Search results for: workload scheduling

Authors: Wen Chen

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To investigate the interleaving effect of subject matter (mathematics vs. history) and perceptual modality (visual vs. auditory materials) on student’s attention and learning outcomes, the present study collected self-reported data on subjective cognitive load (SCL) and attention level, EEG data, and learning outcomes from micro-lectures. Eighty-one 7th grade students were randomly assigned to four learning conditions: blocked (by subject matter) micro-lectures with auditory textual information (B-A condition), blocked (by subject matter) micro-lectures with visual textual information (B-V condition), interleaved (by subject matter) micro-lectures with auditory textual information (I-A condition), and interleaved micro-lectures by both perceptual modality and subject matter (I-all condition). The results showed that although interleaved conditions may show advantages in certain indices, the I-all condition showed the best overall outcomes (best performance, low SCL, and high attention). This study suggests that interleaving by both subject matter and perceptual modality should be preferred in scheduling and planning classes.

Keywords: cognitive load, interleaving effect, micro-lectures, sustained attention

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Authors: Mohamed I. Mahrous, Mohamed G. Ashmawy

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Hybrid genetic algorithm (HGA) is proposed in this paper to determine the economic scheduling of electric power generation over a fixed time period under various system and operational constraints. The proposed technique can outperform conventional genetic algorithms (CGAs) in the sense that HGA make it possible to improve both the quality of the solution and reduce the computing expenses. In contrast, any carefully designed GA is only able to balance the exploration and the exploitation of the search effort, which means that an increase in the accuracy of a solution can only occure at the sacrifice of convergent speed, and vice visa. It is unlikely that both of them can be improved simultaneously. The proposed hybrid scheme is developed in such a way that a simple GA is acting as a base level search, which makes a quick decision to direct the search towards the optimal region, and a local search method (pattern search technique) is next employed to do the fine tuning. The aim of the strategy is to achieve the cost reduction within a reasonable computing time. The effectiveness of the proposed hybrid technique is verified on two real public electricity supply systems with 13 and 40 generator units respectively. The simulation results obtained with the HGA for the two real systems are very encouraging with regard to the computational expenses and the cost reduction of power generation.

Keywords: genetic algorithms, economic dispatch, pattern search

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Authors: Sabah Yasin, Anum Obaid

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Abstract—Working women in Pakistan should not be neglected, as women make up to half of the population, and are highly educated and diversified in their skills and capabilities. With a shift in global economic and social demands the obligations of a women have altered significantly, impacted by the dual pressures of career and personal life. Despite global efforts to improve economic empowerment and health of women, through Sustainable Development Goals, they suffer from social, economic, psychological and physiological challenges. A sound understanding of working women’s nutrition and health-related stress is a prompt necessity, in areas like Faisalabad, thus leading to a public health issue. The current qualitative study is grounded under the paradigm of in-depth interviews with working women, currently working full time in Faisalabad. Participants collected through snowball sampling were women ages 30-40. This study explores the perceptions and experiences as well as barriers and factors effecting the overall wellbeing of working women, regarding nutrition and health-related stress. Findings of the current study disclosed that the nutritional and health well-being of working women in Faisalabad suffers from the impact of various stressors, like long working hours, excessive workload, low income, poor work place culture, unavailability of healthy food choices at work, lack of time, lack of self-care, unattended nutritional deficiencies and overburdened share of responsibilities. Hence, these findings highlight the need for effective strategies and support systems that will address the unique stressors faced by working women and also by educating them in changing their attitudes and understanding psychosocial barriers that impede their ability to maintain nutrition and overall well-being.

Keywords: health triangle, lifestyle behaviors, nutrition-related, professional life, stress, working women

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Authors: R. K. Yadav, S. Baral, H. R. Paudel, R. Basnet

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The Public-Private Mix (PPM) approach is a strategic initiative that involves engaging all private and public healthcare providers in the fight against tuberculosis using international healthcare standards. For tuberculosis control in Nepal, the PPM approach could be a milestone. This study aimed to explore the barriers to a public-private mix approach in the management of tuberculosis cases in Nepal. A total of 20 respondents participated in the study. Barriers to PPM were identified in the following three themes: 1) Obstacles related to TB case detection, 2) Obstacles related to patients, and 3) Obstacles related to the healthcare system. PPM implementation was challenged by following subthemes that included staff turnover, low private sector participation in workshops, a lack of training, poor recording and reporting, insufficient joint monitoring and supervision, poor financial benefit, lack of coordination and collaboration, and non-supportive TB-related policies and strategies. The study concludes that numerous barriers exist in the way of effective implementation of the PPM approach, including TB cases detection barriers such as knowledge of TB diagnosis and treatment, HW attitude, workload, patient-related barriers such as knowledge of TB, self-medication practice, stigma and discrimination, financial status, and health system-related barriers such as staff turnover and poor engagement of the private sector in workshops, training, recording, and re-evaluation. Government stakeholders must work together with private sector stakeholders to perform joint monitoring and supervision. Private practitioners should receive training and orientation, and presumptive TB patients should be given adequate time and counseling as well as motivation to visit a government health facility.

