Traditional Management Systems Research Articles

Evaluation of Responsive With Big Data Technologies

The volume of produced digital data & everyday usage is increasing as a result of rising man-machine interaction, process automation, and falling hardware and software costs.
 The vast amount of digital information produced per second worldwide in unstructured, structured, and semi-structured formats is referred to as big data in this context.
 Big data analytics is a new topic that has inspired researchers all over the world to create, develop, and implement a variety of mechanisms, technologies, architectures, and areas for evaluating the enormous amount of data created every day. Traditional database management systems struggle to make sense of the massive amounts of data that make up "big data." The paper describes a few analyses, including word count, sentiment analysis, and responsive analysis.
 Responsiveness is crucial for improving the system, identifying vulnerabilities, and ensuring that tasks are distributed fairly. Responsive is important data that can be used for making wise decisions.
 Responsive is significant for both strengths and weaknesses, not just when it identifies flaws. If the responsive analysis is performed incorrectly, the analysis's conclusion will likewise be incorrect. As a result, the system as a whole will be inaccurate because the pattern that was discovered will also be incorrect. We will utilize the Map-Reduce framework to create this suggested system for responsive analysis, and Hadoop will be used for storage.

Modelling of barriers in implementing sustainable manufacturer-supplier collaboration and coping strategies

Finding new, creative ways to improve the performance of their supply chains is one of the biggest problems that manufacturing organizations confront in the age of globalization and competition. To achieve better performance, companies should engage in networking activities such as integrating with other supply chain participants. Manufacturing businesses also face sustainability issues caused by suppliers' practices that fail to meet sustainability criteria. In this sense, developing a collaborative relationship with a supplier is essential for successfully implementing sustainable practices and gaining a competitive edge. Therefore, it is imperative for manufacturing companies to effectively manage their relationships with their suppliers by strengthening their suppliers' commitment to sustainability. The concept of sustainable supplier collaboration (SSC) emerges from the combination of sustainability and supplier relationship building. SSC, in general, broadens the traditional supplier management system by incorporating long-term partnerships into the sustainable aspects. Companies have begun to acknowledge the value of SSC and are taking initiatives in this regard. The adoption has been extremely slow, despite the assurances of sustainable collaboration with suppliers. Hence, research is required to determine how supplier collaboration with economic, environmental, and social promises has been hindered. It is important to acknowledge any hurdles that manufacturing organizations may have while developing SSC. Also, a thorough analysis of these barriers is essential so effective and sustainable collaboration with suppliers can be achieved. Therefore, the primary goal of the study is to identify and analyze barriers to sustainable collaboration with suppliers. The integrated methodology of Total Interpretive Structural Modelling-Decision Making Trial and Evaluation Laboratory (TISM-DEMATEL) is used to achieve the purpose of study. An extreme case scenario involving one manufacturer of home appliances and its suppliers is used in a dyadic India based case study. The findings of this study reveal that the most significant barriers to SSC are lack of manufacturer-supplier communications for sustainable standards and appropriate regulations, lack of trust between manufacturer and supplier, lack of scope and focus for sustainable collaboration, unwillingness to share risks and rewards, lack of top management involvement, lack of combined training programs, and lack of consistent and adequate performance measurement systems. These barriers not only contribute directly to hindering SSC efforts but also influence other barriers at intermediate and lower levels. Additionally, the study offers detailed explanations of each barrier, thereby providing valuable insights for better understanding and effective implementation of sustainable manufacturer-supplier collaboration (SMSC).

Conceptual modeling of Big Data extraction phase

As the amount of information exceeds the management and storage capacity of traditional data management systems, several domains need to take into account this growth of data, in particular the decision-making domain known as Business Intelligence (BI). Since the accumulation and reuse of these massive data stands for a gold mine for businesses, several insights that are useful and essential for effective decision making have to be provided. However, it is obvious that there are several problems and challenges for the BI systems, especially at the level of the ETL (Extraction-Transformation-Loading) as an integration system. These processes are responsible for the selection, filtering and restructuring of data sources in order to obtain relevant decisions. In this research paper, our central focus is especially upon the adaptation of the extraction phase inspired from the first step of MapReduce paradigm in order to prepare the massive data to the transformation phase. Subsequently, we provide a conceptual model of the extraction phase which is composed of a conversion operation that guarantees obtaining NoSQL structure suitable for Big Data storage, and a vertical partitioning operation for presenting the storage mode before submitting data to the second ETL phase. Finally, we implement through Talend for Big Data our new component which helps the designer extract data from semi-structured data.

