Hasil untuk "Management information systems"

I. Ansoff

M. Igbaria, S. Parasuraman, Jack J. Baroudi

B. Dervin

L. Zadeh, J. Kacprzyk

LIU Yilong, ZHANG Jun, NI Yiyang

Considering the issues of communication and sensing securities for the reconfigurable intelligent surface (RIS) enabled integrated sensing and communication system, a joint design for the transmit covariance matrix and the reflection matrix of the RIS is proposed to maximize the ergodic secrecy rate under the constraints of legal sensing signal-to-noise ratio (SNR), eavesdropper sensing SNR, transmit power, and the constant modulus for the reflection matrix of the RIS. Firstly, the asymptotic ergodic secrecy rate lower bound and the asymptotic sensing SNRs are derived by exploiting the large dimensional random matrix theory. Then, based on the statistical channel state information, the optimal closed-form optimal solution for the transmit covariance matrix is derived by exploiting the modified water-filling algorithm and the first-order Taylor series expansion, and sub-optimal the reflection matrix of the RIS is obtained by employing the barrier method and the projected gradient ascent method. Finally, numerical simulations validate the accuracy of the large-system analysis and the superiority of the proposed method.

Charles T. Horngren

Walid Alqaisi, Mostafa Soliman, Ahmed Badawi et al.

Abstract This paper presents a quadrotor detection and tracking system that uses a single camera and the Speeded Up Robust Features (SURF) algorithm to extract the image structure and estimate the target's position. The goal is to develop an independent system capable of detecting a followed object’s motion without prior knowledge of its trajectory, without requiring communication with the target, and without relying on external sensors. Feedback Linearization (FL) combined with sliding mode control is used to ensure target tracking. The control system avoids the complex nonlinear control solutions and the highly coupled dynamic behavior of the quadrotor. Nonlinear uncertain disturbances are overcome by using Time Delay Estimation (TDE) of the disturbance.

A. A. Bhat , Aadil Ahmad Mir , S. P. Ahmad  et al.

This study introduces a new and flexible class of probability distributions known as the novel alpha-power X (NAP-X) family. A key development within this framework is the novel alpha-power half-logistic (NAP-HL) distribution, which extends the classical half-logistic model through an alpha-power transformation, allowing for greater adaptability to various data shapes. The paper explores several theoretical aspects of the proposed model, including its moments, quantile function and hazard rate. To assess the effectiveness of parameter estimation, a detailed simulation study is conducted using seven estimation techniques: Maximum likelihood estimation (MLE), Cramér–von Mises estimation (CVME), maximum product of spacings estimation (MPSE), least squares estimation (LSE), weighted least squares estimation (WLSE), Anderson–Darling estimation (ADE) and a right-tailed version of Anderson–Darling estimation (RTADE). The results offer comparative insights into the performance of each method across different sample sizes. The practical value of the NAP-HL distribution is demonstrated using two real datasets from the metrology and engineering domains. In both cases, the proposed model provides a better fit than the traditional half-logistic and related distributions, as shown by lower values of standard model selection criteria. Graphical tools such as fitted density curves, Q–Q and P–P plots, survival functions and box plots further support the suitability of the model for real-world data analysis.

Juan Sebastián Sánchez Gómez, Edwin Andres Arevalo Herrera, Cristian Camilo Torres Puentes

