Search results for: management models

Authors: Yee Hooi Min, Mohdnasir Abdul Hadi

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Tensioned membrane structure in the form of Enneper minimal surface can be considered as a sustainable development for the green environment and technology, it also can be used to support the effectiveness used of energy and the structure. Soap film in the form of Enneper minimal surface model has been studied. The combination of shape and internal forces for the purpose of stiffness and strength is an important feature of membrane surface. For this purpose, form-finding using soap film model has been carried out for Enneper minimal surface models with variables u=v=0.6 and u=v=1.0. Enneper soap film models with variables u=v=0.6 and u=v=1.0 provides an alternative choice for structural engineers to consider the tensioned membrane structure in the form of Enneper minimal surface applied in the building industry. It is expected to become an alternative building material to be considered by the designer.

Keywords: Enneper, minimal surface, soap film, tensioned membrane structure

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Authors: Dimitrios Dimitriou, Maria Sartzetaki

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In the early days of the of civil aviation, airports are totally state-owned companies under the control of national authorities or regional governmental bodies. From that time the picture has totally changed and airports privatisation and airport business commercialisation are key success factors to stimulate air transport demand, generate revenues and attract investors, linked to reliable and resilience of air transport system. Nowadays, airport's corporate strategy deals with policies and actions, affecting essential the business plans, the financial targets and the economic footprint in a regional economy they serving. Therefore, exploring airport corporate strategy is essential to support the decision in business planning, management efficiency, sustainable development and investment attractiveness on one hand; and define policies towards traffic development, revenues generation, capacity expansion, cost efficiency and corporate social responsibility. This paper explores key outputs in airport corporate strategy for different ownership schemes. The airport corporations are grouped in three major schemes: (a) Public, in which the public airport operator acts as part of the government administration or as a corporised public operator; (b) Mixed scheme, in which the majority of the shares and the corporate strategy is driven by the private or the public sector; and (c) Private, in which the airport strategy is driven by the key aspects of globalisation and liberalisation of the aviation sector. By a systemic approach, the key drivers in corporate strategy for modern airport business structures are defined. Key objectives are to define the key strategic opportunities and challenges and assess the corporate goals and risks towards sustainable business development for each scheme. The analysis based on an extensive cross-sectional dataset for a sample of busy European airports providing results on corporate strategy key priorities, risks and business models. The conventional wisdom is to highlight key messages to authorities, institutes and professionals on airport corporate strategy trends and directions.

Keywords: airport corporate strategy, airport ownership, airports business models, corporate risks

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Authors: Oman Sukmana

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Geographically, Indonesia appears to be disaster-prone areas, whether for natural, nonnatural (man-made), or social disasters. This study aimed to construct the knowledge and social wisdom on the local community in the process of disaster management after the eruption of Mt. Kelud. This study, moreover, encompassed two major concerns: (1) the construction of knowledge and social wisdom on the local community in the process of disaster management after the eruption of Mt. Kelud; (2) the conceptual framework of disaster management on the basis of knowledge and social wisdom on the local community. The study was conducted by means of qualitative approach. The data were analyzed by using the qualitative-descriptive technique. The data collection techniques used in this study were in-depth interview, focus group discussion, observation, and documentation. It was conducted at Pandansari Village, Sub-district Ngantang, District Malang as the most at risk area of Mt. Kelud’s eruption. The purposive sampling was applied ad hoc to select the respondents including: the apparatus of Pandansari Village, the local figures of Pandansari Village, the Chief and Boards of the Forum of Disaster Risk Reduction (FPRB), the Head of Malang Regional Disaster Management Agency, and other agencies. The findings of this study showed that the local community has already possessed the adequate knowledge and social wisdom to overcome the disaster. Through the social wisdom, the local community could predict the potential eruption.

Keywords: knowledge, social and local wisdom, disaster management

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Authors: Donghwan Lee, Gichun Cha, Jooyoung Park, Junkyeong Kim, Seunghee Park

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3D shape models of the existing structure are required for many purposes such as safety and operation management. The traditional 3D modeling methods are based on manual or semi-automatic reconstruction from close-range images. It occasions great expense and time consuming. The Terrestrial Laser Scanner (TLS) is a common survey technique to measure quickly and accurately a 3D shape model. This TLS is used to a construction site and cultural heritage management. However there are many limits to process a TLS point cloud, because the raw point cloud is massive volume data. So the capability of carrying out useful analyses is also limited with unstructured 3-D point. Thus, segmentation becomes an essential step whenever grouping of points with common attributes is required. In this paper, members segmentation algorithm was presented to separate a raw point cloud which includes only 3D coordinates. This paper presents a clustering approach based on a fuzzy method for this objective. The Fuzzy C-Means (FCM) is reviewed and used in combination with a similarity-driven cluster merging method. It is applied to the point cloud acquired with Lecia Scan Station C10/C5 at the test bed. The test-bed was a bridge which connects between 1st and 2nd engineering building in Sungkyunkwan University in Korea. It is about 32m long and 2m wide. This bridge was used as pedestrian between two buildings. The 3D point cloud of the test-bed was constructed by a measurement of the TLS. This data was divided by segmentation algorithm for each member. Experimental analyses of the results from the proposed unsupervised segmentation process are shown to be promising. It can be processed to manage configuration each member, because of the segmentation process of point cloud.

