Search results for: uncertain volatility

Authors: Mateusz Janas

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Innovative implementations in the micro, small, and medium-sized enterprises (MSME) sector are among the essential activities considering the current market realities, technological advancements, and digitization trends. MSMEs play a crucial role and significantly influence the economic conditions of countries, as their competitiveness directly impacts the global economy. Business development and investment in innovation and technology are integral parts of every modern enterprise's strategy, seeking to maintain and achieve a desired competitive position. The instability of the socio-economic environment, along with contemporary changes in artificial intelligence implementation and digitization, requires businesses to adopt increasingly newer solutions and actions. Enterprises must strive to survive in the global market and build competitive positions, especially in uncertain conditions. Being aware of the significance of innovative actions is crucial for MSMEs as it enables them to enhance their operations and expand their scope. It is essential for managers and executives of MSMEs to be focused on development and innovation, as their approach will also impact their employees, emphasizing results and maximizing the company's value. Managers of MSMEs must be aware of various threats, costs, opportunities, and gains that can arise from implementing new technical and organizational solutions. Businesses must view development as an integral part of their strategy and continuously strive for improvement.

Keywords: innovation, SME, develop, management

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Authors: Ghulam Murshid

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Carbon dioxide is one of the major greenhouse gas (GHG) contributors. It is an obligation of the industry to reduce the amount of carbon dioxide emission to the acceptable limits. Tremendous research and studies are reported in the past and still the quest to find the suitable and economical solution of this problem needed to be explored in order to develop the most plausible absorber for carbon dioxide removal. Amino acids are reported by the researchers as a potential solvent for absorption of carbon dioxide to replace alkanolamines due to its ability to resist oxidative degradation, low volatility due to its ionic structure and higher surface tension. In addition, the introduction of promoter-like piperazine to amino acid helps to further enhance the solubility. In this work, the effect of piperazine on thermophysical properties and solubility of β-Alanine aqueous solutions were studied for various concentrations. The measured physicochemical properties data was correlated as a function of temperature using least-squares method and the correlation parameters are reported together with it respective standard deviations. The effect of activator piperazine on the CO2 loading performance of selected amino acid under high-pressure conditions (1bar to 10bar) at temperature range of (30 to 60)oC was also studied. Solubility of CO2 decreases with increasing temperature and increases with increasing pressure. Quadratic representation of solubility using Response Surface Methodology (RSM) shows that the most important parameter to optimize solubility is system pressure. The addition of promoter increases the solubility effect of the solvent.

Keywords: amino acids, co2, global warming, solubility

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Authors: Abdelmounaim Lahrech, Hajar Bousfiha

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This paper examines equity market integration between Morocco and France and its consequent implications on international portfolio diversification. In the absence of stock market linkages, Morocco can act as a diversification destination to European investors, allowing higher returns at a comparable level of risk in developed markets. In contrast, this attractiveness is limited if both financial markets show significant linkage. The research empirically measures financial market’s integration in by capturing the conditional correlation between the two markets using the Generalized Autoregressive Conditionally Heteroscedastic (GARCH) model. Then, the research uses the Dynamic Conditional Correlation (DCC) model of Engle (2002) to track the correlations. The research findings show that there is no important increase over the years in the correlation between the Moroccan and the French equity markets, even though France is considered Morocco’s first trading partner. Failing to prove evidence of the stock index linkage between the two countries, the volatility series of each market were assumed to change over time separately. Yet, the study reveals that despite the important historical and economic linkages between Morocco and France, there is no evidence that equity markets follow. The small correlations and their stationarity over time show that over the 10 years studied, correlations were fluctuating around a stable mean with no significant change at their level. Different explanations can be attributed to the absence of market linkage between the two equity markets.

Keywords: equity market linkage, DCC GARCH, international portfolio diversification, Morocco, France

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Authors: Ahmet Emre Yonder

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The concept of present time is inevitably and rapidly changing. That provokes unbalanced, uncertain and elusive platform in the world order. Keeping up with this fluctuation requires a willingness to step beyond the comfort zones and to take a step through unknown. That is the perspectives of organizations in which the shareholders persistently create and then they share their creation. Moreover they are adapted to the unpredictable shifts and they establish vision. These are the meaning of innovation which is a process that converts new ideas to invaluable outcomes and that process can be ensured via innovative leaders. Leaders’ creativity is needed when challenging against countless complicated and unsteady situations in the battlefield. However, little attention has been paid to the importance of being innovative leader apart from innovating new technologies so far. Additionally, in most situation militarist organizations are hesitant to welcome different attitudes and that may discourage new ideas. Furthermore military leaders may complain about the lack of sources in today's world where the sources are very rare. In that point military leaders should change the strategies they apply from conventional views to the innovation of different point of views. But the constant occupation in Air Forces can be counted as a huge obstacle for innovative thinking. An organizational structure is needed to be developed for solutions of the problems which the creative leaders will encounter.This article focuses on how to raise innovative military leaders with innovative thinking skills and the need for a change from conventional to the innovative leadership in Air Forces. It also gives important suggestions to encourage raising innovative military leaders.

