Search results for: Data Management in Cloud

Authors: D. Goustouridis, A. Sideris, I. Sdrolias, G. Loizos, N.-Alexander Tatlas, S. M. Potirakis

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Both daily and long-term management of a heavy-duty vehicles and construction machinery fleet is an extremely complicated and hard to solve issue. This is mainly due to the diversity of the fleet vehicles – machinery, which concerns not only the vehicle types, but also their age/efficiency, as well as the fleet volume, which is often of the order of hundreds or even thousands of vehicles/machineries. In the present paper we present “InteligentLogger”, a holistic heavy-duty fleet management system covering a wide range of diverse fleet vehicles. This is based on specifically designed hardware and software for the automated vehicle health status and operational cost monitoring, for smart maintenance. InteligentLogger is characterized by high adaptability that permits to be tailored to practically any heavy-duty vehicle/machinery (of different technologies -modern or legacy- and of dissimilar uses). Contrary to conventional logistic systems, which are characterized by raised operational costs and often errors, InteligentLogger provides a cost-effective and reliable integrated solution for the e-management and e-maintenance of the fleet members. The InteligentLogger system offers the following unique features that guarantee successful heavy-duty vehicles/machineries fleet management: (a) Recording and storage of operating data of motorized construction machinery, in a reliable way and in real time, using specifically designed Internet of Things (IoT) sensor nodes that communicate through the available network infrastructures, e.g., 3G/LTE; (b) Use on any machine, regardless of its age, in a universal way; (c) Flexibility and complete customization both in terms of data collection, integration with 3rd party systems, as well as in terms of processing and drawing conclusions; (d) Validation, error reporting & correction, as well as update of the system’s database; (e) Artificial intelligence (AI) software, for processing information in real time, identifying out-of-normal behavior and generating alerts; (f) A MicroStrategy based enterprise BI, for modeling information and producing reports, dashboards, and alerts focusing on vehicles– machinery optimal usage, as well as maintenance and scraping policies; (g) Modular structure that allows low implementation costs in the basic fully functional version, but offers scalability without requiring a complete system upgrade.

Keywords: E-maintenance, predictive maintenance, IoT sensor nodes, cost optimization, artificial intelligence, heavy-duty vehicles.

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Authors: Nouha Mhimdi, Wahiba Ben Abdessalem Karaa, Henda Ben Ghezala

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Many methods are used to collect data like questionnaires, surveys, focus group interviews. Or the collection of poor-quality data resulting, for example, from poorly designed questionnaires, the absence of good translators or interpreters, and the incorrect recording of data allow conclusions to be drawn that are not supported by the data or to focus only on the average effect of the program or policy. There are several solutions to avoid or minimize the most frequent errors, including obtaining expert advice on the design or adaptation of data collection instruments; or use technologies allowing better "anonymity" in the responses. In this context, and to overcome the aforementioned problems, we suggest in this paper an approach to achieve the collection of relevant data, by carrying out a large-scale questionnaire-based survey. We have been able to collect good quality, consistent and practical data on hospital emergencies to improve emergency services in hospitals, especially in the case of epidemics or pandemics.

Keywords: Data collection, survey, database, data analysis, hospital emergencies.

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Authors: Rahman Ali, Muhammad Sajjad, Farkhund Iqbal, Muhammad Sadiq Hassan Zada, Mohammed Hussain

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Emission of Carbon Dioxide (CO₂) has adversely affected the environment. One of the major sources of CO₂ emission is transportation. In the last few decades, the increase in mobility of people using vehicles has enormously increased the emission of CO₂ in the environment. To reduce CO₂ emission, sustainable transportation system is required in which smart parking is one of the important measures that need to be established. To contribute to the issue of reducing the amount of CO₂ emission, this research proposes a smart parking system. A cloud-based solution is provided to the drivers which automatically searches and recommends the most preferred parking slots. To determine preferences of the parking areas, this methodology exploits a number of unique parking features which ultimately results in the selection of a parking that leads to minimum level of CO₂ emission from the current position of the vehicle. To realize the methodology, a scenario-based implementation is considered. During the implementation, a mobile application with GPS signals, vehicles with a number of vehicle features and a list of parking areas with parking features are used by sorting, multi-level filtering, exploratory data analysis (EDA, Analytical Hierarchy Process (AHP)) and weighted sum model (WSM) to rank the parking areas and recommend the drivers with top-k most preferred parking areas. In the EDA process, “2020testcar-2020-03-03”, a freely available dataset is used to estimate CO₂ emission of a particular vehicle. To evaluate the system, results of the proposed system are compared with the conventional approach, which reveal that the proposed methodology supersedes the conventional one in reducing the emission of CO₂ into the atmosphere.

