Internal Quality Measures Research Articles

Statistical Modeling of Within-Laboratory Precision Using a Hierarchical Bayesian Approach.

Reproducibility has been well studied in the field of food analysis; the RSD is said to follow a Horwitz curve with certain exceptions. However, little systematic research has been done on predicting repeatability or intermediate precision. We developed a regression method to estimate within-laboratory SDs using hierarchical Bayesian modeling and analyzing duplicate measurement data obtained from actual laboratory tests. The Hamiltonian Monte Carlo method was employed and implemented using R with Stan. The basic structure of the statistical model was assumed to be a Chi-squared distribution, the fixed effect of the predictor was assumed to be a nonlinear function with a constant term and a concentration-dependent term, and the random effects were assumed to follow a lognormal distribution as a hierarchical prior. By analyzing over 300 instances, we obtained regression results that fit well with the assumed model, except for moisture, which was a method-defined analyte. The developed method applies to a wide variety of analytes measured using general principles, including spectroscopy, GC, and HPLC. Although the estimated precisions were within the Horwitz ratio criteria for repeatability, some cases using high-sensitivity detectors, such as mass spectrometers, showed SDs below that range. We propose utilizing the within-laboratory precision predicted by the model established in this study for internal QC and measurement uncertainty estimation without considering sample matrices. Performing statistical modeling on data from double analysis, which is conducted as a part of internal QCs, will simplify the estimation of the precision that fits each analytical system in a laboratory.

Novel View Synthesis with Neural Radiance Fields for Industrial Robot Applications

Abstract. Neural Radiance Fields (NeRFs) have become a rapidly growing research field with the potential to revolutionize typical photogrammetric workflows, such as those used for 3D scene reconstruction. As input, NeRFs require multi-view images with corresponding camera poses as well as the interior orientation. In the typical NeRF workflow, the camera poses and the interior orientation are estimated in advance with Structure from Motion (SfM). But the quality of the resulting novel views, which depends on different parameters such as the number and distribution of available images, the accuracy of the related camera poses and interior orientation, but also the reflection characteristics of the depicted scene, is difficult to predict. In addition, SfM is a time-consuming pre-processing step, and its robustness and quality strongly depend on the image content. Furthermore, the undefined scaling factor of SfM hinders subsequent steps in which metric information is required. In this paper, we evaluate the potential of NeRFs for industrial robot applications. To start with, we propose an alternative to SfM pre-processing: we capture the input images with a calibrated camera that is attached to the end effector of an industrial robot and determine accurate camera poses with metric scale based on the robot kinematics. We then investigate the quality of the novel views by comparing them to ground truth, and by computing an internal quality measure based on ensemble methods. For evaluation purposes, we acquire multiple datasets that pose challenges for reconstruction typical of industrial applications, like reflective objects, poor texture, and fine structures. We show that the robot-based pose determination reaches similar accuracy as SfM in non-demanding cases, while having clear advantages in more challenging scenarios. We also report results of the novel view quality for different NeRF approaches, showing that an additional online pose refinement may be disadvantageous. Finally, we present first results of applying the ensemble method to estimate the quality of the synthetic novel view in the absence of a ground truth.

An analysis of factors contributing to low colonoscopy rates at Kline Health Center in comparison to the national average in the USA (according to the internal quality measures of the medical group fiscal year 2023) and a follow-up initiative to improve colon cancer screening participation.

