system.

Hop to It! A Systematic Review and Longitudinal Meta-analysis of Hop Performance After ACL Reconstruction.

Hop testing is widely used by clinicians to monitor rehabilitation and decide when to return to sport following anterior cruciate ligament reconstruction (ACLR); however, the trajectory of long-term hop performance has not been summarised. To investigate hop performance change over time after ACLR. Systematic review with longitudinal meta-analysis. MEDLINE, EMBASE, CINAHL, Scopus, Cochrane CENTRAL and SPORTDiscus to 28 February 2023. Studies with ≥ 50 participants following primary ACLR, with mean participant age of 18-40years, reporting a quantitative measure of hop performance (e.g. single forward hop distance). Results had to be reported for the ACLR limb and compared with (1) the contralateral limb (within person) and/or (2) an uninjured control limb (between person). We included 136 studies of 23,360 participants. Performance was similar across different hop tests, with steep initial improvements in within-person symmetry, tailing off after 18-24months. ACLR limb hop performance was 5-10% lower compared with the contralateral limb at 1year post-surgery, with largest deficits observed for vertical hop [87.0% contralateral limb (95% CI 85.3-88.8) compared with single forward hop 93.8% (95% CI 92.8-94.9)]. By 3-5years, results were similar between ACLR and contralateral limbs. There were limited data for between-person comparisons (n = 17 studies). Exploratory analyses showed deficits in all forward hopping tests to be very strongly correlated with each other [e.g. single forward and triple hop rho = 0.96 (95% CI 0.90-0.99)], though there was discordance in the relationship between single forward hop and vertical hop performance [rho = 0.27 (95% CI - 0.53 to 0.79)]. Hop performance is comparable to the uninjured limb by 3-5years post-ACLR, with the greatest deficits in within-person symmetry present in vertical and side hop tests. Assessment of hopping in multiple planes and comparison with uninjured controls, may provide the most complete evaluation of functional performance.

Performance Management Decision-Making Model: Case Study on Foreign Language Learning Curriculums

Foreign language learning courses can be regarded as a service operation system, and a complete foreign language learning course performance evaluation model can help improve the effectiveness of student learning. The performance evaluation matrix (PEM) is an excellent tool for evaluation and resource management decision making, and the administrator uses the satisfaction and the importance indices to establish evaluation coordinate points based on the rules of statistical testing. The coordinate points of all service items are plotted into the PEM to grasp the full picture and to make decisions on what to improve or to consider resource transfers so as to elevate the overall satisfaction of the entire service. However, plotting all the coordinate points on the PEM can only be performed by programming, which will lead to limitations in practice. Therefore, instead of the above evaluation rules, this article uses the confidence intervals of decision-making indicators to form a validity evaluation table, to decide which teaching service items should be improved, maintained, or transferred to improve the satisfaction of the entire service system. This form of performance evaluation can be completed using any commonly used word-processing software, so it is easy to apply and promote. Finally, this article provides an applied example to illustrate the proposed method.

A benchmarking protocol for SAR colorization: From regression to deep learning approaches

Synthetic aperture radar (SAR) images are widely used in remote sensing. Interpreting SAR images can be challenging due to their intrinsic speckle noise and grayscale nature. To address this issue, SAR colorization has emerged as a research direction to colorize gray scale SAR images while preserving the original spatial information and radiometric information. However, this research field is still in its early stages, and many limitations can be highlighted. In this paper, we propose a full research line for supervised learning-based approaches to SAR colorization. Our approach includes a protocol for generating synthetic color SAR images, several baselines, and an effective method based on the conditional generative adversarial network (cGAN) for SAR colorization. We also propose numerical assessment metrics for the problem at hand. To our knowledge, this is the first attempt to propose a research line for SAR colorization that includes a protocol, a benchmark, and a complete performance evaluation. Our extensive tests demonstrate the effectiveness of our proposed cGAN-based network for SAR colorization. The code is available at https://github.com/shenkqtx/SAR-Colorization-Benchmarking-Protocol.