Keywords: air force, creativity, leadership, military, innovation

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Authors: Lidija Simunovic

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A Close-out netting cause is a clause within master agreements which reduces credit risks. This clause contains the parties ' advance agreement that the occurrence of a certain event (such as the commencement of bankruptcy proceedings) will result in the termination of the contract and that their mutual claims will be calculated as a net lump-sum to be paid by one party to the other. The legal treatment of the enforceability of close-out netting clauses opens up many legal matters in comparative legal systems because it is not uniformly treated in comparative laws. Certain legal systems take a liberal approach and allow the enforcement of close-out netting clauses. Others are much stricter, and they limit or completely prohibit the enforcement of close-out netting clauses through the mandatory provisions of their national bankruptcy laws. The author analyzes the concept of close-out netting clauses in selected comparative legal systems and examines the differences in their legal treatment by using the historical, analytical, and comparative method. It results that special treatment of the close-out netting in national laws with a liberal approach is often forced by financial industry lobbies and introduced in national laws without the justified reasons. Contrary to that in legal systems with limited or prohibited approach on close-out netting the uncertain enforceability of the close-out netting clause causes potential credit risks. The detected discrepancy on the national legal treatment and national financial markets regarding close-out netting lead to the conclusion to author’s best knowledge that is not possible to use any national model of close-out netting as a role model which perfectly fits all.

Keywords: close-out netting clauses, derivatives, insolvency, offsetting

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Authors: Benga Ebouele, Thomas Tengen

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Implementing either periodic or continuous inventory review model within most manufacturing-companies-supply chains as a management tool may incur higher costs. These high costs affect the system flexibility which in turn affects the level of service required to satisfy customers. However, these effects are not clearly understood because the parameters of both inventory review policies (protection demand interval, order quantity, etc.) are not designed to be fully utilized under different and uncertain conditions such as poor manufacturing, supplies and delivery performance. Coming up with a hybrid model which may combine in some sense the feature of both continuous and a periodic inventory review models should be useful. Therefore, there is a need to build and evaluate such hybrid model on the annual total cost, stock out probability and system’s flexibility in order to search for the most cost effective inventory review model. This work also seeks to find the optimal sets of parameters of inventory management under stochastic condition so as to optimise each policy independently. The results reveal that a continuous inventory system always incurs lesser cost than a periodic (R, S) inventory system, but this difference tends to decrease as time goes by. Although the hybrid inventory is the only one that can yield lesser cost over time, it is not always desirable but also natural to use it in order to help the system to meet high performance specification.

Keywords: demand and lead time randomness, hybrid Inventory model, optimization, supply chain

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Authors: Sarah Marie

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In today's dynamic financial landscape, cryptocurrencies represent a paradigm shift characterized by innovation and intense debate. This study probes into their transformative potential and the challenges they present, offering a balanced perspective that recognizes both their promise and pitfalls. Emulating the engaging style of a TED Talk, this research goes beyond academic analysis, serving as a critical bridge to reconcile the perspectives of cryptocurrency skeptics and enthusiasts, fostering a well-informed dialogue. The study employs a mixed-method approach, analyzing current trends, regulatory landscapes, and public perceptions in the cryptocurrency domain. It distinguishes genuine innovators in this field from ostentatious opportunists, echoing the sentiment that real innovation should be separated from mere showmanship. If one is unfamiliar with who is being referenced, they can likely spot them leaning against their Lamborghinis outside "Crypto" conventions, looking greasy. Major findings reveal a complex scenario dominated by regulatory uncertainties, market volatility, and security issues, emphasizing the need for a coherent regulatory framework that balances innovation with risk management and sustainable practices. The study underscores the importance of transparency and consumer protection in fostering responsible growth within the cryptocurrency ecosystem. In conclusion, the research advocates for education, innovation, and ethical governance in the realm of cryptocurrencies. It calls for collaborative efforts to navigate the intricacies of this evolving landscape and to realize its full potential in a responsible, inclusive, and forward-thinking manner.

Keywords: financial landscape, innovation, public perception, transparency

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Authors: Jiin Jeong, Taekwang Kim, Kwang Ryel Ryu

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The target microgrid in this paper is isolated from the large central power system and is assumed to consist of wind generators, photovoltaic power generators, an energy storage system (ESS), a diesel power generator, the community load, and a dump load. The operation of such a microgrid can be hazardous because of the uncertain prediction of power supply and demand and especially due to the high fluctuation of the output from the wind generators. In this paper, we propose an iterative replanning method for determining the appropriate level of diesel generation and the charging/discharging cycles of the ESS for the upcoming one-hour horizon. To cope with the uncertainty of the estimation of supply and demand, the one-hour plan is built repeatedly in the regular interval of one minute by rolling the one-hour horizon. Since the plan should be built with a sufficiently large safe margin to avoid any possible black-out, some energy waste through the dump load is inevitable. In our approach, the level of safe margin is optimized through learning from the past experience. The simulation experiments show that our method combined with the margin optimization can reduce the dump load compared to the method without such optimization.