Keywords: fuzzy c-means (FCM), point cloud, segmentation, terrestrial laser scanner (TLS)

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Authors: Tatsanawalai Utarasakul, Ch. Hirannukhrao

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The purpose of this research was to investigate the appropriate guidelines for promoting manuscript publication of the academic staff in Faculty of Science and Technology, Suan Sunandha Rajabhat University (SciSSRU). Data were collected from 88 academic staff of SciSSRU. The qualitative approach and knowledge management were used to determine the guidelines for promoting manuscript publication. In addition, TUNA Model was applied in order to follow the process of knowledge management. Simplified techniques were presented and shared with academic staff in the Knowledge Management exhibition, brochure, and websites. The result of this study revealed that, the comparison of number of manuscript publication of academic staff between academic year 2012 and 2013 is rapidly increasing for 60 percentages.

Keywords: knowledge management, articles, publication, academic staff

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Authors: Shanshan Zhu, Mohammad Nasim

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Financial fraud continues to be a major threat to financial institutions across the world, causing colossal money losses and undermining public trust. Fraud prevention techniques, based on hard rules, have become ineffective due to evolving patterns of fraud in recent times. Against such a background, the present study probes into distinct methodologies that exploit emergent AI-driven techniques to further strengthen fraud detection. We would like to compare the performance of generative adversarial networks and graph neural networks with other popular techniques, like gradient boosting, random forests, and neural networks. To this end, we would recommend integrating all these state-of-the-art models into one robust, flexible, and smart system for real-time anomaly and fraud detection. To overcome the challenge, we designed synthetic data and then conducted pattern recognition and unsupervised and supervised learning analyses on the transaction data to identify which activities were fishy. With the use of actual financial statistics, we compare the performance of our model in accuracy, speed, and adaptability versus conventional models. The results of this study illustrate a strong signal and need to integrate state-of-the-art, AI-driven fraud detection solutions into frameworks that are highly relevant to the financial domain. It alerts one to the great urgency that banks and related financial institutions must rapidly implement these most advanced technologies to continue to have a high level of security.

Keywords: AI-driven fraud detection, financial security, machine learning, anomaly detection, real-time fraud detection

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Authors: Ravi Kumar

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Agricultural wastes are the non-product outcomes of agricultural processing whose monetary value is less as compared to its collection cost, transportation, and processing. When such agricultural waste is not properly disposed of, it may damage the natural environment and cause detrimental pollution in the atmosphere. Agricultural development and intensive farming methods usually result in wastes that remarkably affect the rural environments in particular and the global environment in general. Agricultural waste has toxicity latent to human beings, animals, and plants through various indirect and direct outlets. The present paper explores the various activities that result in agricultural waste and the routes that can utilize the agricultural waste in a manageable manner to reduce its adverse impact on the environment. Presently, the agricultural waste management system for ecological agriculture and sustainable development has emerged as a crucial issue for policymakers. There is an urgent need to consider agricultural wastes as prospective resources rather than undesirable in order to avoid the transmission and contamination of water, land, and air resources. Waste management includes the disposal and treatment of waste with a view to eliminate threats of waste by modifying the waste to condense the microbial load. The study concludes that proper waste utilization and management will facilitate the purification and development of the ecosystem and provide feasible biofuel resources. This proper utilization and management of these wastes for agricultural production may reduce their accumulation and further reduce environmental pollution by improving environmental health.

Keywords: agricultural waste, utilization, management, environment, health

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Authors: Mária Hudáková, Mária Lusková

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This report is focused on widening the theoretical knowledge as well as controlling practical application from the risk management point of view, regarding to dynamic business changes that have occurred in Slovakia which recently has been considered to be an environment full of risk and uncertainty. The idea of the report is the proposal of the controlling operation model in the course of risk management process in an enterprise operating in Slovakia, by which the controller is able to identify early risk factors in suggested major areas of the business management upon appropriate business information integration, consecutive control and prognoses and to prepare in time full-value documents in order to suggest measures for reduction thereof. Dealing with risk factors, that can quickly limit the growth potential of the enterprise, is an essential part of managerial activities on each level. This is the reason why mutual unofficial, ergo collegial cooperation of individual departments is necessary for controlling application from the business risk management point of view. An important part of the report is elaborated survey of the most important risk factors existing in major management areas of enterprises operating in Slovakia. The outcome of the performed survey is a catalogue of the most important enterprise risk factors. The catalogue serves for better understanding risk factors affecting the Slovak enterprises, their importance and evaluation.