Incentive Mechanism for the Development of Rural New Energy Industry: New Energy Enterprise–Village Collective Linkages considering the Quantum Entanglement and Benefit Relationship

As an important foundation of and driving force for rural revitalisation, green and low-carbon energy development is an intrinsic requirement for meeting the people’s needs. Rural energy utilization efficiency is low, and there is an urgent need to develop and use renewable green energy. Therefore, the purpose of this study is to explore and clarify the entanglement mechanism between new energy enterprises (NEEs) and village collectives (VCs) considering the mutually beneficial evolutionary stability strategy of the main participants in the rural new energy industry (RNEI) regarding the quantum entanglement state. The quantum evolutionary game model for NEEs and VCs was constructed, and a set of quantum strategies of both parties was introduced. This not only expands the strategy set of the classical game model but also considers the characteristics of quantum entanglement in the implementation of the quantum game. This study also analysed the evolution path and stability strategy of participants in the process of RNEI’s development. The results of this study are presented as follows: (i) after considering the entanglement of states, it is easier to adopt the complete quantum strategy to realize the complete incentive situation that “income increases with the increase of one’s own efforts,” which is conducive to the development of the RNEI. (ii) Observable and quantifiable performance indicators are of greatest importance. Both parties involved in the development of the RNEI should make relevant information open and transparent to promote the smooth implementation of the RNEI development process. (iii) The signing of the “entanglement contract” requires a scientific, complete, specific, and quantifiable performance evaluation system to be established by a professional and independent third-party organization. The study not only makes a certain theoretical contribution to clarifying the mechanism of entanglement between NEEs and village collectives but also provides a theoretical basis for scientific and effective cooperation between NEEs and village collectives.

Establishing a quality assurance program for photon counting detector (PCD) CT: Tips and caveats.

To determine the suitability of a quality assurance (QA) program based on the American College of Radiology's (ACR) CT quality control (QC) manual to fully evaluate the unique capabilities of a clinical photon-counting-detector (PCD) CT system. A daily QA program was established to evaluate CT number accuracy and artifacts for both standard and ultra-high-resolution (UHR) scan modes. A complete system performance evaluation was conducted in accordance with the ACR CT QC manual by scanning the CT Accreditation Phantom with routine clinical protocols and reconstructing low-energy-threshold (T3D) and virtual monoenergetic images (VMIs) between 40 and 120keV. Spatial resolution was evaluated by computing the modulation transfer function (MTF) for the UHR mode, and multi-energy performance was evaluated by scanning a body phantom containing four iodine inserts with concentrations between 2 and 15mg I/cc. The daily QA program identified instances when the detector needed recalibration or replacement. CT number accuracy was impacted by image type: CT numbers at 70keV VMI were within the acceptable range (defined for 120kV). Other keV VMIs and the T3D reconstruction had at least one insert with CT number outside the acceptable range. The limiting resolution was nearly 40 lp/cm based on MTF measurements, which far exceeds the 12 lp/cm maximum capability of the ACR phantom. The CT numbers in the iodine inserts were accurate on all VMIs (3.8% average percentage error), while the iodine concentrations had an average root mean squared error of 0.3mg I/cc. Protocols and parameters must be properly selected on PCD-CT to meet current accreditation requirements with the ACR CT phantom. Use of the 70keV VMI allowed passing all tests prescribed in the ACR CT manual. Additional evaluations such an MTF measurement and multi-energy phantom scans are also recommended to comprehensively evaluate PCD-CT scanner performance.

A collaborative auditing scheme with dynamic data updates based on blockchain

Cloud data auditing is essential to ensure the integrity of cloud data. The main idea of cloud auditing is to entrust the audit task to a third-party auditor (TPA) with powerful computing ability. However, TPA may lead to data leakage and become the single point of failure. Recently, blockchain has been introduced to solve these problems by TPA. However, the dynamic storage structure developed by traditional cloud storage does not apply to the blockchain. This paper proposes a blockchain-based collaborative public auditing scheme for dynamic data. We design the cloud service provider(CSP) to generate a challenge set using the latest block hash. It does not need to interact with the blockchain in the challenge phase, dramatically reducing communication overhead. In addition, considering economic factors, we allow users to seek partners to reduce audit costs. The EigenTrust model evaluates the reputation of each user's audit behaviour, effectively avoiding the probability of malicious users participating. For data update, we introduce the Pseudo Index Linked List(PIL) index management structure, which reduces the size of the index management structure to adapt to the blockchain's characteristics and makes the update operation have a constant time complexity. Through a complete security analysis and performance evaluation, we proved the security and effectiveness of the scheme.