Keywords: microgrid, operation planning, power efficiency optimization, supply and demand prediction

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Authors: N. Guo, C. Xu, Z. C. Yang

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In order to ensure the high reliability of an aircraft, the accurate structural dynamics analysis has become an indispensable part in the design of an aircraft structure. Therefore, the structural finite element model which can be used to accurately calculate the structural dynamics and their transfer relations is the prerequisite in structural dynamic design. A dynamic finite element model updating method is presented to correct the uncertain parameters of the finite element model of a structure using measured modal parameters. The coordinate modal assurance criterion is used to evaluate the correlation level at each coordinate over the experimental and the analytical mode shapes. Then, the weighted summation of the natural frequency residual and the coordinate modal assurance criterion residual is used as the objective function. Moreover, the hybrid pattern search (HPS) optimization technique, which synthesizes the advantages of pattern search (PS) optimization technique and genetic algorithm (GA), is introduced to solve the dynamic FE model updating problem. A numerical simulation and a model updating experiment for GARTEUR aircraft model are performed to validate the feasibility and effectiveness of the present dynamic model updating method, respectively. The updated results show that the proposed method can be successfully used to modify the incorrect parameters with good robustness.

Keywords: model updating, modal parameter, coordinate modal assurance criterion, hybrid genetic/pattern search

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Authors: P. K. Singhal, R. Naresh, V. Sharma

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This paper presents the three optimization models, namely New Binary Artificial Bee Colony (NBABC) algorithm, NBABC with Local Search (NBABC-LS), and NBABC with Genetic Crossover (NBABC-GC) for solving the Wind-Thermal Unit Commitment (WTUC) problem. The uncertain nature of the wind power is incorporated using the Weibull probability density function, which is used to calculate the overestimation and underestimation costs associated with the wind power fluctuation. The NBABC algorithm utilizes a mechanism based on the dissimilarity measure between binary strings for generating the binary solutions in WTUC problem. In NBABC algorithm, an intelligent scout bee phase is proposed that replaces the abandoned solution with the global best solution. The local search operator exploits the neighboring region of the current solutions, whereas the integration of genetic crossover with the NBABC algorithm increases the diversity in the search space and thus avoids the problem of local trappings encountered with the NBABC algorithm. These models are then used to decide the units on/off status, whereas the lambda iteration method is used to dispatch the hourly load demand among the committed units. The effectiveness of the proposed models is validated on an IEEE 10-unit thermal system combined with a wind farm over the planning period of 24 hours.

Keywords: artificial bee colony algorithm, economic dispatch, unit commitment, wind power

Procedia PDF Downloads 375

Authors: Rashid S. Mohammad, Shicheng Zhang, Sun Lu, Syed Jamal-Ud-Din, Xinzhe Zhao

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A compositional reservoir simulation model (CMG-GEM) was used for cyclic CO₂ injection process in unconventional tight reservoir. Cyclic CO₂ injection is an enhanced oil recovery process consisting of injection, shut-in, and production. The study of cyclic CO₂ injection and hydrocarbon recovery in ultra-low permeability reservoirs is mainly a function of rock, fluid, and operational parameters. CMG-GEM was used to study several design parameters of cyclic CO₂ injection process to distinguish the parameters with maximum effect on the oil recovery and to comprehend the behavior of cyclic CO₂ injection in tight reservoir. On the other hand, permeability reduction induced by asphaltene precipitation is one of the major issues in the oil industry due to its plugging onto the porous media which reduces the oil productivity. In addition to asphaltene deposition, solubility of CO₂ in the aquifer is one of the safest and permanent trapping techniques when considering CO₂ storage mechanisms in geological formations. However, the effects of the above uncertain parameters on the process of CO₂ enhanced oil recovery have not been understood systematically. Hence, it is absolutely necessary to study the most significant parameters which dominate the process. The main objective of this study is to improve techniques for designing cyclic CO₂ injection process while considering the effects of asphaltene deposition and solubility of CO₂ in the brine in order to prevent asphaltene precipitation, minimize CO₂ emission, optimize cyclic CO₂ injection, and maximize oil production.

Keywords: tight reservoirs, cyclic O₂ injection, asphaltene, solubility, reservoir simulation

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Authors: Fazıl Gökgöz, Fahrettin Filiz

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Electricity prices have sophisticated features such as high volatility, nonlinearity and high frequency that make forecasting quite difficult. Electricity price has a volatile and non-random character so that, it is possible to identify the patterns based on the historical data. Intelligent decision-making requires accurate price forecasting for market traders, retailers, and generation companies. So far, many shallow-ANN (artificial neural networks) models have been published in the literature and showed adequate forecasting results. During the last years, neural networks with many hidden layers, which are referred to as DNN (deep neural networks) have been using in the machine learning community. The goal of this study is to investigate electricity price forecasting performance of the shallow-ANN and DNN models for the Turkish day-ahead electricity market. The forecasting accuracy of the models has been evaluated with publicly available data from the Turkish day-ahead electricity market. Both shallow-ANN and DNN approach would give successful result in forecasting problems. Historical load, price and weather temperature data are used as the input variables for the models. The data set includes power consumption measurements gathered between January 2016 and December 2017 with one-hour resolution. In this regard, forecasting studies have been carried out comparatively with shallow-ANN and DNN models for Turkish electricity markets in the related time period. The main contribution of this study is the investigation of different shallow-ANN and DNN models in the field of electricity price forecast. All models are compared regarding their MAE (Mean Absolute Error) and MSE (Mean Square) results. DNN models give better forecasting performance compare to shallow-ANN. Best five MAE results for DNN models are 0.346, 0.372, 0.392, 0,402 and 0.409.