H2-rich gas production from co-gasification of biomass/plastics blends: A modeling approach

East Asia experiencing massive population growth, which will certainly challenge traditional waste management systems. In recent years, gasification has attracted much attention since it converts carbon-based residues into valuable gas and requires cheaper gas cleaning equipment compared to available technologies. This study presents an ASPEN plus model for simulation of steam co-gasification of polyethylene (PE) and pine (PI) using various temperatures (740–830 °C), steam/waste ratio, S/W (0.5–0.8) and PE content in the feedstock mixture (0–60 %). The predicted results were compared with the experimental data available in the literature, and a good agreement was achieved. In general, an increase in gasifier temperature and S/W led to higher H2 production and lower tar content in the syngas resulting from co-gasification process. Regarding tar conversion, increasing the gasifier temperature played a more important role compared to adding steam to the gasifier. H2 content and H2 yield gradually increased from 33.01 to 47.81 % and 48.09–57.76 g/kg, respectively, when PE increased from 0 to 60 %, which may be due to a greater amount of hydrogen present in PE. Over a PE content range from 0 to 60 %, tar concentration had a nearly linear increase, which can be attributed to lower oxygen content available in the mixture.

Productive Performance of F1- (Damascus Goat × Desert) under Traditional Management in North Kordofan

This study carried out in North Kordofan state, Western Sudan (latitudes 12:15-16:32 N and longitudes 27-32 E), during the period Feb 2018 - Aug 2021 to assessment the productive and reproductive performance of crossed F1 (Desert× Damascus) under the traditional management systems, to evaluate adaptation of crossed to environmental conditions of study area, to study milk production of the crossed goats. 44 females crossed goat F1 (Damascus×Desert goat) were selected at weaning age. Two mature Damascus bucks were used in the experiment all animals were identified using ear tags and treated against external and internal parasites. All animals will set free during the day and kept in closed pen during the night. The behavior of the animals and the adaptation on the environment was observed and recorded in addition to any problems like disease; Data were analyzed using the Statistical Package for Social Sciences, software package (SPSS, V23, 2017). In this study, the Damascus Bucks were severely affected under the conditions of nature grazing and suffered from parasites and high temperature, Bucks have died as a result of tick fever according to Anatomical symptoms, The parameters of dams varied according to litter size, Females were born as a single reached puberty at (278.2±7 days) with body weight of 20.01 kg while the twins females was puberty age (291.6±9 days), and weight was 16.91kg , The average lactation period was 120 days with average total milk production of 40.46± 1.74 kg, this study conclude that the crossed Females are late in sexual maturity, So The genetic cross as a way to improve the herd without taking into account environmental conditions does not lead to the desired results.

Экологическая оценка накопления и миграции меди в почве возрастных ампелоценозов в результате длительного применения медьсодержащих фунгицидов в регионе Фрушка Гора Республики Сербия

The data on soil copper accumulation and slope migration due to long-term use of copper-containing pesticides in vineyards over 200 years old with different management systems in the conditions of the Fruska Gora region of the Autonomous Province of Vojvodina, Republic of Serbia are discussed. The study focused on brown forest residual carbonate soils found in sloping landscapes with different length, steepness and exposure. The total copper content in the soil on a permanently vegetated slope with a 10º steepness was 2-4 times higher on the farm with an archaic management system compared to the farm with a traditional management system on a 5º steep slope. The copper content variation ranged from 84.5-136.6, 72.3-189.4, and 41.0-247.5 mg/kg in horizons 0-5, 5-15, and 15-30 cm respectively. Copper migration down the slope was observed in both vineyards, although with different intensities. The coefficient of lateral differentiation for farms with lower slope steepness was between 0.90 and 1.45, while for those with higher steepness, it ranged from 0.96 to 5.57. The highest values of the coefficient were observed in the transaccumulative facies at a depth of 15-30 cm. The total copper content in the topsoil of the transit site of the ampelocenosis slope with archaic cultivation system exceeded by 21-47% the maximum permissible value in the Republic of Serbia, while in the lower part of the slope, in the horizons 5-15 and 15-30 cm, it was 2-3 times higher than the normative value. Keywords: COPPER, COPPER-CONTAINING PESTICIDES, VINEYARDS, AMPELOCENOSIS, ACCUMULATION, LATERAL DIFFERENTIATION, SLOPE, SLOPE STEEPNESS, BROWN FOREST SOIL

