Specific Job Research Articles

A Review of Algorithms and Platforms for Offloading Decisions in Mobile Cloud Computing

With the substantial growth of mobile applications and the emergence of cloud computing concepts, therefore mobile Cloud Computing (MCC) has been introduced as a potential mobile service technology. Mobile has limited resources, battery life, network bandwidth, storage, and processor, avoid mobile limitations by sending heavy computation to the cloud to get better performance in a short time, the operation of sending data, and get the result of computation call offloading. In this paper, a survey about offloading types is discussed that takes care of many issues such as offloading algorithms, platforms, metrics (that are used with this algorithm and its equations), mobile cloud architecture, and the advantages of using the mobile cloud. The trade-off between local execution of tasks on end-devices and remote execution on the cloud server for minimizing delay time and energy saving. In the form of a multi-objective optimization problem with a focus on reducing overall system power consumption and task execution latency, meta-heuristic algorithms are required to solve this problem which is considered as NP-hardness when the number of tasks is high. To get minimum cost (time and energy) apply partial offloading on specific jobs containing a number of tasks represented in sequences of zeros and ones for example (100111010), when each bit represents a task. The zeros mean the task will be executed in the cloud and the ones mean the task will be executed locally. The decision of processing tasks locally or remotely is important to balance resource utilization. The calculation of task completion time and energy consumption for each task determines which task from the whole job will be executed remotely (been offloaded) and which task will be executed locally. Calculate the total cost (time and energy) for the whole job and determine the minimum total cost. An optimization method based on metaheuristic methods is required to find the best solution. The genetic algorithm is suggested as a metaheuristic Algorithm for future work.

How Certification Exams Reflect Current Practice.

Certification exams are often the least understood aspect of certification processes. This article delves into the development of certification exams, highlighting their crucial role in assessing the knowledge and skills required for effective job performance. It explores how exams are meticulously crafted to align with specific job tasks, knowledge areas, and skill sets within various nursing specialties. Through collaborative efforts between practicing nurses and exam developers, these exams are designed to uphold validity, reliability, and fairness standards. Ultimately, certification exams are pivotal in evaluating nurses' competencies in vital aspects of clinical practice, facilitated by ongoing partnerships between nurses and certifying bodies. [J Contin Educ Nurs. 2024;55(11):513-516.].

How marketing and sales use digital tools for innovation ideation

With the widespread practice of using digital tools to work from home (WFH), it is not clear how this impacts innovation. While some scholars argue that digital tools limit the spontaneous conversations that are essential for innovation, others consider them the solution for innovation in a hybrid work environment. We suggest that the current confusion about the impact of digital tools on innovation is due to researchers (a) treating innovation as a homogeneous activity, rather than focusing on specific innovation activities, and (b) ignoring the nature of specific jobs of employees participating in this process. This study explores how marketing and sales professionals use digital tools during innovation ideation. The findings show that various digital tools are used for idea generation, assessment, and development. During each of these stages, marketing and sales personnel use a different mix of digital tools – serving different purposes – and face different challenges. Study findings contribute to our understanding of how digital tools impact innovation and help managers to improve innovation ideation in hybrid work environments.

The Influence of Training and Development Programme on Staff Performance: A Case of Tanzania Revenue Authority in the Coast Region