Keywords: barrier, tuberculosis, case finding, PPM, nepal

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Authors: A. M. Maruthesh, B. M. Anandakumar, O. Kumara, Akshatha Gombi, S. R. Rajini

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Women play a vital role in ensuring proper development and growth of children. They also contribute significantly towards income generation, food preparation and health. Nutritional status reflects the health of a person and is influenced by the quality of foods eaten and the ability of the body to utilize these foods to meet its needs it is affected by various socio-economic factors including income, family size, occupation and educational status of the people. The study was undertaken on nutritional status of rural women in Heggadehalli of Doddaballapurtaluk and Venkathalli of Devanahallitaluk in Bengaluru rural district with the sample size of 200 respondents. The prevalence of symptoms of malnutrition in a community is in turn a reflection of dietary consumption of its members. Mean anthropometric measurement of rural women were 153.8 cm of height, 46.8 kg of weight. In comparison with the mean BMI standards, it was observed that 20 percent of women were under nourished, 64 percent of women were normal and 16 percent women were obese. In comparison with the mean waist/hip ratio with standards, it was observed that 84 percent were in normal category and 16 percent were obese. Education, land holding, income and age had significant positive association with anthropometric measurements of rural women. The deficient level of haemoglobin existed in 53 percent of rural women, low in 20 percent and only 27 percent had acceptable level. The occurrence of morbidity symptoms was higher in rural women, its illness reported among women in the study were pain in hands and legs, backache, headache, pain in abdomen, fever, weakness, cold and cough and acidity. This may be due to considerable amount of workload on women who spend 8 to 9 hours at work and after returning continue their day’s work at home also.

Keywords: anthrometry, body index, hemoglobin, nutrient deficiency, rural women, nutritional status

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Authors: Auwal Mustapha Imam

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The aim of the energy management system is to monitor and control utilization, access, optimize and manage energy availability. This can be realized through real-time analyses and energy sources and loads data control in a predictive way. Smart-home monitoring and control provide convenience and cost savings by controlling appliances, lights, thermostats and other loads. There may be different categories of loads in the various homes, and the homeowner may wish to control access to solar-generated energy to protect the storage from draining completely. Controlling the power system operation by managing the converter output power and controlling how it feeds the appliances will satisfy the residential load demand. The Internet of Things (IoT) provides an attractive technological platform to connect the two and make home automation and domestic energy utilization easier and more attractive. This paper presents the use of IoT-based control topology to monitor and control power distribution and consumption by DC loads connected to single-input multiple outputs (SIMO) DC-DC converter, thereby reducing leakages, enhancing performance and reducing human efforts. A SIMO converter was first developed and integrated with the IoT/Raspberry Pi control topology, which enables the user to monitor and control power scheduling and load forecasting via an Android app.

Keywords: flyback, converter, DC-DC, photovoltaic, SIMO

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Authors: Christian Liebchen

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Both from an environmental perspective and with respect to road traffic flow quality, planning so-called green waves along major road axes is a well-established target for traffic engineers. For one-way road axes (e.g. the Avenues in Manhattan), this is a trivial downstream task. For bidirectional arterials, the well-known necessary condition for establishing a green wave in both directions is that the driving times between two subsequent crossings must be an integer multiple of half of the cycle time of the signal programs at the nodes. In this paper, we propose an integer linear optimization model to establish fixed-time green waves in both directions that are as long and as wide as possible, even in the situation where the driving time condition is not fulfilled. In particular, we are considering an arterial along whose nodes separate left-turn signal groups are realized. In our computational results, we show that scheduling left-turn phases before or after the straight phases can reduce waiting times along the arterial. Moreover, we show that there is always a solution with green waves in both directions that are as long and as wide as possible, where absolute priority is put on just one direction. Compared to optimizing both directions together, establishing an ideal green wave into one direction can only provide suboptimal quality when considering prioritized parts of a green band (e.g., first few seconds).

Keywords: traffic light coordination, synchronization, phase sequencing, green waves, integer programming

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Authors: Patrick May Mukonki

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KOV pit (Kamoto Oliveira Virgule) is located 10 km from Kolwezi town, one of the mineral rich town in the Lualaba province of the Democratic Republic of Congo. The KOV pit is currently operating under the Katanga Mining Limited (KML), a Glencore-Gecamines (a State Owned Company) join venture. Recently, the mine optimization process provided a life of mine of approximately 10 years withnice pushbacks using the Datamine NPV Scheduler software. In previous KOV pit studies, we recently outlined the impact of the accuracy of the geological information on a long-term mine plan for a big copper mine such as KOV pit. The approach taken, discussed three main scenarios and outlined some weaknesses on the geological information side, and now, in this paper that we are going to develop here, we are going to highlight, as an overview, those weaknesses, strengths and opportunities, in a global SWOT analysis. The approach we are taking here is essentially descriptive in terms of steps taken to optimize KOV pit and, at every step, we categorized the challenges we faced to have a better tradeoff between what we called strengths and what we called weaknesses. The same logic is applied in terms of the opportunities and threats. The SWOT analysis conducted in this paper demonstrates that, despite a general poor ore body definition, and very rude ground water conditions, there is room for improvement for such high grade ore body.