Campus Management System with ID Card using Face Recognition with LBPH Algorithm

The Face recognition system mentioned is a computer vision and image processing application designed to carry out two primary functions: identifying and verifying a person from an image or a video database. The objective of this research is to provide a more efficient and effective alternative to traditional manual management systems. It can be used in offices, schools, and organizations where security is critical. In the proposed system, initially, all students enrolled in the Academic Year whose information is stored in a database server and released a unique ID Card with their facial image to be a smart campus. The main objective of the proposed system is to automate the time-in, and time-out of students, teachers, staff, and anyone who enters and leaves the campus of the University of Computer Studies, Hinthada (UCSH). This system is implemented with the 405 students in the 2022-2023 Academic Year, 86 permanent staff including the principal whose ID card (Name, Year, Roll No, NRC, Father Name: for students, Name, Rank, Department, NRC, Address: for teachers and staffs). As soon as someone enters the campus of a university, the ID card is scanned, the images of the ID card are captured and the face onthe card will be matched with the faces in the trained dataset to detect by using the Haar cascade classifier, and recognize the face using Local Binary Pattern LBPH algorithm. The proposed system demonstrates strong performance, achieving an accuracy rate of over 90% for everyone entering the campus. It is both effective and efficient, providing a smart solution for identification.

The essence of accounting under the sustainable development view

About the nature of accounting, different people have different opinions in the academic circle. The classic theories mainly include management activity theory, information system theory, business language theory and so on. With the prosperity of economy and the progress of society, sustainable development has gradually become the goal pursued by enterprises and society. Under the concept of sustainable development, society's expectation on accounting has also changed, and only reflecting economic value can no longer meet the needs of enterprises and society. Enterprises and society expect accounting to provide sustainable value that fully reflects the combined benefits of environment, society and governance. Therefore, under the concept of sustainable development, accounting in essence should be a tool to comprehensively determine the sustainability value of an organization by measuring the input of economic capital, environmental capital and social capital and the value created by each of them in a special way. The understanding of the essence of accounting has also expanded from the traditional economic management system to a larger sustainable system.

Risk pre-control mechanism of mines based on evidence-based safety management and safety big data.

The overexploitation of mineral resources and the heavy use of mineral resources have caused serious environmental damage. The growing problem of mine safety also directly threatens the personal safety of the surrounding population and hinders the development of the local economy. Evidence-based safety eliminates the reliance on intuition and unsystematic aspects of traditional safety management systems by taking into account the actual production situations on site, making safety decision-making activities more scientific. However, there is frequently a lag in the transformation and feedback of evidence information, which obstructs the realization of effective safety decision-making activities. From the perspective of process safety management risk analysis and the transformation of safety big data and safety evidence, this paper proposes a new mine risk pre-control mechanism. First and foremost, based on process safety management, evidence-based safety is successfully applied to mine risk control. Secondly, from the perspective of information transformation, a mine risk pre-control mechanism based on evidence-based safety management and safety big data is established. Finally, taking mine open area monitoring as an example, the application analysis of the mine risk pre-control mode constructed above is carried out. The risk pre-control mechanism proposed in this paper provides a new idea for the practice of mine risk management.

Optimization of university human resource management system on faculty members with anxiety

BackgroundDue to outdated work concepts and unscientific performance evaluations, the enthusiasm of university faculty members is not high, and some faculty members experience work anxiety, which affects the normal operation of work. The traditional human resource management system can no longer meet the needs of human resource management in universities and needs to be optimized. In order to stimulate the work enthusiasm of faculty and alleviate their psychological anxiety, research is being conducted to optimize the human resource management system in universities.Subjects and MethodsThe study selected 60 employees with work anxiety and divided them into a control group and an intervention group, with a total of 30 individuals. The former adopts a traditional human resource management system, while the latter adopts an optimized human resource management system with a duration of 6 months. Employees were evaluated using indicators such as the Hamilton Anxiety Scale (HAMA), and SPSS23.0 software was used for data processing.ResultsAfter 6 months, there was a significant difference in work psychological anxiety between the two groups of teaching staff. Compared with the control group, the HAMA score of the intervention group was significantly lower than that of the control group (P<0.01).ConclusionsIt needs to optimize the human resource management system in universities, improve performance evaluation methods, stimulate the enthusiasm of faculty, and ensure that their efforts are treated fairly, then resulting in a significant improvement in their work anxiety.