e23244 Background: The UPMC-Kline Health Center (KHC) located in Harrisburg, PA, has a lower colon cancer screening rate compared to the general patient population in the USA (26.03% vs 78%, respectively, according to the Medical Group Fiscal Year 2023 Internal Quality Measures). To understand the reasons behind this disparity, a comprehensive questionnaire was conducted aiming to identify factors contributing to the lower colonoscopy screening rate and to implement targeted interventions to improve the situation. Methods: Surveys were distributed to eligible patients aged 45 to 75 at the clinic, considering linguistic diversity by preparing questionnaires in Spanish, English, and Nepali. Distribution, randomized and conducted by medical assistants, aims to identify and address specific clinic-related issues. Subsequent assessment, after a few months, will determine improvements resulting from interventions targeting the underlying causes of screening gaps. Results: Over a three-month period, a total of 77 questionnaires were completed and collected. We analyzed responses from 33 patients (42%, 14 females, and 19 males; 16 white/Caucasian, 14 black/African American, 2 Asian, 1 other; 8 Hispanic/Latino, 25 non-Hispanic/Latino) who had not undergone a colonoscopy in the past 10 years. Findings revealed that 72% (24/33) of patients reported not receiving paperwork for scheduling, while 72% (24/33) were not contacted to schedule the test. Additionally, 78% (26/33) of patients did not receive a reminder call or message before their scheduled appointments. 51% (17/33) of patients highlighted a lack of insurance coverage for costs, with 63% (21/33) indicating the need for a co-pay. 57% (19/33) of patients reported difficulties in obtaining the screening test. 51% (17/33) of patients mentioned that their healthcare provider discussed the importance of the screening test, and 54% (18/33) of patients noted that their providers explained the purpose of the test. Conclusions: The survey identifies scheduling, communication, and cost-related barriers to colon cancer screening at KHC. Proposed interventions, including the implementation of automated reminders, integrating technology to facilitate communication, and incorporating flyers within the clinic and patient waiting areas. This quality improvement project is ongoing, with data scheduled for recollection in a few months. These measures are anticipated to foster improvements, aiding more patients in preventing delayed cancer diagnoses. KHC aims to create a patient-friendly environment by addressing scheduling inefficiencies, improving communication, and tackling financial concerns for timely and accessible colon cancer screenings.

Analyzing influential factors in suboptimal cervical cancer screening rates at Kline Health Center and implementing a subsequent initiative for improvement.

e23252 Background: The UPMC-Kline Health Center (KHC) in Harrisburg, PA, shows a lower cervical cancer screening rate compared to the general population in the USA (57.08% vs 78%, respectively, based on the Medical Group Fiscal Year 2023 Internal Quality Measures). To understand this gap, we distributed a comprehensive questionnaire to patients, aiming to pinpoint factors contributing to the lower screening rate and plan targeted interventions for improvement. Methods: We randomly distributed questionnaires to female patients aged 21 to 61 during appointment check-in at the KHC, considering our linguistically diverse patient population with surveys available in Spanish, English, and Nepali. Given the diverse linguistic landscape of our patient population, we prepared questionnaires in Spanish, English, and Nepali. The survey aims to identify and address specific clinic-related problems, with a follow-up assessment after a few months to gauge improvements following interventions targeting the underlying causes of screening gaps. Results: Over a three-month span, 65 questionnaires were completed. Among the participants, 38% (25 patients - 7 white/Caucasian, 11 black/African American, 1 Asian, 7 others; 12 Hispanic, 13 non-Hispanic) revealed that they had not undergone screening within the past three years. The analysis of this subgroup unveiled significant issues: 84% (21/25) did not receive paperwork to schedule the test, 88% (22/25) were not contacted to schedule the test, 76% (19/25) did not receive reminder notifications before appointments, and 72%(18/25) expressed concerns about the lack of insurance coverage for costs. Furthermore, 76% (19/25) indicated the requirement to pay a co-pay, and an equal percentage reported difficulties in obtaining the screening test. Additionally, 72%(18/25) mentioned that their healthcare providers did not discuss the screening's importance, while 76%(19/25) noted their providers did not explain the purpose of the test. Conclusions: These findings underscore critical gaps in communication, accessibility, and cost-related barriers to cervical cancer screening at KHC. This ongoing quality improvement project, scheduled for data recollection in a few months, encompasses proposed interventions such as automated reminders, technology integration for communication, and distributing flyers in clinic and waiting areas to foster open communication and address inadequate discussions about the importance of screening. The aim is to improve patient awareness, engagement, and ultimately prevent delayed cancer diagnoses. KHC is committed to enhancing the cervical cancer screening rate to minimize the likelihood of delayed cancer diagnoses.