Keywords: mine planning, mine optimization, mine scheduling, SWOT analysis

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Authors: Sylvester Akpah, Selasi Vondee

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Unmanned Aerial Vehicles (UAV) as they are also known, drones have attracted increasing attention in recent years due to their ubiquitous nature and boundless applications in the areas of communication, surveying, aerial photography, weather forecasting, medical delivery, surveillance amongst others. Operated remotely in real-time or pre-programmed, drones can fly autonomously or on pre-defined routes. The application of these aerial vehicles has successfully penetrated the world due to technological evolution, thus a lot more businesses are utilizing their capabilities. Unfortunately, while drones are replete with the benefits stated supra, they are riddled with some problems, mainly attributed to the complexities in learning how to master drone flights, collision avoidance and enterprise security. Additional challenges, such as the analysis of flight data recorded by sensors attached to the drone may take time and require expert help to analyse and understand. This paper presents an autonomous drone control system using a chatbot. The system allows for easy control of drones using conversations with the aid of Natural Language Processing, thus to reduce the workload needed to set up, deploy, control, and monitor drone flight missions. The results obtained at the end of the study revealed that the drone connected to the chatbot was able to initiate flight missions with just text and voice commands, enable conversation and give real-time feedback from data and requests made to the chatbot. The results further revealed that the system was able to process natural language and produced human-like conversational abilities using Artificial Intelligence (Natural Language Understanding). It is recommended that radio signal adapters be used instead of wireless connections thus to increase the range of communication with the aerial vehicle.

Keywords: artificial ntelligence, chatbot, natural language processing, unmanned aerial vehicle

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Authors: Glenda Marie D. Balitaan

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The branch of business management that deals with inventory planning and control is known as inventory management. It comprises keeping track of supply levels and forecasting demand, as well as scheduling when and how to plan. Keeping excess inventory results in a loss of money, takes up physical space, and raises the risk of damage, spoilage, and loss. On the other hand, too little inventory frequently causes operations to be disrupted and raises the possibility of low customer satisfaction, both of which can be detrimental to a company's reputation. The United Victorious Feed mill Corporation's present inventory management practices were assessed in terms of inventory level, warehouse allocation, ordering frequency, shelf life, and production requirement. To help the company achieve their optimal level of inventory, a mathematical model was created using Integer Linear Programming. Due to the season, the goal function was to reduce the cost of purchasing US Soya and Yellow Corn. Warehouse space, annual production requirements, and shelf life were all considered. To ensure that the user only uses one application to record all relevant information, like production output and delivery, the researcher built a Visual Basic system. Additionally, the technology allows management to change the model's parameters.

Keywords: inventory management, integer linear programming, inventory management system, feed mill

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Authors: Greg Turner, Bin Lu, Cheer-Sun Yang

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As computing technology advances, smartphone applications can assist in student learning in a pervasive way. For example, the idea of using a mobile apps for the PA Common Trees, Pests, Pathogens, in the field as a reference tool allows middle school students to learn about trees and associated pests/pathogens without bringing a textbook. In the past, some researches study the mobile software Mobile Application Software Development Life Cycle (MADLC) including traditional models such as the waterfall model, or more recent Agile Methods. Others study the issues related to the software development process. Very little research is on the development of three heterogenous mobile systems simultaneously in a small university where the availability of developers is an issue. In this paper, we propose to use a hybride model of Waterfall Model and the Agile Model, known as the Relay Race Methodology (RRM) in practice, to reflect the concept of racing and relaying for scheduling. Based on the development project, we observe that the modeling of the transition between any two phases is manifested naturally. Thus, we claim that the RRM model can provide a de fecto rather than a de jure basis for the core concept in the MADLC. In this paper, the background of the project is introduced first. Then, the challenges are pointed out followed by our solutions. Finally, the experiences learned and the future work are presented.

Keywords: agile methods, mobile apps, software process model, waterfall model

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Authors: Getaneh Berie Tarekegn

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A precise localization system is crucial for many artificial intelligence Internet of Things (AI-IoT) applications in the era of smart cities. Their applications include traffic monitoring, emergency alarming, environmental monitoring, location-based advertising, intelligent transportation, and smart health care. The most common method for providing continuous positioning services in outdoor environments is by using a global navigation satellite system (GNSS). Due to nonline-of-sight, multipath, and weather conditions, GNSS systems do not perform well in dense urban, urban, and suburban areas.This paper proposes a generative AI-based positioning scheme for large-scale wireless settings using fingerprinting techniques. In this article, we presented a semi-supervised deep convolutional generative adversarial network (S-DCGAN)-based radio map construction method for real-time device localization. It also employed a reliable signal fingerprint feature extraction method with t-distributed stochastic neighbor embedding (t-SNE), which extracts dominant features while eliminating noise from hybrid WLAN and long-term evolution (LTE) fingerprints. The proposed scheme reduced the workload of site surveying required to build the fingerprint database by up to 78.5% and significantly improved positioning accuracy. The results show that the average positioning error of GAILoc is less than 0.39 m, and more than 90% of the errors are less than 0.82 m. According to numerical results, SRCLoc improves positioning performance and reduces radio map construction costs significantly compared to traditional methods.