E-Prescription: A practical application of information and communications technology in perspective of Bangladesh

ObjectivesThe healthcare management authorities are responsible for delivering convenient services to the patients. The traditional healthcare management system is quite old and impractical in many cases, including a physical visit. Additionally, the COVID-19 epidemic makes the existing system unattainable, which creates an uncomfortable situation for visiting doctor's chambers that is risky both for doctors and patients. An electronic-prescription (e-prescription) management system can switch the existing one to the online appointment and doctor consulting system. Many developed countries have already adopted such e-prescription management systems, although low-and-middle-income countries (LMICs) like Bangladesh are apathetic. So implementing e-prescription management systems in all countries, including Bangladesh, is the demand of time, especially when information and communication technologies (ICT) are at hand. MethodWe design, develop and test an ICT-based online doctor and patient management system utilizing the latest software and web development tools. ResultsIn the developed e-prescription management system, the patient can visit their profile to make an appointment according to their need and doctor's availability. After that, the patient consults with the doctor based on the appointment's approval by the admin panel. Finally, the patient receives an online e-prescription and collects the medicine from a registered pharmacy with access to the online e-prescription. The e-prescription management system records patient history, including e-prescription, making handling patients easy. ConclusionThe proper use of the developed e-prescription management system will solve many existing problems of the existing healthcare management system, including many concerns that arise due to the advent of COVID-19.

Evaluation on power information data asset management system based on BP neural network

With the popularization and development of the current power system, power information data asset management plays a crucial role in modern power systems. However, traditional management methods have some problems, such as low information processing efficiency, low prediction accuracy, and insufficient decision support. In order to better promote its development and achieve efficient management of power information data assets, this article aimed to use BP neural network (Back Propagation Neural Network) to design a power information data asset management system, achieving efficient processing and accurate analysis of power information data. In the article, data preprocessing was achieved through data separation, data cleaning, and data normalization processing. Compared with the traditional power asset management system, it has better management efficiency, lightens the difficulty of asset management and reduces the error rate. In this paper, the power information data is modeled and trained by BP neural network modeling, and the performance index is minimized by error back propagation, and the optimized BP neural network model is integrated into the power information data asset management system to realize data processing and decision support. In order to verify the performance of the power information data asset management system based on BP neural network, this paper tested its system performance. The research results showed that the average processing accuracy of the system under this method for basic data in 10 test cases reached 91.467 %, and the average rationality of decision support reached 89.6 %. The average processing accuracy of real-time data reached 91.625 %, and the average rationality of decision support reached 90.25 %. The average processing accuracy of application data reached 90.675 %, and the average rationality of decision support reached 90.2 %. The results showed that the system under this method has higher accuracy in data processing and can better achieve decision support. This study highlighted the important impact of BP neural networks on data processing, data prediction, decision support, and data security in power information data asset management systems, providing more possibilities for achieving efficient processing and accurate analysis of power information data.

Enhanced Whale Optimization Algorithm with Wavelet Decomposition for Lithium Battery Health Estimation in Deep Extreme Learning Machines

Lithium battery health state estimation can help optimize battery usage and management strategies. In response to the challenges faced by traditional battery management systems in accurately estimating the State of Health of lithium-ion batteries and addressing issues such as capacity recovery and noise interference, this paper proposes a method based on wavelet decomposition and an improved whale optimization algorithm optimized deep extreme learning machine for estimating the SOH of lithium-ion batteries. Firstly, the lithium-ion battery capacity degradation sequence is extracted, and the wavelet decomposition method is used to decompose the battery capacity into global and local degradation trends. Next, the non-linear convergence factor and the whale optimization algorithm with adaptive weights are employed to optimize the deep extreme learning machine for predicting each trend component. Finally, the prediction results are effectively integrated to obtain the lithium-ion battery SOH. This experimental method is validated using NASA and CALCE datasets, and the results indicate that the root mean square error and mean absolute percentage error are both below 0.95%, with relative accuracy and absolute correlation coefficients exceeding 98%. This demonstrates the method’s excellent accuracy and robustness.