DANTE Digital Pulse Processor for XRF and XAS experiments

DANTE is a new Digital Pulse Processor (DPP) developed for fluorescence detectors, like Silicon Drift Detectors (SDDs) or High Purity Germanium detectors (HPGe), used in X-ray Fluorescence (XRF) and X-ray Absorption Spectroscopy (XAS) experiments at synchrotron facilities. Its main features are its optimal energy resolution and peak stability for detector count rate values up to 1–2 Mcps, and its enhanced rejection of pile-up events. In this paper, we present the first complete evaluation of DANTE performance in SOLEIL synchrotron facility. DANTE has been tested in laboratory with an X-ray generator source and in different experiments at LUCIA and PUMA beamlines at SOLEIL.

Determining the Thermal Resistance of Enclosed Reflective Airspace

Enclosed airspaces of various effective emittances exist in the building envelope in walls, roofs, and double/triple glazing windows, curtain walls and skylight devices. Assessing the energy performance of a building component with enclosed reflective airspaces requires evaluation of all modes of heat transport inside the airspace. The thermal resistance (R-value) of the enclosed airspaces depends on the dimensions and orientation of the airspace, and the emittance and temperature of all surfaces that bound the airspace. To the best of our knowledge, the existing methods used around the world to evaluate the airspace thermal performance (e.g., ISO 6946, AUS/NZ 4859, and methods based on the U.S. NBS data) are one-dimensional and assume isothermal conditions on the hot and cold surfaces. In actual applications, however, the temperatures of both the hot and cold surfaces vary (i.e., they are non-isothermal), and the heat transfer takes place via conduction, convection and surface-to-surface radiation. In some cases, convection is absent or negligible, as is the case for downward heat flow or situations with a small temperature difference between the hot and cold surfaces. Radiation transport is significantly reduced by the presence of a low-emittance surface in the heat flow path. One of the goals of this study is to answer the question “is it a good assumption to use the isothermal conditions on both the hot and cold surfaces for determining/reporting the R-value of enclosed airspaces for different building applications?” A complete evaluation of the thermal performance of enclosed airspaces that includes the impact of bounding materials can now be undertaken in multiple dimensions with convective transport described by computational fluid dynamics. In addition to providing a relatively complete evaluation of the thermal performance of the enclosed airspaces, the adequacy of popular simplifying assumptions can be evaluated. This paper describes the computational process used, along with examples of the variation in thermal resistance with the airspace aspect ratio, realistic thermal boundary conditions and radiative heat transport on all surfaces that bound the airspace. The analysis completed in this research shows that the assumption of isothermal hot and cold surfaces affects calculated R-values for enclosed reflected airspaces by less than 3%. This was demonstrated for the five conventionally considered heat-flow directions and effective emittances from 0 to 0.82.

Vicarious CAL/VAL Approach for Orbital Hyperspectral Sensors Using Multiple Sites

The hyperspectral (HSR) sensors Earth Surface Mineral Dust Source Investigation (EMIT) of the National Aeronautics and Space Administration (NASA) and Environmental Mapping and Analysis Program (EnMAP) of the German Aerospace Center (DLR) were recently launched. These state-of-the-art sensors have joined the already operational HSR sensors DESIS (DLR), PRISMA (Italian Space Agency), and HISUI (developed by the Japanese Ministry of Economy, Trade, and Industry METI and Japan Aerospace Exploration Agency JAXA). The launching of more HSR sensors is being planned for the near future (e.g., SBG of NASA, and CHIME of the European Space Agency), and the challenge of monitoring and maintaining their calibration accuracy is becoming more relevant. We proposed two test sites: Amiaz Plain (AP) and Makhtesh Ramon (MR) for spectral, radiometric, and geometric calibration/validation (CAL/VAL). The sites are situated in the arid environment of southern Israel and are in the same overpass coverage. Both test sites have already demonstrated favorable results in assessing an HSR sensor’s performance and were chosen to participate in the EMIT and EnMAP validation stage. We first evaluated the feasibility of using AP and MR as CAL/VAL test sites with extensive datasets and sensors, such as the multispectral sensor Landsat (Landsat5 TM and Landsat8 OLI), the airborne HSR sensor AisaFENIX 1K, and the spaceborne HSR sensors DESIS and PRISMA. Field measurements were taken over time. The suggested methodology integrates reflectance and radiometric CAL/VAL test sites into one operational protocol. The method can highlight degradation in the spectral domain early on, help maintain quantitative applications, adjust the sensor’s radiometric calibration during its mission lifetime, and minimize uncertainties of calibration parameters. A PRISMA sensor case study demonstrates the complete operational protocol, i.e., performance evaluation, quality assessment, and cross-calibration between HSR sensors. These CAL/VAL sites are ready to serve as operational sites for other HSR sensors.