Training and development programmes play a crucial role in enhancing staff performance within an organization. These programmes are designed to improve employees’ knowledge, skills, and abilities, ultimately leading to increased productivity, efficiency, and overall organizational success. One of the primary reasons why training and development programmes are crucial for staff performance is that they contribute to the enhancement of employees’ skills and knowledge. Through targeted training initiatives, employees can acquire new skills, stay updated with industry best practices, and gain a deeper understanding of their roles within the organization. It is in this context, this study assessed the influence of training and development program on staff performance: a case of Tanzania Revenue Authority, coast region. The study focused on three specific objectives including to identify existing practice of training and development programmes offered by TRA coast region, to determine whether training and development programmes have effects on employees’ performance at TRA coast region and to investigate the current challenges the TRA coast region experiences in training it employees. The study was done at TRA Coast region where by a sample of 92 respondents from the population of 120 senior and operational employees who randomly and stratified sampled participated. The study was guided by transformative learning theory. Descriptive research design was employed. Questionnaires and interview questions were used to collect data. Data was analyzed using descriptive and regression analysis. Findings suggest that on-the-job training at TRA allows employees to acquire specific job- related skills in a real work environment. Through engaging in actual tasks and responsibilities under the guidance of experienced mentors or supervisors, employees can develop a deeper understanding of their roles and responsibilities, Findings further suggest that off-the-job training opportunities have played a significant role in enhancing employees’ overall professional development at the Tanzania Revenue Authority (TRA). It was revealed from the study that TRA is relevant to employees’ job responsibilities, and that the feedback received during on-the-job training is constructive while training and positively impacted employees’ job performance. Findings revealed that off-the-job training opportunities enhanced employees’ overall professional development. The study concludes that on-the-job training programmes at TRA are relevant to employees’ job responsibilities, and for that case the feedback received during on- the-job training is constructive. The study also concluded that induction training provided by TRA Coast Region adequately familiarizes new employees with organizational policies and procedures. It was recommended that the management of TRA should continue investing in training and development programmes since Training and development programmes leads to improved employee performance by equipping them with the necessary skills and knowledge to carry out their duties effectively.

Perceptions of nursing graduates regarding artificial intelligence interviews: A Q-methodology study

Background & Aim: The integration of Artificial Intelligence (AI) in recruitment processes is increasingly prevalent, particularly within medical institutions. AI interviews are becoming a common practice, and their impact on the perceptions and experiences of candidates is a subject of growing interest. Nursing graduates, who are often at the forefront of medical practice, frequently encounter these AI-driven evaluations during their job searches. This study attempted to examine the perception of AI interviews among nursing graduates who have experienced AI interviews in medical institutions. Methods & Materials: The Q-methodology was applied by selecting 34 Q samples from the 102 concourses extracted through a literature review and in-depth clinical interviews with nursing graduates. The P sample consisted of 35 nursing graduates who had experienced AI interviews. Data were collected using the PQ Method's Q-methodology program, measured on a 9-point scale frame, and Q samples were normally distributed. Results: The study identified four factors of perception: Proactive AI Interview Preparation, Negative Perception of AI Interviews, Positive Perception of AI Interviews, and Critical Acceptance of AI Interviews. Conclusion: In conclusion, perceptions of AI interviews can be categorized into four main types, highlighting both the positive and negative aspects of this technology. The positive aspects include efficiency, fairness, and convenience, while the negative aspects involve concerns about privacy, bias, and the lack of human elements. To design AI interview programs tailored to specific job roles, it is crucial to balance these pros and cons. Additionally, reducing the burden of AI interviews through informative resources and pre-training programs is essential. For successful implementation, ongoing improvements, transparency, and a balanced integration of human judgment are necessary.

Relationship between Job Characteristics Model and Job Satisfaction with Mediating Effect of Organizational Commitment

This research discovers the relationship between Job Characteristics Model (JCM) and job satisfaction using the mediator organizational commitment on private universities faculties in Bangladesh. This study is an empirical study to understand how specific job characteristics, as defined by the JCM—namely skill variety, task identity, task significance, autonomy, and feedback—affect employee’s commitment. Besides, the study tries to find out the impact of organizational commitment on job satisfaction. Moreover, researcher investigate how organizational commitment mediates the relationship between JCM and Job Satisfaction using 489 sample of faculty members from private universities in Bangladesh. For conducting this research, respondents have been selected by using convenience sampling method through a structured questionnaire. The findings reveal that JCM and organizational commitment has positive relationship, besides organizational commitment can play positive impact over the job satisfaction of the faculty members. Finally, this research depicts how organizational commitment strongly mediates the relationship between job characteristics model and job satisfaction. These insights contribute to existing literature by highlighting the importance of fostering organizational commitment for improving job satisfaction within the educational sector in Bangladesh. The study's implications suggest that university management should focus on designing jobs that enhance employee commitment to maximize satisfaction, ultimately leading to better organizational outcomes.

