Reasonable Time Research Articles

Patient Experience With Resident Versus Staff Physicians: Results From a Cross-Sectional Patient Survey From Canadian Family Medicine Residencies.

We compared experiences of patients who reported usually being seen by a resident with those usually seen by a staff physician. We analyzed responses to a patient experience survey distributed at 13 family medicine teaching practices affiliated with the University of Toronto between May and June 2020. We analyzed responses to seven questions pertaining to timely access, continuity, and patient-centeredness. We compared responses between two types of usual primary care clinicians and calculated odds ratios before and after adjustment for patient characteristics. We analyzed data from 6,545 unique surveys; 18.6% reported their usual clinician was a resident physician. Resident patients were more likely to be older, born outside of Canada, report a high school education or less, and report having difficulty making ends meet. Compared to patients of staff physicians, patients of resident physicians had lower odds of being able to see their preferred primary care clinician and lower odds of getting nonurgent care in a reasonable time. They also had lower odds of reporting patient-centered care, but we found no significant differences in whether the time for an urgent appointment was about right or whether accessing care after hours was easy. In our setting, patients who reported usually seeing resident physicians had worse continuity of care and timeliness for nonurgent care than patients who reported usually seeing staff physicians despite resident patients being older, sicker, and having a lower socioeconomic position. Postgraduate training programs need to test models to support access and continuity for resident patient panels.

In situ Diazonium Salt Formation and Photochemical Aryl-Aryl Coupling in Continuous Flow Monitored by Inline NMR Spectroscopy.

A novel class of diazonium salts is introduced for the photochemical aryl-aryl coupling to produce (substituted) biphenyls. As common diazonium tetrafluoroborate salts fail, soluble and safe aryl diazonium trifluoroacetates are applied. In this mild synthesis route no catalysts are required to generate an aryl-radical by irradiation with UV-A light (365 nm). This reactive species undergoes direct C-H arylation at an arene, forming the product in reasonable reaction times. With the implementation of a continuous flow setup in a capillary photoreactor 13 different biphenyl derivatives are successfully synthesized. By integrating an inline 19F-NMR benchtop spectrometer, samples are reliably quantified as the fluorine-substituents act as a probe. Here, real-time NMR spectroscopy is a perfect tool to monitor the continuously operated system, which produces fine chemicals of industrial relevance even in a multigram scale.

Злоупотребление процессуальными правами и реализация дискреционных прав властными субъектами в досудебном производстве: понятие и соотношение

In the course of pre-trial proceedings, government entities are authorised to carry out procedural actions and make decisions, most of which are determined as a result of an assessment of the sufficiency of the grounds and conditions for this, based on internal conviction. Sometimes the discretionary rights of such participants are difficult to assess from the point of view of the validity and sufficiency of the information (evidence) available in the audit materials or the criminal case. This leads to appeals against the actions and decisions of officials as having been carried out with abuse of procedural authority. But can this right be abused? To answer this question, it is necessary to clarify the essence of abuse of procedural rights and determine their relationship with discretionary ones. In the course of the study, by analysing the available approaches and practices of applying the norms of the Criminal Procedure Code, it is concluded that an intentional dishonest act under the guise of the exercise of one’s procedural rights by a government entity, excluding the subsequent proper exercise by other participants in criminal proceedings of their procedural rights or their procedural duties within a reasonable time, should entail procedural, disciplinary or criminal liability depending on the consequences and be regarded as abuse. Abuses of the right by the prosecutor and the person in charge of the criminal case to timely grant the status of a participant, to charge, to cancel procedural decisions, during investigative actions, and when choosing measures of criminal procedural coercion have been identified and considered in relation to discrete powers. Some ways to overcome such abuses are presented.

Reflectance characterization of Starlink-like satellite with HELIOS brightness testing facility

