In today’s rapidly evolving business landscape, organizations must continuously adapt to stay competitive. AI-driven human resource (HR) analytics has emerged as a strategic tool to enhance workforce agility and inform decision-making processes. By leveraging advanced algorithms, machine learning models, and predictive analytics, HR departments can transform vast data sets into actionable insights, driving talent management, employee engagement, and overall organizational efficiency. AI’s ability to analyze patterns, forecast trends, and offer data-driven recommendations empowers HR professionals to make proactive decisions in (...) hiring, skill development, performance management, and retention. (shrink)

This paper explores the application of AI-driven HR analytics in shaping workforce agility, focusing on how real-time data collection, analysis, and modeling foster an adaptable workforce. It highlights the role of predictive analytics in forecasting workforce needs, identifying skill gaps, and optimizing talent deployment. Additionally, the paper discusses how AI enhances strategic decision-making by providing precise metrics and insights into employee behavior, productivity, and satisfaction. The integration of AI into HR systems ultimately shifts HR from a traditionally reactive to (...) a highly proactive, data-driven function. (shrink)

By embracing AI-driven HR analytics, organizations can anticipate market shifts, prepare their workforce for future challenges, and stay ahead of the competition. This study outlines the essential components of AI-driven HR analytics, demonstrates its impact on workforce agility, and concludes with potential future enhancements to further optimize HR functions. Key words: Predictive Workforce Analytics, Talent Optimization, Machine Learning in.

This paper explores the application of AI-driven HR analytics in shaping workforce agility, focusing on how real-time data collection, analysis, and modeling foster an adaptable workforce. It highlights the role of predictive analytics in forecasting workforce needs, identifying skill gaps, and optimizing talent deployment. Additionally, the paper discusses how AI enhances strategic decision-making by providing precise metrics and insights into employee behavior, productivity, and satisfaction. The integration of AI into HR systems ultimately shifts HR from a traditionally reactive to (...) a highly proactive, data-driven function. (shrink)

Plastic waste is a significant environmental problem for almost all countries; therefore, protecting the environment from the problem is crucial. The most sensible solution to these problems is substituting the natural aggregates with substantial plastic waste in various building materials. This study aimed to optimise the mixed design ratio of cement brick containing plastic waste as aggregate replacement. Plastic cement brick mixtures were prepared by the incorporation of four different types of plastic waste such as polyethylene terephthalate (PET), high-density polyethylene, (...) low-density polyethylene and polypropylene into cement bricks with different cement contents (150, 300 and 450 g) and plastic replacement percentages (0, 3 and 6%). Compressive strength and water absorption of the plastic cement bricks were analysed using a statistical model through the response surface methodology. It revealed the optimum cement brick mixed design is C3-1% PET with the compressive strength of 27.50 MPa and water absorption of 1.16%. The optimised plastic cement brick also satisfied the general ASTM C62-17 requirements for building bricks despite the higher porosity observed by the scanning electron microscopy. The results from Fourier transform infrared spectroscopy analysis also showed that the addition of the plastic waste into cement brick was unlikely to modify the chemical compound within the cement brick mixtures. Thus, the proposed mathematical model can predict the required hardened properties of plastic cement bricks and could lead to greater utilisation of plastic waste in building materials. (shrink)

The IPAP Schizophrenia Algorithm was originally designed in the form of a flow chart to help physicians optimise the treatment of schizophrenic patients. We examined the current version from the perspective of recent work on terminologies and ontologies thereby drawing on the resources of Basic Formal Ontology, and this with the objective to make the algorithm appropriate for Semantic Web applications. We found that Basic Formal Ontology is a rich enough theory to represent all the entities involved and that applying (...) the theory to the IPAP schizophrenia algorithm results in a representation that can be used by software agents to perform monitoring and control in a referent tracking environment. (shrink)

A commonly raised criticism against celebrity culture is that it celebrates people who become famous without any connection to their skills, talents or achievements. A culture in which people become famous simply for being famous is criticized for being shallow and inauthentic. In this paper we offer a defence of celebrity by arguing against this criticism. We begin by outlining what we call the Talent Argument: celebrity is a negative cultural phenomenon because it creates and sustains fame without any (...) connection to the accomplishments that arise from an expression of talent or skill. By appealing to the metaphysics of talent and skill, we argue against the Talent Argument and propose that being a celebrity requires the skills that are necessary to acquire and maintain one’s status as a celebrity. A celebrity is more likely to be talented and successful in their expression of these skills, and even celebrities who are ‘famous for being famous’ will often display talents and skills that give rise to their fame. This means that those who critique celebrity culture should not do so by appealing to the Talent Argument. We show how our account of celebrity, talent and skill works to reject both the strong version of the Talent Argument, as well as a weaker and more plausible version of the argument we call the Valuable Talents argument. We conclude by noting that our analysis has demonstrated the need to explore more closely the kinds of skills that are necessary to cultivate celebrity status. This allows for a more nuanced understanding of what a celebrity is, and the values that are attached to celebrity culture. (shrink)