Quantitative measurement of internal quality of carrots using hyperspectral imaging and multivariate analysis

The study aimed to measure the carotenoid (Car) and pH contents of carrots using hyperspectral imaging. A total of 300 images were collected using a hyperspectral imaging system, covering 472 wavebands from 400 to 1000 nm. Regions of interest (ROIs) were defined to extract average spectra from the hyperspectral images (HIS). We developed two models: least squares support vector machine (LS-SVM) and partial least squares regression (PLSR) to establish a quantitative analysis between the pigment amounts and spectra. The spectra and pigment contents were predicted and correlated using these models. The selection of EWs for modeling was done using the Successive Projections Algorithm (SPA), regression coefficients (RC) from PLSR models, and LS-SVM. The results demonstrated that hyperspectral imaging could effectively evaluate the internal attributes of carrot cortex and xylem. Moreover, these models accurately predicted the Car and pH contents of the carrot parts. This study provides a valuable approach for variable selection and modeling in hyperspectral imaging studies of carrots.

Egg Quality, Yolk Fatty Acid Profiles from Laying Hens Housed in Conventional Cage and Cage-Free Production Systems in the Andean Tropics.

Egg consumers worldwide have increased their concerns about laying hens' welfare and its impact on final egg product quality. This study compared the egg quality parameters under the conventional cage (CC) and cage-free (CF) egg production systems in the tropics. The study was conducted on a commercial farm in Colombia using Hy-Line Brown pullets, reared under the same conditions for the first 15 wks. At 16 wks, the hens were distributed into two housing systems, CC and CF, on the same farm. The hens were fed the same diet for each phase in both systems and feed intake varied slightly. Egg samples were collected every six wks, from 22 to 82 wks of age. A total of 3960 eggs were analyzed at 11 sampling times. Parameters such as albumen height, egg weight, yolk color, eggshell thickness, eggshell strength, and Haugh units were determined using a DET-6000 machine. At 22 and 82 wks, screening for Salmonella spp. status was conducted using environmental and egg samples. Additionally, at 34, 64, and 82 wks, yolk samples were obtained for fatty acid profiles and crude protein (CP) analysis. The data were analyzed in a completely randomized block design with repeated measures (11 times): mean separation by Student's t-test yolk pigmentation, Haugh Units, and albumen height (p < 0.001) were higher in the CF compared with the CC between 38 and 69 wks of age, and eggs at 63 and 82 wks (p < 0.05) were heavier in the CF compared to the CC. Likewise, eggs from the CC had better eggshell strength from 57 to 82 wks. In the egg yolk fatty acid profile at the 34th wk, the pentadecanoic, palmitic, and heptadecanoic acids had higher concentrations in the CF systems than the CC. At the 64th wk, the egg yolk fatty acids-lauric, myristic, and heptadecanoic-had higher concentrations in the CF; likewise, at the 82nd wk, egg yolks from the CC had higher concentrations of lauric, heptadecanoic, and nervonic fatty acids than the CF. The eggs and environmental samples were negative for Salmonella spp. throughout the whole production phase. These results indicated that the production system might impact internal and external egg quality measures, potentially due to various stressors, including environmental factors or behavior restrictions.

A multinomial modeling approach to assess supplier delivery performance for buyer-supplier alignment

Purpose Untimely delivery of goods and services, especially in a post-COVID landscape, is a critical harbinger of end-to-end fulfillment. Existing literature in supplier delivery modeling is focused on penalizing suppliers for late deliveries built into a contractual transaction, which eventually erodes trust. As such, a holistic modeling technique focused on long-term relationship building is missing. This study aims to design a supplier evaluation model that analytically equates supplier delivery performance to cost realization while replicating a core attribute of successful supply chains – alignment, leading to long-term supplier relationships. Design/methodology/approach The supplier evaluation model designed in this paper uses delivery deviation as a unit of measure as opposed to delivery duration to enhance consistency with enterprise resource planning protocols. A one-sided modified Taguchi-type quality loss function (QLF) models delivery lateness to construct a multinomial probability penalty cost function for untimely delivery. Prescriptive analytics using simulation and optimization of the proposed mathematical model supports buyer–supplier alignment. Findings The supplier evaluation model designed herein not only optimizes likelihood parameters for early and late deliveries for competing suppliers to enhance total landed cost comparisons for on-shore, near-shore and off-shore suppliers but also allows for the creation of an efficient frontier toward supply base optimization. Research limitations/implications At a time of systemic disruptions such as the COVID pandemic, global supply chains are at risk of business continuity. Supplier evaluation models need to focus on long-term relationship modeling as opposed to short-term contractual penalty-based modeling to enhance business continuity. The model offered in this paper is grounded in alignment – a cornerstone of successful supply chain integration, and offers an interesting departure from traditional modeling techniques in this genre. Practical implications The results from this analytical approach offer flexibility to a supply manager toward building redundancies in the supply chain using an efficient frontier within the supply landscape, which also helps to manage disruption and maintain end-to-end fulfillment. Originality/value The model offered in this paper is grounded in alignment – a cornerstone of successful supply chain integration, and offers an interesting departure from traditional modeling techniques in this genre. The authors offer a rational solution by creating an evaluation model that uses penalty cost modeling as an internal quality measure to rate suppliers and uses the outcome as a yardstick for negotiations instead of imposing penalties within contracts.

