Resource Manager Research Articles

General resource manager for computationally demanding scientific software (MARE)

General resource manager for computationally demanding scientific software (MARE)

The implementations of green employee relations in supporting environmental performance at Hilton Bali Resort

Hilton Bali Resort is one of the hotels implementing Green Employee Relations. Hilton Bali Resort is concerned with employee performance by providing various employee activities that impact environmental performance. However, until now, the implementation of green employee relations has yet to be fully implemented at Hilton Bali Resort. This research aims to analyze the implementation of green employee relations and to find out how green employee relations can support environmental performance at Hilton Bali Resort. This research uses a qualitative approach with data analysis techniques, the Miles and Huberman Interactive model, which consists of data reduction, data display, and conclusion drawing/verification. Collecting data is done by interviewing the Human Resources Manager and Learning and Development Manager, doing direct observation, and validating by documentation. There are three green employee relations practices that Hilton Bali Resort has implemented, and three green employee relations practices still need to be executed perfectly. Every function of green employee relations has aided environmental performance. All parts of green employee relations can support the planet indicator: involving green practices, introducing green whistleblowing and helplines, training union representatives, joint consultations in resolving environmental issues, providing sharing programs, and recognizing unions. The profit indicator also has yet to be assisted by all functions of green employee relations. The suggestion through this research is that Hilton Bali Resort can implement the other green employee relations practices that have not been fully implemented by Hilton Bali Resort, namely introducing green whistleblowing and helplines, joint consultations in resolving environmental issues, and recognizing the union as a key stakeholder.

Remote work and human resources challenges from the Covid-19 pandemic scenario: The cases of Italy and Portugal

This study presents the preliminary results of a European project (EURECA) being carried out in Italy and Portugal. One of its aims is to understand the role of remote work arising from the recent pandemic. The question that drove this research was: What is the role of remote work resulting from the emergent changes of the 2019 pandemic scenario in Portuguese and Italian organisations?. Case studies were used as the methodological approach, and the qualitative and inductive work directed the research, guided by the assumptions of practice-based theory. Thus, interviews were conducted with human resource managers and/or directors of companies/public institutions. So far, the sample comprises 16 organisations. The results show that before the crisis, which lasted about two years, most organisations did not engage in remote work. Afterwards, human resources practices had to adapt to this new reality, and hybrid work (a combination of remote and face-to-face work) is currently present in most of the organisations studied. New challenges are also appearing in this area, including new information systems, career management, and training and performance evaluation, among others. Hence, this new model of work design also brings new challenges to organisations and management. The implications pressing issue are several: practical (for management and organisations); theoretical (new inputs on HR practices, remote working and change management); and methodological (reinforcing the importance of case studies and practice-based theory in a comparative analysis of the Portuguese and Italian contexts). Avenues for further research are also proposed.

Human resource development and job satisfaction among nurses

The skills of a good nurse manager, the quality and quantity of human resources, and the development of human resources to face changes both the internal and external environments begin with building nurses' commitment to various indicators of human resources development in hospitals that have an impact on customer or patient satisfaction. Quantitative research with an analytical observational approach was conducted in hospitals, with a sample of 136 nurses from the population obtained by probability sampling. The results of the statistical test that training is the human resources development factor that most affect the job satisfaction of nurses in hospitals with an Exp (B) ratio or odds of 1.790, indicating that nurses with more specialized training tend to be 1.790 times more satisfied than nurses with less specialized training, and that this is also true since their Exp B grades are good. This study concludes that training has a big impact on how happy nurses are. As healthcare providers in hospitals, nurses need to optimize their abilities and competencies to raise the standard of nursing care. Nursing directors are essential in building and recruiting, and measuring nurse competencies.

Designing and Curating EDI Book Displays at IALS

AbstractIn this article David Percik, Information Resources Manager at the Institute of Advanced Legal Studies, reports on a project at IALS to plan out and curate a series of book displays focusing on historically disadvantaged groups. He discusses how the themes of the displays were selected, the consequences of having two differing available spaces, and the work done by the library team to expand the displays beyond books on shelves.

Strategy of the Human Resources Department in Recruiting Quality Employees at Quest Prime Pemuda Hotel in Semarang.