Keywords: controlling, information, risks, risk factor, crisis

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Authors: Muhammad Tahir Hassan, Stas Burek, Muhammad Asif, Mohamed Emad

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Industrial sector in Pakistan accounts for 25% of total energy consumption in the country. The performance of this sector has been severely affected due to the adverse effect of current energy crises in the country. Energy conservation potentials of Pakistan’s industrial sectors through energy management can save wasted energy which would ultimately leads to economic and environmental benefits. However due to lack of financial incentives of energy efficiency and absence of energy benchmarking within same industrial sectors are some of the main challenges in the implementation of energy management. In Pakistan, this area has not been adequately explored, and there is a lack of focus on the need for industrial energy efficiency and proper management. The main objective of this research is to evaluate the current energy management performance of Pakistani industrial sector and empirical investigation of the existence of various barriers to industrial energy efficiency. Data was collected from the respondents of 192 small and medium-sized enterprises (SME’s) of Pakistan i.e. foundries, textile, plastic industries, light engineering, auto and spare parts and ceramic manufacturers and analysed using Statistical Package for the Social Sciences (SPSS) software. Current energy management performance of manufacturing SME’s in Pakistan has been evaluated by employing two significant indicators, ‘Energy Management Matrix’ and ‘pay-off criteria’, with modified approach. Using the energy management matrix, energy management profiles of overall industry and the individual sectors have been drawn to assess the energy management performance and identify the weak and strong areas as well. Results reveal that, energy management practices in overall surveyed industries are at very low level. Energy management profiles drawn against each sector suggest that performance of textile sector is better among all the surveyed manufacturing SME’s. The empirical barriers to industrial energy efficiency have also been ranked according to the overall responses. The results further reveal that there is a significant relationship exists among the industrial size, sector type and nature of barriers to industrial energy efficiency for the manufacturing SME’s in Pakistan. The findings of this study may help the industries and policy makers in Pakistan to formulate a sustainable energy policy to support industrial energy efficiency keeping in view the actual existing energy efficiency scenario in the industrial sector.

Keywords: barriers, energy conservation, energy management profile, environment, manufacturing SME's of Pakistan

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Authors: Oumaima Ben Abderrahim, Mohamed Houcine Elhedhili, Leila Saidane

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In this paper, we propose a trust management system based on clustering architecture for the social internet of things called TMBCO-SIOT. The proposed model integrates numerous factors such as direct and indirect trust; transaction factor; precaution factor; and social modeling of trust. The novelty of our approach can be summed up in two aspects. The first aspect concerns the architecture based on the community of interest (CoT) where each community is headed by an administrator (admin). However, the second aspect is the trust management system that tries to prevent On-Off attacks and mitigates dishonest recommendations using the k-means algorithm and guarantor things. The effectiveness of the proposed system is proved by simulation against malicious nodes.

Keywords: IoT, trust management system, attacks, trust, dishonest recommendations, K-means algorithm

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Authors: Amin Salighehdar, Ziwen Ye, Mingzhe Liu, Ionut Florescu, Alan F. Blumberg

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Storm surge is an abnormal water level caused by a storm. Accurate prediction of a storm surge is a challenging problem. Researchers developed various ensemble modeling techniques to combine several individual forecasts to produce an overall presumably better forecast. There exist some simple ensemble modeling techniques in literature. For instance, Model Output Statistics (MOS), and running mean-bias removal are widely used techniques in storm surge prediction domain. However, these methods have some drawbacks. For instance, MOS is based on multiple linear regression and it needs a long period of training data. To overcome the shortcomings of these simple methods, researchers propose some advanced methods. For instance, ENSURF (Ensemble SURge Forecast) is a multi-model application for sea level forecast. This application creates a better forecast of sea level using a combination of several instances of the Bayesian Model Averaging (BMA). An ensemble dressing method is based on identifying best member forecast and using it for prediction. Our contribution in this paper can be summarized as follows. First, we investigate whether the ensemble models perform better than any single forecast. Therefore, we need to identify the single best forecast. We present a methodology based on a simple Bayesian selection method to select the best single forecast. Second, we present several new and simple ways to construct ensemble models. We use correlation and standard deviation as weights in combining different forecast models. Third, we use these ensembles and compare with several existing models in literature to forecast storm surge level. We then investigate whether developing a complex ensemble model is indeed needed. To achieve this goal, we use a simple average (one of the simplest and widely used ensemble model) as benchmark. Predicting the peak level of Surge during a storm as well as the precise time at which this peak level takes place is crucial, thus we develop a statistical platform to compare the performance of various ensemble methods. This statistical analysis is based on root mean square error of the ensemble forecast during the testing period and on the magnitude and timing of the forecasted peak surge compared to the actual time and peak. In this work, we analyze four hurricanes: hurricanes Irene and Lee in 2011, hurricane Sandy in 2012, and hurricane Joaquin in 2015. Since hurricane Irene developed at the end of August 2011 and hurricane Lee started just after Irene at the beginning of September 2011, in this study we consider them as a single contiguous hurricane event. The data set used for this study is generated by the New York Harbor Observing and Prediction System (NYHOPS). We find that even the simplest possible way of creating an ensemble produces results superior to any single forecast. We also show that the ensemble models we propose generally have better performance compared to the simple average ensemble technique.

