Quality Performance Improvement Research Articles

Impact of construction site manager’s technical and managerial skills on quality performance of construction projects in Ghana

Globally, the performance of the construction industry is often cited as one of low performance. Whilst concerted efforts have been made aimed at improving the performance of the construction industry through various strategies, the impact of construction site managers’ technical and managerial skills remains relatively unexplored. This study assesses the impact of construction site manager’s technical and managerial skills on quality performance of construction projects in Ghana. The descriptive survey design was used for the study. Purposive sampling technique was used to select 115 respondents for the study. The findings of the study revealed that construction site managers were not especially skilled in technical, legal, interpersonal, managerial, and business skills. The findings of the study suggest that the level of implementation of quality management practices among construction site managers for attaining high quality standards was acceptably high. The study revealed that the most significant skill requirements that can improve quality performance at construction sites was managerial and technical skills. The findings of the study disclosed that there is a statistically significant positive correlation between construction site manager’s skills and quality performance of construction projects they managed. It is recommended among others that efforts should be made by the top management of construction firms to create a quality management culture throughout the entire organisations. . Keywords: Construction Site Manager, Managerial Skills, Technical Skills, Quality Performance.

Assessing Lean Six Sigma and quality performance improvement in Italian public healthcare organizations: a validated scale

PurposeThis study aims to fully assess the readiness for Lean Six Sigma (LSS) and Quality Performance Improvement (QPI) in an Italian Public Healthcare ecosystem.Design/methodology/approachDrawing from previously established survey development and adaptation protocols, a replication study was carried out; Lean, Six Sigma and QPI were extracted and validated through confirmatory factor analysis in an Italian Public Healthcare setting, with a sample of health professionals from the Campania region.FindingsThis study reports the adaptation of an existing scale for measuring LSS and QPI in an Italian public healthcare organisation. This analysis extracts six conceptual domains and constitutes an original adaptation of an existing scale to assess the readiness to adopt Lean, Six Sigma and Quality Performance in Italian Public Health Organizations. The constructs show strong levels of internal consistency, as demonstrated by each item factor loading and each subscale reliability.Practical implicationsManagers, policymakers and academics can employ the proposed tool to assess the public healthcare ecosystem’s capability to implement LSS initiatives and strategies to improve quality performance.Originality/valueThis is one of the first studies to assess cross-regional organisational readiness for LSS and QPI in an Italian Public Healthcare environment at this scope and level.

English-Chinese Translation Quality Assessment Based on Phrase Statistical Machine Translation Decoding Algorithm

Machine learning translation is the automated process of translating text from one language to another using computational algorithms and statistical models. neural network-based approaches, particularly using models like sequence-to-sequence (Seq2Seq) with attention mechanisms, have shown remarkable performance improvements in translation quality. This paper proposes a Statistical Stochastic Gradient Machine Translation Decoding (SSGM-TD) algorithm for the English–Chinese translation for the quality assessment. The proposed SSGM-TD model uses statistical analysis for the estimation and evaluation of the features for the computation of variables. The proposed SSGM – TD model estimates the stochastic gradient with the regression analysis for the feature estimation. The developed SSGM-TD model is implemented with the machine learning model for the automated translation of the English–Chinese languages. The simulation analysis is performed for the evaluation of the quality assessment in the translation process. The detailed evaluation is conducted using various metrics, including BLEU and METEOR scores, offering quantitative insights into the algorithm's performance. The classification process of the SSGM-TD algorithm is examined, revealing its proficiency in correctly classifying positive and negative instances. Precision, recall, and F1 score metrics provide a significant evaluation of the algorithm's classification capabilities. The decoding results and quality assessments are presented with providing a comprehensive view of the algorithm's strengths and potential areas for improvement. The quality assessments incorporate both quantitative metrics and human evaluations, ensuring a holistic understanding of the algorithm's translation capabilities. The consistency between automated metrics and human assessments underscores the algorithm's commendable performance in maintaining semantic accuracy and linguistic coherence.