The HELIOS (High Efficiency Light Intensity Observation System) project addresses the issue of excessive brightness from LEO satellite constellations. The system aims to develop a reflectance model of a satellite prior to launch, enabling the validation of compliance with astronomer guidelines, which suggest a minimum magnitude of 7. This ensures that the constellation is not visible to the naked eye and does not excessively interfere with astronomical observations. Additionally, the reflectance model obtained can be used for attitude determination by comparing the light curves with those obtained from observations. This application extends to Space Traffic Management, debris reentry prediction, and active debris removal. The system utilizes a light source consisting of 14 high-power LEDs with different wavelengths that replicate the solar spectrum. The light is positioned on an arc and can slide along a rail, allowing sampling at various angles. The arc itself can rotate on its axis, enabling the placement of the light source at any point on the hemisphere. At the center of the hemisphere, a scaled 3D printed model of the satellite under study is placed, with surface finishes resembling the actual satellite. Creating models with varying levels of detail permits to assess their impact on the reflectance model. Finally, the robotic arm Arm4NDO (Arm For Near Distance Observations) permits the movement of a high-efficiency quantum camera mounted at its end across the entire hemisphere’s surface for data acquisition. The camera records a video, stopping at points of interest for capturing frames. To strike a balance between continuous data acquisition and reasonable testing times, both the light source and capture points are positioned every 15° in elevation and azimuth. The initial test campaign aimed to determine optimal camera settings (exposure, aperture, and ISO) to achieve good model visibility and a dark background. Preliminary tests focused on Starlink’s chassis and the most significant observation configurations. Frames of interest were extracted from the videos, and their luminous flux (sum of pixel intensity values) was derived. With the obtained data, curves normalized relative to the maximum were plotted, allowing for a comparison of flux variations among different configurations.

Big data clustering based on spark chaotic improved particle swarm optimization

In recent years, the surge in continuously accelerating data generation has given rise to the prominence of big data technology. The MapReduce architecture, situated at the core of this technology, provides a robust parallel environment. Spark, a leading framework in the big data landscape, extends the capabilities of the traditional MapReduce model. Coping with big data, especially in the realm of clustering, requires more efficient techniques. Meta-heuristic-based clustering, known for offering global solutions within reasonable time frames, emerges as a promising approach. This paper introduces a parallel-distributed clustering algorithm for big data within the Spark Framework, named Spark, chaotic improved PSO (S-CIPSO). Centered on particle swarm optimization (PSO), the proposed algorithm is enhanced with a chaotic map and an efficient procedure. Test results, conducted on both real and artificial datasets, establish the superior performance and quality of clustering results achieved by the proposed approach. Additionally, the scalability and robustness of S-CIPSO are validated, demonstrating its effectiveness in handling large-scale datasets.

Orthogonal systems based stable estimator for non parametric regression problems

. In this work, we study a univariate as well as a multivariate Jacobi polynomial-based estimator for solving the fundamental problem of non parametric (NP) regression. The proposed NP regression estimator aims to approximate a possibly very low regular regression function from the knowledge of its noised values given at some n random sampling points. We first study the univariate version of the proposed estimator, then extend this study to the general multivariate case with random sampling vectors drawn according to an unknown distribution. Our proposed estimator has the advantage of being stable with reasonable time complexity. Moreover, it has an optimal convergence rate under the weak condition that the regression function has a certain low Sobolev smoothness property. Although the proposed estimators are studied under the hypothesis that the random sampling vectors are supported on the d dimensional unit hypercube, by applying trivial transformations, the results of this work are still valid in the more general setting of any d dimensional hyperrectangle. Finally, the theoretical results of this work are illustrated by some numerical simulations on synthetic as well as real datasets.

Analysis of Fluid-Injection-Induced Seismicity Using a Dynamic Sliding Model Incorporating the Rate- and State-Dependent Friction Law