Keywords: Bayesian learning, ensemble model, statistical analysis, storm surge prediction

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Authors: Linda Chularojmontri, Seewaboon Sireeratawong, Suvara Wattanapitayakul

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Terminalia arjuna Roxb. (family Combretaceae) is commonly known as ‘Sa maw thet’ in Thai. The fruit is used in traditional medicine as natural mild laxatives, carminative and expectorant. Aim of the study: This research aims to study the anti-inflammatory, analgesic and antipyretic activities of Terminalia arjuna extract by using animal models in comparison to the reference drugs. Materials and Methods: The anti-inflammatory study was conducted by two experimental animal models namely ethyl phenylpropionate (EPP)-induced ear edema and carrageenan-induced paw edema. The study of analgesic activity used two methods of pain induction including acetic acid and heat-induced pain. In addition, the antipyretic activity study was performed by induced hyperthermia with yeast. Results: The results showed that the oral administration of Terminalia arjuna extract possessed acute anti-inflammatory effect in carrageenan-induced paw edema. Terminalia arjuna extract showed the analgesic activity in acetic acid-induced writhing response and heat-induced pain. This indicates its peripheral effect by inhibiting the biosynthesis and/or release of some pain mediators and some mechanism through Central nervous system. Moreover, Terminalia arjuna extract at the dose of 1000 and 1500 mg/kg body weight showed the antipyretic activity, which might be because of the inhibition of prostaglandins. Conclusion: The findings of this study indicated that the Terminalia arjuna extract possesses the anti-inflammatory, analgesic and antipyretic activities in animals.

Keywords: analgesic activity, anti-inflammatory activity, antipyretic activity, Terminalia arjuna extract

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Authors: Jinil Patel, Sarthak Patel, Sarthak Thakkar, Deepti Saraswat

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Recently, the COVID-19 outbreak has spread across the world, leading the World Health Organization to classify it as a global pandemic. To save the patient’s life, the COVID-19 symptoms have to be identified. But using an AI (Artificial Intelligence) model to identify COVID-19 symptoms within the allotted time was challenging. The RT-PCR test was found to be inadequate in determining the COVID status of a patient. To determine if the patient has COVID-19 or not, a Computed Tomography Scan (CT scan) of patient is a better alternative. It will be challenging to compile and store all the data from various hospitals on the server, though. Federated learning, therefore, aids in resolving this problem. Certain deep learning models help to classify Covid-19. This paper will have detailed work of certain deep learning models like VGG19, ResNet50, MobileNEtv2, and Deep Learning Aggregation (DLA) along with maintaining privacy with encryption.

Keywords: federated learning, COVID-19, CT-scan, homomorphic encryption, ResNet50, VGG-19, MobileNetv2, DLA

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Authors: Samuel Quashie

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Ph.D. Construction Management methodology and mixed methods are organized to guide the researcher to assemble and assess data in the research activities. Construction management research is close to business management and social science research. It also contributes to researching the phenomenon and answering the research question, generating an integrated management system for post-disaster reconstruction in construction and related industries. Research methodology and methods drive the research to achieve the goal or goals, contribute to knowledge, or increase knowledge. This statement means the research methodology, mixed methods, aim, objectives, and processes address the research question, facilitate its achievement and foundation to conduct the study. Mixed methods use project-based case studies, interviews, observations, literature and archival document reviews, research questionnaires, and surveys, and evaluation of integrated systems used in the construction industry and related industries to address the research work. The research mixed methods (qualitative, quantitative) define the research topic and establish a more in-depth study. The research methodology is action research, which involves the collaboration of participants and service users to collect and evaluate data, studying the phenomenon, research question(s) to improve the situation in post-disaster reconstruction phase management.

Keywords: methodology, Ph.D. research, post-disaster reconstruction, mixed-methods qualitative and quantitative

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Authors: Heeba A. Gurku

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Introduction: Cone Beam CT(CBCT) images play an integral part in proper patient positioning in cancer patients undergoing radiation therapy treatment. But these images are low in quality. The purpose of this study is to generate high-quality synthetic CT images from CBCT using generative models. Material and Methods: This study utilized two datasets from The Cancer Imaging Archive (TCIA) 1) Lung cancer dataset of 20 patients (with full view CBCT images) and 2) Pancreatic cancer dataset of 40 patients (only 27 patients having limited view images were included in the study). Cycle Generative Adversarial Networks (GAN) and its variant Attention Guided Generative Adversarial Networks (AGGAN) models were used to generate the synthetic CTs. Models were evaluated by visual evaluation and on four metrics, Structural Similarity Index Measure (SSIM), Peak Signal Noise Ratio (PSNR) Mean Absolute Error (MAE) and Root Mean Square Error (RMSE), to compare the synthetic CT and original CT images. Results: For pancreatic dataset with limited view CBCT images, our study showed that in Cycle GAN model, MAE, RMSE, PSNR improved from 12.57to 8.49, 20.94 to 15.29 and 21.85 to 24.63, respectively but structural similarity only marginally increased from 0.78 to 0.79. Similar, results were achieved with AGGAN with no improvement over Cycle GAN. However, for lung dataset with full view CBCT images Cycle GAN was able to reduce MAE significantly from 89.44 to 15.11 and AGGAN was able to reduce it to 19.77. Similarly, RMSE was also decreased from 92.68 to 23.50 in Cycle GAN and to 29.02 in AGGAN. SSIM and PSNR also improved significantly from 0.17 to 0.59 and from 8.81 to 21.06 in Cycle GAN respectively while in AGGAN SSIM increased to 0.52 and PSNR increased to 19.31. In both datasets, GAN models were able to reduce artifacts, reduce noise, have better resolution, and better contrast enhancement. Conclusion and Recommendation: Both Cycle GAN and AGGAN were significantly able to reduce MAE, RMSE and PSNR in both datasets. However, full view lung dataset showed more improvement in SSIM and image quality than limited view pancreatic dataset.