The relations between rationality and optimization have been widely discussed in the wake of Herbert Simon's work, with the common conclusion that the rationality concept does not imply the optimization principle. The paper is partly concerned with adding evidence for this view, but its main, more challenging objective is to question the converse implication from optimization to rationality, which is accepted even by bounded rationality theorists. We discuss three topics in succession: (1) rationally defensible cyclical choices, (2) (...) the revealed preference theory of optimization, and (3) the infinite regress of optimization. We conclude that (1) and (2) provide evidence only for the weak thesis that rationality does not imply optimization. But (3) is seen to deliver a significant argument for the strong thesis that optimization does not imply rationality. (shrink)

This paper explores how talent flow network and the firm life cycle affect the innovative performances of firms. We first established an interorganizational talent flow network with the occupational mobility data available from the public resumes on LinkedIn China. Thereafter, this information was combined with the financial data of China’s listed companies to develop a unique dataset for the time period between 2000 and 2015. The empirical results indicate the following: (1) The breadth and depth of firms’ embedding (...) in the talent flow network positively impact their innovative performances; (2) Younger firms’ innovations are mostly promoted by the breadth of network embedding, but this positive effect weakens as firms increase in age; (3) Mature firms’ innovations are primarily driven by the depth of network embedding, and this positive effect strengthens as firms increase in age. This paper enriches and deepens the studies of talent flow networks, and it provides practical implications for innovation management based on talent flow for various types of firms at different development stages. (shrink)

This article presents a simple derivation of optimization models for reaction networks leading to a generalized form of the mass-action law, and compares the formal structure of Minimum Information Divergence, Quadratic Programming and Kirchhoff type network models. These optimization models are used in related articles to develop and illustrate the operation of ontology alignment algorithms and to discuss closely connected issues concerning the epistemological and statistical significance of sharp or precise hypotheses in empirical science.

: In today's data-driven world, the efficient management of network resources is crucial for optimizing performance in data centers and large-scale networks. Load balancing is a critical process in ensuring the equitable distribution of data across multiple paths, thereby enhancing network throughput and minimizing latency. This paper presents a comprehensive approach to load balancing using advanced optimization techniques integrated with multipath routing protocols. The primary focus is on dynamically allocating network resources to manage the massive volume of data generated (...) by modern applications. By leveraging algorithms such as Genetic Algorithms (GA) and Particle Swarm Optimization (PSO), the proposed method efficiently distributes data across multiple paths, ensuring balanced network utilization. The combination of these algorithms with multipath routing significantly reduces congestion and improves overall network performance. Simulations conducted on various network scenarios demonstrate the effectiveness of this approach, showcasing improvements in data throughput, reduced packet loss, and enhanced quality of service (QoS). (shrink)

The Genetic Algorithm (GA) and Simulated Annealing (SA), two techniques for global optimization, were applied to a reduced (simplified) form of the phase problem (RPP) in computational crystallography. Results were compared with those of "enhanced pair flipping" (EPF), a more elaborate problem-specific algorithm incorporating local and global searches. Not surprisingly, EPF did better than the GA or SA approaches, but the existence of GA and SA techniques more advanced than those used in this study suggest that these techniques still (...) hold promise for phase problem applications. The RPP is, furthermore, an excellent test problem for such global optimization methods. (shrink)

The theme of this issue of the St. Gallen Business Review is "Harmony". For this reason, we would like to discuss whether two aspects of our life- world are in harmony, namely economic optimization and morality. What is the relation between them? According to a widely shared view, which is one aspect of the doctrine of "mainstream economics", the functioning of an economic system does not require moral behaviour on the part of the individual economic agent. In what follows, (...) we will try to convince you that this is false. If all economic agents – managers, employees, bankers, consumers and so on – were purely self-interested, as mainstream economics assumes, our economic practice would fail. There are various reasons for this. Here we will focus on one of them, namely the pivotal role of interpersonal communication. (shrink)

In today's data-driven world, the efficient management of network resources is crucial for optimizing performance in data centers and large-scale networks. Load balancing is a critical process in ensuring the equitable distribution of data across multiple paths, thereby enhancing network throughput and minimizing latency. This paper presents a comprehensive approach to load balancing using advanced optimization techniques integrated with multipath routing protocols. The primary focus is on dynamically allocating network resources to manage the massive volume of data generated by (...) modern applications. By leveraging algorithms such as Genetic Algorithms (GA) and Particle Swarm Optimization (PSO), the proposed method efficiently distributes data across multiple paths, ensuring balanced network utilization. The combination of these algorithms with multipath routing significantly reduces congestion and improves overall network performance. (shrink)