This article highlights the critical role of specialized digital tools in enhancing project management and monitoring in Colombia's public sector, it showcases how Microsoft Office 365 and Power Platform have been effectively utilized to optimize royalty-funded initiatives, automating processes and improving decision-making through advanced data análisis. These tools enable process optimization, task automation, and enhanced data analysis, significantly improving the administration of resources and facilitating timely, well-informed decision-making. The methodology is quantitative and complementary information is taken from the technical and legal opinions of the participating professionals. For its execution, a combined approach had to be followed: a PMBOK methodology that gave a clear roadmap and an agile SCRUM methodology capable of highly prioritizing schedule management to provide effective results. In this process, the tools used are Power BI, Power Apps, and Power Automate; these are used to automate tasks and improve operational efficiency by addressing specific issues and contributing to project management and project optimization. Through this project, a proper technological infrastructure has been built for senior management strategic management, planning team tactical management, and operative monitoring to implement BI systems successfully. The project is structured in several phases: initial preparation and planning; implementation; and personnel training, emphasizing continuous training and personnel adaptation to manage resistance to change. Implementing BI and digital tools facilitates teams to work closely together, with noticeable improvements in coordination and operational efficiency. This paper deals with the optimization of monitoring project management of the SGR in the Office of the Attorney General of the Nation, and this experience seeks to be an example to other entities and to inspire them to walk these paths toward a culture of innovation and permanent improvement within the public sector in Colombia. These Microsoft tools are available to most national public servants and contractors, so generating the solution does not imply additional costs. The experience is well documented in the present work and provides a replicable model that can adapt to multiple contexts, promoting greater efficacy and efficiency in public administration.

Anindya Majhi, Pritha Bhattacharjee, Angela Harris et al.

Abstract India is famous for her badlands. These vast, intensely degraded landscapes occur extensively across Central and Western India, wherein they have had several adverse effects on both environment and society. However, accurate information on their current spatial extents, as well as the spatial distribution and severity of gully erosion elsewhere in the country was hitherto lacking. Considering that India has planned to effectively halt land degradation by 2030 in line with the agenda of the United Nations, and as precise spatial data is indispensable in planning and implementing land management interventions, we have created an exhaustive spatial inventory of gully erosion features in India by recording their location, extents and current management status from high-resolution satellite imagery available on Google Earth Pro. Through this first of its kind mapping endeavour and attendant spatial analysis, we have recorded the presence of gully landforms in 19 of India’s 28 states and the National Capital Region of Delhi and have estimated the total gullied area in the country between 7,451 and 8,157 km2. According to our results, states occupying 38% of Indian territory (viz., Rajasthan, Uttar Pradesh, Madhya Pradesh, Jharkhand, Gujarat and Chhattisgarh) are affected by 92% of the total gullied area of the country. We have noted a clear east-west divide in terms of the relative dominance of the mapped gully erosion features, with badlands being common in Western India and gully systems being the dominant gully feature in the east. A similar observation has interestingly also been made as regards gully management, with the major proportion of unmanaged gully erosion features occurring in Eastern India. Ultimately, we have identified 77 districts across India where urgent rehabilitative intervention is required, more than 70% of which are in Eastern and Southern India where unmanaged (active) gullies are common. That contemporary gully erosion in Eastern India poses a more serious land management challenge than that of the vast badlands of Central and Western India is a truly unexpected finding of our analysis. Our mapped data and analytical results shall be integral to efforts aiming to ameliorate the land degradation caused by gully erosion across India by supporting policymaking and planning at the governmental level and serving as useful guidance for land managers and practitioners on the ground.

M. Shaw, C. Subramaniam, G. Tan et al.

Akwasi Tagoe, Alexander Silva, Cengiz Koparan et al.

Efficiently managing agricultural systems necessitates accurate data collection from crops to examine phenotypic characteristics and improve productivity. Traditional data collection processes for specialty horticultural crops are often subjective, labor-intensive, and may not provide accurate information for precise management decisions in phenotypic studies and crop production. Reliable and standardized techniques to record and evaluate crop features using agricultural technology are essential for improving agricultural systems. The objective of the research was to develop a methodology for accurate measurement of blackberry flowers and vegetation coverage using UAV remote sensing and image analysis. The UAV captured 20,812 images in the visible spectrum, and ImageJ software (version 1.54k) was used for segmenting floral and vegetative coverage to calculate variety-specific flower coverage. A moderately strong positive correlation (r = 0.71) was found between flower-to-vegetation ratio (FVR) and visually estimated flower area, validating UAV-derived flower coverage as a reliable method for estimating flower density in blackberries. The regression model explained 51% of the variance in flower estimates (R² = 0.51), with a root mean square error (RMSE) of 2.79 flower/cm². Additionally, distinct temporal flowering patterns were observed between primocane- and floricane fruiting blackberries. Vegetative growth also exhibited stability, with strong correlations between consecutive weeks. The temporal analysis provided insight into growth phases and flowering peaks critical for time-sensitive management practices. UAV computer vision for quantifying blackberry phenotypic features is an effective tool and a unique methodology that speeds up the data collection process at high accuracy for breeding research and farm data management.