Keywords: CT images, CBCT images, cycle GAN, AGGAN

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Authors: Batool Ismaeel, Umair Farooq, Saad Mushtaq

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Construction projects in the oil industry can be very complex, having unknown outcomes and uncertainties that cannot be easily predicted. Each project has its unique risks generated by a number of factors which, if not controlled, will impact the successful completion of the project mainly in terms of schedule, cost, quality, and safety. This paper highlights the historic risks associated with projects in the south and east region of Kuwait Oil Company (KOC) collated from the company’s lessons learned database. Starting from Contract Award through to handover of the project to the Asset owner, the gaps in project execution in terms of managing risk will be brought to discussion and where a well-defined systematic approach in project risk management reflecting many claims, change of scope, exceeding budget, delays in engineering phase as well as in the procurement and fabrication of long lead items should be adopted. This study focuses on a proposed feasible approach in risk management for engineering, procurement and construction (EPC) level projects including the various stakeholders involved in executing the works from International to local contractors and vendors in KOC. The proposed approach covers the areas categorized into organizational, design, procurement, construction, pre-commissioning, commissioning and project management in which the risks are identified and require management and mitigation. With the effective deployment and implementation of the proposed risk management system and the consideration of it as a vital key in achieving the project’s target, the outcomes will be more predictable in the future, and the risk triggers will be managed and controlled. The correct resources can be allocated on a timely basis for the company for avoiding any unpredictable outcomes during the execution of the project. It is recommended in this paper to apply this risk management approach as an integral part of project management and investigate further in the future, the effectiveness of this proposed system for newly awarded projects and compare the same with those projects of similar budget/complexity that have not applied this approach to risk management.

Keywords: construction, project completion, risk management, uncertainties

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Authors: Dila Ram Bhandari

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Throughout the 20th century, new governments were created where identities such as ethnic, religious, linguistic, caste, communal, tribal, and others played a part in the development of constitutions and the legal system of victim and criminal justice. Acute issues with extremism, poverty, environmental degradation, cybercrimes, human rights violations, crime against, and victimization of both individuals and groups have recently plagued South Asian nations. Everyday massive number of crimes are steadfast, these frequent crimes have made the lives of common citizens restless. Crimes are one of the major threats to society and also for civilization. Crime is a bone of contention that can create a societal disturbance. The old-style crime solving practices are unable to live up to the requirement of existing crime situations. Crime analysis is one of the most important activities of the majority of intelligent and law enforcement organizations all over the world. The South Asia region lacks such a regional coordination mechanism, unlike central Asia of Asia Pacific regions, to facilitate criminal intelligence sharing and operational coordination related to organized crime, including illicit drug trafficking and money laundering. There have been numerous conversations in recent years about using data mining technology to combat crime and terrorism. The Data Detective program from Sentient as a software company, uses data mining techniques to support the police (Sentient, 2017). The goals of this internship are to test out several predictive model solutions and choose the most effective and promising one. First, extensive literature reviews on data mining, crime analysis, and crime data mining were conducted. Sentient offered a 7-year archive of crime statistics that were daily aggregated to produce a univariate dataset. Moreover, a daily incidence type aggregation was performed to produce a multivariate dataset. Each solution's forecast period lasted seven days. Statistical models and neural network models were the two main groups into which the experiments were split. For the crime data, neural networks fared better than statistical models. This study gives a general review of the applied statistics and neural network models. A detailed image of each model's performance on the available data and generalizability is provided by a comparative analysis of all the models on a comparable dataset. Obviously, the studies demonstrated that, in comparison to other models, Gated Recurrent Units (GRU) produced greater prediction. The crime records of 2005-2019 which was collected from Nepal Police headquarter and analysed by R programming. In conclusion, gated recurrent unit implementation could give benefit to police in predicting crime. Hence, time series analysis using GRU could be a prospective additional feature in Data Detective.