A study of university procurement performance based on big data on government procurement

The scale of government purchases in colleges and universities has been growing as a result of the elevated importance China has given to education. Investments in scientific research and education have also expanded dramatically. Most universities currently pay little attention to performance evaluation in government procurement work, do not fully complete government procurement performance evaluation work, or are still in the mapping stage of government procurement performance evaluation. As a result, the performance evaluation index is comparatively small. In this paper, we establish a government procurement performance evaluation system for universities in combination with big data on government procurement, and we put forward recommendations for universities to further improve the performance management of government procurement. We do this by analyzing the current situation of government procurement in contemporary universities and the shortcomings in the performance evaluation work of S colleges and universities.

SealFSv2: combining storage-based and ratcheting for tamper-evident logging

Tamper-evident logging is paramount for forensic audits and accountability subsystems. It is based on a forward integrity model: upon intrusion, the attacker is not able to counterfeit the logging data generated before controlling the system. There are local and distributed solutions to this problem. Distributed solutions are suitable for common scenarios, albeit not appropriate for autonomous and loosely connected systems. Moreover, they can be complex and introduce new security issues. Traditional local tamper-evident logging systems use cryptographic ratchets. In previous works, we presented SealFS (from now on, SealFSv1), a system that follows a radically different approach for local tamper-evident logging based on keystream storage. In this paper, we present a new version, SealFSv2, which combines ratcheting and storage-based log anti-tamper protection. This new approach is flexible and enables the user to decide between complete theoretical security (like in SealFSv1) and partial linear degradation (like in a classical ratchet scheme), exchanging storage for computation with user-defined parameters to balance security and resource usage. We also describe an implementation of this scheme. This implementation, which showcases our approach, is an optimized evolution of the original sealfs Linux kernel module. It implements a stackable file system that enables transparent tamper-evident logging to all user space applications and provides instant deployability. Last, we present a complete performance evaluation of our current implementation and a fair performance comparison of the two opposite approaches for local tamper-evident logging (i.e., storage-based vs. ratcheting). This comparison suggests that, on current systems and general-purpose hardware, the storage-based approach and hybrid schemes perform better than the traditional ratchet approach.

A Fuzzy Improvement Testing Model of Bank APP Performance

Numerous studies have pointed out that the issue of global warming is getting increasingly more serious. Therefore, the concepts of circular economy (CE) and sharing economy have been more and more valued by enterprises and governments. With the gradual popularization and maturity of the Internet of Things (IoT), various smart APP platforms have sprung up rapidly. For example, the fuzzy evaluation model of bank APP performance was proposed in such an environment, aiming to improve the APP service performance by means of evaluating, analyzing, improving, and enhancing customers’ satisfaction with their use of APPs, and increasing the number of users of APPs. Since the follow-up of the article did not mention the improved testing model used to verify the improvement effect, this paper then proposed a fuzzy two-tailed testing model with two indices before and after the improvement based on the confidence interval to verify whether the improvement has had a significant effect. This complete bank APP fuzzy performance evaluation, analysis, and improvement model measured the bank APP operation performance using customer time intervals, so the data collection time was short. Not only can it meet enterprises’ need for rapid response and grasp the opportunity for improvement to achieve the effect of energy-saving and carbon reduction, but it also can satisfy enterprises’ requirement to pursue fast and accurate decision-making. Furthermore, the fuzzy two-tailed test proposed by this paper was based on the confidence interval, which can reduce the risk of misjudgment caused by sampling error. Plenty of studies have indicated that the designs based on confidence intervals can integrate expert experience and past data so that the accuracy of testing can be maintained in the case of small-sized samples.