Keywords: location-aware services, feature extraction technique, generative adversarial network, long short-term memory, support vector machine

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Authors: Sarieh Poortaghi, Zakiyeh Jafaryparvar, Marzieh Hasanpour, Reza Negarandeh

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Aim: This article aims to discuss how violence against health care workers especially nurses affects health care systems and the quality of care of the patients. In this paper causes of violence and strategies to reduce it have been discussed. Methods: Discourse of the literature considering the violence against nurses during the COVID-19 pandemic and its reasons and outcomes. Results: The COVID-19 pandemic has led to a significant increase in violence against healthcare providers. The attacker against nurses may be among patients, companions, visitors, colleagues such as doctors and other nurses, supervisors, and managers. Many individuals who experience violence in healthcare environments refrain from reporting it. The causes of violence against nurses include spending long periods with patients, perceiving nursing as a low-status profession, gender of nurses, direct and frequent contact with patients and their companions, inadequate facilities and high workload, weak healthcare delivery systems in public hospitals and inequality in health, nature of the department and shift type of personnel, work shifts and staff shortages, forcing nurses to work in non-standard conditions during the COVID-19 pandemic, prohibition of patient visits during the pandemic, patient death and nurses' sense of incompetence, and expressing stress through aggression. Workplace violence leads to a decrease in job satisfaction and an increase in continuous psychological stress, which has a negative impact on the personal and professional lives of nurses. Potential strategies for reducing workplace violence include protecting healthcare workers through laws, improving communication with patients and their families, critically analyzing information in social media, facilitating patient access through remote medical strategies, and improving access to primary healthcare services.

Keywords: nurses, health care workers, Covid-19, nursing

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Authors: Helen Pluut, Remus Ilies, Nikos Dimotakis, Maral Darouei

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This study aims to examine recovery from work as an important daily activity with implications for workplace behavior. Building on affective events theory and the stressor-detachment model as frameworks, this paper proposes and tests a comprehensive within-individual model that uncovers the role of recovery processes at home in linking workplace demands (e.g., workload) and stressors (e.g., workplace incivility) to next-day organizational citizenship behaviors (OCBs). Our sample consisted of 126 full-time employees in a large Midwestern University. For a period of 16 working days, these employees were asked to fill out 3 electronic surveys while at work. The first survey (sent out in the morning) measured self-reported sleep quality, recovery experiences the previous day at home, and momentary effect. The second survey (sent out close to the end of the workday) measured job demands and stressors as well as OCBs, while the third survey in the evening assessed job strain. Data were analyzed using Hierarchical Linear Modeling (HLM). Results indicated that job demands and stressors at work made it difficult to unwind properly at home and have a good night’s sleep, which had repercussions for next day’s morning effect, which, in turn, influenced OCBs. It can be concluded that processes of recovery are vital to an individual’s daily effective functioning and behavior at work, but recovery may become impaired after a hard day’s work. Thus, our study sheds light on the potentially persistent nature of strain experienced as a result of work and points to the importance of recovery processes to enable individuals to avoid such cross-day spillover. Our paper will discuss this implication for theory and practice as well as potential directions for future research.

Keywords: affect, job demands, organizational citizenship behavior, recovery, strain

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Authors: Brian Romansky

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There are many practical, commercially available robots and semi-autonomous systems that are currently available for use in a wide variety of construction tasks. Adoption of these technologies has the potential to reduce the time and cost to deliver a project, reduce variability and risk in delivery time, increase quality, and improve safety on the job site. These benefits come with a cost for equipment rental or contract fees, access to specialists to configure the system, and time needed for set-up and support of the machines while in use. Calculation of the net ROI (Return on Investment) requires detailed information about the geometry of the site, the volume of work to be done, the overall project schedule, as well as data on the capabilities and past performance of available robotic systems. Assembling the required data and comparing the ROI for several options is complex and tedious. Many project managers will only consider the use of a robot in targeted applications where the benefits are obvious, resulting in low levels of adoption of automation in the construction industry. This work demonstrates how data already resident in many BIM (Building Information Model) projects can be used to automate ROI estimation for a sample set of commercially available construction robots. Calculations account for set-up and operating time along with scheduling support tasks required while the automated technology is in use. Configuration parameters allow for prioritization of time, cost, or safety as the primary benefit of the technology. A path toward integration and use of automatic ROI calculation with a database of available robots in a BIM platform is described.

Keywords: automation, BIM, robot, ROI.

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Authors: Silvina Caíno-Lores, Jesús Carretero

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Large scale computing infrastructures have been widely developed with the core objective of providing a suitable platform for high-performance and high-throughput computing. These systems are designed to support resource-intensive and complex applications, which can be found in many scientific and industrial areas. Currently, large scale data-intensive applications are hindered by the high latencies that result from the access to vastly distributed data. Recent works have suggested that improving data locality is key to move towards exascale infrastructures efficiently, as solutions to this problem aim to reduce the bandwidth consumed in data transfers, and the overheads that arise from them. There are several techniques that attempt to move computations closer to the data. In this survey we analyse the different mechanisms that have been proposed to provide data locality for large scale high-performance and high-throughput systems. This survey intends to assist scientific computing community in understanding the various technical aspects and strategies that have been reported in recent literature regarding data locality. As a result, we present an overview of locality-oriented techniques, which are grouped in four main categories: application development, task scheduling, in-memory computing and storage platforms. Finally, the authors include a discussion on future research lines and synergies among the former techniques.