Keywords: time series analysis, forecasting, ARIMA, machine learning

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Authors: Mohammad Talebi

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Supply chain administration could be a concern for all the countries within the world, whereas there's no special approach towards supportability. Generally, for one decade, manufactured insights applications in keen supply chains have found a key part. In this paper, applications of artificial intelligence in supply chain management have been clarified, and towards Canadian plans for smart supply chain management (SCM), a few notes have been suggested. A hierarchical framework for smart SCM might provide a great roadmap for decision-makers to find the most appropriate approach toward smart SCM. Within the system of decision-making, all the levels included in the accomplishment of smart SCM are included. In any case, more considerations are got to be paid to available and needed infrastructures.

Keywords: smart SCM, AI, SSCM, procurement

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Authors: Aminu Mubarak Sadis

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This study appraised the maintenance management practice in Federal University Dutse and Jigawa State Polytechnic Dutse, in Nigeria. The Physical Planning, Works and Maintenance Departments of the two Higher Institutions (Federal University Dutse and Jigawa State Polytechnic) are responsible for production and maintenance management of their physical assets. Over–enrollment problem has been a common feature in the higher institutions in Nigeria, Data were collected by the administered questionnaires and subsequent oral interview to authenticate the completed questionnaires. Random sampling techniques was used in selecting 150 respondents across the various institutions (Federal University Dutse and Jigawa State Polytechnic Dutse). Data collected was analyzed using Statistical Package for Social Science (SPSS) and t-test statistical techniques The conclusion was that maintenance management activities are yet to be given their appropriate attention on functions of the university and polytechnic which are crucial to improving teaching, learning and research. The unit responsible for maintenance and managing facilities should focus on their stated functions and effect changes were possible.

Keywords: appraisal, maintenance management, university, Polytechnic, practices

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Authors: Mohsen Farhadloo, Majid Farhadloo

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Aspect-level opinion mining that aims at discovering aspects (aspect identification) and their corresponding ratings (sentiment identification) from customer reviews have increasingly attracted attention of researchers and practitioners as it provides valuable insights about products/services from customer's points of view. Instead of addressing aspect identification and sentiment identification in two separate steps, it is possible to simultaneously identify both aspects and sentiments. In recent years many graphical models based on Latent Dirichlet Allocation (LDA) have been proposed to solve both aspect and sentiment identifications in a single step. Although LDA models have been effective tools for the statistical analysis of document collections, they also have shortcomings in addressing some unique characteristics of opinion mining. Our goal in this paper is to address one of the limitations of topic models to date; that is, they fail to directly model the associations among topics. Indeed in many text corpora, it is natural to expect that subsets of the latent topics have higher probabilities. We propose a probabilistic graphical model called focus-LDA, to better capture the associations among topics when applied to aspect-level opinion mining. Our experiments on real-life data sets demonstrate the improved effectiveness of the focus-LDA model in terms of the accuracy of the predictive distributions over held out documents. Furthermore, we demonstrate qualitatively that the focus-LDA topic model provides a natural way of visualizing and exploring unstructured collection of textual data.

Keywords: aspect-level opinion mining, document modeling, Latent Dirichlet Allocation, LDA, sentiment analysis

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Authors: Bongs Lainjo

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Educational institutions and authorities that are mandated to run education systems in various countries need to implement a curriculum that considers the possibility and existence of elementary school dropouts. This research focuses on elementary school dropout rates and the ability to replicate various predictive models carried out globally on selected Elementary Schools. The study was carried out by comparing the classical case studies in Africa, North America, South America, Asia and Europe. Some of the reasons put forward for children dropping out include the notion of being successful in life without necessarily going through the education process. Such mentality is coupled with a tough curriculum that does not take care of all students. The system has completely led to poor school attendance - truancy which continuously leads to dropouts. In this study, the focus is on developing a model that can systematically be implemented by school administrations to prevent possible dropout scenarios. At the elementary level, especially the lower grades, a child's perception of education can be easily changed so that they focus on the better future that their parents desire. To deal effectively with the elementary school dropout problem, strategies that are put in place need to be studied and predictive models are installed in every educational system with a view to helping prevent an imminent school dropout just before it happens. In a competency-based curriculum that most advanced nations are trying to implement, the education systems have wholesome ideas of learning that reduce the rate of dropout.

Keywords: elementary school, predictive models, machine learning, risk factors, data mining, classifiers, dropout rates, education system, competency-based curriculum

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Authors: Ana-Marija Stjepić, Dalia Suša Vugec

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Today, digital transformation is one of the leading topics that occupy the attention of scientific circles and business experts. Organizational success is most often reflected through the successful managing of business processes. Given the growing market for digital innovations and its ever-increasing impact on business, organizations need to be prepared for organizational changes that come with the digital era. In order to maintain their competitive advantage in the global market, organizations must adapt their processes to new digitalization conditions. The main goal of this study is to point out the link between the digital transformation and the business process management concept. Therefore, in order to contribute to the scientific field that explores the potential relation between business process management concept and digital transformation, a literature review has been conducted. Papers have been searched within the Business Process Management Journal by keywords related to the term digital transformation. Selected papers have been analyzed according to the topic, type of publication, year of publication, keywords, etc. The results reveal a growing number of papers published on the topic of digital transformation to the Business Process Management Journal, but the lack of case studies. This paper contributes to the extension of academic literature in this important, yet insufficiently researched, scientific field that creates the bond between two strong concepts of digital transformation and business process management.