Keywords: CO2 emission, IoT, EDA, Weighted Sum Model, WSM, regression, smart parking system.

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Authors: Yu-Min Chang, Kuo-Sheng Tsai, Hung-Te Tsai, Chia-Hsin Li

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This paper presents the early-warning lights classification management system for industrial parks promoted by the Taiwan Environmental Protection Administration (EPA) since 2011, including the definition of each early-warning light, objectives, action program and accomplishments. All of the 151 industrial parks in Taiwan were classified into four early-warning lights, including red, orange, yellow and green, for carrying out respective pollution management according to the monitoring data of soil and groundwater quality, regulatory compliance, and regulatory listing of control site or remediation site. The Taiwan EPA set up a priority list for high potential polluted industrial parks and investigated their soil and groundwater qualities based on the results of the light classification and pollution potential assessment. In 2011-2013, there were 44 industrial parks selected and carried out different investigation, such as the early warning groundwater well networks establishment and pollution investigation/verification for the red and orange-light industrial parks and the environmental background survey for the yellow-light industrial parks. Among them, 22 industrial parks were newly or continuously confirmed that the concentrations of pollutants exceeded those in soil or groundwater pollution control standards. Thus, the further investigation, groundwater use restriction, listing of pollution control site or remediation site, and pollutant isolation measures were implemented by the local environmental protection and industry competent authorities; the early warning lights of those industrial parks were proposed to adjust up to orange or red-light. Up to the present, the preliminary positive effect of the soil and groundwater quality management system for industrial parks has been noticed in several aspects, such as environmental background information collection, early warning of pollution risk, pollution investigation and control, information integration and application, and inter-agency collaboration. Finally, the work and goal of self-initiated quality management of industrial parks will be carried out on the basis of the inter-agency collaboration by the classified lights system of early warning and management as well as the regular announcement of the status of each industrial park.

Keywords: Industrial park, soil and groundwater quality management, early-warning lights classification, SOP for reporting and treatment of monitored abnormal events.

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Authors: J. D. D. Daniel, K. N. Goh, S. M. Yusop

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Trends in business intelligence, e-commerce and remote access make it necessary and practical to store data in different ways on multiple systems with different operating systems. As business evolve and grow, they require efficient computerized solution to perform data update and to access data from diverse enterprise business applications. The objective of this paper is to demonstrate the capability of DTS [1] as a database solution for automatic data transfer and update in solving business problem. This DTS package is developed for the sales of variety of plants and eventually expanded into commercial supply and landscaping business. Dimension data modeling is used in DTS package to extract, transform and load data from heterogeneous database systems such as MySQL, Microsoft Access and Oracle that consolidates into a Data Mart residing in SQL Server. Hence, the data transfer from various databases is scheduled to run automatically every quarter of the year to review the efficient sales analysis. Therefore, DTS is absolutely an attractive solution for automatic data transfer and update which meeting today-s business needs.

Keywords: Data Transformation Services (DTS), ObjectLinking and Embedding Database (OLEDB), Data Mart, OnlineAnalytical Processing (OLAP), Online Transactional Processing(OLTP).