Lower and upper bounds for scheduling a real-life assembly problem with precedences and resource constraints

In this work, we consider a real-life scheduling problem involving the production of off-road vehicles using a three-level assembly process, subject to precedence, machines, and resource constraints. This problem shares multiple characteristics with other scheduling problems such as the Parallel Machine Scheduling and Flexible Flow Shop Problems. However, it also comprises less investigated aspects such as a specific job precedence structure resulting in a directed rooted in-tree and a global resource constraint limiting the number of simultaneously active machines. We present a straightforward adaptation of a time-indexed mathematical formulation to the problem and introduce a new lower-bounding procedure. To solve the problem, we propose constructive heuristics based on classical priority rules and adaptations of job sequencing heuristics. We also propose CORE, a specialized approach tailored to leverage the problem structure. All the algorithms are extensively evaluated on two benchmark sets, various shop floor configurations, and eight real-life scenarios. Our results reveal the general effectiveness of job sequencing approaches and demonstrate the overall superiority of CORE.

A cluster approach to matching the competences of data specialists with skills in demand on the labour market

This paper addresses the challenge of aligning the competences of data specialists with skills in demand on the labour market in the rapidly evolving field of data science. Using an open dataset of 3,744 IT job postings, the study applies K-means clustering to identify key skill groupings for data specialist positions. The optimal number of clusters is determined using the elbow method, resulting in four distinct clusters: Data Analyst & Engineer, Data Platform Engineer, Data Science & Engineering Specialist, and Cloud Data Engineer. The research methodology employs unsupervised learning techniques, specifically K-means clustering, to analyze the distribution of skills across job postings. The clusters are visualized using t-distributed Stochastic Neighbor Embedding (t-SNE), providing insights into the relationships between different skill sets. The study reveals that job titles do not always unambiguously define the required skills, emphasizing the importance of focusing on specific skill sets rather than job titles alone. To bridge the gap between specific subject competences academic programs and industry requirements, the paper proposes a novel approach for comparing the proportion of skills in job clusters with the proportion of professional competencies in academic programs. This method is demonstrated using the Information Systems and Technologies Master's program at Kherson State University as a case study. The chi-square test is applied to confirm the statistical similarity between the skill structure of the Data Science & Engineering Specialist cluster and the competency structure of the academic program. The findings highlight the importance of continuous adaptation of profile of academic program to meet evolving industry needs. The proposed approach provides a data-driven framework for universities to align their programs with labor market demands, potentially improving graduate employability in the data science field. The study also underscores the need for personalized learning paths that can be tailored to individual career goals and skill gaps. Future research directions include the development of an artificial intelligence system to form individualized educational trajectories based on the skills required for specific job clusters. This could further enhance the alignment between education and industry needs, preparing students more effectively for the dynamic data science job market.

Морально-етичні норми в юриспруденції

It was found that the moral and ethical norms in jurisprudence were reflected in the relevant Codes, Instructions, Rules of Conduct, etc., which are aimed at ensuring the principle of peoplecenteredness and contribute to the formation and development of a morally mature specialist with high value orientations in the field of professional duties and interpersonal communication Compliance with moral and ethical standards in jurisprudence is a guarantee of maintaining stable professional relationships in the legal team and contributes to maintaining a positive image of the legal profession. It was emphasized that professional activity implemented in the “person-to-person” format requires not only proper expertise, but also perfect standards of moral and ethical interaction to prevent violation of human rights and freedoms and personal values. Jurisprudence is one of the areas where the official-business interaction between representatives of this profession and citizens is tangential to a person’s private life and personal boundaries. That is why it is important to regulate the ethical aspect of such interaction for full cooperation and the most positive resolution of problematic issues. It is noted that ethical codes define a system of value orientations of representatives of a certain professional direction, in particular, persons who perform specific job duties and are empowered to cooperate with their colleagues or subordinates, as well as all physical and legal entities with whom they cooperate. Attention is focused on the fact that the proper level of moral and ethical culture of a lawyer contributes to the prevention and avoidance of his professional deformation, because a high level of professionalism, unfortunately, is not an obstacle to the development of professional deformation. A developed moral and ethical culture and the desire for personal development do not allow signs of antivalue behavior of a person to manifest. When forming and implementing moral and ethical norms in Ukrainian jurisprudence, the experience and practice of the world legal community is taken into account. Recognition and observance of international standards enables the active cooperation of relevant competent authorities with international organizations to ensure law and order and prevent violations of human rights.