Keywords: business process management, digital transformation, digitalization, process change

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Authors: Aljon Pangan

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The Philippines being an archipelagic country, is surrounded by coastlines (36,289 km), coastal waters (226,000 km²), oceanic waters (1.93 million km²) and territorial waters (2.2 million km²). Studies show that the Philippine coastal ecosystems are the most productive and biologically diverse in the world, however, plagued by degradation problems due to over-exploitation and illegal activities. The existence of coastal degradation issues in the country led to the emergence of Coastal Resource Management (CRM) as an approach to both national and local government in providing solutions for sustainable coastal resource utilization. CRM applies the idea of planning, implementing and monitoring through the lens of collaborative governance. It utilizes collective action and decision-making to achieve sustainable use of coastal resources. The Municipality of Bagac in Bataan is one of the coastal municipalities in the country who crafts its own CRM Program as a solution to coastal resource degradation and problems. Information and Communications Technology (ICT), particularly Integrated Imaging Management System (IIMS) is one approach that can be applied in the formula of collaborative governance which entails the Government, Private Sector, and Civil Society. IIMS can help policymakers, managers, and citizens in managing coastal resources through analyzed spatial data describing the physical, biological, and socioeconomic characteristics of the coastal areas. Moreover, this study will apply the qualitative approach in deciphering possible impacts of the application of IIMS in the Coastal Resource Management policy making and implementation of the Municipality of Bagac.

Keywords: coastal resource management, collaborative governance, integrated imaging management system, information and communication technology

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Authors: Mohamad Ghozali Hassan, Abdul Aziz Othman, Mohd Azril Ismail

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Adapting quickly to environmental dynamism is essential for an organization to develop outsourcing strategic and management in order to sustain competitive advantage. This research used the Partial Least Squares Structural Equation Modeling (PLS-SEM) tool to investigate the factors of environmental dynamism impact on the strategic outsourcing success among electrical and electronic manufacturing industries in outsourcing management. Statistical results confirm that the inclusion of customer demand, technological change, and competition level as a new combination concept of environmental dynamism, has positive effects on outsourcing success. Additionally, this research demonstrates the acceptability of PLS-SEM as a statistical analysis to furnish a better understanding of environmental dynamism in outsourcing management in Malaysia. A practical finding contributes to academics and practitioners in the field of outsourcing management.

Keywords: environmental dynamism, customer demand, technological change, competition level, outsourcing success

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Authors: Chen Jun

Abstract:

This study investigates the impact of family involvement, a pivotal factor shaping the management structure of family firms, on the firm’s innovation outputs. The independent variable focuses on the percentage number of family members serving as directors, supervisors and senior management. Our hypothesis suggests that family involvement tends to make management more conservative, thereby increasing the likelihood of impeding innovation investments and resulting in adverse effects on innovation output. Our findings reveal that Chinese family firms with high family involvement exhibit poorer innovation outputs compared to those with lower family involvement. Subsample analyses indicate that this negative influence of family involvement on innovation output is strengthened as the firm faces higher industry competition and a low marketization context. The findings of our paper contribute to the literature on family involvement by empirically illustrating how family involvement hinders innovation efforts and performance in Chinese family firms.

Keywords: family firm, family involvement, firm innovation, Chinese family firm

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Authors: Marine Kobalava

Abstract:

The article analyzes current global crises in the world, explains the causes of crises, substantiates that in the main cases the process accompanying the crisis are conflict situations. The paper argues that crises can become predictable if threats are identified and addressed by a company, organization, corporation, and others. Accordingly, mechanisms for the neutralization of conflict potential are proposed, the need to develop a communication strategy and create and redistribute information flows is justified. Conflict situations are assessed according to the types of crisis and it is considered that the conflict can become a prerequisite for the crisis. The paper substantiates the need to differentiate theories of crises and conflicts. Based on the evaluative judgment, conflict management measures are proposed taking into account institutionalization, conflict resolution norms and rules. The paper identifies the potential for conflicts created in the context of global crises and suggests local ways and mechanisms for their effective management. The involvement of the company's Public relations (PR) and relevant communication from the qualified staff is considered important. Conclusions are drawn on the problems of effective conflict management caused by global crises and recommendations for conflict resolution have been proposed.