Pengaruh Disiplin Kerja Dan Lingkungan Kerja Terhadap Kinerja Karyawan Pada PT Alakaram Kila Azkia Garmen Tangerang

PT Alakaram Kila Azkia Garmen is a company engaged in the textile industry. The company produces various types of clothing. Their products include a variety of T-shirts, pants, and shirts. The company's brand is NUX. This company typically focuses on production quality and design. In carrying out its operations, PT Alakaram Kila Azkia Garmen has many employees who are a driving factor in improving performance quality. This research focuses on determining the extent to which work discipline and the work environment affect employee performance at PT Alakaram Kila Azkia Garmen. The research method used is a quantitative approach with data collection techniques using saturated samples or non-probability sampling, where the entire population is used as a sample. The population in question consists of all employees of PT Alakaram Kila Azkia Garmen, totaling 60 respondents, using questionnaires on a Likert scale. For data processing and analysis, SPSS 25 software is used with multiple linear analysis techniques, including instrument tests, partial and simultaneous hypothesis tests. This study finds that there is a positive and significant influence, both partially and simultaneously, between the variables of work discipline and work environment on employee performance at PT Alakaram Kila Azkia Garmen.

Power in coordinating supply chain projects in humanitarian settings: A case study of Rohingya refugee camps

AbstractHow and why is power used in humanitarian projects? Coordinating organizations, such as UN agencies, carry power and influence over NGOs to advance the interests of beneficiaries. However, coordination can be managed by a single authority or by multiple authorities that share or delegate responsibilities. Furthermore, coordinators may leverage different types of power, including non‐mediated forms like referent and expert power, or mediated forms such as reward, legitimate, or coercive power. This research draws upon 57 interviews regarding organizational behavior with members of international and local non‐governmental organizations (NGOs), UN agencies, and government officials involved in managing Rohingya refugee camps in Southern Bangladesh. The observations suggest that in single‐authority layered projects, referent and expert powers are commonly employed, leading to improvements in quality and delivery performance. Reward power is typically wielded informally and is linked to cost performance. In dual‐layered projects, legitimate power is used to enhance quality and delivery performance. This article's originality lies in its extension of the use of power to multi‐tiered supply chain settings; its contribution is to organizational theory regarding the resolution of principal‐agent issues; and its insights are into the nuanced effects of different types of power based on project types. It offers valuable guidance to policymakers and practitioners, highlighting effective approaches for coordinating inter‐organizational efforts in challenging and unconventional supply chain settings.

Improvement of Quality Performance in Mask Production by Feature Selection and Machine Learning Methods and An Application

With the development of technology, large databases become more accessible thanks to automation systems that automatically keep data and allow the use of large databases in many areas. Machine learning approaches, a sub-branch of artificial intelligence, are used in making decisions about the process by analyzing the data stored in databases and converting them into information. In this paper, the body production process of the surgical (medical) mask is analyzed. As it is known, surgical masks have become a part of our lives by becoming widespread all over the world with the COVID-19 pandemic. In the surgical mask body production process, using the real data of the production factors, first of all, filtering feature selection methods and analyzes were made and the feature selection method to be used was determined. With the specified feature selection method, the factors affecting the product quality are determined. Secondly, machine learning methods were used to determine the values and value ranges of factors (features) in the production of defect-free products. The performances of the machine learning models established in the second stage were increased by feature selection analysis. In the study, together with the parameter optimizations made to machine learning algorithms, it was seen that the best algorithm to estimate the defective product rate was the Ibk algorithm with 92.3% accuracy, 91.9% F measurement and 93% AUC value. Finally, in line with the decision rules revealed in the study, it was observed that the fabric types used for the upper/middle/lower layers that make up the body part in the mask body production process greatly affect the rates of defective or defect-free products. If the rod apparatus around the nose belongs to class k, it has been determined that many masks are defective. Improvement suggestions were presented according to the application results.