The Effect of Managerial Skills on Internal Service Quality: A Study of City Administrations in Amhara Regional State, Ethiopia, Based on Katz’s Managerial Skills Model and Yaoli’s Internal Service Quality Measures

Previous studies have yet to identify the managerial skills that significantly impact internal service quality in city administrations, creating a gap in understanding. The current study uses Katz&amp;#39;s Managerial Skills Model and Yaoli&amp;#39;s Internal Service Quality to identify correlations between managerial skills and Measures to determine practical abilities that affect internal service quality. The survey examines the effectiveness of managerial skills on internal service quality. The research design is a cross-sectional survey with a sample size of 4 municipalities, 196 employees, and 12 managers selected using a multi-stage stratified sampling technique. Three types of managerial skills and seven dimensions of internal service quality measures were considered, in which each of the skill types and sizes was measured with Likert scale self-administered questionnaires. Arithmetic mean, median and factor analysis were used to analyze inter-related Likert scale data, and their performance was compared. The result found that factor analysis is the best method to analyze the collected Likert scale data. Eventually, weighted least square (WLS) estimation was fitted where technical skill (&amp;beta; = 0.31, P &amp;lt; 0.01) and conceptual skill (&amp;beta; =0.3, P_value &amp;lt; 0.01) were found significant and had a positive effect. However, Human skill (&amp;beta; = -0.07, P_value = 0.073) was insignificant at a 5% significance level, meaning technical, managerial skills and human managerial skills significantly positively affect internal service quality; the conceptual managerial skill was insignificant at a 5% significance level. The weighted least square estimation showed better performance concerning R-square, MSE, AIC and BIC values; with the trimmer, the better. Multiple linear regressions and partial and semi-partial correlations were run, and the significance and direction of correlation were equivalent to that of WLS. The study&amp;#39;s conclusion highlights that enhancing managerial technical and human skills can improve internal service quality. This improvement can enhance external service quality, employee job satisfaction, and performance.

Processing inflation news: A discussion of Binz, Ferracuti, and Joos (2023)

Binz, Ferracuti, and Joos (2023) examine whether better internal information systems can mitigate the association between inflation and investment. According to Real Business Cycle models, inflation should not impact real decisions like investment, yet empirically the two are positively related. Lucas (1972) theorizes that imperfect information can cause agents to rationally extrapolate from their local set of information to make conclusions about what is happening in aggregate. Motivated by this model, the authors argue that better internal information systems allow managers to disentangle firm-level real shocks from nominal shocks. My discussion evaluates the measurement of internal information quality and questions how distinct it is from external information quality. Next, I relate the findings to a growing literature that examines how individuals and firms form economic expectations. Finally, I consider whether and how these findings can inform policy.

Improving internal control quality as a corporate response to the Forbes Rich List

This study takes advantage of the Forbes Rich List as an external shock to examine its effect on internal control quality in mainland China. Using the difference-in-differences (DiD) method for a large sample of 17,910 firm-year observations from 2000 to 2014, we find that firms controlled by entrepreneurs included in the Forbes Rich List tend to have higher internal control quality than firms not controlled by entrepreneurs in the list. The listed entrepreneurs improve their firms’ internal control quality by means of reducing the information asymmetry between the firms and outsiders. Further tests show that the event effect is more pronounced when firms have higher misreporting costs and when listed entrepreneurs hold chairman positions than in other situations. Our results remain robust after applying the propensity score matching method, stacked DiD estimation, and an alternative measure of internal control quality. These findings enrich the literature on the effect of the Rich List and the determinants of internal control quality in emerging markets.