Keywords: global crises, conflict situations, conflict identification, conflict management, conflict potential

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Authors: Wafula Simon Peter, Kimuli Nabayego Ibtihal, Nabaggala Kimuli Nashua

Abstract:

The worldwide use of information and communications technology (ICT) equipment and other electronic equipment is growing and consequently, there is a growing amount of equipment that becomes waste after its time in use. This growth is expected to accelerate since equipment lifetime decreases with time and growing consumption. As a result, e-waste is one of the fastest-growing waste streams globally. The United Nations University (UNU) calculates in its second Global E-waste Monitor 44.7 million metric tonnes (Mt) of e-waste were generated globally in 2016. The study population was 80 respondents, from which a sample of 69 respondents was selected using simple and purposive sampling techniques. This research was carried out to investigate the problem of e-waste and come up with a framework to improve e-waste management. The objective of the study was to develop a framework for improving e-waste management at the College of Engineering, Design, Art and Technology (CEDAT). This was achieved by breaking it down into specific objectives, and these included the establishment of the policy and other Regulatory frameworks being used in e-waste management at CEDAT, the determination of the effectiveness of the e-waste management practices at CEDAT, the establishment of the critical challenges constraining e-waste management at the College, development of a framework for e-waste management. The study reviewed the e-waste regulatory framework used at the college and then collected data which was used to come up with a framework. The study also established that weak policy and regulatory framework, lack of proper infrastructure, improper disposal of e-waste and a general lack of awareness of the e-waste and the magnitude of the problem are the critical challenges of e-waste management. In conclusion, the policy and regulatory framework should be revised, localized and strengthened to contextually address the problem. Awareness campaigns, the development of proper infrastructure and extensive research to establish the volumes and magnitude of the problems will come in handy. The study recommends a framework for the improvement of e-waste.

Keywords: e-waste, treatment, disposal, computers, model, management policy and guidelines

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Authors: Itulelo Matiyabu Imaja, Manoj Maharaj, Patrick Ndayizigamiye

Abstract:

Lack of transparency in public funds management is observed in many African countries. The DR Congo is among the most corrupted countries in Africa, and this is due mainly to lack of transparency and accountability in public funds management. Corruption has a negative effect on the welfare of the country’s citizens and the national economic growth. Public funds collection and allocation are the major areas whereby malpractices such as bribe, extortion, embezzlement, nepotism and other practices related to corruption are prevalent. Hence, there is a need to implement strong mechanisms to enforce transparency in public funds management. Many researchers have suggested some control mechanisms in curbing corruption in public funds management focusing mainly on law enforcement and administrative reforms with little or no insight on the role that ICT can play in preventing and curbing the corrupt behaviour. In the Democratic Republic of Congo (DRC), there are slight indications that the government of the DR Congo is integrating ICT to fight corruption in public funds collection and allocation. However, such government initiatives are at an infancy stage, with no tangible evidence on how ICT could be used effectively to address the issue of corruption in the context of the country. Hence, this research assesses the role that ICT can play for transparency in public funds management and suggest a framework for its adoption in the Democratic Republic of Congo. This research uses the revised Capability model (Capability, Empowerment, Sustainability model) as the guiding theoretical framework. The study uses the exploratory design methodology coupled with a qualitative approach to data collection and purposive sampling as sampling strategy.

Keywords: corruption, DR congo, ICT, management, public funds, transparency

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Authors: Stefan Bradu, Daniel Siegel, Jameson Loyal, Andrea Leaf, Alana Kurtti, Usha Alapati, Jared Jagdeo

Abstract:

Compared with all other variants of nodular melanoma, patients with polypoid nodular melanoma have the lowest 5-year survival rate. The pathophysiology and management of polypoid melanoma are scarcely reported in the literature. Although surgical excision is the cornerstone of melanoma management, treatment of polypoid melanoma is complicated by several negative prognostic factors, including early metastasis. This report demonstrates the successful treatment of a rapidly developing red nodular polypoid melanoma with metastasis using surgery and adjuvant nivolumab in a SARS-CoV-2-positive patient who delayed seeking care due to the COVID-19 pandemic. In addition to detailing the successful treatment approach, the immunosuppressive effects of SARS-2-CoV and its possible contribution to the rapid progression of polypoid melanoma are discussed. This case highlights the complex challenges of melanoma diagnosis and management during the COVID-19 pandemic.

Keywords: covid-19, dermatology, immunotherapy, melanoma, nivolumab

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Authors: Wynne De Jong, Robert Miller, Ross Riggs

Abstract:

Beyond the number of nurses providing care for patients, having nurses with the right skills, experience and education is essential to ensure the best possible outcomes for patients. Research studies continue to link nurse staffing and skill mix with nurse-sensitive patient outcomes; numerous studies clearly show that superior patient outcomes are associated with higher levels of regulated staff. Due to the limited number of tools and processes available to assist nurse leaders with staffing models of care, nurse leaders are constantly faced with the ongoing challenge to ensure their staffing models of care best suit their patient population. In 2009, several hospitals in Ontario, Canada participated in a research study to develop and evaluate an RN/RPN utilization toolkit. The purpose of this study was to develop and evaluate a toolkit for Registered Nurses/Registered Practical Nurses Staff mix decision-making based on the College of Nurses of Ontario, Canada practice standards for the utilization of RNs and RPNs. This paper will highlight how an organization has further developed the Patient Care Needs Assessment (PCNA) questionnaire, a major component of the toolkit. Moreover, it will demonstrate how it has utilized the information from PCNA to clearly identify patient and family care needs, thus providing evidence-based results to assist leaders with matching the best staffing skill mix to their patients.

Keywords: nurse staffing models of care, skill mix, nursing health human resources, patient safety

Procedia PDF Downloads 314