How do Danish humanities PhD school leaders constitute their roles? Interactions of biography, place and time

Purpose Increasingly governmental policy around PhD education has resulted in greater university oversight of programs and student experience – often through creating central PhD Schools. While student experience is well researched, the experiences of Heads of these units, who are responsible for creating student experience, have been invisible. This exploratory Danish case study begins such a conversation: its purpose to examine the perceptions of five Heads of PhD Humanities Schools, each responsible for steering institutional decisions within Danish PhD policy landscapes. Design/methodology/approach A qualitative approach integrated three distinct analyses: a review of Danish PhD education policies and university procedures, each university’s job specifications for the Heads of the Schools and the Heads’ views on their responsibilities. Findings The Heads differentiated between their own and today’s PhD student experience. They had held prior leadership roles and fully supported institutional regulations. They cared deeply for the students under their charge and were working to achieve personal goals to enhance PhD experience. Their leadership perspective was relational: enhancing individual student learning through engaging with multiple PhD actors (e.g. program leaders) – when possible at a personal level – to improve PhD practices. Originality/value This study contributes an expanded perspective on how PhD School Heads constitute their roles by empirically linking: macro-national policies and institutional regulations and individuals’ biographies to their support of the PhD regimes – with implications for academic leadership generally. The authors argue research into PhD School leadership is essential, as it is such individuals who create the organisational settings that students experience.

Nonlinear Analysis of EDF Scheduling Framework for Resource Distribution in Cloud Computing

In modern times, the field of information technology is significantly shifting towards cloud computing. This innovative technology involves the permanent storage of resources on servers, which clients access via the internet. Typically, a cloud comprises a collection of resources known as virtual machines, capable of managing both computational tasks and storage needs. As the demand for cloud services continues to rise, the scheduling of these resources presents a considerable challenge. Scheduling refers to the workflow management necessary to complete tasks within the system. An efficient scheduler adapts its scheduling policy dynamically in response to changing conditions and task requirements. Cloud computing represents a recently developed technology where resources, whether physical or virtual machines, are permanently stored on servers and accessed by users through the internet. The cloud offers various service models, including Platform as a Service (PaaS), Software as a Service (SaaS), and Infrastructure as a Service (IaaS). In this context, IaaS refers to a set of resources, including virtual machines, that provide computational and storage services. Given the increasing adoption of cloud technology, resource scheduling has become a critical task. Hence, optimizing the scheduling of requests to ensure the best utilization of cloud resources is essential. This paper introduces a Nonlinear Analysis of EDF Scheduling Framework for resource allocation that considers deadlines and processing times when assigning resources to specific jobs. The performance metrics, including Average Turnaround Time, Average Waiting Time, and Average Deadline Violation, show a significant improvement when compared to traditional scheduling models such as First-Come, First-Served (FCFS), the Shortest Job First (SJF), and Simple Earliest Deadline First (EDF) models.

Enhancing the hiring process: A predictive system for soft skills assessment

Human Resource Management faces the ongoing challenge of identifying top-performing candidates to enhance organizational success. Traditional recruitment methods heavily rely on assessing hard skills alone, overlooking the importance of soft skills in identifying individuals who excel in their roles. To address this, our paper introduces a novel predictive model that leverages Artificial Intelligence in the hiring process. By analyzing soft skills extracted from CVs, cover letters, websites, professional social media, and psychometric tests, the model accurately predicts potential candidates suitable for specific job roles. This system effectively eliminates poor hiring decisions, reduces time and effort, minimizes recruitment costs, and mitigates turnover risks. The implementation of our proposed model employs various predictive machine learning classifiers, with key input soft skills including creativity, collaboration, empathy, curiosity, and critical thinking. Notably, the Support Vector Machine classifier emerges as the top-performing model in terms of predictive accuracy

Immigrant overeducation across two generations: the role of gender and part-time work

Abstract Overeducation implies having a higher level of education than that required to perform a specific job. In this regard, a large body of literature shows that first-generation immigrants born in developing countries experience a higher likelihood of being overeducated than natives due in part to their foreign origin (i.e. immigrant overeducation). However, evidence is remarkably scarce regarding the overeducation of second-generation immigrants. Using a matched employer–employee database for Belgium over the period 1999–2016 and generalized ordered logit regressions, we contribute to the literature with one of the first studies on the intergenerational nexus between overeducation and origin among tertiary-educated workers. Our estimates suggest that immigrant overeducation disappears across two generations, except for workers from the Near and Middle East and the Maghreb. Moreover, we show that immigrant overeducation is a persistent intergenerational phenomenon among part-time workers. Our gender-interacted estimates confirm this conclusion for both male and female workers.