The Human Resources Department has the responsibility to oversee and manage human resources and everything related to the strategy of recruiting quality employees and the period of time when the Human Resources Department is looking for new candidate replacements. The importance of the ability to recruit quality employees for the Human Resources Department is one of the factors in improving professional human resources, and recruitment problems can be resolved well, thus reducing existing issues. This study aims to determine the strategy of recruiting quality employees at the Quest Prime Hotel and to overcome obstacles in the employee recruitment process at the Quest Prime Hotel. This research is a qualitative study that takes place at the Quest Prime Pemuda Hotel in Semarang. The subject of this study is the Human Resources Manager. The methods used in this study are Observation, Interview, and Documentation, thus obtaining accurate data. The form of recruitment process implemented by the Human Resources Department is by analyzing the required positions, screening the workforce, conducting interviews and selections, and making decisions, so as to obtain new employees with quality standards.

Influence of Collective Bargaining on Organizational Performance in the Tea Factories Managed by the Kenya Tea Development Agency

This study investigated the influence of collective bargaining on organizational performance in tea factories managed by KTDA. The Kenyan tea industry faces numerous challenges that have impacted its overall performance and one potential explanation that has gained increased attention is the role of trade unions in enhancing the industry's fortunes. The study determined the relationship between Organizational Performance and Collective Bargaining. A Descriptive Survey design was adopted to conduct the study in the sixty-six (66) tea factories managed by the KTDA, which operates in all the tea-growing regions within Kenya. The factories were categorized into seven strata based on their regional location, and a sample size of 30% was randomly drawn from each stratum. This resulted in a total of 23 factories being selected for the study. Thereafter, the Human Resource and Administration Manager and Union Official were selected using purposive sampling, whereas Union Members were chosen randomly, resulting in three (3) respondents from each of the 23 sampled factories, totaling 69 respondents. Both primary and secondary data were used in this study, with primary data being collected using structured questionnaires. The questionnaires were tested and revised, and reliability was assessed, yielding a Cronbach's alpha coefficient of 0.786 that affirmed the reliability of the measure. The collected data underwent both descriptive and inferential statistical analysis. The analysis revealed that collective bargaining (Beta = 0.347, t = 3.296, p =0.002) had a significant positive effect on organizational performance. The study recommended that organizations should improve the quality of collective bargaining practices in the workplace for improved organizational performance.

Transactional Cross-Chain Smart Contract Invocations

Blockchains have become increasingly important in recent years and have expanded their applicability to many domains beyond finance and cryptocurrencies. This adoption has particularly increased with the introduction of smart contracts, which are immutable, user-defined programs directly deployed on blockchain networks. However, many scenarios require business transactions to simultaneously access smart contracts on multiple, possibly heterogeneous blockchain networks while ensuring the atomicity and isolation of these transactions, which is not natively supported by current blockchain systems. Therefore, in this work, we introduce the Transactional Cross-Chain Smart Contract Invocation (TCCSCI) approach that supports such distributed business transactions while ensuring their global atomicity and serializability. The approach introduces the concept of Resource Manager Smart Contracts, and 2PC for Blockchains (2PC4BC), a client-driven Atomic Commit Protocol (ACP) specialized for blockchain-based distributed transactions. We validate our approach using a prototypical implementation, evaluate its introduced overhead, and prove its correctness.

The Impact of Online Education in Bangladesh- A Case Study During Covid 19

Educational Data mining is a conspicuous research area that helps to develop an educational context. The primary purpose of this work is to find out the factors or attributes for finding out the impact of online education on school-level students in Bangladesh. To prepare the attributes, help was taken from some of the renowned persons of the English Medium and Bangla medium Schools in Bangladesh, such as the principal, vice-principal, coordinator, teacher, human resources manager, parents, and students. A set of questionnaires with 20 different questions were prepared. Google Forms collects data from students to identify the relevant attributes. This study reveals the main factors of online education in Bangladesh for school-level students. This study finds the strengths and weaknesses of online education for students. It refers to the idea of overcoming the disadvantages of online education. In the future, this study will help to implement a better online education system for school students in Bangladesh

Machine learning in run-time control of multicore processor systems

Abstract Modern embedded and cyber-physical applications consist of critical and non-critical tasks co-located on multiprocessor systems on chip (MPSoCs). Co-location of tasks results in contention for shared resources, resulting in interference on interconnect, processing units, storage, etc. Hence, machine learning-based resource managers must operate even non-critical tasks within certain constraints to ensure proper execution of critical tasks. In this paper we demonstrate and evaluate countermeasures based on backup policies to enhance rule-based reinforcement learning to enforce constraints. Detailed experiments reveal the CPUs’ performance degradation caused by different designs, as well as their effectiveness in preventing constraint violations. Further, we exploit the interpretability of our approach to further improve the resource manager’s operation by adding designers’ experience into the rule set.