Keywords: deep learning, artificial neural networks, energy price forecasting, turkey

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Authors: Soebowo Musa

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Mining industries are known to be very volatile due to their sensitive nature toward changes in the environment, particularly coal mining. Heavy equipment distributors and coal mining contractors are among heavily affected by such volatility. They are facing more uncertainty on the sustainability of the coal mining industry. Strategic alliances and organizational capabilities such as innovation capability have long been seen as ways to stay competitive with a focus more on the strategic alliances partner-to-partner in serving their customers. In today’s rapid change in the environment, a shift in consumer behaviors, and the human-centric business approach, this study looks at the strategic alliance partner-to-customer relationship in both the industrial organization and resource-based theories. This study was conducted based on 250 respondents from the strategic alliances partner-to-customer between heavy equipment distributors and coal mining contractors in Indonesia. This study finds strategic alliances have the highest association toward cost reduction, a proxy of operational efficiency followed by its association toward innovation capability. Further, strategic alliances and innovation capability have a positive relationship with customer loyalty, while innovation capability and customer loyalty have no significant relationships toward the firm’s competitive advantage. This study also indicates that cost reduction is not a condition to develop customer loyalty in the strategic alliance partner-to-customer relationship. It confirms strategic alliances are a strategy that creates a firm’s operational efficiency, innovation capability that develops customer loyalty, and competitive advantage.

Keywords: strategic alliance, innovation capability, cost reduction, customer loyalty, competitive advantage

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Authors: Zair Firdaous, Fourka Mohamed, Elfelsoufi Zoubir

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The arrival of e-commerce has changed the supply chain management on the operational level as well as on the organization and strategic and even tactical decisions of the companies. The optimization of resources is an issue that is needed on the tactical and operational strategic plan. This work considers the allocation of resources in the case of pure players that have launched online sales. The aim is to improve the level of customer satisfaction and maintaining the benefits of e-retailer and of its cooperators and reducing costs and risks. We first modeled the B2C chain with all operations that integrates and possible scenarios since online retailers offer a wide selection of personalized service. The personalized services that online shopping companies offer to the clients can be embodied in many aspects, such as the customizations of payment, the distribution methods, and after-sales service choices. Every aspect of customized service has several modes. At that time, we analyzed the optimization problems of supply chain resource in customized online shopping service mode. Then, we realized an optimization model and algorithm for the development based on the analysis of the of the B2C supply chain resources. It is a multi-objective optimization that considers the collaboration of resources in operations, time and costs but also the risks and the quality of services as well as dynamic and uncertain characters related to the request.

Keywords: supply chain resource, e-commerce, pure-players, optimization

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Authors: M. Bonopera, N. Tullini, C. C. Chen, T. K. Lin, K. C. Chang

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This paper presents the extension of a static method for the axial load identifications in prismatic beam-columns with uncertain length and unknown boundary conditions belonging to generic space structures, such as columns of space frames or struts and ties of space trusses. The non-destructive method requires the knowledge of the beam-column flexural rigidity only. Flexural displacements are measured at five cross sections along the beam-column subjected to an additional vertical load at the mid-span. Unlike analogous dynamic methods, any set of experimental data may be used in the identification procedure. The method is verified by means of many numerical and experimental tests on beam-columns having unknown boundary conditions and different slenderness belonging to three different space prototypes in small-scale. Excellent estimates of the tensile and compressive forces are obtained for the elements with higher slenderness and when the greatest possible distance between sensors is adopted. Moreover, the application of larger values of the vertical load and very accurate displacement measurements are required. The method could be an efficacious technique in-situ, considering that safety inspections will become increasingly important in the near future, especially because of the improvement of the material properties that allowed designing space structures composed of beam-columns with higher slenderness.

Keywords: force identification, in-situ test, space structure, static test

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Authors: Amal Hentati, Mbarka Selmi, Tarek Kormi, Julien Baroth, Barthelemy Harthong

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The impact of uncertainties on the performance assessment of shallow foundations is often significant. The need of the geotechnical engineers to a more objective and rigorous description of soil variations permitting to quantify these uncertainties and to incorporate them into calculation methods led to the development of reliability approaches. In this context, a mechanical-reliability coupling was developed in this paper, using a program coded in Matlab and the finite element software Abaqus, for the bearing capacity assessment of shallow foundations. The reliability analysis, based on the finite element method, assumed both soil cohesion and friction angle as uncertain parameters characterized by normal or lognormal probability distributions. The inherent spatial variability of both soil properties was, then, taken into account using 1D stationary random fields. The application of the proposed methodology to a shallow foundation subjected to a centered vertical loading permitted to highlight the proposed process interest. Findings proved the insufficiency of the conventional approach to predict the foundation failure and a high sensitivity of the ultimate loads to the soil properties uncertainties, mainly those related to the friction angle, was noted. Moreover, an asymmetry of both displacement and velocity fields was obtained.