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Authors: P. S. Hiremath, Siddu P. Algur

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With the explosive growth of information sources available on the World Wide Web, it has become increasingly difficult to identify the relevant pieces of information, since web pages are often cluttered with irrelevant content like advertisements, navigation-panels, copyright notices etc., surrounding the main content of the web page. Hence, tools for the mining of data regions, data records and data items need to be developed in order to provide value-added services. Currently available automatic techniques to mine data regions from web pages are still unsatisfactory because of their poor performance and tag-dependence. In this paper a novel method to extract data items from the web pages automatically is proposed. It comprises of two steps: (1) Identification and Extraction of the data regions based on visual clues information. (2) Identification of data records and extraction of data items from a data region. For step1, a novel and more effective method is proposed based on visual clues, which finds the data regions formed by all types of tags using visual clues. For step2 a more effective method namely, Extraction of Data Items from web Pages (EDIP), is adopted to mine data items. The EDIP technique is a list-based approach in which the list is a linear data structure. The proposed technique is able to mine the non-contiguous data records and can correctly identify data regions, irrespective of the type of tag in which it is bound. Our experimental results show that the proposed technique performs better than the existing techniques.

Keywords: Web data records, web data regions, web mining.

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Authors: Muhammad Rana, Quazi Mamun, Rafiqul Islam

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In the Internet of Things (IoT), many devices are connected and accumulate a sheer amount of data. These Internet-driven raw data need to be transferred securely to the end-users via dependable networks. Consequently, the challenges of IoT security in various IoT domains are paramount. Cryptography is being applied to secure the networks for authentication, confidentiality, data integrity and access control. However, due to the resource constraint properties of IoT devices, the conventional cipher may not be suitable in all IoT networks. This paper designs a robust and effective lightweight cipher to secure the IoT environment and meet the resource-constrained nature of IoT devices. We also propose a symmetric and block-cipher based lightweight cryptographic algorithm. The proposed algorithm increases the complexity of the block cipher, maintaining the lowest computational requirements possible. The proposed algorithm efficiently constructs the key register updating technique, reduces the number of encryption rounds, and adds a layer between the encryption and decryption processes.

Keywords: Internet of Things, IoT, cryptography block cipher, s-box, key management, IoT security.

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Authors: H. W. Ker

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Longitudinal data typically have the characteristics of changes over time, nonlinear growth patterns, between-subjects variability, and the within errors exhibiting heteroscedasticity and dependence. The data exploration is more complicated than that of cross-sectional data. The purpose of this paper is to organize/integrate of various visual-graphical techniques to explore longitudinal data. From the application of the proposed methods, investigators can answer the research questions include characterizing or describing the growth patterns at both group and individual level, identifying the time points where important changes occur and unusual subjects, selecting suitable statistical models, and suggesting possible within-error variance.

Keywords: Data exploration, exploratory analysis, HLMs/LMEs, longitudinal data, visual-graphical methods.

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Authors: Kumar Padmanabh, Rajarshi Roy

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In this paper a special kind of buffer management policy is studied where the packet are preempted even when sufficient space is available in the buffer for incoming packets. This is done to congestion for future incoming packets to improve QoS for certain type of packets. This type of study has been done in past for ATM type of scenario. We extend the same for heterogeneous traffic where data rate and size of the packets are very versatile in nature. Typical example of this scenario is the buffer management in Differentiated Service Router. There are two aspects that are of interest. First is the packet size: whether all packets have same or different sizes. Second aspect is the value or space priority of the packets, do all packets have the same space priority or different packets have different space priorities. We present two types of policies to achieve QoS goals for packets with different priorities: the push out scheme and the expelling scheme. For this work the scenario of packets of variable length is considered with two space priorities and main goal is to minimize the total weighted packet loss. Simulation and analytical studies show that, expelling policies can outperform the push out policies when it comes to offering variable QoS for packets of two different priorities and expelling policies also help improve the amount of admissible load. Some other comparisons of push out and expelling policies are also presented using simulations.

Keywords: Buffer Management Policy, Diffserv, ATM, Pushout Policy, Expeling Policy.