Summary Earthquakes can be triggered by fluid injection into underground formations. Fluid injection can cause large changes in the underground volume that exert stresses on nearby preexisting faults, leading to seismic activity. Assuming an increase in underground development activities in the future, our understanding of the mechanism underlying induced seismicity must be improved, and methods must be developed to properly assess the risk of seismic events. The objective of this study is to develop a seismicity prediction model that calculates the magnitude and timing of triggered earthquakes or seismic events occurring during various subsurface fluid injection activities. We developed an injection-induced seismicity analysis model that predicts the dynamic earthquake nucleation caused by changes in stress and pore pressure that occur during various subsurface activities. The governing equations consisting of the dynamic motion of the poroelastic spring-slider system, rate and state friction laws and pore pressure diffusion equation were solved using the embedded semi-implicit Runge-Kutta (SIRK) method. The dynamic sliding model was also incorporated into the finite element method (FEM) model, considering the variations in the stresses and pore pressures in the formation. A field case study was also conducted to compare the model results with typical microseismicity responses observed from hydraulic fracturing treatments in shale fields. Contrary to the popular understanding derived from Amonton’s law, the dynamic friction model revealed that a large normal stress on the fault leads to rapid sliding. A larger normal stress accumulates a large amount of elastic energy until it slips owing to fluid injection, nucleating large seismic waves. The poroelastic spring-slider model estimated reasonable microseismic magnitudes for hydraulic fracturing treatment but overestimated the time required to trigger a microseismic event under field conditions. To improve the analysis results, the poroelastic spring-slider model was coupled with a linear elastic FEM that considered the complex interplay of stress changes from hydraulic fracturing and the associated pore pressure variation in the formation. Compared with the field data, the coupled simulation model estimated a reasonable timing for the induced microseismic events when the increasing pore pressure during hydraulic fracturing penetrated deep into the formation. These findings suggest the existence of permeable natural fractures in the formation, which intensify early frictional sliding during treatment. The seismicity prediction model presented in this study simulates the magnitude and timing of seismic nucleation, helping to manage and mitigate the environmental impacts of induced seismicity during various subsurface development activities, such as oil and gas extraction, hydraulic fracturing, geothermal, and carbon dioxide sequestration. Moreover, the case study results imply that the time series of seismic events predicted by the model can be used to understand the possible fracture geometry and extent of fluid invasion for field applications. Key Terms and Phrases induced seismicity, subsurface fluid injection, rate- and state-dependent friction law, embedded semi-implicit Runge-Kutta method, finite element analysis

Cost and response time optimization of edge architectures

The cloud service provider market has recently expanded its offerings by providing edge as a service. This involves offering resources equivalent to those already available in the cloud, but through data centers located closer to the end user, with the goal of improving service latencies. Application providers face the challenge of selecting appropriate resources, both from the edge and cloud, to deploy their applications in a way that minimizes deployment costs while satisfying latency requirements. This paper presents Edarop (EDge ARchitecture OPtimization), an innovative orchestration mechanism for the optimal allocation of virtual machines in geographically distributed edge and cloud infrastructures. Edarop is capable of handling different edge and cloud vendors, each offering various types of VMs in different regions, with different prices, and network latencies. It also supports multiple simultaneous applications with different latency requirements and load profiles. Edarop employs Integer Linear Programming (ILP) to ensure the globally optimal solution within a reasonable time frame for the considered use cases. Several variants of the mechanism are provided, depending on whether the objective is to minimize cost, response times, or both. These variants are compared to each other and to alternative approaches, with the results showing that, unlike other methods, Edarop consistently respects latency constraints while minimizing the proposed objectives.

Research on Large Language Model for Coal Mine Equipment Maintenance Based on Multi-Source Text

The efficient management and utilization of coal mine equipment maintenance knowledge is an indispensable foundation for advancing the establishment of intelligent mines. This knowledge has problems such as scattered, low sharing, and insufficient management, which restricts the development of coal mine intelligence. For the above-mentioned problems, a large language model for the maintenance of coal mine equipment based on multi-source text (XCoalChat) was proposed to better manage and utilize the existing massive knowledge of coal mine equipment maintenance. The dataset of coal mine equipment maintenance based on ReliableCEMK-Self-Instruction was constructed to obtain a wide and diverse amount of knowledge through sample generation. Aiming at the illusory problem of the large language model, a knowledge graph enhancement method based on the “Coal Mine Equipment Maintenance System—Full Life Cycle—Specification” was proposed to improve the knowledge density. A triple-LoRA fine-tuning mechanism and DPO direct preference optimization method were introduced into the top of the baseline model, which guarantees that XCoalChat can handle multiple Q&A and maintenance decision analysis tasks with limited computing power. Compared with ChatGLM, Bloom, and LLama, the comprehensive assessment of XCoalChat was performed by experiments including coal mine dialog consulting, coal mine professional consulting, and maintenance decision analysis. The results showed that XCoalChat achieved the best response accuracy in professional consulting and maintenance decision analysis; XCoalChat also took the least reasoning time on average. XCoalChat outperformed other mainstream large language models, which verify that XCoalChat is an effective large language model in the field of coal mine equipment maintenance.