Qin Tang, Qin Tang, Fei Yan et al.

ObjectiveThis study examines biosafety management practices in a psychiatric hospital’s laboratory in China, focusing on how outdated information technology impacts the hospital’s ability to respond to public health emergencies. The goal is to enhance the hospital’s emergency response capabilities by updating risk assessments, biosafety manuals, and implementing a comprehensive quality management system alongside a specialized infection control system for significant respiratory diseases.MethodsWe utilized an integrated research approach, expanding the scope of risk assessments, updating the biosafety manual according to the latest international standards, and implementing a quality management system. A specialized infection control system for significant respiratory diseases was introduced to improve emergency response capabilities.ResultsUpdated risk assessments and a new biosafety manual have significantly improved the identification and management of biosafety threats. Implementing new quality management and infection control systems has enhanced response efficiency and operational standardization.ConclusionThe measures taken have strengthened the biosafety management and emergency response capabilities of the laboratory department, highlighting the importance of information technology in biosafety management and recommending similar strategies for other institutions.

Anuradha K., Mallik Banitamani, Krishna Vamsi M.

Sentiment analysis is a form of opinion mining technique that identifies the polarity of extracted opinions. Nowadays, opinion mining has become an important research area in recent decades to identify the polarity of the statements. Various research works have been carried out on sentiment analysis. However, the existing sentimental analysis techniques, such as time and space complexity, still have considerable limitations. To deal with these issues, this paper proposed the Cucconi Feature Extracted Random Decision Forest Classification (CFDFC) Approach. The main objective of the CFDFC approach is to provide effective sentiment analysis with improved accuracy and reduced time complexity. The proposed CFDFC framework comprisespre-processing, feature extraction, and classification. The pre-processing step eliminates stop words and stem words from user reviews. After the pre-processing step, the feature extraction process is carried out to minimize the dimensionality and time consumption for opinion classification. Cucconi's projective feature extraction process is used in this work to reduce dimensionality. Finally, the classification process is formulated using a random decision forest classifier. The random decision forest classifier uses the ID3 DT (decision tree) as a weak learner to classify the review statements. The performance evaluation of the proposed approach is carried out using performance metrics such as accuracy, error rates, recall values, and time and space complexities concerning the number of review statements gathered from the dataset. The results show that the proposed CFDFC model achieves remarkable accuracy, recall, and minimal time complexity compared to existing methods.

Arun Rai, Xinlin Tang

Ádám Lenner, Zoltán Lajos Papp, Csaba Szabó et al.