Keywords: mechanical-reliability coupling, finite element method, shallow foundation, random fields, spatial variability

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Authors: Ons Triki, Fathi Abid

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The basic objective of this paper is twofold. It resides in designing a model for a contingent convertible lease contract that can ensure the financial stability of a company and recover the losses of the parties to the lease in the event of default. It also aims to compare the convertible lease contract on inefficiencies resulting from the debt-overhang problem and asset substitution with other financing policies. From this perspective, this paper highlights the interaction between investments and financing policies in a dynamic model with existing assets and a growth option where the investment cost is financed by a contingent convertible lease and equity. We explore the impact of the contingent convertible lease on the capital structure. We also check the reliability and effectiveness of the use of the convertible lease contract as a means of financing. Findings show that the rental convertible contract with a sufficiently high conversion ratio has less severe inefficiencies arising from risk-shifting and debt overhang than those entailed by risky debt and pure-equity financing. The problem of underinvestment pointed out by Mauer and Ott (2000) and the problem of overinvestment mentioned by Hackbarth and Mauer (2012) may be reduced under contingent convertible lease financing. Our findings predict that the firm value under contingent convertible lease financing increases globally with asset volatility instead of decreasing with business risk. The study reveals that convertible leasing contracts can stand for a reliable solution to ensure the lessee and quickly recover the counterparties of the lease upon default.

Keywords: contingent convertible lease, growth option, debt overhang, risk-shifting, capital structure

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Authors: Anil Ranjitbhai Patel, Clement John Shaji, Peter Liggesmeyer

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Safety and security of autonomous vehicles (AVs) is a growing concern, first, due to the increased number of safety-critical functions taken over by automotive embedded systems; second, due to the increased exposure of the software-intensive systems to potential attackers; third, due to dynamic interaction in an uncertain and unknown environment at runtime which results in changed functional and non-functional properties of the system. Frequently occurring environmental uncertainties, random component failures, and compromise security of the AVs might result in hazardous events, sometimes even in an accident, if left undetected. Beyond these technical issues, we argue that the safety and security of AVs against accidental and deliberate faults are poorly understood and rarely implemented. One possible way to overcome this is through a well-known diversity approach. As an effective approach to increase safety and security, diversity has been widely used in the aviation, railway, and aerospace industries. Thus, the paper proposes fault-tolerance by diversity model takes into consideration the mitigation of accidental and deliberate faults by application of structure and variant redundancy. The model can be used to design the AVs with various types of diversity in hardware and software-based multi-version system. The paper evaluates the presented approach by employing an example from adaptive cruise control, followed by discussing the case study with initial findings.

Keywords: autonomous vehicles, diversity, fault-tolerance, adaptive cruise control, safety, security

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Authors: Seyed Mohammad Hashemi, Shahrokh Barati

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The problem of fault-tolerant control (FTC) by accommodation method has been studied in this paper. The fault occurs in any system components such as actuators, sensors or internal structure of the system and leads to loss of performance and instability of the system. When a fault occurs, the purpose of the fault-tolerant control is designate strategy that can keep the control loop stable and system performance as much as possible perform it without shutting down the system. Here, the section of fault detection and isolation (FDI) system has been evaluated with regard to actuator's fault. Designing a fault detection and isolation system for a multi input-multi output (MIMO) is done by an unknown input observer, so the system is divided to several subsystems as the effect of other inputs such as disturbing given system state equations. In this observer design method, the effect of these disturbances will weaken and the only fault is detected on specific input. The results of this approach simulation can confirm the ability of the fault detection and isolation system design. After fault detection and isolation, it is necessary to redesign controller based on a suitable modification. In this regard after the use of unknown input observer theory and obtain residual signal and evaluate it, PID controller parameters redesigned for iterative. Stability of the closed loop system has proved in the presence of this method. Also, In order to soften the volatility caused by Annie variations of the PID controller parameters, modifying Sigma as a way acceptable solution used. Finally, the simulation results of three tank popular example confirm the accuracy of performance.