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Authors: Pablo Cardozo Herrera

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In a dynamic market of Information Technology (IT) Service and with high quality demands and high performance requirements in decreasing costs, it is imperative that IT companies invest organizational effort in order to increase the effectiveness of their Information Technology Service Management (ITSM) processes through the improvement of ITSM project management and through solid support to the strategic decision-making process of IT directors. In this article, the author presents an analysis of common issues of IT companies around the world, with strategic needs of information unmet that provoke their ITSM processes and projects management that do not achieve the effectiveness and efficiency expected of their results. In response to the issues raised, the author proposes a framework consisting of an innovative theoretical framework model of ITSM management and a technological solution aligned to the Information Technology Infrastructure Library (ITIL) good practices guidance and ISO/IEC 20000-1 requirements. The article describes a research that proves the proposed framework is able to integrate, manage and coordinate in a holistic way, measurable and auditable, all ITSM processes and projects of IT organization and utilize the effectiveness assessment achieved for their strategic decision-making process increasing the process maturity level and improving the capacity of an efficient management.

Keywords: Innovation in IT services, ITSM processes, ITIL and ISO/IEC 20000-1, IT service management, IT service excellence.

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Authors: Shahrinaz Ismail, Mohd Sharifuddin Ahmad

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This paper presents an analytical framework for an effective online personal knowledge management (PKM) of knowledge workers. The development of this framework is prompted by our qualitative research on the PKM processes and cognitive enablers of knowledge workers in eight organisations selected from three main industries in Malaysia. This multiple-case research identifies the relationships between the effectiveness of four online PKM processes: get/retrieve, understand/analyse, share, and connect. It also establishes the importance of cognitive enablers that mediate this relationship, namely, method, identify, decide and drive. Qualitative analysis is presented as the findings, supported by the preceded quantitative analysis on an exploratory questionnaire survey.

Keywords: Bottom-up approach, knowledge organisation, organisational knowledge management, personal knowledge management, software agent technology.

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Authors: Ling Zheng, Yaping Wei, Kang Cao, Zheng Huang, Songpo Shi

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Not only is municipal pattern the institution basement of urban management, but it also determines the forms of the management results. There-s a considerable possibility of bankruptcy for China-s current municipal pattern as it-s an overdraft of land deal in fact. Based on the analysis of China-s current municipal pattern, the passage proposed an assumption of a new pattern verified legitimacy by conceptual as well as econometric models. Conclusion is: the added supernumerary value of investment in public goods was not included in China-s current municipal pattern, but hidden in the rising housing prices; we should set housing tax or municipal tax to optimize the municipal pattern, to correct the behavior of local governments and to ensure the regular development of China-s urbanization.

Keywords: Urban management, China's municipal pattern, land financial institution, housing tax, Public goods.

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Authors: Isa Nakhai Kamal Abadi, Esmaeel Saberi, Ehsan Mirjafari

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Every organization is continually subject to new damages and threats which can be resulted from their operations or their goal accomplishment. Methods of providing the security of space and applied tools have been widely changed with increasing application and development of information technology (IT). From this viewpoint, information security management systems were evolved to construct and prevent reiterating the experienced methods. In general, the correct response in information security management systems requires correct decision making, which in turn requires the comprehensive effort of managers and everyone involved in each plan or decision making. Obviously, all aspects of work or decision are not defined in all decision making conditions; therefore, the possible or certain risks should be considered when making decisions. This is the subject of risk management and it can influence the decisions. Investigation of different approaches in the field of risk management demonstrates their progress from quantitative to qualitative methods with a process approach.

Keywords: Risk Management, Information Security, Methodology, Probability.

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Authors: Cindy Wang-Cowham, Judy Ningyu Tang

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The paper contributes towards the development of scarce literature on HR knowledge management. Drawing literature from knowledge management, the authors define the meaning of HR knowledge and propose that there are social mechanisms in organizations that facilitate the management and sharing of HR knowledge. Instead of investigating the subject in large multinational corporations, the present paper examines it in a large Chinese privately owned enterprise, which has an international standing. The main finding of the case analysis is that communication and feedback plays a pivotal role when managing HR knowledge. Social mechanisms can stimulate the communication and feedback between employees, thus facilitate knowledge exchange.

Keywords: HR knowledge, knowledge management, large privately owned enterprises, China.

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Authors: M. El Mousadik, F. Elkandoussi

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The concern for increased rigor in social management has led more and more Moroccan business leaders to question the value of applying social audit as an essential tool in the management of human resources. Hotel companies are not excluded; in fact, they are expected to implement such an audit to develop sound and credible human resources management (HRM) policies. The main objective of this paper is to establish the relationship between the practice of social audit as a tool, and its impact on the tourism sector, especially on hotels at one of the Morocco’s first and most popular city for tourism, Agadir. This exploratory study of properties in Agadir has revealed that hotel executives are aware of the importance of social auditing to hone their decisions in the field of HRM.