Nexus Among Internal Audit Quality, Corporate Governance and Performance of Selected Banks in Africa

Using a quantitative data set of 213 banks selected from 11 African nations between 2015 and 2020 and ordered probit regression techniques, this study examines the relationship between internal audit quality, corporate governance, and the performance of banks in Africa. The study finds that corporate governance mechanisms (such as board size, board expertise, and corporate governance disclosures), and internal audit quality measures (such as audit experience and internal audit presence) are the critical drivers of bank’s performance in Africa. Findings imply that banks with board members experts in accounting and auditing with the support of experienced professional internal auditors and disclosed corporate governance mechanisms reduce the chances of bankruptcy. The study is one of the few studies that provide insights into internal audit quality and corporate governance mechanisms on the performance of banks in Africa, implying that the findings do not only add to the literature but also to policy and practice. Other implications for theory, regulators, shareholders, policymakers, management, global advocacy agencies, investors and other stakeholders are presented.

Non-destructive evaluation of soluble solid content in fruits with various skin thicknesses using visible–shortwave near-infrared spectroscopy

Abstract Visible–shortwave near-infrared spectroscopy has been used for internal quality measurement, but the optical penetration to the thickness of fruit skin becomes a challenge. This research aimed to develop partial least square regression model for the soluble solid content (SSC) measurement of fruits having various skin thicknesses, namely dragon fruit, tomato, guava, sapodilla, and banana. The spectra of each fruit were taken in a reflectance mode over a wavelength range of 400–1,000 nm. The best models obtained from banana and sapodilla yielded determination coefficient of prediction (R 2 p) of 0.88 and 0.90 and root mean square error of prediction (RMSEP) 0.39 and 0.38°Brix, respectively. The banana and sapodilla SSC prediction models should be able to be used carefully in a variety of applications. Tomato and guava had moderately thinner skin but had the lower R 2 p of 0.64 and 0.76 and the RMSEP of 0.17 and 0.26°Brix, respectively. The poorest model was yielded by dragon fruit, which had the thickest skin with the R 2 p of 0.59 and the RMSEP of 0.40°Brix. The model for guava, although having low R 2 p, can still be utilized as a screening criterion and in some other ‘approximate’ applications. However, the SSC prediction model for tomatoes and dragon fruit is not recommended to use and requires additional research. In addition to the effect of skin thickness, other fruit morphological influences the result of this study. Internal structure and seed number influence the reflection optical geometry, which also affects the SSC prediction model.

Intservqual Model di Stasiun Perpindahan Selama Masa Pandemik Covid-19

An interchange station or transfer station is a train station for more than one route that allows passengers to move from one route to another without leaving the station by paying a one-way fare. The purpose of this study was to determine the level of internal service capability in the organization in the field of internal customer service at the crossing station between front-line staff and support staff during the covid 19 pandemic. The research method used was a quantitative method with an analysis of internal quality measurements using the Intservqual model and measurements based on there is a gap between the service expected by internal customers (employees of other departments) and the service they actually receive. The sample used is accidental sampling of 105 support staff and 23 front line staff. The results of the study show that there is a gap that is still in a negative position, meaning that based on each dimension of the two gaps, it is still necessary to improve internal services between front-line staff and support staff.

Effects of L-valine in layer diets containing 0.72% isoleucine.