Keywords: fault tolerant control, fault detection and isolation, actuator fault, unknown input observer

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Authors: Melvin Chan, Chew Lee Teo

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There has been a growing emphasis in elevating the teachers’ proficiency and competencies through continuing professional development (CPD) opportunities. In this era of a Volatile, Uncertain, Complex, Ambiguous (VUCA) world, teachers are expected to be collaborative designers, critical thinkers and creative builders. However, many of the CPD structures are still revolving in the model of transmission, which stands in contradiction to the cultivation of future-ready teachers for the innovative world of emerging technologies. This article puts forward the framing of CPD through a Principle-Based, Technological-Driven Knowledge Building Approach grounded in the essence of andragogy and progressive learning theories where growth is best exemplified through an authentic immersion in a social/community experience-based setting. Putting this Knowledge Building Professional Development Model (KBPDM) in operation via a Professional Learning Team (PLT) situated in a Secondary School in Singapore, research findings reveal that the intervention has led to a fundamental change in the learning paradigm of the teachers, henceforth equipping and empowering them successfully in their pedagogical design and practices for a 21^st century classroom experience. This article concludes with the possibility in leveraging the Learning Analytics to deepen the CPD experiences for educators.

Keywords: continual professional development, knowledge building, learning paradigm, principle-based

Procedia PDF Downloads 130

Authors: Noorlizawati Abd Rahim, Zainai Mohamed, Zaidatun Tasir, Astuty Amrin, Haliyana Khalid, Nina Diana Nawi

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Entrepreneurial leaders have been sought as in-demand talents to lead profit-driven organizations during turbulent and unprecedented times. However, research regarding the pertinence of their roles in the public sector has been limited. This paper examined the characteristics of the challenging experiences encountered by senior leaders in public universities that require them to embrace entrepreneurialism in their leadership. Through a focus group interview with five Malaysian university top senior leaders with experience being Vice-Chancellor, we explored and developed a framework of institutional adversity characteristics and exemplary entrepreneurial leadership competency in the face of adversity. Complexity of diverse stakeholders, multiplicity of academic disciplines, unfamiliarity to lead different and broader roles, leading new directions, and creating change in high velocity and uncertain environment are among the dimensions that characterise institutional adversities. Our findings revealed that learning agility, opportunity recognition capacity, and bridging capability are among the characteristics of entrepreneurial university leaders. The findings reinforced that the presence of specific attributes in institutional adversity and experiences in overcoming those challenges may contribute to the development of entrepreneurial leadership capabilities.

Keywords: bridging capability, entrepreneurial leadership, leadership development, learning agility, opportunity recognition, university leaders

Procedia PDF Downloads 110

Authors: Firdaous Zair, Zoubir Elfelsoufi, Mohammed Fourka

Abstract:

The allocation of resources is an issue that is needed on the tactical and operational strategic plan. This work considers the allocation of resources in the case of pure players, manufacturers and Click & Mortars that have launched online sales. The aim is to improve the level of customer satisfaction and maintaining the benefits of e-retailer and of its cooperators and reducing costs and risks. Our contribution is a decision support system and tool for improving the allocation of resources in logistics chains e-commerce B2C context. We first modeled the B2C chain with all operations that integrates and possible scenarios since online retailers offer a wide selection of personalized service. The personalized services that online shopping companies offer to the clients can be embodied in many aspects, such as the customizations of payment, the distribution methods, and after-sales service choices. In addition, every aspect of customized service has several modes. At that time, we analyzed the optimization problems of supply chain resource allocation in customized online shopping service mode, which is different from the supply chain resource allocation under traditional manufacturing or service circumstances. Then we realized an optimization model and algorithm for the development based on the analysis of the allocation of the B2C supply chain resources. It is a multi-objective optimization that considers the collaboration of resources in operations, time and costs but also the risks and the quality of services as well as dynamic and uncertain characters related to the request.

Keywords: e-commerce, supply chain, B2C, optimisation, resource allocation

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Authors: Gia Sirbiladze

Abstract:

Route planning problems are among the activities that have the highest impact on logistical planning, transportation, and distribution because of their effects on efficiency in resource management, service levels, and client satisfaction. In extreme conditions, the difficulty of vehicle movement between different customers causes the imprecision of time of movement and the uncertainty of the feasibility of movement. A feasibility level of vehicle movement on the closed route of the disaster-streaking zone is defined for the construction of an objective function. Experts’ evaluations of the uncertain parameters in q-rung ortho-pair fuzzy numbers (q-ROFNs) are presented. A fuzzy bi-objective combinatorial optimization problem of fuzzy vehicle routine problem (FVRP) is constructed based on the technique of possibility theory. The FVRP is reduced to the bi-criteria partitioning problem for the so-called “promising” routes which were selected from the all-admissible closed routes. The convenient selection of the “promising” routes allows us to solve the reduced problem in real-time computing. For the numerical solution of the bi-criteria partitioning problem, the -constraint approach is used. The main results' support software is designed. The constructed model is illustrated with a numerical example.