ACR-ARS Practice Parameter for the Performance of Proton Beam Therapy

PurposeThis practice parameter for the performance of proton beam radiation therapy was revised collaboratively by the American College of Radiology (ACR) and the American Radium Society (ARS). This practice parameter was developed to serve as a tool in the appropriate application of proton therapy in the care of cancer patients or other patients with conditions in which radiation therapy is indicated. It addresses clinical implementation of proton radiation therapy, including personnel qualifications, quality assurance (QA) standards, indications, and suggested documentation. Materials and MethodsThis practice parameter for the performance of proton beam radiation therapy was developed according to the process described under the heading The Process for Developing ACR Practice Parameters and Technical Standards on the ACR website (https://www.acr.org/Clinical-Resources/Practice-Parameters-and-Technical-Standards) by the Committee on Practice Parameters – Radiation Oncology of the ACR Commission on Radiation Oncology in collaboration with the ARS. ResultsThe qualifications and responsibilities of personnel, such as the proton center Chief Medical Officer or Medical Director, Radiation Oncologist, Radiation Physicist, Dosimetrist and Therapist, are outlined, including the necessity for continuing medical education. Proton therapy standard clinical indications and methodologies of treatment management are outlined by disease site and treatment group (e.g. pediatrics) including documentation and the process of proton therapy workflow and equipment specifications. Additionally, this proton therapy practice parameter updates policies and procedures related to a quality assurance and performance improvement program (QAPI), patient education, infection control, and safety. ConclusionAs proton therapy becomes more accessible to cancer patients, policies and procedures as outlined in this practice parameter will help ensure quality and safety programs are effectively implemented to optimize clinical care.

Finding the key nodes to minimize the victims of the malicious information in complex network

Safeguarding crucial nodes provides a direct approach to impede the dissemination of malicious information in complex networks, such as the Internet. However, determining the optimal budget size, represented as k, for protecting nodes is a challenging problem classified as NP-hard. In this study, we investigate the origin of the NP-hard property, known as the influence redundancy mechanism, as a means to address this problem. The influence redundancy characterizes the intricate interactions among key nodes. Subsequently, we introduce an objective function that allows for the optimization of the set of key nodes. Our objective is to minimize the spectral radius of the adjacency matrix after removing these key nodes. We mathematically prove that the objective function exhibits the submodular property, and our proposed method achieves an approximation ratio of (1−1/e) with a time complexity of O(NlogN), where N represents the size of the network. Experimental results show that the identified key nodes outperform classical methods in 20 empirical networks, specifically in the Susceptible-Infected-Recovered (SIR) model and Independent Cascade (IC) model, thus confirming their improved performance quality.

Soft Computing-Based System for Performance Modeling of Object-Oriented Programming (OOP) Software

Performance is a vital attribute for most software, making performance investigation an essential software engineering task. The problem is that modern applications are challenging to analyse for performance. The advancement of Software engineering has seen the application of scientific approach at various stages of Software Development Life Cycle (SDLC). New technique is available for implementation known as soft computing. This approach is a synergistic combination of artificial intelligence methodologies to model and solve real world problems that are either impossible or challenging to be modeled mathematically. The complexity, the commercial constraints and the expectation for high quality software demand, measuring the quality performance of an Object-Oriented Software (OOS). This work presents a set of testing metric (criteria) which hold the potential for ensuring remarkable improvements in quality performance of Object-Oriented software (OOS). A Prediction Model focused on identifying and evaluating the quality of the performance model based on the data set of software design components. The software design properties are comprehensive elucidated and integrating concepts of fuzzy logic and software engineering. The system enables the performance of modeling of Object-Oriented software using Fuzzy Inference System (FIS) to accurately predict the quality Object Oriented Software based on quality performance criteria such as reliability, efficiency, functionality and maintainability. Empirical validation of the results using checking data set is made to prove the usefulness of the design metrics and design quality attributes on the software prediction models. The purpose of this work is to provide development tool to solves practical problems, and focus on identifying and evaluating the quality performance of software design components. Again, the results demonstrate that, despite the research including approaches explicitly aimed at object-oriented software, there are substantial challenges in providing realistic feedback on the performance of large-scale object-oriented applications accordingly.