In a previous study with LSL-LITE layers (-23 to 30-week-old), isoleucine at 0.72% and 0.84% produced values for FCR at 1.45 and 1.44, respectively and shared significance with 0.78% isoleucine (1.49). Considering that FCR is an important standard in the poultry industry due to the cost for adding feed ingredients such as synthetic amino acids and the low FCR of 1.45, 0.72% isoleucine was chosen for further study with LSL-LITE layers (n = 490 at 33- to 40-week-old) to determine effects on production and egg quality. The study included 7 diets (2730 Kcal kg metabolizable energy and constant isoleucine at 0.72%) containing varying quantities of valine [0.72 (Control), 0.75, 0.78, 0.81, 0.84, 0.87 or 0.90%] x 7 replicates x 10 hens/replicate. Significance at P ≤ 0.05 and P < 0.10 was determined. Level and week were significant for feed intake, egg production, and FCR; the interaction of level x week (L*W) was significant for feed intake and FCR. An isoleucine:valine of 1.233 corresponding to 0.72% isoleucine and 0.87% valine produced the lowest FCR of 1.30 (a 2.26% decrease compared to the Control at 1.33 ± 0.04). All measurements for external egg quality, except shape index and eggshell thickness, were significant for level. Week was significant for all parameters except shell thickness; L*W was significant for external quality measurements except shape index and shell thickness. Level, week, and L*W were significant for internal egg quality measurements. Serum protein and H1 titer were significant for level. Various production, egg quality, and biochemical measurements were significantly different from the control (0.72% isoleucine and 0.72% valine) at 0.81 to 0.87% valine. Findings of this study will aid researchers and commercial producers in narrowing the range of isoleucine, valine, and leucine needed for effects on particular parameters. Knowledge gained from this and others studies will eventually lead to an understanding of synergistic and antagonistic effects of branched chain amino acids in feed for various genetic types of layers throughout their productive lifetime.

Internal Information Quality and State Tax Planning*

ABSTRACTThis study examines the association between internal information quality and state tax planning. Prior literature documents a positive association between internal information quality and summary measures of tax avoidance. However, we know little about specific forms of tax planning and internal information quality. State tax planning is difficult because of the number of jurisdictions, variety of tax rules, variation of enforcement, and apportionment requirements. We find that internal information quality facilitates state tax planning and is most important when firms face more restrictive state tax laws and when domestic firms relative to multinational firms have international income shifting opportunities. Our results provide a baseline of the economic effects of internal information quality on different forms of tax planning. Understanding internal information quality's role in state tax planning is especially relevant as countries propose to modify international tax rules to mirror the state taxation format of a single‐entity system with apportionment.

The effectiveness of soaking Moringa leaves (Moringa oleifera L) on the internal quality of chicken eggs Gallus gallus domestica

The purpose of this study was to analyze the effectiveness of soaking eggs using a solution of Moringa leaves for 24 hours on the internal quality of broiler eggs. Soaking aims to provide a layer on the pores of the egg shell so that it can keep the eggs from microbes and inhibit the release of gas from the egg. This type of research is experimental with Completely Randomized Design (CRD). The number of eggs used is 1000 eggs. The egg samples used are 420 eggs. The eggs used are in good condition, namely brown eggs, clean, intact, not cracked, texture smooth and oval in shape. The randomization method used random sampling in the form of a lottery system. Each of the 420 eggs is labeled. The eggs that were taken at random were divided into 4 treatment groups. Each treatment group consisted of 5 replications. Therefore, 20 treatment replications were obtained. Measurement of storage time and internal quality of eggs will be tested for 21 days. This is done to determine the level of egg resistance accurately, because the embryonic development period of the egg occurs for 21 days. Egg parameter measurements were carried out every day, at 08.00 WITA. Egg quality parameters were taken every 7 days. Egg quality parameters analyzed were egg white index, egg yolk index, and egg weight loss. All measurement data were analyzed by analysis of variance (ANOVA). If the results of the analysis have an effect, the Tukey test is continued with 95% confidence (α&gt; 0.05). The data that has been analyzed explains that chicken eggs that get soaked in a solution of Moringa leaves have a higher index of egg yolk and egg white than eggs that are not soaked in a solution of Moringa leaves. The most optimal concentrations in maintaining the egg yolk and egg white index are 30% and 45% Therefore, soaking eggs with Moringa leaves serves to maintain the internal quality of eggs seen from the yolk index and egg white index.