The Story of AWS Glue

AWS Glue is Amazon's serverless data integration cloud service that makes it simple and cost effective to extract, clean, enrich, load, and organize data. Originally launched in August 2017, AWS Glue began as an extract-transform-load (ETL) service designed to relieve developers and data engineers of the undifferentiated heavy lifting needed to load databases, data warehouses, and build data lakes on Amazon S3. Since then, it has evolved to serve a larger audience including ETL specialists and data scientists, and includes a broader suite of data integration capabilities. Today, hundreds of thousands of customers use AWS Glue every month. In this paper, we describe the use cases and challenges cloud customers face in preparing data for analytics and the tenets we chose to drive Glue's design. We chose early on to focus on ease-of-use, scale, and extensibility. At its core, Glue offers serverless Apache Spark and Python engines backed by a purpose-built resource manager for fast startup and auto-scaling. In Spark, it offers a new data structure --- DynamicFrames --- for manipulating messy schema-free semi-structured data such as event logs, a variety of transformations and tooling to simplify data preparation, and a new shuffle plugin to offload to cloud storage. It also includes a Hivemetastore compatible Data Catalog with Glue crawlers to build and manage metadata, e.g. for data lakes on Amazon S3. Finally, Glue Studio is its visual interface for authoring Spark and Python-based ETL jobs. We describe the innovations that differentiate AWS Glue and drive its popularity and how it has evolved over the years.

Assessing Employee Engagement Level in FnB Service Industry: Case Study PT XYZ Indonesia

The food and beverage service industry has grown rapidly in Bandung region over the past ten years. The industry itself is a customer-focused industry. In this regard, employees are a valuable asset for a company. Therefore, a company needs to have employees engaged in their workplace. The ability of engaged employees to assist the business in numerous ways, particularly concerning sustainability, has also been demonstrated. As a holding company founded in 2017, PT XYZ manages six cafe branches in Bandung and Cimahi. During an interview, the human resources manager stated that in 2022, the turnover rate increased by 4% compared to the previous year in 2021, when there were no resignations at all. Apart from that, many employees are content to stay in the company. In addition, the company had never conducted an employee engagement assessment to measure employee engagement to the company since it did not have the tools while measuring employee engagement is considered important for improving its overall performance. The researcher chose the Aon Hewitt employee engagement model to measure employee engagement because it can classify and identify facets of employee engagement consisting of “say, stay, strive.” The model can also determine which drivers influence an employee’s engagement or disengagement. A Likert scale-based questionnaire from 1 to 6 was distributed to 122 employees as part of the research’s quantitative methodology. The study’s findings indicate that 81% of PT XYZ employees are highly engaged, with an average of 80% of employees representing “say, stay, strive.” In addition, diversity and inclusion is a driver that influences employees to be engaged, with a value of 92.37, while the last-ranked driver is a risk, with a value of 64.69.

The impact of management gender diversity on productivity: The contextual role of industry gender composition

Managers of different genders play an important role in the success of an organization. Little is known, however, about how management gender diversity is associated with employee productivity at different levels of diversity and the context that might influence this relationship. Integrating the knowledge-based view with role congruity theory, we propose a U-shaped relationship between management gender diversity and employee productivity. As role congruity–related gender stereotypes can be salient in male-majority industries, we advance knowledge by proposing industry gender composition as a key contingency. Building on the integration of theories, we propose that the U-shaped curvilinear relationship will be more pronounced in male-majority industries than in female-majority industries. The predictions were tested using data collected from 248 medium- to large-sized for-profit organizations in Australia via a human resource manager survey and an archival source. The regression results indicate a U-shaped curvilinear relationship across industries and provide the first evidence of a U-shaped curvilinear relationship in male-majority industries and an inverted U-shaped curvilinear relationship in female-majority industries. The findings support the integration of the knowledge-based view and role congruity theory, advance knowledge of industry gender composition dynamics, and provide leaders insights into the specific effects of various management gender compositions. JEL Classification: M12, M14

Runtime Resource Management with Multiple-Step-Ahead Workload Prediction

Modern embedded platforms need sophisticated resource managers to utilize their heterogeneous computational resources efficiently. Furthermore, such platforms are subject to fluctuating workloads that are unforeseeable at design time. Predicting the incoming workload could enhance the efficiency of resource management in this situation. But is that the case? And, if so, how substantial is this improvement? Does multiple-step-ahead prediction of the workload contribute to this improvement? How precise must the prediction be to improve decisions rather than cause harm? By proposing a prediction-based resource manager that aims at meeting task deadlines while minimizing energy usage, and by conducting extensive tests, we attempt to provide answers to the aforementioned questions.