Keywords: data locality, data-centric computing, large scale infrastructures, cloud computing

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Authors: Graham Hancox, Saydia Razak, Sue Hignett, Jo Barnes, Jyri Silmari, Florian Kading

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In the event of a Chemical, Biological, Radiological and Nuclear (CBRN) incident rapidly gaining, situational awareness is of paramount importance and advanced technologies have an important role to play in improving detection, identification, monitoring (DIM) and patient tracking. Understanding how these advanced technologies can fit into current response systems is essential to ensure they are optimally designed, usable and meet end-users’ needs. For this reason, Human Factors (Ergonomics) methods have been used within an EU Horizon 2020 project (TOXI-Triage) to firstly describe (map) the hierarchical structure in a CBRN response with adapted Accident Map (AcciMap) methodology. Secondly, Hierarchical Task Analysis (HTA) has been used to describe and review the sequence of steps (sub-tasks) in a CBRN scenario response as a task system. HTA methodology was then used to map one advanced technology, ‘Tag and Trace’, which tags an element (people, sample and equipment) with a Near Field Communication (NFC) chip in the Hot Zone to allow tracing of (monitoring), for example casualty progress through the response. This HTA mapping of the Tag and Trace system showed how the provider envisaged the technology being used, allowing for review and fit with the current CBRN response systems. These methodologies have been found to be very effective in promoting and supporting a dialogue between end-users and technology providers. The Human Factors methods have given clear diagrammatic (visual) representations of how providers see their technology being used and how end users would actually use it in the field; allowing for a more user centered approach to the design process. For CBRN events usability is critical as sub-optimum design of technology could add to a responders’ workload in what is already a chaotic, ambiguous and safety critical environment.

Keywords: AcciMap, CBRN, ergonomics, hierarchical task analysis, human factors

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Authors: Peifang Hsieh

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The prevention of child abuse has aroused serious concerns in Taiwan because of the disparity between the increasing amount of reported child abuse cases that doubled over the past decade and the scarcity of social workers. New Taipei city, with the most population in Taiwan and over 70% of its 4 million citizens are migrant families in which the needs of children can be easily neglected due to insufficient support from relatives and communities, sees urgency for a social support system, by preemptively identifying and outreaching high-risk families of child abuse, so as to offer timely assistance and preventive measure to safeguard the welfare of the children. Big data analysis is the inspiration. As it was clear that high-risk families of child abuse have certain characteristics in common, New Taipei city decides to consolidate detailed background information data from departments of social affairs, education, labor, and health (for example considering status of parents’ employment, health, and if they are imprisoned, fugitives or under substance abuse), to cross-reference for accurate and prompt identification of the high-risk families in need. 'The Service Center for High-Risk Families' (SCHF) was established to integrate data cross-departmentally. By utilizing the machine learning 'random forest method' to build a risk prediction model which can early detect families that may very likely to have child abuse occurrence, the SCHF marks high-risk families red, yellow, or green to indicate the urgency for intervention, so as to those families concerned can be provided timely services. The accuracy and recall rates of the above model were 80% and 65%. This prediction model can not only improve the child abuse prevention process by helping social workers differentiate the risk level of newly reported cases, which may further reduce their major workload significantly but also can be referenced for future policy-making.

Keywords: child abuse, high-risk families, big data analysis, risk prediction model

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Authors: Taki Eddine Seghier, Mohd Hamdan Ahmad, Yaik-Wah Lim, Samuel Opeyemi Williams

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The assessment of building sustainability to achieve a specific green benchmark and the preparation of the required documents in order to receive a green building certification, both are considered as major challenging tasks for green building design team. However, this labor and time-consuming process can take advantage of the available Building Information Modeling (BIM) features such as material take-off and scheduling. Furthermore, the workflow can be automated in order to track potentially achievable credit points and provide rating feedback for several design options by using integrated Visual Programing (VP) to handle the stored parameters within the BIM model. Hence, this study proposes a BIM-based tool that uses Green Building Index (GBI) rating system requirements as a unique input case to evaluate the building sustainability in the design stage of the building project life cycle. The tool covers two key models for data extraction, firstly, a model for data extraction, calculation and the classification of achievable credit points in a green template, secondly, a model for the generation of the required documents for green building certification. The tool was validated on a BIM model of residential building and it serves as proof of concept that building sustainability assessment of GBI certification can be automatically evaluated and documented through BIM.

Keywords: green building rating system, GBRS, building information modeling, BIM, visual programming, VP, sustainability assessment

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Authors: Laura Hervai

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One of the most significant phenomena of the 2000s was the emergence of social media sites and web 2.0 that revolutionized communication processes. Social networking platforms have fundamentally changed social and political participation of the public, which require organisations in the public and non-profit sector not only to adapt to these new trends but also to actively engage their audiences. Opportunity for interaction, freer expression of opinion and the proliferation of user generated content are major changes brought by web 2.0 technologies. Furthermore, due to the wide penetration of mobile technologies, social media sites are capable of connecting underdeveloped regions to the global flow of information. Taking advantage of these characteristics, organisations have the opportunity to engage much wider audiences, exploit new ways to raise awareness or reach out to regions that are difficult to access. The early adopters of these new communication tools soon recognized the need of developing social media guidelines for their organisations as well as the increased workload that they require. While ten years ago communication officers could handle their organisation’s social media presence, today it is a separate profession. International organisations face several challenges related to their social media presence. Early adopters have contributed to the development of best practices among which the ethics of social media usage still remained problematic. Another challenge for international organisations is to adapt to country-specific social media trends while they have to comply with the requirements of their parent organisation as well. However in the 21st century social media presence can be crucial to the successful operation of international organisations, their importance is still not taken seriously enough. The measurement of the effects and influence of social networking on the organisations’ productivity is an unsolved problem thus further research should focus on this matter. Research methods included primary research of major IGOs’ and NGOs’ social media presence and guidelines along with secondary research of social media statistics and scientific articles in the topic.