Internal audit quality, punitive measures and accountability in Ugandan statutory corporations

PurposeThis study aims to (1) examine the contribution of internal audit quality, punitive measures to accountability in statutory corporations in developing countries such as Uganda and (2) test whether internal audit quality mediates the relationship between punitive measures and accountability in Uganda's statutory corporations.Design/methodology/approachThis study is cross-sectional and correlational. Data were collected through a questionnaire survey conducted for 82 statutory corporations. The study's unit of analysis was a statutory corporation. Chief Internal Auditors and Chief Finance Officers were the study's unit of inquiry. Data were analyzed through correlation coefficients and linear regression using Statistical Package for Social Sciences.FindingsThe results suggest that internal audit quality and punitive measures independently predict accountability. However, punitive measures do not predict accountability in the presence of internal audit quality. Results further indicate that internal audit quality mediates the relationship between punitive measures and accountability in Uganda's statutory corporations.Originality/valueThis study confirms internal audit quality (a preventive measure) as a significant predictor of accountability in statutory corporations relative to punitive measures. To achieve accountability, more emphasis thus needs to be put on preventive mechanisms than on punitive mechanisms. This study also enhances our understanding of the relationship between punitive measures, internal audit quality and accountability. In this study, we arrive at new evidence on the mediating role of internal audit quality in the relationship between punitive measures and accountability in Uganda's statutory corporations.

MODELS FOR THE PREDICTION OF QUALITY PARAMETERS OF TABLE EGGS STORED UNDER DIFFERENT CONDITIONS

A total of 144 newly - laid eggs obtained from Lohmann Brown layers were distributed and stored under three storage conditions: room temperature, polythene bag/room temperature and refrigeration. Changes in Haugh unit, yolk ), index and percentage weight loss were evaluated between 0 and 14 days at intervals of two days each, Haugh unit, yolk index, and albumen have significantly (P&gt;0.001), while percentage weight loss increased (P&lt;0.001) with storage duration, Generally, quality on the parameters of refrigerated eggs were significantly (P&lt;0.05) higher than those stored used in polythene bag or those stored open in the room o. Polythene-bagged eggs had the least percentage weight loss. Significant (P&lt;0.001) storage method x storage duration interactions were obtained. Regressing the internal egg quality measurement (Y) over storage period (X) in simple linear Y = a +bx) or the exponential (Y = ab ). regression functions showed that the predictive ability measured as also the r2 - values was generally higher with the. exponential than the simple linear model. The predictive ability of each egg quality parameter was higher with the polythene - bagged eggs than with other storage conditions. Using the simple linear prediction model, table eggs purchased randomly from retail egg shops had quality values of eggs that were about 4 - 11 days after lay prior to purchase.

Comparative analysis of sequential community detection algorithms based on internal and external quality measure

Community detection is a dominant research field in social media mining. Numerous algorithms have been developed to detect community structure in network. Each of them focuses on different characteristic of data and generates different communities for same dataset. So cluster validation or comparative analysis of these algorithms is required to compare the efficiency of these algorithms. There are two known ways for cluster validation: Internal Quality Measure (IQM) and External Quality Measure (EQM). IQM evaluates the cluster without reference to external information while EQM requires already known clusters i.e. ground truth for comparison. Most of the researchers have compared Community Detection algorithms on the basis of either IQM or EQM but not both. In this paper, we have tried to compare nine existing sequential community detection algorithms on the basis of both IQM and EQM and we observed that overall performance of Louvain, Fastgreedy and Walktrap algorithm is more efficient than other algorithms. From this paper, researchers working in this area can get information about major sequential community detection algorithms and their efficiency on small real world datasets. They can incorporate the findings to develop more efficient algorithms.

Model Pengukuran Kualitas Audit Internal (Studi Pada Auditor Internal Pada Perusahaan Swasta, BUMD dan BUMN di Kota Medan)

The purpose of this study is to analyze the internal audit quality measurement model, with a study of internal auditors in private companies, BUMD and BUMN in Medan City. Determination of sample size is obtained by multiplying the number of construct variables with the total number of indicators, so as to obtain 170 people. Primary data were collected through questionnaire distribution techniques, and analyzed using Structural Equation Modeling method. The results of this study prove that there is a significant direct effect on independence, competence and motivation on due professional care; and there is a significant influence of independence, competence, motivation and due professional care on audit quality. Moreover, the results of this study found that indirectly, independence, competence and motivation proved to significantly influence audit quality through due professional care.