The sexual function of female medical staff at Nam Dinh General Hospital in 2023

Objective: To describe female sexual function among health care workers at Nam Dinh Provincial General Hospital in 2023 and analyze some factors related to female sexual dysfunction in them Methods: A Cross-sectional descriptive study was used on 312 female medical staff at Nam Dinh Provincial General Hospital in 2023. Results: The percentage of female sexual dysfunction among healthcare workers is 42.95%. The female sexual dysfunction forms from highest to lowest are decreased desire (55.77%), decreased excitement (54.17%), lack of vaginal lubrication (50.64%), dissatisfaction ( 49.04%), difficulty achieving orgasm (47.76%), and pain during intercourse (38.78%). Some factors related to female sexual dysfunction found in the study were age, occupation, education level, housing status, and health status of the research subjects (p<0.05). Conclusion: The overall rate of sexual dysfunction among female medical staff at Nam Dinh Provincial General Hospital is relatively high. Therefore, measures for improvement are much needed. For example psychological counseling in periodic health checks, reasonable working time arrangements, and human resources arrangements. Keywords: Function, medical staff, Nam Dinh.

Some Aspects of the Genesis of Evaluation Categories

The article is devoted to the study of evaluation categories in historical retrospect. The author draws attention to the formal certainty of legal norms. He emphasizes that the effectiveness of the application of legislation largely depends on the clarity and accuracy of the interpretation of legal norms. At the same time, both in the history of law and in modern conditions, the use of exclusively certain terms in legal regulation does not allow for full regulation of constantly changing social relations. In this regard, the legislator, due to objective necessity, is forced to apply concepts of a more abstract content. The article provides examples of such a method of legal regulation in various sources of law, starting with the norms of Ancient Babylon and Ancient Rome. The author analyzes such concepts as severe punishment, great sin, unfair execution, good faith, reasonable time, etc. The article draws attention to the expansion of this method of legal regulation and its extension from the sphere of private legal regulation to the public sphere. Based on the analysis, conclusions are drawn regarding the role and importance of evaluation categories in the legal system. It is emphasized that historical experience shows that the mechanism of legal regulation will not be effective without the use of evaluation categories.

Aplicación de la prisión preventiva y su prolongación

The current research work aims to determine whether preventive detention and its extension are currently being applied under strict compliance with the regulations (Articles 268º and 274º of the CPP) by those involved (Public Ministry – Judiciary), without violating fundamental rights of the accused, for this; The basic descriptive level research methodology with a qualitative approach was also used; It has a research design based on thematic analysis, the interview guide, documentary guide, magazines and research papers were used as tools. The result has been that preventive detention and its extension are being applied as an early sentence and due to political or media pressure or extensive interpretations of the established budgets. It is concluded that its application violates fundamental rights such as the right to freedom, presumption of innocence, to be tried within a reasonable time and that it has lost its exceptional nature.

Comment rendre l’accouchement par césarienne plus « naturel » ?

Gentle caesarean section is not a surgical technique but a different approach of C-section allowing more implication of the parents in birth. It begins before the procedure, and continues in a friendly atmosphere, with the wish to take into account the autonomy, the choices of the parents and the blood-tie with the newborn. The parents are invited to participate actively to the birth, being present, choosing the background music, making pushing forces, viewing the delivery and having a skin to skin contact with the newborn. This approach is supposed to be less traumatic and to strengthen the link with the baby. However the benefit is not documented in the literature. Parents have to be informed and accept that the schedule can be changed at any time for safety reasons in case of complication.

Comparing laser-induced breakdown spectroscopy and visible near-infrared spectroscopy for predicting soil properties: A pan-European study

Soil organic carbon (SOC), texture, clay/organic carbon (OC) ratio, and extractable phosphorus are among the key soil descriptors representing the physical, chemical, and biological properties. However, analyzing these soil properties using conventional methods of analysis is time-consuming and often involves the use of hazardous chemicals. Therefore, scaling these methods to analyze more samples covering large geographical distributions within a reasonable turn-around time has become a challenge. In this study, two rapid techniques, namely laser-induced breakdown spectroscopy (LIBS) and visible and near-infrared spectroscopy (vis-NIRS), were compared for the prediction of SOC, texture, extractable phosphorus, and clay/OC ratio. A total of 896 samples collected from 23 European countries from the Land Use/Cover Area frame Survey (LUCAS) database were used to represent a wide distribution in terms of soil texture and geographical coverage. The data was manually split into calibration and validation samples while ensuring a representative geographical distribution in the calibration and validation set for the selected samples. Partial least square regression (PLSR) models were developed for both LIBS and vis-NIRS and compared based on prediction accuracy. LIBS outperformed vis-NIRS in predicting SOC, sand content, and clay/OC ratio, with root mean square error of prediction (RMSEP) values of 1.79 %, 12 %, and 7.69, respectively. Conversely, vis-NIRS yielded slightly higher RMSEP values for SOC, sand content, and clay/OC ratio predictions at 1.88 %, 15 %, and 8.13, respectively. Both LIBS and vis-NIRS performed similarly in predicting clay content, with an RMSEP of 6 %. However, there was a low predictive ability for silt and phosphorus concentration, as shown by the weak correlations (R2 < 0.5) between the predicted and reference soil properties. There was no significant difference between LIBS and vis-NIRS predictions for clay, silt, and SOC content (p > 0.05). However, there was a significant difference between the predicted sand content (p = 0.011) and clay/OC ratio (p < 0.001). The overall better performance of LIBS highlights its potential for application in a wide range of soils, especially for soils covering large geographical distributions and varying soil properties. Further, both techniques present opportunities for rapid determination of soil properties important for evaluating soil health on continental scales.