Keywords: international organisations, non-profit sector, NGO, social media, social network

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Authors: Meera Shanker

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Excellent education and financial need have encouraged Indian women to go out and work in well-paid and high-status occupations. In the era of cutthroat competition, women are expected to work hard to produce the desired result; hence, workload and expectations haveincreased. At home, they are anticipated to take care of family members, children, and household work. Women are stretching themselves mechanically to remain in the job competition and try to give their best at home. Consequentially, they are under tremendous pressure, stressed, and having issues related to physical-mental wellness. Mental healthcare is often ignored and not accepted due to a lack of awareness and cultural barriers. These further compounds the problem, resulting in decreased productivity in economic terms and an increase in stress-related physical-mental ailments. The main objective of the study was to find out the impact of stress on the physical-mental wellbeing of working women in India, along with their awareness and acceptability related to mental health. Six hundred and one woman working at various levels took part in this study, responding to the items related to stress and physical-mental illness. Finally, 21 items were retained under four meaningful factors measuring stress dimensions along with 17 items with three factors measuring physical-mental wellbeing. Confirmatory Factor Analysis (CFA), path analysis, in Structural Equation Modeling (SEM), was used to get a relationship, validity of the instruments. The psychometric properties of items and Cronbach’s Alpha reliabilities calculated for the subscales were relatively acceptable. The subscale correlations, regression, and path analysis of stress dimensions with physical-mental illness were found to be positive, indicating the growing stress among working women in India, which is impacting their physical-mental health. Single item analysis revealed that 77 percent of women have never visited psychologists. However, 70 percent of working women were not ready to seek the help of a psychologist.

Keywords: working women, stress, physical-mental well-being, confirmatory factor analysis

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Authors: Yuet Wah Echo Yeung

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Practice learning is an important component of social work education. Practice educators are charged with the responsibility to support and enable learning while students are on placement. They also play a key role in teaching students to integrate theory and practice, as well as assessing their performance. Current literature highlights the structural factors that make it difficult for practice educators to create a positive learning environment for students. Practice educators find it difficult to give sufficient attention to their students because of the lack of workload relief, the increasing emphasis on managerialism and bureaucratisation, and a range of competing organisational and professional demands. This paper reports the challenges practice educators face and how they manage these challenges in this context. Semi-structured face-to-face interviews were conducted with thirteen practice educators who support students in statutory and voluntary social care settings in the Northwest of England. Interviews were conducted between April and July 2017 and each interview lasted about 40 minutes. All interviews were recorded and transcribed. All practice educators are experienced social work practitioners with practice experience ranging from 6 to 42 years. On average they have acted as practice educators for 13 years and all together have supported 386 students. Our findings reveal that apart from the structural factors that impact how practice educators perform their roles, they also faced other challenges when supporting students on placement. They include difficulty in engaging resistant students, complexity in managing power dynamics in the context of practice learning, and managing the dilemmas of fostering a positive relationship with students whilst giving critical feedback. Suggestions to enhance the practice educators’ role include support from organisations and social work teams; effective communication with university tutors, and a forum for practice educators to share good practice and discuss placement issues.

Keywords: social work education, placement challenges, practice educator, practice learning

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Authors: Pratibha Srivastava, Chithra V. J., Sudhakar S., Nitin K. D.

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A closed-loop system comprises of a controller, a response system, and an actuating system. The controller, which is the system under test for us, excites the actuators based on feedback from the sensors in a periodic manner. The sensors should provide the feedback to the System Under Test (SUT) within a deterministic time post excitation of the actuators. Any delay or miss in the generation of response or acquisition of excitation pulses may lead to control loop controller computation errors, which can be catastrophic in certain cases. Such systems categorised as hard real-time systems that need special strategies. The real-time operating systems available in the market may be the best solutions for such kind of simulations, but they pose limitations like the availability of the X Windows system, graphical interfaces, other user tools. In this paper, we present strategies that can be used on a general purpose operating system (Bare Linux Kernel) to achieve a deterministic deadline and hence have the added advantages of a GPOS with real-time features. Techniques shall be discussed how to make the time-critical application run with the highest priority in an uninterrupted manner, reduced network latency for distributed architecture, real-time data acquisition, data storage, and retrieval, user interactions, etc.