The Effect of Self Efficacy Leadership and Business Experience on Entrepreneurial Performance with Innovative Behaviour as an Intervening Variable in the Branch Management of the Indonesian Young Entrepreneurs Association in Medan City

The purpose of this study was to analyze the effect of Self-efficacy, Leadership, and Business Experience on Entrepreneurial Performance with Innovative Behavior as an Intervening Variable in the Branch Management of the Indonesian Young Entrepreneurs Association of Medan City. This research uses descriptive quantitative research methods to study young entrepreneurs in the Indonesian Young Entrepreneurs Association of Medan City. This study used probability sampling and the Slovin formula to select 350 respondents. Data were collected through questionnaires and secondary sources such as literature and journals. The results showed that self-efficacy has a positive effect on entrepreneurial performance in BPC Hipmi Medan City, while leadership has a positive effect on entrepreneurial performance. Business experience also has a positive impact on entrepreneurial performance. However, self-efficacy hurts innovative behavior. This research shows that entrepreneurs in HIPMI Medan City need high self-efficacy, digital technology for innovation, and creative ideas. Leadership is essential to coordinate business goals, improve performance quality, and accept criticism to sustain the market and maintain market share.

Status of duck breeding in India

Duck is the second most important species of poultry after chicken in India. Due to its many advantages, it is popular in the coastal states and states having large water bodies. Different indigenous and exotic breeds that are being evaluated and reported through research findings are summarized in this review. The history of import of exotic breeds to the country with breeding programme initiated for these breeds in India are discussed with reference to the status of breeds in respect to meat and egg production improved through selection in other countries. The status of purebred selection and breeding programme in indigenous duck being undertaken in our country are very few and being documented with reference to world scenario. Crossbreeding experiment using indigenous and exotic breeds in the countries are reported in respect to growth, conformation traits, production, reproduction, carcass quality, egg quality, egg weight and feed conversion ratio. Performance of the crossbred improved in respect to different traits measured compared to the indigenous breed showing heterosis in positive direction. General combining ability, specific combining ability and reciprocal effects are found to be significant for most of the traits studied in a 3×3 diallel cross using indigenous duck of Odisha, Khaki Campbell and White Pekin. The importance of availability of quality germplasm and performance improvement through duck breeding in India is to be taken on priority. Besides this, the conservation and documentation of all the indigenous breeds and variety is need of the hour. Commercial exploitation of indigenous duck breeds as they are well adapted to our harsh climatic conditions needs to be explored.

Plasmon-induced flexibility and refractive index measurement in a sensor designed by a cavity, two rings, two teeth and two plasmonic waveguides

In this research, we design a plasmonic refractive index sensor and examine it numerically, using transparency, refractive index, sensitivity, FOM fit shape and Q quality factor, to optimize and improve performance quality. We will be. To design the structure of this sensor, we use two plasmonic waveguides, a cavity, two rings and two teeth. The resonant wavelengths and refractive index of the resonators are investigated and simulated by the finite difference time domain (FDTD) method, and we draw the obtained diagrams using MATLAB software. After completing the sensor design, due to the fact that the amplifiers are very sensitive to changes in the refractive index, so by changing the refractive index and changing the dimensions of the structure, we can weaken or strengthen the passage coefficient in the resonant modes. These plasmonic sensors with a simple frame and high optical resolution can be used to measure refractive index in the medical, chemical and food industries.

Quality Performance and Capacity Improvement Model for the Service Sector Industries

Quality Performance and Capacity Improvement Model for the Service Sector Industries

Improving Task and Quality Performance: The Role of Affective Commitment, Engaged Employees and Creativity

Employee work quality within the fashion industry has received limited attention in the research literature. In order to fill this void in existing research, the author endeavored to examine the study model through a predictive methodology. This study utilized a survey methodology in which 72 employees from the fashion industry sector were selected as participants. The researcher employed the Structural Equation Modelling (SEM-PLS) technique to forecast the proposed study model. The analysis findings indicate that affective commitment considerably impacts employee engagement, namely in terms of dedication and employee creativity. The research findings also suggest that the factors of devotion and creativity exert a notable influence on task performance. Furthermore, it is seen that effective utilization of creativity can propel task performance, consequently exerting a positive influence on improving performance quality. The findings of this study indicate that the fashion industry sector has the potential to improve task and quality performance through the cultivation of affective commitment, dedication, and employee inventiveness.