Keywords: Social audit, hotel companies, human resources management, social piloting.

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Authors: Feng Xiao, Zhou Hongyu, YuCaixia

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Based on an analysis of the current research and application of Road maintenance, geographic information system (WebGIS) and ArcGIS Server, the platform overhead construction for Road maintenance development is studied and the key issues are presented, including the organization and design of spatial data on the basis of the geodatabase technology, middleware technology, tiles cache index technology and dynamic segmentation of WebGIS. Road maintenance geographic information platform is put forward through the researching ideas of analysis of the system design. The design and application of WebGIS system are discussed on the basis of a case study of BaNan district of Chongqing highway maintenance management .The feasibility of the theories and methods are validated through the system.

Keywords: WebGIS, Tile, Road maintenance, dynamic segmentation

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Authors: Suparna Karmakar, Ranjan Dasgupta

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Railway Stations are prone to emergency due to various reasons and proper monitor of railway stations are of immense importance from various angles. A Petri-net representation of a web-service-based Emergency management system has been proposed in this paper which will help in monitoring situation of train, track, signal etc. and in case of any emergency, necessary resources can be dispatched.

Keywords: Business process, Petri net, Rail Station Emergency Management, Web service based system

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Authors: N. Akhavan Moghaddam, K. Tahvildari, S.Taghvaie

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Biodisel is a type of biofuel having similar properties of diesel fuel but lacks substances (undesirable emissions) such as sulfur, nitrogen and aromatic polycyclic. Upon filtration of waste oil, the biodiesel fuel was produced via carrying out transestrification reaction of triglycerides followed by conducting viscosity, density, flash point, cloud point, pour point and copper strip corrosion tests on the samples and comparing with EN14214 and ASTM 6751 standards and all results were found in the permitted limit. The highest yield of biodiesel production reaction was found 46.6435 g when Sodium Hydroxide catalyst in amount of 0.375g was employed, 44.2347 g when Sodium methoxide catalyst in amount of 0.5g was employed and 56.5124 g when acid sulfuric catalyst in amount of 1g was employed and 47.3290 g when two stage reaction was done.

Keywords: Biodiesel, Transesterification, Basic catalyst, Acidic catalyst.

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Authors: M. S. Razana, Z. W. Shafiuddin

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Internal auditing is one of the most important activities for organizations that implement information security management systems (ISMS). The purpose of internal audits is to ensure the ISMS implementation is in accordance to the ISO/IEC 27001 standard and the organization’s own requirements for its ISMS. Competent internal auditors are the main element that contributes to the effectiveness of internal auditing activities. To realize this need, CyberSecurity Malaysia is now in the process of becoming a certification body that certifies ISMS internal auditors. The certification scheme will assess the competence of internal auditors in generic knowledge and skills in management systems, and also in ISMS-specific knowledge and skills. The certification assessment is based on the ISO/IEC 19011 Guidelines for auditing management systems, ISO/IEC 27007 Guidelines for information security management systems auditing and ISO/IEC 27001 Information security management systems requirements. The certification scheme complies with the ISO/IEC 17024 General requirements for bodies operating certification systems of persons. Candidates who pass the exam will be certified as an ISMS Internal Auditor, whose competency will be evaluated every three years.

Keywords: ISMS internal audit, ISMS internal auditor, ISO/IEC 17024, Competence, Certification.

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Authors: T. Mathumathi, S. Ganesh, R. Gunabalan

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This work presents an approach for AC load flow based centralized model for congestion management in the forward markets. In this model, transaction maximizes its profit under the limits of transmission line capacities allocated by Independent System Operator (ISO). The voltage and reactive power impact of the system are also incorporated in this model. Genetic algorithm is used to solve centralized congestion management problem for multilateral transactions. Results obtained for centralized model using genetic algorithm is compared with Sequential Quadratic Programming (SQP) technique. The statistical performances of various algorithms such as best, worst, mean and standard deviations of social welfare are given. Simulation results clearly demonstrate the better performance of genetic algorithm over SQP.