Sound analysis is an important field of research for improving precision livestock farming systems. If the information carried by livestock sounds is interpreted correctly, it could be used to improve management and welfare assessment in this field. Therefore, we hypothesized that the nasal vocalization of a mother cow could have a calming effect on conspecifics. The nasal vocalization in our study was recorded from a mother cow (not part of the test herd) while it was licking its day-old calf. The raw sound was analyzed, cleaned from noises, and the most representative vocalization was lengthened to two minutes. Thirty cows having calves were randomly selected from eighty Hungarian grey cattle cows. Two test days were selected, one week apart; the weather circumstances in both days were similar. The herd was collected in a paddock, and the test site (a restraining crate with a headlock) was 21 m away from them. The cows from the herd were gently moved to the restraining crate, and, after the installation of the headlock, Polar^® heart rate monitors were fixed on the animals. The recording of the RR intervals was carried out for two minutes. On day one of the test, the processed nasal sound was played to every second cow during the heart rate monitoring. When the sound ended, the heart rate monitor was removed. On test day two, the sound and no sound treatments were switched among the participating cows. At the end of the measurement, the headlock was opened, letting the animals out voluntarily, and a flight test was performed along a 5 m distance. The time needed to pass the 5 m length was measured with a stopwatch and divided by the distance. The RR intervals were analyzed with the Kubios HRV Standard (ver. 3.5.0) software. The following data were recorded for the entire measurement: average and maximum heart rate; SD1 and SD2; pNN50; VLF, LF, and HF. The quasi-periodic signal detected in the sound analyses can hardly be heard, even when it is enhanced to the maximum. This can be considered a vibration probably caused by the basis of articulation, such as a vibration of the tongue, for example. The SD2/SD1 ratio (0.97 vs. 1.07 for the animals having no sound and sound played, respectively, <i>p</i> = 0.0110) and the flight speed (0.92 vs. 1.08 s/m for the animals having no sound and sound played, respectively, <i>p</i> = 0.0409) indicate that the sound treatment had a calming effect on the restrained cows. The day of the test did not influence any of the measured parameters; therefore, no effect of the routine was observed. The yes–no sequence of the sound treatment significantly reduced the pNN50 and flight speed values, suggesting a somewhat more positive association with the headlock and the effectiveness of the processed nasal sound. In conclusion, we have demonstrated that, by means of sound analyses, not only information about individuals and the herd can be gathered but that, with proper processing, the sound obtained can be used to improve animal welfare.

Jacek Gad

Purpose – The article aims to determine the implementation extent of the regulations around appointment and characteristics of audit committees and regulations concerning disclosure of information about the audit committee in Polish practice. Design/methodology/approach – The author analyzed the informative content of management reports and corporate governance statements. The survey covered all domestic companies listed on the Warsaw Stock Exchange in the years from 2017 to 2021. Findings – The new guidelines resulting from hard law had a significant impact on the corporate governance on the Polish capital market. According to the research results, over the analyzed years, the share of companies listed on the Warsaw Stock Exchange, which appointed an audit committee within the supervisory board, clearly increased. Moreover, the research found that in the period under study, not all companies fulfilled the obligation to disclose information about the audit committee resulting from hard law. In particular, this applies to disclosures on how the members of the audit committee acquired competencies in the area of accounting. Practical implications – The article concerns the operation of the audit committee in public companies listed on the Polish capital market. The study can serve as a reference point for further research on corporate governance. The results of the research may be an indication for those who create legal solutions in the area of corporate governance. Originality/value – This is the first such comprehensive study on the characteristics of the audit committee and disclosures about the audit committee resulting from the introduction of hard law in this area.

Davide Andrea Guastella, Evangelos Pournaras

Smart mobility initiatives encompass innovative methods to support traffic management experts in decisions for how to improve urban infrastructures and reduce carbon footprint. Accurate and continuous information about traffic is necessary to implement effectively such decisions. This is not always possible because of the cost of the information: it is not possible to install sensor devices at large scale because of financial costs and privacy; employing a plethora of sensors requires significant computational capabilities to process the generated data. A centralized data analysis can hinder real-time applications, and limit their practical deployment in traffic management systems. This paper introduces a novel privacy-aware method for estimating traffic density using edge computing and without over-deploying privacy-intrusive surveillance technologies such as cameras. The objective is to reduce the cost of collecting data while providing accurate information to support traffic operators in decision making. We evaluate the proposed solution using a realistic traffic data of Bologna in Italy. Results shows that it yields a 45&#x0025; lower average estimation error compared to standard prediction methods. Virtual traffic monitoring devices are associated with software agents that collect data from simulated traffic and estimate traffic density measurements when this information is not available. In our experiments, when we replace 50&#x0025; of camera devices with cooperative low-cost edge devices, we obtain an average percentage error of just 22&#x0025;. This result indicates that the cooperation between virtual traffic monitoring devices offers a means to avoid massive deployment of camera surveillance devices using low-cost information provided by connected vehicles. We also compared the results to those obtained by standard regression techniques.

Matthew Pirretti, Patrick Traynor, P. Mcdaniel et al.

J. Rowley