Impact Assessment of Elevation Angles on Signal Propagation at VHF and UHF Frequencies for Improved Rural Telephony

Rural telephony is challenging in the remote part of Nigeria due to inadequate telecommunication infrastructure, exorbitant cost of communication systems and poor road network for extension of fiber network. These factors constitute poor or no cellular network services in many villages. Alternatively, using Television White Space (TVWS) technology to facilitate telephony services in the rural areas through Ultra High Frequency (UHF) and Very High Frequency (VHF) spectrum is cost effective. Thus, this research investigates impact of elevation angle on signal propagation at UHF/VHF frequencies. The experimental test scenarios took measurements of received signal quality performance at different elevation angles and transmit power levels to obtain more stable results for substantive inference. The experimental test scenario considered a communication link, operating at UHF frequency of 436 MHz. During the experiment, azimuth and propagation loss for the communication link were kept constant while the receiving antenna elevation angles were varied to assess the impact of elevation angles. The assessment examined results obtained during the experiment. Comparing the received signal quality performance at zero (00) elevation angle, it has been observed that the received signal quality improves when the transmit power allocation increases. Results further show that for a given transmit power level of 34dBm, at zero (00) elevation angle test configuration, received signal quality performance of 1.80 dB, 6.90 dB at 300 elevation angle and 10.9 dB at 600 elevation angle were obtained, compared to improved quality performance of 11.8 dB at 00 elevation angle, 19.90 dB at 300 elevation angle and 24.92 dB at 600 elevation angle when the transmit power level was increased to 46.98 dBm. It is deduced from the experimental results that elevation angle of receiving antenna has significant influence on the received signal quality performance. This insight is very useful in the design and network planning of rural telecommunication services using TVWS frequencies for improved rural broadband penetration.

Implementation of Transformational Leadership of Madrasah Principals in State Tsanawiyah Madrasah (MTsN) 4 and State Tsanawiyah Madrasah (MTsN) 5 Tulungagung, East Java, Indonesia in Improving Performance Quality

This study aims to revisit the pattern of transformational leadership in improving the quality of performance. This is generally motivated by the existence of decentralization in the world of education, where the madrasah head is given freedom to make decisions in the madrasah environment. Therefore, the leadership style of the madrasah head will affect the quality of all elements in the madrasah environment. This condition is in response to the number of educators who are indifferent to increasing their competence as educators, which affects the quality of their performance. Finally, there is a sense of discomfort in the process of subordinate performance. The main purpose of transformational leadership is presented in educational institutions to improve the quality of performance by implementing its major theories, namely, Idealized Influence, Inspirational Motivation, Intellectual stimulation, Individual Consideration. In order to provide an academic framework, this study uses a qualitative approach with the type of field research through primary sources conducted through observation, interviews, and documentation steps that are then carried out through data reduction, data display, and data verification. The findings in this study indicate the following: 1) the implementation of transformational leadership of madrasah principals in building subordinate trust, 2) implementation in building motivation to subordinates is carried out by madrasah principals by providing rewards and punishments to subordinates in an effort to provide appreciation, 3) implementation in building the innovation power of subordinates is carried out by the madrasah head by analyzing the performance of subordinates, building communication with subordinates, making clear job descriptions, and actualizing subordinate thoughts about their potential so that subordinates are able to improve their quality, 4) implementation in building the individual abilities of subordinates carried out by the madrasah head, namely by creating discussion space between subordinates, building subordinate thinking, and increasing workshops in madrasah.

Development of measurement scale for performance of health care organization through Structural Equation Modeling

The purpose of this research was to look at the link between healthcare service quality characteristics, service quality performance, and patient loyalty to healthcare companies. Data were gathered from 50 Andhra Pradesh healthcare institutions. To test the psychometric qualities (reliability & validity) of measuring scales, a confirmatory factor analysis was conducted. To test the hypotheses Structural Equation Modelling was used. To examine their effect on healthcare service quality, five healthcare service quality activities are considered: efficiency, safety, tangibles, empathy, and degree of improvement. In turn, it was determined if service quality had an impact on the organization's operational performance. The study's findings will be valuable to healthcare providers by encouraging them to embrace service quality items, resulting in improvements in both service quality and organizational performance.