Keywords: Congestion management, Genetic algorithm, Sequential quadratic programming.

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Authors: Towards Better Quality in Healthcare, Operations Management: A Developmental Literature Review

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This work presents the various perspectives, dimensions, components and definitions given to quality in the operations management (OM) and healthcare services (HCS) literature in time, highlighting gaps and learning opportunities between the two disciplines through a thorough search into their rich and distinct body of knowledge. Greater and new insights about the general nature of quality are obtained with findings such as in OM, quality has been approached in six fairly distinct paradigms (excellence, value, conformity to specifications, attributes, satisfaction and meeting or exceeding customer expectations), whereas in HCS, two approaches are prominent (Donabedian’s structure, process and outcomes model and Lohr and Schroeder’s circumscribed definition). The two disciplines views on quality seem to have progressed much in parallel with little cross-learning from each other. This work then proposes an encompassing definition of quality as a lever and suggests further research and development avenues for a better use of the concept of quality by academics and practitioners alike toward the goals of greater organizational performance and improved management in healthcare and possibly other service domains.

Keywords: Healthcare, management, operations, quality, services.

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Authors: Abeba Nigussie Turi, Xiangming Samuel Li

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Data-driven business models are more typical for established businesses than early-stage startups that strive to penetrate a market. This paper provided an extensive discussion on the principles of data analytics for early-stage digital entrepreneurial businesses. Here, we developed data-driven decision-making (DDDM) framework that applies to startups prone to multifaceted barriers in the form of poor data access, technical and financial constraints, to state some. The startup DDDM framework proposed in this paper is novel in its form encompassing startup data analytics enablers and metrics aligning with startups' business models ranging from customer-centric product development to servitization which is the future of modern digital entrepreneurship.

Keywords: Startup data analytics, data-driven decision-making, data acquisition, data generation, digital entrepreneurship.

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Authors: Minsoo Lee, Yearn Jeong Kim, Yun-mi Kim, Sujeung Cheong, Sookyung Song

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Bio-chips are used for experiments on genes and contain various information such as genes, samples and so on. The two-dimensional bio-chips, in which one axis represent genes and the other represent samples, are widely being used these days. Instead of experimenting with real genes which cost lots of money and much time to get the results, bio-chips are being used for biological experiments. And extracting data from the bio-chips with high accuracy and finding out the patterns or useful information from such data is very important. Bio-chip analysis systems extract data from various kinds of bio-chips and mine the data in order to get useful information. One of the commonly used methods to mine the data is classification. The algorithm that is used to classify the data can be various depending on the data types or number characteristics and so on. Considering that bio-chip data is extremely large, an algorithm that imitates the ecosystem such as the ant algorithm is suitable to use as an algorithm for classification. This paper focuses on finding the classification rules from the bio-chip data using the Ant Colony algorithm which imitates the ecosystem. The developed system takes in consideration the accuracy of the discovered rules when it applies it to the bio-chip data in order to predict the classes.

Keywords: Ant Colony System, DNA chip data, Classification.

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Authors: K. N. Penna, E. J. Hoffman, T. R. Carter

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This paper suggests that cultural landscape management plans in an Indigenous context are more effective if designed by taking into consideration context-related social and cultural aspects, adopting people-centred and cultural-based approaches for instance. In relation to working in Indigenous and mining contexts, we draw upon and contribute to international policies on human rights that promote the development of management plans that are co-designed through genuine engagement processes. We suggest that the production of management plans that are built upon culturally relevant frameworks leads to more inclusive economic development, a greater sense of trust, and shared managerial responsibilities. In this paper, three issues related to Indigenous engagement and cultural landscape management plans will be addressed: (1) the need for effective communication channels between proponents and Traditional Owners (Australian original Aboriginal peoples who inhabited specific regions), (2) the use of a culturally sensitive approach to engage local representatives in the decision-making processes, and (3) how design of new management plans can help in establishing shared management.