The article examines the process of formation inventory of the enterprise and determines the optimal volume of commodity resources for sale. A generalization of author’s approaches to the formation and evaluation of inventories of the enterprise is carried out. The marketing-logistic approach was applied for the purpose of distribution groups of commodity resources due to the risk of non-fulfillment the order for the supply of goods of the enterprise. In order to ensure an effective process of commodity provision of the (...) enterprises, the costs associated with the formation of inventories are determined. The formalized scheme of the formation commodity provision and the process of optimization inventory of the enterprise is offered. The analysis the structure of the company’s inventory is carried out, the volume of goods turnover is defined, the stocks are grouped for various clustering characteristics. To conduct the study, statistical information was used on commodity resources of the enterprises, statistical methods (grouping, structure analysis, estimation of dynamic series), tools for assessing the efficiency of inventory use, HML-FMR clustering were used. The necessity of using XYZ and ABC analysis is indicated in order to obtain more reliable results and forecast values of the product support of the enterprise. Economic-mathematical modeling is applied and graphically shown the difference in the formation of commodity resources by various features of HML-FMR clustering. The calculations allow the enterprise to determine the optimal amount of commodity resources in accordance with the needs of consumers and their solvent demand, to plan financial resources for the formation of inventories, to develop assortment policy in accordance with demand for products and their implementation. The results of calculations the volume of merchandising of the enterprise, taking into account the HML-FMR clustering affect the formation of final financial performance of the enterprise — income and profits. (shrink)

Why do some people become WNBA champions or Olympic gold medalists and others do not? What is ‘special’ about those very few incredibly skilled athletes, and why do they, in particular, get to be special? In this paper, I attempt to make sense of the relationship that there is, in the case of sports champions, between so-called ‘talent’, i.e. natural predisposition for particular physical activities and high-pressure competition, and practice/training. I will articulate what I take to be the ‘mechanism’ (...) that allows certain people to rise to the Olympus of athletic excellence, and what being part of this elite club ‘feels like’. My proposal is based on the idea that so-called talent and practice interact in complex and unsystematic ways. I will also argue that becoming a top athlete involves undergoing a special kind of transformation, which makes such people qualitatively different from any ‘normal’ sport amateur, even when the difference might not be immediately visible to the ‘untrained’ eye. (shrink)

One of the reasons why there is no Hegelian school in contemporary ethics in the way that there are Kantian, Humean and Aristotelian schools is because Hegelians have been unable to clearly articulate the Hegelian alternative to those schools’ moral psychologies, i.e., to present a Hegelian model of the motivation to, perception of, and responsibility for moral action. Here it is argued that in its most basic terms Hegel's model can be understood as follows: the agent acts in a responsible (...) and thus paradigmatic sense when she identifies as reasons those motivations which are grounded in his or her talents and support actions that are likely to develop those talents in ways suggested by his or her interests. (shrink)

In today's data-driven world, the efficient management of network resources is crucial for optimizing performance in data centers and large-scale networks. Load balancing is a critical process in ensuring the equitable distribution of data across multiple paths, thereby enhancing network throughput and minimizing latency. This paper presents a comprehensive approach to load balancing using advanced optimization techniques integrated with multipath routing protocols. The primary focus is on dynamically allocating network resources to manage the massive volume of data generated by (...) modern applications. By leveraging algorithms such as Genetic Algorithms (GA) and Particle Swarm Optimization (PSO), the proposed method efficiently distributes data across multiple paths, ensuring balanced network utilization. The combination of these algorithms with multipath routing significantly reduces congestion and improves overall network performance. (shrink)

The research methodology involves data preprocessing, feature engineering, model training, and performance evaluation. We employ optimization methods such as Genetic Algorithms and Grid Search to fine-tune model parameters, ensuring robust and generalizable models. The dataset used includes patient medical records, with features like age, blood pressure, cholesterol levels, and lifestyle habits serving as inputs for the ML models. Evaluation metrics, including accuracy, precision, recall, F1-score, and the area under the ROC curve (AUC-ROC), assess the model's predictive power.

This paper will be concerned with hard choices—that is, choice situations where an agent cannot make a rationally justified choice. Specifically, this paper asks: if an agent cannot optimize in a given situation, are they facing a hard choice? A pair of claims are defended in light of this question. First, situations where an agent cannot optimize because of incompleteness of the binary preference or value relation constitute a hard choice. Second, situations where agents cannot optimize because the binary preference (...) or value relation violates acyclicity do not constitute a hard choice. (shrink)