Probabilistic evaluation of post-earthquake functional recovery for a tall RC core wall building using F-Rec framework

This paper presents a detailed evaluation of the functional recovery of a 42-story reinforced concrete core wall building located at a site of high seismicity using a newly developed, fully probabilistic, and comprehensive analytical framework for the assessment of post-earthquake functional recovery of buildings. This innovative framework allows complete and detailed evaluation of the seismic performance of tall buildings considering all structural and nonstructural building components/systems, and the calculation of performance metrics relevant for the assessment of functional recovery, including building’s post-earthquake functionality along with the duration and path of functional recovery. A nonlinear model of the building is created in OpenSees using a recently developed three-dimensional macro model for RC walls. Building seismic response is obtained for three seismic hazard levels corresponding to Service-Level Earthquake (SLE), Design-Based Earthquake (DBE), and Maximum Considered Earthquake (MCE). Based on the results of nonlinear analyses, damage-impaired losses are calculated using FEMA P-58 tools, while the building recovery process is evaluated using a novel framework for functional recovery (F-Rec framework). Building seismic performance obtained using new, advanced structural and recovery models suggest that the post-earthquake functionality of the tall building is primarily governed by the structural subsystem. In particular, for SLE, the functionality of the building is compromised mostly due to the damage to shear walls resulting in 3 to 6 months of functional recovery time (FRT); for DBE, the building’s functionality is fully impaired due to significant damage to slab-column connections and shear walls (FRT = 8 to 13 months); and for MCE, the building’s functionality is fully impaired due to significant damage to slab-column connections, shear walls, coupling beams, and partition walls (FRT = 12 to 16 months). Given the great contribution of tall buildings to community resilience, this study reveals a need for the development of design requirements for improving the post-earthquake functionality of tall buildings.

An integrated mathematical method for traffic analysis of elevator systems

The present study proposes a new analytical method for traffic analysis of modern elevator systems. The method analyzes probabilistically the complete operation of any configuration of modern directional collective elevator systems, for any combination of building type and architecture and passenger traffic pattern and demand. It presents very low computational cost and it produces results that can be used for a complete evaluation of the service performance and for a further detailed energy consumption analysis of the elevator system being analyzed.The method is structured in four discrete calculation modules that have been programmatically implemented and cooperate through a numerical iterative procedure that converges providing the final average operation state of the elevator system.

Measuring Cannulation Skills for Hemodialysis: Objective Versus Subjective Assessment.

Lack of cannulation skill during hemodialysis treatments results in poor clinical outcomes due to infiltration and other cannulation-related trauma. Unfortunately, training of patient care technicians and nurses, specifically on the “technical” aspects of cannulation, has traditionally not received much attention. Simulators have been successfully deployed in many medical specialties for assessment and training of clinical skills. However, simulators have not been as widely used in nursing, especially in the context of training clinical personnel in the dialysis unit. We designed a state-of-the-art simulator for quantifying skill for hemodialysis cannulation. In this study, 52 nurses and patient care technicians with varying levels of clinical experience performed 16 cannulations on the simulator with different fistula properties. We formulated a composite metric for objectively measuring overall success of cannulation and compared this metric with subjective assessment by experts. In addition, we examined if years of clinical experience correlated with objective and subjective scores for cannulation skill. Results indicated that, while subjective and objective metrics generally correlated with each other, the objective metric was more precise and better suited for quantifying cannulation skill. Further, the simulator-based objective metric provides several advantages over subjective ratings, including providing fine-grained assessment of skill, consistency in measurement unaffected by subjective biases, and basing assessment on a more complete evaluation of performance. Years of clinical experience, however, demonstrated little correlation with either method of skill assessment. The methods presented for cannulation skill assessment in this study, if widely applied, could result in improved cannulation skill among our PCTs and nurses, which could positively impact patient outcomes in a tangible way.