Manpower Planning at SMMA Enterprises Ltd

The case study provides insights into the nuances of manpower planning in the construction industry in a post-pandemic context. This case study was developed by collecting data from employee interviews, web pages of SMMA Enterprises Ltd and research articles in the field of manpower planning. The case deals with SMMA Enterprises Ltd which is one of the leading infrastructure development companies in India. SMMA Enterprises Ltd were at crossroads in terms of manpower planning and were trying to restructure the manpower to optimize the cost. The sudden lockdown and the subsequent project delay due to COVID-19 further exacerbated the challenges faced by the company. The protagonist, in this case, is the human resources manager at SMMA Enterprises Ltd. She has a problem in terms of how to deal with manpower planning going forward especially in the challenging times because of the pandemic. Additionally, she also has a manpower planning problem because of the extension of the project. This case study can be used by academicians for classroom teaching and also can be used by practitioners as a reference case.

Digging behind the scenes: prioritizing human resources practices related to hospitality employees' attitudes and behaviors after the COVID-19 pandemic

PurposeThis study aims to provide a new vision for investigating the different human resources management (HRM) practices in hotels after the COVID-19 pandemic.Design/methodology/approachA quantitative research approach was adopted using confirmatory factor analysis and structural equation modeling to reveal updated priorities and relations as stated by 504 hospitality employees.FindingsThe research approach contributed to highlighting exciting findings, as training and development (T&D) had an insignificant effect on turnover intention (IT) or affective organizational commitment (AOC) following the COVID-19 pandemic; job security (JS) had the highest impact on AOC and compensation had the highest effect on TI.Practical implicationsIndividual HRM practices have different strong impacts on employee outcomes. This paper provides human resource directors with realistic and practical implications to boost individuals' AOC and reduces their intention to quit their job in conditions of uncertainty and ambiguity.Originality/valueThis pioneering study reveals the influence of HRM practices in the hospitality HRM systems regarding employee attitudes and behaviors, especially after the COVID-19 pandemic. It provides novel theoretical and practical contributions.

Reliability-Aware and Energy-Efficient Workflow Scheduling in IaaS Clouds

Nowadays, more and more workflow applications with different computing requirements are migrated to clouds and executed with cloud resources. Workflow scheduling becomes a critical problem in the cloud environment, which focuses on meeting various quality of service (QoS) constraints. Workflow reliability and energy consumption are two essential parts in clouds and minimizing energy consumption for scheduling workflow with the reliability constraint is a challenging issue. In response to the challenge, we propose a workflow scheduling algorithm named REWS to reduce energy consumption and satisfy workflow reliability constraints. In REWS, a new sub-reliability constraint prediction strategy is adopted to break down the workflow reliability constraint to task sub-reliability constraints and the effectiveness of this strategy is proved. Moreover, an update method is adopted to adjust the task sub-reliability constraint for reducing energy consumption. In addition, a brief system framework which consists of five parts: workflow analyzer, reliability decomposer, resource manager, workflow scheduler and feedback processer is built to support the algorithm implementation of REWS. We conduct the experiments using both synthetic data and real-world data to evaluate the proposed REWS approach. The results demonstrate the superiority of REWS as compared with the state-of-the-art algorithms. <i>Note to Practitioners</i>&#x2014;Workflow scheduling is a challenging issue in emerging trends of the cloud environment that focuses on satisfying various QoS constraints. In this paper, we investigate a reliability-aware and energy-efficient workflow scheduling problem in cloud computing. A novel workflow scheduling algorithm called REWS, is designed to reduce the energy consumption and meet the workfolw reliability constraint. The basic idea of REWS is to divide the workflow reliability constraint into task sub-reliability constraints and schedule tasks with an energy-efficient scheduling strategy. We conduct the experiments to evaluate the proposed REWS and the results demonstrate that REWS outperforms the state-of-the-art algorithms.