Egalitarians must address two questions: i. What should there be an equality of, which concerns the currency of the ‘equalisandum’; and ii. How should this thing be allocated to achieve the so-called equal distribution? A plausible initial composite answer to these two questions is that resources should be allocated in accordance with choice, because this way the resulting distribution of the said equalisandum will ‘track responsibility’ — responsibility will be tracked in the sense that only we will be responsible for (...) the resources that are available to us, since our allocation of resources will be a consequence of our own choices. But the effects of actual choices should not be preserved until the prior effects of luck in constitution and circumstance are first eliminated. For instance, people can choose badly because their choice-making capacity was compromised due to a lack of intelligence (i.e. due to constitutional bad luck), or because only bad options were open to them (i.e. due to circumstantial bad luck), and under such conditions we are not responsible for our choices. So perhaps a better composite answer to our two questions (from the perspective of tracking responsibility) might be that resources should be allocated so as to reflect people’s choices, but only once those choices have been corrected for the distorting effects of constitutional and circumstantial luck, and on this account choice preservation and luck elimination are two complementary aims of the egalitarian ideal. Nevertheless, it is one thing to say that luck’s effects should be eliminated, but quite another to figure out just how much resource redistribution would be required to achieve this outcome, and so it was precisely for this purpose that in 1981 Ronald Dworkin developed the ingenuous hypothetical insurance market argumentative device (HIMAD), which he then used in conjunction with the talent slavery (TS) argument, to arrive at an estimate of the amount of redistribution that would be required to reduce the extent of luck’s effects. However recently Daniel Markovits has cast doubt over Dworkin’s estimates of the amount of redistribution that would be required, by pointing out flaws with his understanding of how the hypothetical insurance market would function. Nevertheless, Markovits patched it up and he used this patched-up version of Dworkin’s HIMAD together with his own version of the TS argument to reach his own conservative estimate of how much redistribution there ought to be in an egalitarian society. Notably though, on Markovits’ account once the HIMAD is patched-up and properly understood, the TS argument will also allegedly show that the two aims of egalitarianism are not necessarily complementary, but rather that they can actually compete with one another. According to his own ‘equal-agent’ egalitarian theory, the aim of choice preservation is more important than the aim of luck elimination, and so he alleges that when the latter aim comes into conflict with the former aim then the latter will need to be sacrificed to ensure that people are not subordinated to one another as agents. I believe that Markovits’ critique of Dworkin is spot on, but I also think that his own positive thesis — and hence his conclusion about how much redistribution there ought to be in an egalitarian society — is flawed. Hence, this paper will begin in Section I by explaining how Dworkin uses the HIMAD and his TS argument to estimate the amount of redistribution that there ought to be in an egalitarian society — this section will be largely expository in content. Markovits’ critique of Dworkin will then be outlined in Section II, as will be his own positive thesis. My critique of Markovits, and my own positive thesis, will then make a fleeting appearance in Section III. Finally, I will conclude by rejecting both Dworkin’s and Markovits’ estimates of the amount of redistribution that there ought to be in an egalitarian society, and by reaffirming the responsibility-tracking egalitarian claim that choice preservation and luck elimination are complementary and not competing egalitarian aims. (shrink)

Wireless Sensor Networks (WSNs) have become increasingly prevalent in various applications, ranging from environmental monitoring to smart cities. However, the limited energy resources of sensor nodes pose significant challenges in maintaining network longevity and data transmission efficiency. Duty-cycled WSNs, where sensor nodes alternate between active and sleep states to conserve energy, offer a solution to these challenges but introduce new complexities in data transmission. This paper presents an optimized approach to aggregated packet transmission in duty-cycled WSNs, utilizing advanced optimization (...) techniques to enhance energy efficiency, reduce latency, and improve network throughput. By aggregating data packets from multiple nodes before transmission, the proposed method minimizes the number of transmissions, thereby conserving energy. Optimization algorithms such as Genetic Algorithms (GA) and Particle Swarm Optimization (PSO) are employed to determine the optimal aggregation and transmission schedules, taking into account factors such as network topology, node energy levels, and data urgency. T. (shrink)

This qualitative case study investigates the environmental implications of tourist arrivals in Matabungkay Beach, Lian, and their impact on the destination image. Through in-depth interviews with seven key stakeholders, including local residents, business owners, and environmental activists, the study explores perceptions, concerns, and potential solutions regarding the intersection of tourism and environmental sustainability. Findings reveal a complex relationship between tourism and environmental degradation, with participants expressing concerns about poor waste management, impacts on destination image, and health concerns. These challenges not (...) only threaten the natural beauty and biodiversity of the area but also tarnish the destination's image, affecting its appeal to tourists and potential investors. Despite these challenges, participants highlight existing initiatives and potential solutions, including community-based conservation efforts, sustainable tourism practices, and enhanced regulations. Collaboration among stakeholders is emphasized as crucial for achieving a balance between tourism development and environmental preservation. The study underscores the need for comprehensive strategies includes formulated an ordinance for comprehensive waste management and pollution control ordinance to optimize the destination image of Matabungkay Beach while addressing its environmental challenges. By integrating sustainable practices and fostering community engagement, the destination can enhance its appeal while safeguarding its natural resources for future generations. (shrink)