The Relationship Between Locus of Control, Perceived Organizational Support and Job Satisfaction in Emergency Service Workers

With this study we provide conclusive evidence on the importance of locus of control and organizational support provided by bosses/colleagues in the workplace for optimal satisfaction and adaptation of emergency department employees. Thus, employees who have a high level of externality (have an externalist orientation) dimension of locus of control, as well as a high level of perceived organizational support from their managers and/or colleagues, will more frequently have higher levels of specific job satisfaction and general job satisfaction. The mentioned personality characteristics, together with other characteristics, can become predictors used in the process of psychological assessment for selection purposes to predict adaptation at work. In this sense, from the data obtained it can be seen that the variation in generic job satisfaction can be explained in 12.6% by the perceived organizational support variable, and the variation in specific job satisfaction can be explained in 63.4% by the externality variable, as a dimension of locus of control.

Exploring Educational Neuroscience as a Professional Practice

Educational neuroscience can be viewed in a twofold manner: as a field of study and as a profession. This review is specifically focused on exploring educational neuroscience as a profession, arguing that depicting its professional landscape is of equal significance to the understanding of its disciplinary boundaries. Accordingly, when educational neuroscientists have the necessary training and skills to provide educational services to individuals, groups, or organizations, they should be legally authorized and receive the same licensure and recognition benefits as their peers from other disciplines. It is not argued that every educational neuroscientist is or should be a professional practitioner. However, providing a specific job description for educational neuroscience professionals may facilitate their efforts to secure positions that fully utilize their skills and expertise.

Mental distress and well-being in geriatric professionals: The role of job satisfaction

BackgroundAs limited evidence is available on health professionals’ experience during the post-pandemic period, the interplay between job satisfaction components, mental distress and well-being was investigated among workers of an Italian geriatric institution. MethodsIn Spring 2022, 205 participants (females =75.6%), primarily healthcare assistants (36.6%), nurses (16.6%), and rehabilitation professionals (14.1%), completed the General Health Questionnaire (GHQ), the Mental Health Continuum-Short Form (MHC-SF), and the Job Satisfaction Questionnaire. Data analyses comprised Multiple Regressions, Relative Weight Analyses, and ANOVA. FindingsSatisfaction with working conditions and leadership exhibited negative associations with distress, while satisfaction with patients, colleagues, results, and leadership were positively correlated with well-being. Participants with high well-being levels scored significantly lower across mental distress dimensions than participants reporting poor well-being levels. ConclusionsResults showed that specific job satisfaction components relate differently to distress and well-being, suggesting the need for implementing organizational resources, psychological support, and interprofessional collaboration in healthcare services.

Ворохобова Департамента здравоохранения города Москвы.

To reduce the workload of nursing staff, it is necessary to develop new approaches to the organization of work, new methods and forms of managing these personnel. Purpose of the study is to develop a system for the distribution of duties of non-medical personnel in order to improve the efficiency of medical organization functioning, basing on the example of the Vorohobov’s City Clinical Hospital № 67. The system will significantly reduce the workload of medical personnel, increase staff motivation and improve the quality of medical services provided. Material and methods. The features of the the Vorohobov’s City Clinical Hospital № 67 functioning, as well as the personnel reform carried out, contributing to the optimization of the activities of medical personnel, are considered. A quantitative analysis of the costs and structure of the nurses working time in the Vorohobov’s City Clinical Hospital № 67 was carried out on the basis of statistical accounting methods: an inventory of tasks and a survey of nurses in a separate building of the medical organization were performed. Results. It was revealed that the greatest time costs for performing labor operations that do not require medical qualifications during the working day fall on the nurses of treatment (procedure) room and dressing examination (bandaging room). Specific job responsibilities that can be delegated to non-medical staff have been identified. According to the results of a quantitative study, the modernization of labor organization principles in medical organizations on the example of the Vorohobov’s City Clinical Hospital № 67 consists in delegating labor operations, such as document handling and working with electronic resources, to non-medical personnel. Findings. The results of the study can be used by the management of medical organizations in the organization of labor and the distribution of the workload of medical and non-medical personnel to improve the quality of medical services provided.