An adaptive core mapping algorithm on NoC for future heterogeneous system-on-chip

The mapping analysis needs to have a complete performance assessment of Network-on-Chip (NoC) based on delay, throughput, and energy consumption measurements. This paper proposes an Adaptive Core Mapping (ACM) algorithm, which can dynamically react and recover from the failed core through spare core replacement to maintain system functionality. The core mapping methodology considered the complete performance evaluation for different routing algorithms. Mapping simulations executed on the NoC Simulator (Noxim), adjusted to perform a re-enactment for various routing algorithms, such as XY, WEST-FIRST, NORTH-LAST, and ODD-EVEN routings. A significant improvement observed in energy consumption, average delay, and throughput in the proposed work compared with existing algorithms. The proposed adaptive core mapping algorithm is synthesized and simulated using Vivado Design Suite 2018.3 and verified on the Kintex-7 FPGA KC705 board. The performance parameters, such as area, power consumption, and throughput, are obtained. The results show that the proposed algorithm is helpful for less area, power consumption, and high-speed applications in the NoC environment.

NB-IoT and LTE-M towards massive MTC: Complete performance evaluation for 5G mMTC

Since the emerging 5G wireless network is expected to significantly revolutionize thefield of communication, its standardization and design should regard the internet ofthings (IoT) among the main orientations. Also, emerging IoT applications introducenew requirements other than throughput to support massive machine-type commu-nication (mMTC) where small data packets are occasionally sent. Therefore, moreimportance is attached to coverage, latency, power consumption, and connection den-sity. For this purpose, the third generation partnership project (3GPP) has introducedtwo novel cellular IoT technologies supporting mMTC, known as NB-IoT and LTE-M. This paper aims to determine the system configuration and deployment required forNB-IoT and LTE-M technologies to fully meet the 5G mMTC requirements in termsof coverage, throughput, latency, battery life, and connection density. An overview ofthese technologies and their design principles is also described. A complete evalua-tion of NB-IoT and LTE-M performance against 5G mMTC requirements is presented,and it is shown that these requirements can be met but only under certain conditionsregarding system configuration and deployment. This is followed by a performancecomparative analysis, which is mainly conducted to determine the limits and suitableuse cases of each technology.

Performance evaluation of aerospace relay based on evidential reasoning rule with distributed referential points

In current researches of performance evaluation with evidential reasoning (ER) rule, the referential points of evidence are generally set as a quantitative value or an interval value. However, these two types cannot handle fuzzy uncertainty and probabilistic uncertainty simultaneously, which decreases the evaluation accuracy. In this paper, a new ER rule-based performance evaluation model for aerospace relay with distributed referential points is proposed. Firstly, in order to effectively embed the expert knowledge and capture the performance information, the Gaussian distribution is used to describe the referential points. Secondly, a complete performance evaluation model is constituted by calculating and optimizing the evidence parameters. Finally, the sensitivity analysis is performed on the model to locate the weak component of aerospace relay. A case study of the JRC-7 M aerospace relay is carried out to validate the effectiveness of the proposed model.

Understanding Short Text Through Lexical Semantic Analysis

Information of quick texts is crucial for many packages however there are many demanding situations. First, the fast texts do not constantly look at a written language’s syntax. As a end result, traditional natural language processing gear cannot be without problems applied, ranging from element-of-talk tagging to dependency parsing. second, brief texts usually do now not incorporate sufficient statistical signals to help a few of the state of play Thirdly, short texts are greater ambiguous land noisier, land are generated in a big quantity, which further will increase the problem of coping with them. We argue that semantic knowledge is important for better understanding of brief texts. on this paintings, we build a prototype gadget for short text expertise that takes advantage of semantic expertise furnished by using a famous know-how base and harvests it automatically Our methods for responsibilities which includes text segmentation, component-of-speech tagging, and idea labeling, inside the feel that during these kind of duties we awareness on semantic. We perform a complete evaluation of the overall performance on actual-existence facts. The outcomes display that semantic information is critical for the understanding of quick texts and our information-intensive technique.