This paper investigated "The Parable of the Talents and Economic Management: Lessons for the Nigerian Nation." The subject matter of economic management in Africa in general and Nigeria, in particular, is one that concerns nearly every discipline, and which has inevitably lent itself to much pontification by economist and non-economist alike. Nigeria evolved as a nation-state in 1914 due to the amalgamation of diverse independent nationstates by the British under Lord Frederick Lugard. Since then, it has evolved different economic principles, (...) especially with the discovery of oil in Oloibiri. Historically, the Nigerian economy showed early signs of growth but is currently in a state of recession irrespective of all the economic policies by different administrations. This is contingent on mismanagement of the country's economic and human resources. The main issue that should be in the mind of researchers now is not the inevitability of recession, but its cure and how to recover from it. It is on this note that this paper looked at the Parable of the Talents according to Matt. 25:14-30 using the principle of exegesis in the interpretation of the text. It anchors its submission using the principle of accountability and Maslow's theory of motivation to chart the pathway for the management of the Nigerian economy. The paper concluded that for the proper management of Nigeria's economy there must be accountability, motivation, dignity of labour and giving of appointments base on the capacity of a worker. (shrink)

In modern data centers, managing the distribution of workloads efficiently is crucial for ensuring optimal performance and meeting Service Level Agreements (SLAs). Load balancing algorithms play a vital role in this process by distributing workloads across computing resources to avoid overloading any single resource. However, the effectiveness of these algorithms can be significantly enhanced through the integration of advanced optimization techniques. This paper proposes an SLA-driven load balancing algorithm optimized using methods such as genetic algorithms, particle swarm optimization, (...) and simulated annealing. By focusing on both resource utilization and SLA compliance, the proposed approach aims to reduce latency, improve throughput, and maximize overall system efficiency. (shrink)

t Intentional sampling methods are non-randomized procedures that select a group of individuals for a sample with the purpose of meeting specific prescribed criteria. In this paper we extend previous works related to intentional sampling, and address the problem of sequential allocation for clinical trials with few patients. Roughly speaking, patients are enrolled sequentially, according to the order in which they start the treatment at the clinic or hospital. The allocation problem consists in assigning each new patient to one, and (...) only one, of the alternative treatment arms. The main requisite is that the profiles in the alternative arms remain similar with respect to some relevant patients’ attributes (age, gender, disease, symptom severity and others). We perform numerical experiments based on a real case study and discuss how to conveniently set up perturbation parameters, in order to yield a suitable balance between optimality – the similarity among the relative frequencies of patients in the several categories for both arms, and decoupling – the absence of a tendency to allocate each pair of patients consistently to the same arm. (shrink)

The Internet of Things (IoT) connects schemes, programs, data management, and operations, and as they continuously assist in the corporation, they may be a fresh entryway for cyber-attacks. Presently, illegal downloading and virus attacks pose significant threats to IoT security. These risks may acquire confidential material, causing reputational and financial harm. In this paper hybrid optimization mechanism and deep learning,a frame is used to detect the attack prevention in IoT. To develop a cybersecurity warning system in a huge data (...) set, the cybersecurity warning systems index system is first constructed, then the index factors are picked and measured, and finally, the situation evaluation is done.Numerous bio-inspired techniques were used to enhance the productivity of an IDS by lowering the data dimensionality and deleting unnecessary and noisy input. The Grey Wolf Optimization algorithm (GWO) is a developed bio-inspired algorithm that improves the efficacy of the IDS in detecting both regular and abnormal congestion in the network. The smart initialization step integrates the different pre-processing strategies to make sure that informative features are incorporated in the early development stages, has been improved. Researchers pick multi-source material in a big data environment for the identification and verification of index components and present a parallel reduction approach based on the classification significance matrix to decrease data underlying data characteristics. For the simulation of this situation, grey wolf optimization and whale optimization were combined to detect the attack prevention and the deep learning approach was presented. Utilizing system software plagiarism, the TensorFlow deep neural network is intended to classify stolen software. To reduce the noise from the signal and to zoom the significance of each word in the perspective of open-source plagiarism, the tokenization and weighting feature approaches are utilized. Malware specimens have been collected from the Mailing database for testing purposes. The experimental findings show that the suggested technique for measuring cyber security hazards in IoT has superior classification results to existing methods. Hence to detect the attack prevention in IoT process Whale with Grey wolf optimization (WGWO) and deep convolution network is used. (shrink)