Job Analysis and Curriculum Design of South Korean Animal-Assisted Therapy Specialists Using DACUM.

This study analyzed the jobs of animal-assisted therapy specialists using the Development of a Curriculum (DACUM) technique, a job analysis method for the duties and tasks performed in a specific job. It derived nine duties and 54 tasks through a verification process. In addition, by analyzing the knowledge, skills, and attitudes according to the task, the duties of animal-assisted therapy specialists were derived with 37 knowledge points (K), 32 skills (S), and 46 attitudes (A). The curriculum was designed based on the results derived from the job analysis. The final derived subjects were "understanding the counselee", "clinical practice", "therapy-assisted animal management", "case conceptualization", "psychological test and evaluation", "program development", "understanding and practice of counseling psychology", "animal-assisted intervention introduction", "evaluation analysis and report", "case study and practice", "case guidance and management", "training and behavior", and "animal welfare". These results can improve the professionalism of animal-assisted therapy specialists and the overall quality of the therapy site.

Faktor Utama Keterlambatan Pembayaran Dalam Proyek Perumahan Subsidi dan Komersial

In the implementation of housing development, the problem of late payment delays is a common issue encountered in commercial and subsidized housing projects during construction. These delays impact the timely completion and lead to disputes among the involved parties, which include owners, contractors, and subcontractors. This study aims to analyze the primary factors contributing to late payment in construction projects, specifically in commercial and subsidized housing. The analysis is conducted from the perspective of the owner, contractors, and subcontractors. The study involves six owner respondents, six contractor respondents, and four subcontractor respondents. The survey results were analyzed using the Analytical Hierarchy Process (AHP) to assess the significance of various factors influencing payment delays in both housing schemes. The analysis results indicate that financial issues with the owner's company are crucial factors from the owner's perspective in causing payment delays in both commercial and subsidized housing projects. A major challenge faced by contractors is the lack of capital availability, which can lead to delays that affect all involved parties. Meanwhile, discrepancies between job specifications not following the contract from the subcontractor's viewpoint highlight the importance of clear communication and rigorousness. All parties involved in housing projects need to improve financial management, enhance capital procurement, and tighten the supervision of contract implementation. By identifying key factors, adopting best practices can help mitigate the risk of payment delays and improve efficiency in future housing project implementations, whether commercial or subsidized.

Exploring the Use of Resume Reviews to Understand Skill Sets Valued in Biomedical Engineers by Employers

The breadth of opportunities in biomedical engineering (BME) creates both a diversity of career options for students pursuing the degree and a potential hurdle in communicating the relevance of their skills when applying for specific jobs. This conundrum has driven research efforts seeking to understand what is valued by BME employers. Our work explored this area of need through an analysis of researcher-designed resumes (DRs) based on skills potentially of interest to BME recruiters in industry and academia. DRs were distributed to potential employers through an online survey asking about their perspectives on the quality of a subset of four DRs based on their indicated area of expertise. We performed a quantitative and qualitative analysis of 12 industry and 6 academic responses and compared our results to existing BME resume evaluation rubrics. Our results confirm a quantitative alignment between existing BME resume rubrics and employer’s perceptions which was previously unexplored. Qualitative results pointed toward (1) the importance of how experiences are represented as an important differentiator in resume reviews, (2) the acknowledgment from reviewers that resumes are only one step in a job application, and (3) specific similarities and differences in the skills that academic and industry employers look for in BME resumes. Our work provides validity evidence from employer perspectives to support the use of existing resume guidance tools in BME. Our qualitative data analysis expands that guidance by making recommendations for additional tools to craft resumes that clearly communicate the relevant experiences of an applicant.