Gluteal Tendon Tear Healing on Ultrasound 10 Weeks Following a Single Platelet-Rich Plasma Injection: A Case Report

Tendinosis with or without tendon tear is a common form of tendon pathology and should be managed differently from inflammatory tendinitis although both are termed tendinopathy. The current tendinopathy management involves rest, icing, a brace, oral anti-inflammatory medicine, and physiotherapy. Should that fail a trial of Corticosteroid (CS) injection allow surgery as a last resort. This article presents a middle-aged male, a human resources manager who suffered two occasions of tendinopathy with the first one being a gradual development of symptomatic right common flexor origin calcific tendinosis (golfer’s elbow) on ultrasound (USS) secondary to competitive squash that failed conservative management and USS-guided CS injection. He had a long-term symptomatic recovery after six weeks following a single autologous platelet-rich plasma (PRP) therapy. Three years later he injured his right hip following a twisting injury to the right hip/gluteal area resulted in debilitating symptoms, USS scan revealed gluteus minimus/ medius calcific tendinosis, a partial split tear of the gluteus minimus, and trochanteric bursitis. He failed physiotherapy and anti-inflammatory medicine. He elected PRP therapy over CS injection, he became symptoms free six weeks after the injection. Teen weeks post-injection USS revealed a complete resolution of gluteus minimus tendon tear and no trochanteric bursitis, no clear tendinosis features but calcifications present. This case demonstrates the use of relatively safe affordable clinic-based PRP therapy for long-term symptomatic control of tendinopathy with/without a tear. This is superior to oral anti-inflammatory and CS injections. Additionally, the healing of the tendon tear could save people from avoiding invasive surgery with its complications and long recovery time. Thanks to the regenerative healing power of the growth factors and signaling proteins in platelets that stimulate the internal mesenchymal stem cells. We recommend a large-scale randomized control trial to confirm those findings and standardization of the PRP technique, hoping regenerative medicine to become the mainstream therapy in several musculoskeletal pathologies, particularly in resistant injuries.

SGA Model for Prediction in Cloud Environment

With virtual information, cloud computing has made applications available to users everywhere. Efficient asset workload forecasting could help the cloud achieve maximum resource utilisation. The effective utilization of resources and the reduction of datacentres power both depend heavily on load forecasting. The allocation of resources and task scheduling issues in clouds and virtualized systems are significantly impacted by CPU utilisation forecast. A resource manager uses utilisation projection to distribute workload between physical nodes, improving resource consumption effectiveness. When performing a virtual machine distribution job, a good estimation of CPU utilization enables the migration of one or more virtual servers, preventing the overflow of the real machineries. In a cloud system, scalability and flexibility are crucial characteristics. Predicting workload and demands would aid in optimal resource utilisation in a cloud setting. To improve allocation of resources and the effectiveness of the cloud service, workload assessment and future workload forecasting could be performed. The creation of an appropriate statistical method has begun. In this study, a simulation approach and a genetic algorithm were used to forecast workloads. In comparison to the earlier techniques, it is anticipated to produce results that are superior by having a lower error rate and higher forecasting reliability. The suggested method is examined utilizing statistics from the Bit brains datacentres. The study then analyses, summarises, and suggests future study paths in cloud environments.

CORRUPTION AND INFRASTRUCTURE DEVELOPMENT BASED ON STOCHASTIC ANALYSIS

&amp;lt;p&amp;gt;The effects of corruption in urban development and urban affairs management in several south Asian countries are examined through a series of specific, distinctive, and provocative cases for which the data is more readily available. The stories and themes provide a starting point for analyzing corruption as a symptom and factor of underdevelopment, affecting efforts to use and allocate scarce resources for a higher quality of life in cities. It shows how corruption stifles imaginative and creative solutions to urban challenges while increasing future revenue sources. 3Ps has provided a chance for the public section to look at various funding expertise and options from the business sector to prepare the public infrastructure. On the other hand, governments in the source of budget limitations and other competing demands for state sources can&amp;amp;rsquo;t supply each citizenry&amp;amp;rsquo;s infrastructure. Besides, the private sector has been considered a better resource manager, and the government should concentrate on policymaking. Where P3s are put to fair use, the advantages are immense. Unfortunately, vulnerable to bribery. This is the case; whatever benefits 3P offers in reducing the urban infrastructure deficit may be eroded due to corruption, which could lead to an increase in construction or facility costs.&amp;amp;rsquo; rehabilitation. Secondly, a PPP process marred by corruption could lead to inferior construction substances. One of the fund&amp;amp;rsquo;s big chunks will be diverted to the public officials&amp;amp;rsquo; bribing via the project company. Thirdly, a corrupt process could compromise officials&amp;amp;rsquo; integrity that has been charged with accountability for inspecting and approving construction works.&amp;lt;/p&amp;gt;