Application of the reliability of repairable systems on solving problems from constructing production systems takes an important place in the process of finding the optimal solution among the suggested system choices. The basic hypothesis when using the reliability of the repairable systems is that every machine is representing a component, a fact that is debatable when talking about technical sciences. However, considering the second assumption of the stationary process, the function of the availability is introduced. It represents the measure between (...) the reliability and the benefit of maintaining the components and the system as a whole one. An additional and the last reason for analyzing constructing machine as a whole one has an economic reason. From the aspect of the total cost and the capacity of the system, the function of the availability is catching more and more impact in the process of determinating the total cost in bill of quantities as the most important part of tender documents. Until former works, techno-economic optimisation usually ran over when choosing the system of the construction machines. In the work, there are shown the methodologies for gathering and analyzing the indicators of availabilities per unit of a company's machine park. The time of demission and reparation have been investigated among 34 components in the period of 6 years. Based on the obtained result for different conditions of machine exploitation and facilities, it is suggested the methodology of the future behaviour of the corresponding within the model optimization availability of constructing production system with the aim of eliminating extra criterion. The suggested model takes in consideration the total cost of the components when they are functional, and when they are not. This kind of approach enables the one who take choices decision of the height of profits, in the lenght of work in function of the projection of cash flow and managing with real indicators of functioning the system at the project level. Given the fact that the maintanance policy of machines is based on availability, and not on reliability of components, with the aim of maximizing the availability of different budget scenarios, a logical approach to the selection of the objective function in the terms of management of construction production systems is to minimize costs for a given availability of system constructing machinery is based on the use of historical data base with the values of the operational availability of components, conditions in which they function, in the process of forecasting the project availability for projects that follow. Ranking variant solutions is the result of the adopted function of the aim as a consequence due to enlargement methods of availability for serial parallel systems with the associated restrictions. For optimal system availability is taken a value that belongs to minimal total cost. However, it is predicted that after the end of the financial year, the real and projected indicators of system functions get compared to each other. Informational support to the proposed model is informational company system, which was built in the PHP programming language on the Linux software platform, and with data based in My SQL. The suggested model is tested on the system for the production and embedding bitumen bound materials on the specific project. Obtained results confirm the assumptions used in work. (shrink)

Intentional sampling methods are non-probabilistic procedures that select a group of individuals for a sample with the purpose of meeting specific prescribed criteria. Intentional sampling methods are intended for exploratory research or pilot studies where tight budget constraints preclude the use of traditional randomized representative sampling. The possibility of subsequently generalize statistically from such deterministic samples to the general population has been the issue of long standing arguments and debates. Nevertheless, the intentional sampling techniques developed in this paper explore pragmatic (...) strategies for overcoming some of the real or perceived shortcomings and limitations of intentional sampling in practical applications. (shrink)

The rapid evolution of phishing techniques necessitates more sophisticated detection and classification methods. In this paper, we propose a novel approach to phishing content classification using a Genetic Ranking Optimization Algorithm (GROA), combined with dynamic weighting, to improve the accuracy and ranking of phishing versus legitimate content. Our method leverages features such as URL structure, email content analysis, and user behavior patterns to enhance the detection system's decision-making process. The Genetic Ranking Optimization Algorithm (GROA) is used to rank (...) phishing content based on multiple features by optimizing the ranking system through iterative selection and weighting. Dynamic weighting further enhances the process by adjusting the weights of features based on their importance in real-time. This hybrid approach enables the model to learn from the data, improving classification over time. (shrink)

Abstract: Leadership quality is treated as both a specialized role and a social influence process and today’s business environment requires executives who are able to operate on a global scale. Talent development includes mobility between business units domestically and abroad. It is essential that job shifts and production structure be fundamentally aligned because developing large pool of talent could lead to oversupply and the developed team would simply have no place to go. The study was focused to establish (...) effects of talent development practices on leadership quality of financial sector regulatory institutions in Kenya through explanatory and cross-sectional survey design. A total population of 636 employees in the six financial sector regulatory institutions in Kenya were targeted. Stratified random sampling was embraced thus deriving 127 employees as the sample population. Both primary and secondary data was used where Primary data was collected using questionnaires which was analysed used SPSS software and presented as percentages, frequencies, means, charts and standard deviations. The study established that employee assessment, employee sourcing, leadership grooming and employee development programmes affect leadership quality. Human resource department needs to step up and play a critical role on employees’ talent development. There is need for management to have employee assessment on regular basis as this will help in identifying the skills they have and those they require, hence improving leadership quality. Over and above, the management need to have clear policies on employee assessment, sourcing, development and leadership grooming with an aim of improving. (shrink)

Cardiovascular diseases (CVD) represent a significant cause of morbidity and mortality worldwide, necessitating early detection for effective intervention. This research explores the application of machine learning (ML) algorithms in predicting cardiovascular diseases with enhanced accuracy by integrating optimization techniques. By leveraging data-driven approaches, ML models can analyze vast datasets, identifying patterns and risk factors that traditional methods might overlook. This study focuses on implementing various ML algorithms, such as Decision Trees, Random Forest, Support Vector Machines, and Neural Networks, optimized (...) through techniques like hyperparameter tuning, cross-validation, and feature selection to improve prediction accuracy. (shrink)