Keywords: Culture-Centred Approach, Holons’ Hierarchy, Inclusive Economic Development, Indigenous Engagement.

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Authors: Md. Aminul Islam, Adel Merabet, Rachid Beguenane, Hussein Ibrahim

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This paper presents a simulation and mathematical model of stand-alone solar-wind-diesel based hybrid energy system (HES). A power management system is designed for multiple energy resources in a stand-alone hybrid energy system. Both Solar photovoltaic and wind energy conversion system consists of maximum power point tracking (MPPT), voltage regulation, and basic power electronic interfaces. An additional diesel generator is included to support and improve the reliability of stand-alone system when renewable energy sources are not available. A power management strategy is introduced to distribute the generated power among resistive load banks. The frequency regulation is developed with conventional phase locked loop (PLL) system. The power management algorithm was applied in Matlab^®/Simulink^® to simulate the results.

Keywords: Solar photovoltaic, wind energy, diesel engine, hybrid energy system, power management, frequency and voltage regulation.

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Authors: Klaus Stranacher, Vesna Krnjic, Thomas Zefferer

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The public sector holds large amounts of data of various areas such as social affairs, economy, or tourism. Various initiatives such as Open Government Data or the EU Directive on public sector information aim to make these data available for public and private service providers. Requirements for the provision of public sector data are defined by legal and organizational frameworks. Surprisingly, the defined requirements hardly cover security aspects such as integrity or authenticity. In this paper we discuss the importance of these missing requirements and present a concept to assure the integrity and authenticity of provided data based on electronic signatures. We show that our concept is perfectly suitable for the provisioning of unaltered data. We also show that our concept can also be extended to data that needs to be anonymized before provisioning by incorporating redactable signatures. Our proposed concept enhances trust and reliability of provided public sector data.

Keywords: Trusted Public Sector Data, Integrity, Authenticity, Reliability, Redactable Signatures.

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Authors: M. Hajduk-Stelmachowicz

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This paper presents results of empirical studies that were conducted in enterprises from Podkarpackie Voivodeship (Poland). It shows the experiences of those enterprises resulting from implementing and improving the eco-innovativeness management that is formal Environmental Management System (EMS). This study shows the expected and obtained internal benefits which are the effects of a functioning EMS. The aim of this paper is to determine whether the information included in international theoretical studies concerning the benefits of implementing, functioning and improving formal EMS (which is based on the international standard ISO 14001) are confirmed by the effects of the enterprises- activities.

Keywords: Eco-innovations, Environmental Management System (EMS), ISO 14001, Podkarpackie Voivodeship (Poland).

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Authors: Jenny Hall, Alison Jaquet

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Universities’ push toward the production of high quality research is not limited to academic staff and experienced researchers. In this environment of research rich agendas, Higher Degree Research (HDR) students are increasingly expected to engage in the publishing of good quality papers in high impact journals. IFN001: Advanced Information Research Skills (AIRS) is a credit bearing mandatory coursework requirement for Queensland University of Technology (QUT) doctorates. Since its inception in 1989, this unique blended learning program has provided the foundations for new researchers to produce original and innovative research. AIRS was redeveloped in 2012, and has now been evaluated with reference to the university’s strategic research priorities. Our research is the first comprehensive evaluation of the program from the learner perspective. We measured whether the program develops essential transferrable skills and graduate capabilities to ensure best practice in the areas of publishing and data management. In particular, we explored whether AIRS prepares students to be agile researchers with the skills to adapt to different research contexts both within and outside academia. The target group for our study consisted of HDR students and supervisors at QUT. Both quantitative and qualitative research methods were used for data collection. Gathering data was by survey and focus groups with qualitative responses analyzed using NVivo. The results of the survey show that 82% of students surveyed believe that AIRS assisted their research process and helped them learn skills they need as a researcher. The 18% of respondents who expressed reservation about the benefits of AIRS were also examined to determine the key areas of concern. These included trends related to the timing of the program early in the candidature and a belief among some students that their previous research experience was sufficient for postgraduate study. New insights have been gained into how to better support HDR learners in partnership with supervisors and how to enhance learning experiences of specific cohorts, including international students and mature learners.