Keywords: real time data acquisition, real time kernel preemption, scheduling, network latency

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Authors: Getaneh Berie Tarekegn

Abstract:

A precise localization system is crucial for many artificial intelligence Internet of Things (AI-IoT) applications in the era of smart cities. Their applications include traffic monitoring, emergency alarming, environmental monitoring, location-based advertising, intelligent transportation, and smart health care. The most common method for providing continuous positioning services in outdoor environments is by using a global navigation satellite system (GNSS). Due to nonline-of-sight, multipath, and weather conditions, GNSS systems do not perform well in dense urban, urban, and suburban areas.This paper proposes a generative AI-based positioning scheme for large-scale wireless settings using fingerprinting techniques. In this article, we presented a novel semi-supervised deep convolutional generative adversarial network (S-DCGAN)-based radio map construction method for real-time device localization. We also employed a reliable signal fingerprint feature extraction method with t-distributed stochastic neighbor embedding (t-SNE), which extracts dominant features while eliminating noise from hybrid WLAN and long-term evolution (LTE) fingerprints. The proposed scheme reduced the workload of site surveying required to build the fingerprint database by up to 78.5% and significantly improved positioning accuracy. The results show that the average positioning error of GAILoc is less than 39 cm, and more than 90% of the errors are less than 82 cm. That is, numerical results proved that, in comparison to traditional methods, the proposed SRCLoc method can significantly improve positioning performance and reduce radio map construction costs.

Keywords: location-aware services, feature extraction technique, generative adversarial network, long short-term memory, support vector machine

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Authors: Zekang Lan, Yan Xu, Yingkun Huang, Dian Huang, Shengzhong Feng

Abstract:

Jobs on high-performance computing (HPC) clusters can suffer significant performance degradation due to inter-job network interference. Topology-aware job allocation problem (TJAP) is such a problem that decides how to dedicate nodes to specific applications to mitigate inter-job network interference. In this paper, we study the window-based TJAP on a fat-tree network aiming at minimizing the cost of communication hop, a defined inter-job interference metric. The window-based approach for scheduling repeats periodically, taking the jobs in the queue and solving an assignment problem that maps jobs to the available nodes. Two special allocation strategies are considered, i.e., static continuity assignment strategy (SCAS) and dynamic continuity assignment strategy (DCAS). For the SCAS, a 0-1 integer programming is developed. For the DCAS, an approach called neural simulated algorithm (NSA), which is an extension to simulated algorithm (SA) that learns a repair operator and employs them in a guided heuristic search, is proposed. The efficacy of NSA is demonstrated with a computational study against SA and SCIP. The results of numerical experiments indicate that both the model and algorithm proposed in this paper are effective.

Keywords: high-performance computing, job allocation, neural simulated annealing, topology-aware

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Authors: Solomon Ojo

Abstract:

The study set out to investigate the role of perceived leadership style on achievement motivation of selected bank employees. The study was a cross-sectional survey. A total of 585 bank workers took part in the study; 283 (48.4%) were males while 302% (51.6%) were females. Mean age of 31.8 yrs (SD = 7.8 yrs) was reported for the participants for the study. Questionnaires were used for data collection. Data was analyzed using both descriptive and inferential statistic. The t- test for independent measures was used to test all the hypotheses, using the statistical package for social sciences version 21.0. The results in the study revealed that bank employees who perceived their leaders as high on consideration style of leadership reported more job satisfaction than bank employees who perceived their leaders as low on consideration style of leadership [t(583) = 16.43, p<.001]; bank employees who perceived their leaders as high in initiating structure style reported more job satisfaction than bank employees who perceived their leaders as low in initiating structure style [t(583)=12.06, p<.01]. The results showed further the influence of perceived leadership styles on all measures of job satisfaction. First, the result showed that bank employees who perceived their leaders as high on consideration style reported more satisfaction with hours worked each day than bank employees who perceived their leaders as low on consideration style [t(583) = 9.23, p<.01]. Second, the results revealed that bank employees who perceived their leaders as high on consideration style reported more satisfaction with flexibility in scheduling than bank employees who perceived their leaders as low on consideration style [t(583) = 8.80, p<.01]. Third, it was shown that bank employees who perceived their leaders as high on consideration style reported more satisfaction with location of work than bank employees who perceived their leaders as low on consideration style [t(583) = 14.17, p<.01] e.t.c. The results were extensively discussed in relation to relevant body of literature.

Keywords: leadership styles, job satisfaction, bank employees, perceived

Procedia PDF Downloads 219

Authors: Mona Almanasef, Angel Chater, Jane Portlock

Abstract:

Introduction: A 'flipped classroom' uses technology to shift the traditional lecture outside the scheduled class time and uses the face-to-face time to engage students in interactive activities. Aim of the Study: Assess the feasibility, acceptability, and effectiveness of using the 'flipped classroom' teaching format with MPharm students in two pharmacy schools in the UK: UCL School of Pharmacy and the School of Pharmacy and Biomedical Sciences at University of Portsmouth. Methods: An experimental mixed methods design was employed, with final year MPharm students in two phases; 1) a qualitative study using focus groups, 2) a quasi-experiment measuring knowledge acquisition and satisfaction by delivering a session on rheumatoid arthritis, in two teaching formats: the flipped classroom and the traditional lecture. Results: The flipped classroom approach was preferred over the traditional lecture for delivering a pharmacy practice topic, and it was comparable or better than the traditional lecture with respect to knowledge acquisition. In addition, this teaching approach was found to overcome the perceived challenges of the traditional lecture method such as fast pace instructions, student disengagement and boredom due to lack of activities and/or social anxiety. However, high workload and difficult or new concepts could be barriers to pre-class preparation, and therefore successful flipped classroom. The flipped classroom encouraged learning scaffolding where students could benefit from application of knowledge, and interaction with peers and the lecturer, which might, in turn, facilitate learning consolidation and deep understanding. This research indicated that the flipped classroom was beneficial for all learning styles. Conclusion: Implementing the flipped classroom at both pharmacy institutions was successful and well received by final year MPharm students. Given the attention now being put on the Teaching Excellence Framework (TEF), understanding effective methods of teaching to enhance student achievement and satisfaction is now more valuable than ever.