This capstone is centered around the development of an efficient electronic property inventory system tailored for school assets, driven by the overarching objective of resource optimization to ensure equitable access to vital materials for all learners. The methodology follows the “ISSO” framework (Ignite, Strategize, Systematize, Operationalize), complemented by a Logical Framework. The project employs a homegrown digitalized system constructed through a waterfall model approach, which undergoes alpha and beta testing. The study’s analysis utilizes a t-Test to evaluate its impact. (...) The outcomes reveal that real-time property monitoring significantly enhances custodianship, while digitalization yields improvements in reliability, efficiency, and usability, effectively overhauling the conventional inventory process. The electronic system fosters stakeholder engagement, supporting communication, budget allocation, and audits. Comparative testing demonstrates clear advantages over traditional manual methods. In conclusion, this study underscores the merits of a refined electronic property inventory system. Notably, the research suggests a need for careful consideration of process complexities in outsourcing decisions and showcases the swift, precise, and transparent accounting provided by e-AIMSS deployments, thereby nurturing transparency and public confidence. This innovative approach holds promise for broader application within the realm of e-government processes. (shrink)

Rousseau argues that holding the talented in high public esteem leads the less talented to esteem their natural virtues less highly and therefore to neglect the cultivation of these virtues. D’Holbach’s response to Rousseau indicates a sense in which esteeming talent can avoid these detrimental consequences. The starting point of d’Holbach’s defense of the sciences and arts is an analysis of the impact that despotic regimes have on esteeming talent. He argues that there is not only a problem (...) of over-valuing talent but also a problem of under-valuing talent. These considerations form the background for his conception of valuing talent in the right way. The phenomenon of political deception in despotic regimes indicates a sense in which talent can be regarded as a tool for solving a pressing political problem: Genuinely estimable uses of talent are those that oppose despotism and support republican virtues. Esteeming such talent does not lead to a loss of esteem and self-esteem for ordinary people because republican virtues themselves are a source of esteem and self-esteem. Comparison with some aspects of the response of d’Holbach’s friend, Claude-Adrien Helvétius, to Rousseau will accentuate the specific strengths of d’Holbach’s argument. (shrink)

Cloud computing is the provision of IT resources (IaaS) on-demand using a pay as you go model over the internet. It is a broad and deep platform that helps customers builds sophisticated, scalable applications. To get the full benefits, research on a wide range of topics is needed. While resource over provisioning can cost users more than necessary, resource under provisioning hurts the application performance. The cost effectiveness of cloud computing highly depends on how well the customer can optimize the (...) cost of renting resources (VMs) from cloud providers. The issue of resource provisioning optimization from cloud-consumer potential is a complicated optimization issue, which includes much uncertainty parameters. There is a much research avenue available for solving this problem as it is in the real-world. Here, in this paper we provide details about various optimization techniques for resource provisioning. (shrink)

Clark acknowledges but resists the indirect mind–world relation inherent in prediction error minimization (PEM). But directness should also be resisted. This creates a puzzle, which calls for reconceptualization of the relation. We suggest that a causal conception captures both aspects. With this conception, aspects of situated cognition, social interaction and culture can be understood as emerging through precision optimization.

It is a remarkable thing to find oneself suddenly surprised by an author after having spent years analysing, interpreting, and teaching their works. And yet, that is precisely the experience of many Kant specialists in recent times, as greater attention than ever has been placed on Kant’s discussions of gender and race. Part of the disorientation for Kantians surely comes from the way in which these investigations—oriented as they are by questions of empire as opposed to say, metaphysics—are able to (...) make a body of work that has been long-familiar seem strange and new. It is in this vein that I want to use my discussion here as an opportunity to reconsider one of Kant’s most familiar texts, the Groundwork of the Metaphysics of Morals, in order to focus on the case of moral failure presented by the person who has chosen an easy path in life: one who has ‘seine Talente verrosten ließ’ (4:423; let their talents rust, 75), to use Kant’s phrase.1 With this in focus, I will identify four subsequent counter examples offered up by Kant, each meant to offer specific cases of non-Europeans in a manner that can provide further moral instruction on this point. What this approach should reveal is not only Kant’s unsurprising consistency regarding the need for self-improvement, but also the compatibility he evidently saw between engaging his readers in moral guidance, on the one hand, and identifying non-European others as counterexamples of a morally worthless existence, on the other. (shrink)

During the 11,000 years patriarchy ruled it embedded male-bias in over 20,000 names thus making language suit their ideology of eternal males rule. Every male-biased name stops our species from seeing reality-as-it-is. Every bias hides a truth creating ignorance of what actually exists to be seen and known.

A comment on Paul Schoemaker's target article in Behavioral and Brain Sciences, 14 (1991), p. 205-215, "The Quest for Optimality: A Positive Heuristic of Science?" (https://doi.org/10.1017/S0140525X00066140). This comment argues that the optimizing model of decision leads to an infinite regress, once internal costs of decision (i.e., information and computation costs) are duly taken into account.