PERFORMANCE EVALUATIONS OF THE MANTA RAY FORAGING OPTIMIZATION ALGORITHM IN REAL-WORLD CONSTRAINED OPTIMIZATION PROBLEMS

Metaheuristic algorithms are often preferred for solving constrained engineering design optimization problems. The most important reason for choosing these algorithms is that they guarantee a satisfactory response within a reasonable time. The swarm intelligence-based manta ray foraging optimization algorithm (MRFO) is a metaheuristic algorithm proposed to solve engineering applications. In this study, the performance of MRFO is evaluated on 19 mechanical engineering optimization problems in the CEC2020 real-world constrained optimization problem suite. In order to increase the MRFO performance, three modifications are made to the algorithm; in this way, the enhanced manta ray foraging optimization (EMRFO) algorithm is proposed. The effects of the modifications made are analyzed and interpreted separately. Its performance has been compared with the algorithms in the literature, and it has been shown that EMRFO is a successful and preferable algorithm for this problem suite.

Inventing Ancestors and Limited Empiricism in Chosŏn Korea: A Case of the Kigye Yu Lineage

AbstractThis paper investigates how the members of the Kigye Yu lineage imagined and invented their ancestral roots during the Chosŏn dynasty (1392–1910) and how such a pursuit of ancestral origins led to subsequent developments in genealogical records. As early as the fifteenth century, Chosŏn elites began to show interests in genealogy that included identifying remote ancestors from ancient times for various political, social, and cultural reasons. From the seventeenth century, the transformation of kinship organization in line with the Confucian ideal of patriliny and elites’ competition for power and prestige intensified genealogical consciousness. Elites became heavily invested in searching for ancestral origins in the form of their lineages’ founders and their tombs. While claiming to rely on documentary and physical evidence, elites often deviated from their professed empiricism and adopted evidence from dubious sources such as oral testimonies and geomancy to rationalize invented ancestral roots. Such pliable approaches, often observed in other early modern cultures such as late imperial China and Europe, opened a floodgate of lineages glorifying their ancestry by pushing their origins back even to mythical founders of ancient Korean and Chinese kingdoms, and adorning their lineages with invented heroes. At the same time, loopholes and blank spots in genealogies enabled quasi- and nonelites to become a member of prominent lineages by grafting their names onto their family trees.

Equilibrium core modeling of a pebble bed reactor similar to the Xe-100 with SCALE

As the nuclear industry moves towards licensing and constructing advanced reactors, new attention has been focused on the advanced reactor designs that have past operational experience, such as pebble-bed high-temperature gas-cooled reactors (PB-HTGRs). Pebble-bed reactor designs have many advantages, such as their higher operating temperatures and online refueling capabilities. However, high-fidelity computational modeling of pebble-bed reactor designs, from reactor startup to operation at equilibrium, is more challenging compared to conventionally fueled reactors due to the continuous movement of the fuel pebbles through the reactor during operation. In previous work at Oak Ridge National Laboratory (ORNL), the SCALE Leap-In method for Cores at Equilibrium (SLICE) was developed around tools within the SCALE code system. This iterative method can effectively generate pebble-bed reactor zone-wise fuel inventories at equilibrium core operation within a reasonable computational time. The objective of this work was to further verify the ORNL SLICE method and to investigate the impact of considering temperature profiles during the application of the method. The SLICE method was applied to a modular high-temperature gas-cooled reactor design based upon publicly available design specifications of the Xe-100 pebble-bed reactor. Upon comparing the results from the SLICE method to published literature, the differences in the eigenvalue keffective were on the order of several hundred pcm (percent millirho). To investigate one possible cause of these differences, a study looking at the sensitivity of the full-core equilibrium keffective and discharge nuclide inventory to temperature was performed by developing equilibrium cores of two additional temperature profiles. From this temperature study, differences on the order of hundreds of pcm for the full-core equilibrium keffective, and up to 15% difference for the discharge inventories were found. These results indicated the strong dependence on temperature that needs to be considered for future work in equilibrium modeling of PB-HTGRs.