The Concept of a Subsystem to Support the Management of the Protection of Intangible Assets of Companies from a Behavioural Perspective

The human factor is the biggest challenge for enterprises in providing the expected level of security, whereas the lack of educated personnel is one of the key problems in building an effective system for protection against data and information threats. A human being is a non-programmable element of the system and it is difficult to predict his or her behavior in information management processes and in the face of a specific event. Humans cannot be programmed like some security applications or hardware solutions with predictable performance. Human actions very often have a stochastic effect on the operation of the system. They can be ill-considered, haphazard, affected by emotions, and taken without due attention and adequate knowledge and experience (Pham et al., 2019). All these imperfections are exploited by those whose goal is to destroy or obtain information. According to data published by several information security companies, attacks carried out by purpose-built bots and web applications that exploit a technical factor (e.g., system vulnerabilities) are becoming increasingly rare, and are being replaced by attacks in which human interaction is a key factor. The curiosity and trust, leading well-meaning individuals to click, install, open, and send information, are being exploited by cybercriminals who are increasingly adept at using social engineering techniques.
 The aim of the present paper is to discuss the theoretical basis of information security issues from the behavioral perspective and to present the concept of a subsystem that implements measures to minimize the impact of the human factor on the emergence of threats to the intangible resources of a business entity. The concept is to create an information and organizational space to support the operation of the traditional information security management system in small and medium-sized enterprises. The concept is presented using the object-oriented approach which focuses on the functional elements of the system, and the subject-oriented approach, which takes into account the relationships between the various individuals who affect the security of the information system. The author's models of each approach were presented along with a description of how they work.

The Impact of Network Structure Elements on the Building of Service-Oriented Government in China from the Perspective of Network Governance

Building a service-oriented government to the satisfaction of the people is a basic goal and direction of the development of the Chinese government. In the current era, it has become a consensus for the government and non-governmental organizations to jointly govern public affairs. Network governance focuses on the realization and promotion of public interests as the core value, and pays attention to coordinating the complex interaction of diversified actors. It advocates sharing power in the cooperative network and jointly dealing with all kinds of problems. Compared with the traditional management system, network governance can coordinate and manage cross-border cooperation networks among governments at all levels and departments more effectively. The purpose of this study is to explore the impact of network governance on the building of service-oriented government in China. Through a questionnaire survey of 408 civil servants, this study analyzes the relationship between the network structure elements and the government service effect. The results show that the cooperation network with high stability and high intensity is positively related to the improvement of government service effect. In addition, the the government concept and the network cooperation ability are also closely related to the government service effect. These findings show the important influence of network governance in the process of building a service-oriented government, and put forward the relevant measures for the building of service-oriented government.

Equestrianism's social license to operate: assumptions, reality and the future

Horse sports and equestrian activities are high risk to the horses and people undertaking them. Societal views on using animals for human entertainment are changing and there is increased debate on how animal welfare is safeguarded. Traditional management systems that reduce opportunities for expression of normal behaviour and high levels of disease and injury in horses interacting with humans have increased public scrutiny on the use of horses by humans, resulting in equestrianism's social license to operate being questioned. A social license to operate is a virtual license from society to engage in an activity – without this, the future of equestrianism is under threat. This review explores what constitutes a social license to operate and considers how stakeholders in the equestrian sector could work together to generate an effective social license to operate to ensure horses have a good life in all aspects of their relationship with humans.