Keywords: blended learning, flipped classroom, inverted classroom, pharmacy education

Procedia PDF Downloads 136

Authors: Getaneh Berie Tarekegn

Abstract:

A precise localization system is crucial for many artificial intelligence Internet of Things (AI-IoT) applications in the era of smart cities. Their applications include traffic monitoring, emergency alarming, environmental monitoring, location-based advertising, intelligent transportation, and smart health care. The most common method for providing continuous positioning services in outdoor environments is by using a global navigation satellite system (GNSS). Due to nonline-of-sight, multipath, and weather conditions, GNSS systems do not perform well in dense urban, urban, and suburban areas.This paper proposes a generative AI-based positioning scheme for large-scale wireless settings using fingerprinting techniques. In this article, we presented a novel semi-supervised deep convolutional generative adversarial network (S-DCGAN)-based radio map construction method for real-time device localization. We also employed a reliable signal fingerprint feature extraction method with t-distributed stochastic neighbor embedding (t-SNE), which extracts dominant features while eliminating noise from hybrid WLAN and long-term evolution (LTE) fingerprints. The proposed scheme reduced the workload of site surveying required to build the fingerprint database by up to 78.5% and significantly improved positioning accuracy. The results show that the average positioning error of GAILoc is less than 39 cm, and more than 90% of the errors are less than 82 cm. That is, numerical results proved that, in comparison to traditional methods, the proposed SRCLoc method can significantly improve positioning performance and reduce radio map construction costs.

Keywords: location-aware services, feature extraction technique, generative adversarial network, long short-term memory, support vector machine

Procedia PDF Downloads 74

Authors: Dana Mohammed, Fatemah Abdullah, Hawraa Ali, Najat Al-Shaer, Rawan Al-Awadhi, , Magdy Helal

Abstract:

We study the patient service performance at the emergency department of a major Kuwaiti public hospital, using discrete simulation and lean concepts. In addition to the common problems in such health care systems (over crowdedness, facilities planning and usage, scheduling and staffing, capacity planning) the emergency department suffered from several cultural and patient behavioural issues. Those contributed significantly to the system problems and constituted major obstacles in maintaining the performance in control. This led to overly long waiting times and the potential of delaying providing help to critical cases. We utilized the visual management tools to mitigate the impact of the patients’ behaviours and attitudes and improve the logistics inside the system. In addition a proposal is made to automate the date collection and communication within the department using RFID-based barcoding system. Discrete event simulation models were developed as decision support systems; to study the operational problems and assess achieved improvements. The simulation analysis resulted in cutting the patient delays to about 35% of their current values by reallocating and rescheduling the medical staff. Combined with the application of the visual management concepts, this provided the basis to improving patient service without any major investments.

Keywords: simulation, visual management, health care system, patient

Procedia PDF Downloads 475

Authors: Davaakhuu Vandannyam, Amarsaikhan Dashtseren, Oyungoo Badamdorj

Abstract:

Background: Shift work and extended working hours are increasing in many industries and organization's in the world. Over a 24 hour period, the circadian clock regulates sleep/wake patterns, body temperature, hormone levels, digestion and many other functions. Depending on the time of day or night, the human body is programmed for periods of wakefulness and sleep, high and low body temperature, high and low digestive activity and so on. Shift work is highly prevalent in industrialized societies (>20%) but, when it includes night work, it has pronounced negative effects on sleep, subjective and physiological sleepiness, performance, accident risk, as well as on health outcomes such as cardiovascular disease and certain forms of cancer. Method: In this cross-sectional field study, 634 shift work and day work nurses from a plant were involved, with participation rate of 100% (634 nurses). The general health questionnaire (GHQ-28) and RLS, ESS, ISI, FSS were used to evaluate the level of insomnia, sleepiness, fatigue and restless legs syndrome, respectively. Results: As a result of research on some indicators of health risks caused from work shift, it was proven that prevalence of restless legs syndrome was at 5.5% and 25.9% are in risk of becoming sick, 42.3% are in fatigue, 3.5% in high stage of insomnia and 27.4% are sleepy on duty. Insomnia of nurses mainly affected from long-hour shift, dissatisfaction, workload, lose of focus and use of coffee. There is sleepiness lies in the workplace due to number of shifts, unsatisfactory performance and emergency calls between shifts. It has been determined that risk of sickness influenced by number of shifts in a month and long hour shift, dissatisfaction and use of coffee and divisions are causing restless legs syndrome. Conclusions: Among the nurses, it was found that the prevalence of insomnia is 31.6%, sleepiness 27.4%, fatigue 42.3%, restless legs syndrome 35% and stress 25.9%. These factors of shift work affecting health tend to go up as working hours increase and more common among shift work nurses.

Keywords: shiftwork, insomnia, sleepiness, restless

Procedia PDF Downloads 252