Phishing attacks remain one of the most prevalent cybersecurity threats, affecting individuals and organizations globally. The rapid evolution of phishing techniques necessitates more sophisticated detection and classification methods. In this paper, we propose a novel approach to phishing content classification using a Genetic Ranking Optimization Algorithm (GROA), combined with dynamic weighting, to improve the accuracy and ranking of phishing versus legitimate content. Our method leverages features such as URL structure, email content analysis, and user behavior patterns to enhance the (...) detection system's decision-making process. (shrink)

The rapid increase of the old age people imposes the reconsideration of the rehabilitation techniques and procedures and/or the development of the existing ones, at least from two points of view: the limitation use of the pharmaceutical drugs because of their secondary effects in the debilitated organisms and their avoidance; the high risk of the induced anxiety states, depression or other symptoms as a consequence of the main disease, i.e. the neuro-degenerative or mobility dysfunctions, limiting again the use of such (...) excessive drug medication. Moreover, Alzheimer’s or Parknson’s diseases are otherwise incurable, so the application of rehabilitating procedures like music-based therapy becomes preferential. The advances both in the identification of the specific auditory musical-sensitive circuits and of the non- musical neuro-connections but activated indirectly by music, otherwise inaccessible by other techniques, and in the understanding of consciousness, which can be described by seven cognitive centers, allows to improve and develop the music based therapy. A multitask procedure based on the activation of these cognition centers is presented, allowing to increase the personal psychical engagement of the patient in the recommended music based therapeutic program, addressed both to the rehabilitation of the main degenerative disease and to the secondary induced dysfunctions. This procedure combines the evidence based medicine assisted by laboratory expertise for the determination of a correct diagnostic, and narrative based medicine allowing to quantify the personal engaging qualities of the patient with respect to the proposed music based program, reducing in this way the gap between these two basic procedures and bringing in a first plane the patient care, not only the disease, with beneficial consequence for the therapy efficiency and for the patient-medical care relations. (shrink)

The predictive coding (PC) theory of attention identifies attention with the optimization of the precision weighting of prediction error. Here we provide some challenges for this identification. On the one hand, the precision weighting of prediction error is too broad a phenomenon to be identified with attention because such weighting plays a central role in multimodal integration. Cases of crossmodal illusions such as the rubber hand illusion and the McGurk effect involve the differential precision weighting of prediction error, yet (...) attention does not shift as one would predict. On the other hand, the precision weighting of prediction error is too narrow a phenomenon to be identified with attention, because it cannot accommodate the full range of attentional phenomena. We review criticisms that PC cannot account for volitional attention and affect-biased attention, and we propose that it may not be able to account for feature-based and intellectual attention. (shrink)

The Genetic Ranking Optimization Algorithm (GROA) is used to rank phishing content based on multiple features by optimizing the ranking system through iterative selection and weighting. Dynamic weighting further enhances the process by adjusting the weights of features based on their importance in real-time. This hybrid approach enables the model to learn from the data, improving classification over time. The classification system was evaluated using benchmark phishing datasets, and the results demonstrated a significant improvement in detection accuracy and reduced (...) false positives. (shrink)

Purpose: Due to the increase in energy demand and the effects of global warming, energy-efficient buildings have gained significant importance in the modern construction industry. To create a suitable framework with the aim of reducing energy consumption in the building sector, the external walls of a residential building were considered with two criteria of global warming potential and energy consumption. -/- Design/methodology/approach: In the first stage, to achieve a nearly zero-energy building, energy analysis was performed for 37 different states of (...) thermal insulation. Then, the insulation materials’ life cycle assessment was performed. These results were used to find a set of optimal modes in the Pareto front by using non-dominated sorting genetic algorithm II multi-objective genetic algorithm. Thus, based on the data obtained from this method, it was possible to compare and choose different thermal insulation materials based on the distance from the Pareto front, reducing the environmental effects. -/- Findings: The results showed that replacing the windows was possible to save 3.24% in energy consumption. Also, selecting the proper insulation reduced energy consumption value by 63.13%. Finally, this building can save 69.31% of energy consumption compared to the base building by following the zero-energy building standard. As a result, the Pareto curve was introduced as a guide for the optimal design of the building’s wall insulation. -/- Originality/value: The proposed method provides designers with a framework for latent carbon analysis to access quickly and select optimal scenarios. It can also be used without restrictions for other decisions with different goals and criteria. (shrink)

This paper will be concerned with hard choices—that is, choice situations where an agent cannot make a rationally justified choice. Specifically, this paper asks: if an agent cannot optimize in a given situation, are they facing a hard choice? A pair of claims are defended in light of this question. First, situations where an agent cannot optimize because of incompleteness of the binary preference or value relation constitute a hard choice. Second, situations where agents cannot optimize because the binary preference (...) or value relation violates acyclicity do not constitute a hard choice. (shrink)

The classification system was evaluated using benchmark phishing datasets, and the results demonstrated a significant improvement in detection accuracy and reduced false positives. The proposed model outperformed traditional machine learning algorithms, showing promise for real-world deployment in phishing detection systems. We conclude with suggestions for future improvements, such as incorporating more behavioral data and deploying the system in realtime monitoring applications.