Keywords: q-rung ortho-pair fuzzy sets, facility location selection problem, multi-objective combinatorial optimization problem, partitioning problem

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Authors: Zhuoyuan Wang, Benson T. H. Lim, Imriyas Kamardeen

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Effective service quality management has long been touted as a means of improving project and organisational performance. Particularly, in construction projects, main contractors are often seen as a broker between clients and subcontractors, and their service quality is thus associated with the overall project affinity and outcomes. While a considerable amount of research has focused on the aspect of clients-main contractors, very little research has been done to explore the effect of contractors’ service quality on subcontractors’ behaviours and so project outcomes. In addressing this gap, this study surveyed 97 subcontractors in the Chinese Construction industry and data was analysed using the Partial Least Square (PLS) Structural Equation Modelling (SEM) technique. The overall findings reveal that subcontractors categorised main contractors’ service quality into three dimensions: assurance; responsiveness; reliability and empathy. Of these, it is found that main contractors’ ‘assurance’ and ‘responsiveness’ positively influence subcontractors’ intention to engage in contractual behaviours. The results further show that the subcontractors’ intention to engage in organizational citizenship behaviours is associated with how flexible and committed the main contractors are in reliability and empathy. Collectively, both subcontractors’ contractual and organizational citizenship behaviours positively influence the overall project outcomes. In conclusion, the findings inform contractors different strategies towards managing and gaining subcontractors’ behaviour commitment in a socially connected, yet complex and uncertain, business environment.

Keywords: construction firms, organisational citizenship behaviour, service quality, social exchange theory

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Authors: Sagir M. Yusuf, Chris Baber

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In this paper, we describe how Bayesian inferential reasoning will contributes in obtaining a well-satisfied prediction for Distributed Constraint Optimization Problems (DCOPs) with uncertainties. We also demonstrate how DCOPs could be merged to multi-agent knowledge understand and prediction (i.e. Situation Awareness). The DCOPs functions were merged with Bayesian Belief Network (BBN) in the form of situation, awareness, and utility nodes. We describe how the uncertainties can be represented to the BBN and make an effective prediction using the expectation-maximization algorithm or conjugate gradient descent algorithm. The idea of variable prediction using Bayesian inference may reduce the number of variables in agents’ sampling domain and also allow missing variables estimations. Experiment results proved that the BBN perform compelling predictions with samples containing uncertainties than the perfect samples. That is, Bayesian inference can help in handling uncertainties and dynamism of DCOPs, which is the current issue in the DCOPs community. We show how Bayesian inference could be formalized with Distributed Situation Awareness (DSA) using uncertain and missing agents’ data. The whole framework was tested on multi-UAV mission for forest fire searching. Future work focuses on augmenting existing architecture to deal with dynamic DCOPs algorithms and multi-agent information merging.

Keywords: DCOP, multi-agent reasoning, Bayesian reasoning, swarm intelligence

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Authors: Zviad Ghadua, Biswa Bhattacharya

Abstract:

The Flash Flood Guidance (FFG) provides the rainfall amount of a given duration necessary to cause flooding. The approach is based on the development of rainfall-runoff curves, which helps us to find out the rainfall amount that would cause flooding. An alternative approach, mostly experimented with Italian Alpine catchments, is based on determining threshold discharges from past events and on finding whether or not an oncoming flood has its magnitude more than some critical discharge thresholds found beforehand. Both approaches suffer from large uncertainties in forecasting flash floods as, due to the simplistic approach followed, the same rainfall amount may or may not cause flooding. This uncertainty leads to the question whether a probabilistic model is preferable over a deterministic one in forecasting flash floods. We propose the use of a Bayesian probabilistic approach in flash flood forecasting. A prior probability of flooding is derived based on historical data. Additional information, such as antecedent moisture condition (AMC) and rainfall amount over any rainfall thresholds are used in computing the likelihood of observing these conditions given a flash flood has occurred. Finally, the posterior probability of flooding is computed using the prior probability and the likelihood. The variation of the computed posterior probability with rainfall amount and AMC presents the suitability of the approach in decision making in an uncertain environment. The methodology has been applied to the Posina basin in Italy. From the promising results obtained, we can conclude that the Bayesian approach in flash flood forecasting provides more realistic forecasting over the FFG.

Keywords: flash flood, Bayesian, flash flood guidance, FFG, forecasting, Posina

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Authors: Sara Iqbal

Abstract:

Introduction:Renal transplant is increasingly one of the most popular transplants within the UK; with an aging population along with obesity epidemic we are witnessing increasing rates of diabetes – one of the commonest indications for renal transplant. However, the demand is far greater than supply. Many donors are provided by women of child-bearing age; however the long-term effects are still uncertain. Aim:Determine pregnancy outcomes and complications of women of child-bearing age following renal donation. Methods: A review of the current available literature was preformed using MEDLINE and EMBASE up to 2014. Search criteria included key terms such as pregnancy outcome post-renal donor, pregnancy outcomes and complications. Relevant articles were selected based on pure methodological medical research, after careful analysis, they were recorded within this review. Results: Out of 1141 women involved in transplant studies, 574 pregnancies reported having donated a single-renal donor prior to pregnancy. Of which a staggering miscarriage rate 32.4% (n=186) was reported, amongst this other complications included gestational hypertension of 10% (n=59) and gestational diabetes 2.3% (n=13). Other significantly noted complications included chronic hypertension, low-birth weights, and pregnancy-related death. Conclusions: After unilateral renal donor transplant, haemodynamics change along with pregnancy, predisposing women to developing several complications compared to pregnancies with no history any renal-donor transplant. Despite this, further investigation is required in order to accurately determine the safety of renal-donors in women of child-bearing age.