Lean Six Sigma and quality performance in Italian public and private hospitals: a gender perspective

PurposeLean Six Sigma in public and private healthcare organisations has received considerable attention over the last decade. Nevertheless, such process improvement methodologies are not generalizable, and their effective implementation relies on contextual variables. The purpose of this study is to explore the readiness of Italian hospitals for Lean Six Sigma and Quality Performance Improvement (LSS&QPI), with a focus on gender differences.Design/methodology/approachA survey comprising 441 healthcare professionals from public and private hospitals was conducted. Multivariate analysis of variance was used to determine the mean scores on the LSS&QPI dimensions based on hospital type, gender and their interaction.FindingsThe results showed that public healthcare professional are more aware of quality performance improvement initiatives than private healthcare professionals. Moreover, gender differences emerged according to the type of hospital, with higher awareness for men than women in public hospitals, whereas for private hospitals the opposite was true.Research limitations/implicationsThis study contributes to the Lean Six Sigma literature by focusing on the holistic assessment of LSS&QPI implementation.Practical implicationsThis study informs healthcare managers about the revolution within healthcare organisations, especially public ones. Healthcare managers should spend time understanding Lean Six Sigma as a strategic orientation to promote the “lean hospital”, improving processes and fostering patient-centredness.Originality/valueThis is a preliminary study focussing on analysing inter-relationship between perceived importance of soft readiness factors such as gender dynamics as a missing jigsaw in the current literature. In addition, the research advances a holistic assessment of LSS&QPI, which sets it apart from the studies on single initiatives that have been documented to date.

Safety attitudes culture remain stable in a transplant center: evidence from the coronavirus pandemic.

We sought to understand how safety culture may evolve during disruption, by using the COVID-19 pandemic as an example, to identify vulnerabilities in the system that could impact patient outcomes. A cross-sectional analysis of transplant personnel at a high-volume transplant center was conducted using the Safety Attitudes Questionnaire (SAQ). Survey responses were scaled and evaluated pre- and post-COVID-19 (2019 and 2021). Two-hundred and thirty-eight responses were collected (134 pre-pandemic and 104 post-pandemic). Represented organ groups included: kidney (N = 89;38%), heart (N = 18;8%), liver (N = 54;23%), multiple (N = 66;28%), and other (N = 10;4%). Responders primarily included nurses (N = 75;34%), administration (N = 50;23%), and physicians (N = 24;11%). Workers had high safety, job satisfaction, stress recognition, and working conditions satisfaction (score >75) both before and after the pandemic with overlapping responses across both timepoints. Stress recognition, safety, and working conditions improved post-COVID-19, but teamwork, job satisfaction, and perceptions of management were somewhat negatively impacted (all p > 0.05). Despite the serious health care disruptions induced by the pandemic, high domain ratings were notable and largely maintained in a high-volume transplant center. The SAQ is a valuable tool for healthcare units and can be used in longitudinal assessments of transplant culture of safety as a component of quality assurance and performance improvement initiatives.

NEURAL NETWORK SYSTEM FOR ANALYSIS OF UNBALANCED HETEROGENEOUS DERMATOLOGICAL DATA ON THE BASIS OF A MULTIMODAL NEURAL NETWORK

To date, skin cancer is the most frequently diagnosed form of oncopathology. Visual diagnosis of this cancer type in the early stages is difficult due to similar visual manifestations in benign and malignant types of pigmented formations, and its accuracy depends on the experience of dermatologist. Artificial intelligence technologies are able to equal and surpass accuracy of visual diagnostic methods, but there is a risk of false positive prognosis, when malignant pigmented formation may be recognized as benign. One of the possible ways to improve recognition accuracy and reduce false positive conclusions is simultaneous use of different preprocessing methods, heterogeneous data analysis, and use of modified learning loss functions to eliminate negative impact of unbalanced dermatological data. The study presents an intelligent system for unbalanced heterogeneous dermatological data analyzing based on a multimodal neural network trained using modified cross-entropy loss function. The accuracy of classification of pigmented skin lesions in 10 diagnostically significant categories in the proposed system based on the AlexNet convolutional neural network architecture reached 83.87%. Due to the emerging synergy when using various methods to improve performance quality of intelligent systems, the number of false positive forecasts of the intelligent system was reduced, and the accuracy was increased by 1.31-4.91 percentage points, depending on the convolutional neural network architecture. Implementation of the developed system as a tool for auxiliary diagnostics can reduce the consumption of financial and labor resources involved in the medical industry, as well as increase the chance of early detection of pigmentary oncopathologies.