Electric Vehicle Routing Problem with an Enhanced Vehicle Dispatching Approach Considering Real-Life Data

Although the EVRP (Electric Vehicle routing problem) has promising results on the environmental scale, its implementation has proved challenging. The difficulty of the EVRP resides in the limited driving range of the electric vehicles, combined with the significant charging time. While the charging cost is less than the cost of fuel, this charge time adds to the overall travel time and may overlap with customers’ time windows. All these factors increased the computational time exponentially and resulted in the need to overlook some constraints such as traffic congestion, road conditions, weather impact on energy consumption, and driving style, to name a few, in order to speed up execution time. While this method proved effective in accelerating the process of the EVRP, it did, however, render the approach unrealistic, as it steered far from real-life settings and made the approach unpredictable when facing dynamic and changing parameters. In this paper, we try to remedy this issue by proposing an approach in which we try to replicate real-life parameters such as heterogenous fleets, energy consumption, and infrastructure data. The objective of our approach was to minimize the total travel time, travel distance, energy consumed, and the number of vehicles deployed. To solve this problem, we propose a three-stages approach, in which the first stage consists of a newly developed dispatching approach where customers are assigned to vehicles. The second stage uses the genetic algorithm to find a set of optimal paths, and, finally, in the third stage, charging stations are inserted in the selected paths. Upon testing our approach on Solomon’s instances, our approach proved effective in finding optimal solutions in a reasonable time for five- to fifteen-customer datasets. However, when trying to solve larger datasets, the approach was slowed down by the extreme number of constraints it had to satisfy.

A Flow-Based Formulation for Parallel Machine Scheduling Using Decision Diagrams

We present a new flow-based formulation for identical parallel machine scheduling with a regular objective function and without idle time. The formulation is constructed with the help of a decision diagram that represents all job sequences that respect specific ordering rules. These rules rely on a partition of the planning horizon into, generally nonuniform, periods and do not exclude all optimal solutions, but they constrain solutions to adhere to a canonical form. The new formulation has numerous variables and constraints, and hence we apply a Dantzig-Wolfe decomposition to compute the linear programming relaxation in reasonable time; the resulting lower bound is stronger than the bound from the classical time-indexed formulation. We develop a branch-and-price framework that solves three instances from the literature for the first time. We compare the new formulation with the time-indexed and arc time–indexed formulation by means of a series of computational experiments. History: Accepted by Andrea Lodi, Area Editor for Design &amp; Analysis of Algorithms—Discrete. Funding: This work was partially funded by the European Union’s Horizon 2020 research and innovation program under [Marie Skłodowska-Curie Grant 754462]. Supplemental Material: The software that supports the findings of this study is available within the paper and its Supplemental Information ( https://pubsonline.informs.org/doi/suppl/10.1287/ijoc.2022.0301 ) as well as from the IJOC GitHub software repository ( https://github.com/INFORMSJoC/2022.0301 ). The complete IJOC Software and Data Repository is available at https://informsjoc.github.io/ .

Enhancing the Construction Efficiency of Mid Rise Construction Projects with Partial Precast Construction Technique By IJISRT

The primary success parameter of every construction project is to achieve the better quality products, in the most reasonable time and at an economic cost. Along with the materials the method of construction used in mid rise construction projects contributes mainly for the cost of the project, time duration to complete the project &amp; structural behavior such as stability, durability, quality etc. of these structures. This paper is about understanding the need for creating an awareness about the construction method to be adopted &amp; enhancing the construction efficiency of mid rise construction projects with partial precast concrete construction technique. The study also speaks about the cost, time and quality effectiveness as compared to cast in-situ concrete construction techniques for the mid rise construction projects. The research findings shows that partial precast construction for mid rise construction projects is time and quality effective. Thus, we can achieve the cost effectiveness in partial precast concrete construction if the recommendations made are implemented.