Keywords: Data management, enhancing learning experience, publishing, research higher degree students.

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Authors: Brennan Lodge

Abstract:

Amidst a complex regulatory landscape, Retrieval Augmented Generation (RAG) emerges as a transformative tool for Governance Risk and Compliance (GRC) officers. This paper details the application of RAG in synthesizing Large Language Models (LLMs) with external knowledge bases, offering GRC professionals an advanced means to adapt to rapid changes in compliance requirements. While the development for standalone LLMs is exciting, such models do have their downsides. LLMs cannot easily expand or revise their memory, and they cannot straightforwardly provide insight into their predictions, and may produce “hallucinations.” Leveraging a pre-trained seq2seq transformer and a dense vector index of domain-specific data, this approach integrates real-time data retrieval into the generative process, enabling gap analysis and the dynamic generation of compliance and risk management content. We delve into the mechanics of RAG, focusing on its dual structure that pairs parametric knowledge contained within the transformer model with non-parametric data extracted from an updatable corpus. This hybrid model enhances decision-making through context-rich insights, drawing from the most current and relevant information, thereby enabling GRC officers to maintain a proactive compliance stance. Our methodology aligns with the latest advances in neural network fine-tuning, providing a granular, token-level application of retrieved information to inform and generate compliance narratives. By employing RAG, we exhibit a scalable solution that can adapt to novel regulatory challenges and cybersecurity threats, offering GRC officers a robust, predictive tool that augments their expertise. The granular application of RAG’s dual structure not only improves compliance and risk management protocols but also informs the development of compliance narratives with pinpoint accuracy. It underscores AI’s emerging role in strategic risk mitigation and proactive policy formation, positioning GRC officers to anticipate and navigate the complexities of regulatory evolution confidently.

Keywords: Retrieval Augmented Generation, Governance Risk and Compliance, Cybersecurity, AI-driven Compliance, Risk Management, Generative AI.

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Authors: Karishma Kashyap, Subha D. Parida

Abstract:

Rapid population growth and urbanization is creating pressure throughout the world. This has a dramatic effect on a lot of elements which include water, food, transportation, energy, infrastructure etc. as few of the key services. Built environment sector is growing concurrently to meet the needs of urbanization. Due to such large scale development of buildings, there is a need for them to be monitored and managed efficiently. Along with appropriate management, climate adaptation is highly crucial as well because buildings are one of the major sources of greenhouse gas emission in their operation phase. Buildings to be adaptive need to provide a triple bottom approach to sustainability i.e., being socially, environmentally and economically sustainable. Hence, in order to deliver these sustainability outcomes, there is a growing understanding and thrive towards switching to green buildings or renovating new ones as per green standards wherever possible. Academic institutions in particular have been following this trend globally. This is highly significant as universities usually have high occupancy rates because they manage a large building portfolio. Also, as universities accommodate the future generation of architects, policy makers etc., they have the potential of setting themselves as a best industry practice model for research and innovation for the rest to follow. Hence their climate adaptation, sustainable growth and performance management becomes highly crucial in order to provide the best services to users. With the objective of evaluating appropriate management mechanisms within academic institutions, a feasibility study was carried out in a recent 5-Star Green Star rated university building (housing the School of Construction) in Victoria (south-eastern state of Australia). The key aim was to understand the behavioral and social aspect of the building users, management and the impact of their relationship on overall building sustainability. A survey was used to understand the building occupant’s response and reactions in terms of their work environment and management. A report was generated based on the survey results complemented with utility and performance data which were then used to evaluate the management structure of the university. Followed by the report, interviews were scheduled with the facility and asset managers in order to understand the approach they use to manage the different buildings in their university campuses (old, new, refurbished), respective building and parameters incorporated in maintaining the Green Star performance. The results aimed at closing the communication and feedback loop within the respective institutions and assist the facility managers to deliver appropriate stakeholder engagement. For the wider design community, analysis of the data highlights the applicability and significance of prioritizing key stakeholders, integrating desired engagement policies within an institution’s management structures and frameworks and their effect on building performance

Keywords: Building Optimization, Green Building, Post Occupancy Evaluation, Stakeholder Engagement.

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