Keywords: renal transplant, pregnancy, complications, medical and health sciences

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Authors: Abeer A. Q. Ahmed, Tracey McKay

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Biomass can provide a sustainable source for the production of high valued chemicals. Under the uncertain availability of fossil resources biomass could be the only available source for chemicals in future. Cellulose and hemicellulose can be hydrolyzed into their building blocks (hexsoses and pentoses) which can be converted later to the desired high valued chemicals. A cellulase- and xylanase- producing bacterial strain identified as Paenibacillus illinoisensis CX11 by 16S rRNA gene sequencing and phylogenetic analysis was found to have the ability to saccharify different lignocellulosic materials. Cellulase and xylanase activities were evaluated by 3,5-dinitro-salicylic acid (DNS) method using CMC and xylan as substrates. Results showed that P. illinoisensis CX11 have cellulase (2.63± 0.09 mg/ml) and xylanase (3.25 ± 0.2 mg/ml) activities. The ability of P. illinoisensis CX11 to saccharify lignocellulosic materials was tested using wheat straw (WS), wheat bran (WB), saw dust (SD), and corn stover (CS). DNS method was used to determine the amount of reducing sugars that were released from lignocellulosic materials. P. illinoisensis CX11 showed to have the ability to saccharify lignocellulosic materials and producing total reducing sugars as 2.34 ± 0.12, 2.51 ± 0.37, 1.86 ± 0.16, and 3.29 ± 0.20 mg/l from WS, WB, SD, and CS respectively. According to the author's knowledge, current findings are the first to report P. illinoisensis CX11 as a cellulase and xylanase producing species and that it has the ability to saccharify different lignocellulosic materials. This study presents P. illinoisensis CX11 that can be good source for cellulase and xylanase enzymes which could be introduced into lignocellulose bioconversion processes to produce high valued chemicals.

Keywords: cellulase, high valued chemicals, lignocellulosic materials, Paenibacillus illinoisensis CX11, Xylanase

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Authors: Anwar Hussain, Muhammad Iqbal

Abstract:

The changes in the prices of the agriculture commodities combined with changes in population and agriculture productivity affect farmers’ profitability and standard of living. This study intends to estimate various domestic terms of trade for agriculture sector and also to assess the volatility in the standard of living and profitability of farmers. The terms of trade has been estimated for Pakistan and its provinces using producer prices indices, consumer price indices, input prices indices and quantity indices using the data for the period 1990-91 to 2008-09. The domestic terms of trade of agriculture sector has been improved in terms of both approaches i.e. the ratio of producer prices indices to consumer prices indices and the real per capita income approach. However, the cross province estimates indicated that the terms of trade also improved for Khyber Pakhtunkhwa, Sindh and Punjab while Balochistan’s domestic terms of trade deteriorated drastically. In other words the standard of living of the farmers in Pakistan and its provinces except Balochistan improved. Using the input prices, the domestic terms of trade deteriorated for Pakistan as a whole and its provinces as well. This also explores that as a whole the profitability of the farmers reduced during the study period. The farmers pay more prices for inputs as compared to they receive for their produce. This further indicates that the poverty at the gross root level has been increased. Further, summing, the standard of living of the farmers improved but their profitability reduced, which indicates that the farmers do not completely rely on the farm income but also utilize some other sources of income for their livelihood. The study supports to give subsidies on farm inputs so as to improve the profitability of the farmers.

Keywords: agricultural terms of trade, farmers’ profitability, farmers’ standard of living, consumer and producer price indices, quantity indices

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Authors: Ji-Seok Koo, Hee‑Yong Kwon, Hui-Young Yun, Kyung-Hui Wang, Youn-Seo Koo

Abstract:

This paper presents a forecasting system for PM2.5 levels in Seoul, South Korea, leveraging a combination of chemical transport modeling and ConvLSTM-DNN machine learning technology. Exposure to PM2.5 has known detrimental impacts on public health, making its prediction crucial for establishing preventive measures. Existing forecasting models, like the Community Multiscale Air Quality (CMAQ) and Weather Research and Forecasting (WRF), are hindered by their reliance on uncertain input data, such as anthropogenic emissions and meteorological patterns, as well as certain intrinsic model limitations. The system we've developed specifically addresses these issues by integrating machine learning and using carefully selected input features that account for local and distant sources of PM2.5. In South Korea, the PM2.5 concentration is greatly influenced by both local emissions and long-range transport from China, and our model effectively captures these spatial and temporal dynamics. Our PM2.5 prediction system combines the strengths of advanced hybrid machine learning algorithms, convLSTM and DNN, to improve upon the limitations of the traditional CMAQ model. Data used in the system include forecasted information from CMAQ and WRF models, along with actual PM2.5 concentration and weather variable data from monitoring stations in China and South Korea. The system was implemented specifically for Seoul's PM2.5 forecasting.

Keywords: PM2.5 forecast, machine learning, convLSTM, DNN

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