On the Abolition of the Death Penalty for Drug Offences in China

The Criminal Law Amendment (VIII) Act and the Criminal Law Amendment (IX) Act abolished the death penalty for many non-violent crimes, in line with the provisions of our Constitution on “respecting and safeguarding human rights” and in line with the international trend towards abolition of the death penalty. However, unlike many of the non-violent crimes that have been abolished, drug offences, which are also non-violent crimes, remain on the list of capital punishment. Over the past two decades, many academic and judicial leaders have worked towards the abolition of the death penalty for drug offences. However, due to the myth of the deterrent effect of the death penalty for drug offences and the heavy-handedness of the traditional drug management system, the goal of abolishing drug offences has never been achieved. The author argues that the death penalty for drug offences, as a non-violent crime, should not be treated as the most serious crime in criminal law and should be abolished. The aim of this article is to discuss the author’s ideas and rationale for the abolition of the death penalty for drug offences and to suggest some possible measures or ways to abolish the death penalty for drug offences.

Modern paradigm of personnel management system of the transport industry

Methods. The scientific foundations of the research are general scientific theories – recognized concepts of enterprise personnel management; classification and analytical method – in the process of clarifying the constituent elements of personnel development, specifying the content of personnel technologies, researching the factors of employee activity activation. The used methods of statistical and trend analysis made it possible to identify trends and factors in the formation of the personnel management paradigm at domestic enterprises Results. The dominant trends of changes in personnel management of a modern enterprise are singled out: active use of HR technologies; transferring the implementation of individual business processes to external executors under outsourcing conditions; building new career models; automation of HR processes; formation of learning culture; taking into account changes in the labor market during personnel management. It has been demonstrated that traditional personnel management systems are transformed today into talent management, training and development of creative and intellectual activity of personnel. Employees who have a well-developed intuition, a sufficient level and set of knowledge, skills and abilities become a key factor in the success of the enterprise in the modern conditions of the digital world. Novelty. The specifics of effective personnel technologies in the field of personnel management of enterprises in the transport industry are summarized and the feasibility of their application to increase the competitiveness of companies in modern conditions of a radical change in the business paradigm is substantiated. Practical value consists in the possibility of applying the provided proposals regarding personnel management of transport industry enterprises, in particular, regarding their introduction of progressive personnel technologies using elements of the digital economy to increase the efficiency of economic activity in conditions of uncertainty. New personnel management systems are supposed to ensure the mobility of all company employees, sociality, knowledge and people management and, as a result, change the organizational structure, culture, perception of changes, transformation of personnel competencies and the management system as a whole.

Online Order Management System

Abstract: Our proposed online order management system is a platform that provides sellers with a comprehensive overview of their stock and orders. The platform streamlines the order management process, allowing the seller to view and manage their products and stocks with ease. Unlike traditional online order management systems, our platform goes beyond basic stock management and incorporates two machine learning algorithms to improve the seller's efficiency and profitability. The first machine learning algorithm provides the seller with insights into the popularity of a particular product category during a specific month. By notifying the seller of trends, they can better plan their stock levels to maximize profits. For example, if a seller notices that a particular product category is in high demand during the holiday season, they can increase their stock levels to meet the increased demand and maximize their profits. The second machine learning algorithm dynamically sets prices for the seller's products based on factors such as demand, date, and product category. This algorithm takes into account market trends and consumer behavior to set a price that is both competitive and profitable for the seller. For example, if a particular product is in high demand during a particular day, the algorithm will adjust the price to reflect the increased demand and allow the seller to sell the product at a higher price. In addition to these two machine learning algorithms, our online order management system includes a range of other features to help sellers manage their business effectively and efficiently. This includes order tracking, stock management, and customer management, all of which can be accessed from a single dashboard. The implementation of these machine learning algorithms is a crucial aspect of our online order management system, as they allow sellers to make informed decisions about their business. By using data and insights to optimize stock levels and pricing strategies, sellers can maximize their profits and minimize their losses. It is a comprehensive platform that provides sellers with the tools they need to manage their business effectively and efficiently.

Research on the Application of Cloud Computing in University Library Management System

At present, most libraries have to build their own library management system, which is undoubtedly a high-input work for large libraries or small and medium-sized libraries in developed areas. As a newly emerging technology in recent years, the huge advantages of cloud computing are incomparable to many traditional technologies. The biggest feature of cloud computing is that it can transfer the computing power of the computer to the corresponding software, from which customers can access the computer's storage system to obtain the information they need, so that resources can be shared and users can get it in time. Therefore, the traditional library management system architecture will also be challenged, and it is urgent to develop a library management system based on cloud computing. This paper studies the architecture of university library management system based on cloud computing.