Search results for: uncertainty level

Authors: Paulo José Sigaúque, Paulo Rosman

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The Itajurú channel, located in the Eastern side of the Araruama lagoon, Rio de Janeiro state, is the one who makes the connection between Araruama lagoon and the sea. It is important to understand the hydrodynamic circulation of the location and effects of the sedimentological processes, and also estimate of the hydrodynamic and sedimentological processes in the future after the sea level change due to effects of climate change. This work presents results of a study about sediments dynamics in the Araruama lagoon focusing on the Itajurú channel region considering the present mean sea level and a foreseen sea level rise of 0.5 meters due to climate changes. The study was conducted with the aid of computer modeling for hydrodynamic and morphodynamic in SisBaHiA®. The results indicate that Araruama lagoon is composed by two hydrodynamics compartments; one is dominated by the action of the tide between the entrance of the channel and the strait of Perynas, and another one by the action of wind in narrow region between strait of Perynas and western extreme of the lagoon. With sea level rise, the magnitude of current velocities and flow rates is increased and consequently flow of sediment transport from upstream to downstream of Itajurú channel is increased and has more effect in the bridge Feliciano Sodré.

Keywords: hydrodinamic, superelevation, sea level, climate change

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Authors: I. V. Kuzminov

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The research is dedicated to the issue of Bosporus evolution and its key role in the Black Sea forming. Up till nowadays, there is no distinct picture of the historical and geographical events of the last 10 thousand years on the territory from Altai up to the Alps. The present article is an attempt to clarify and, moreover, link the presented version to the historical and climatic events of this period. The paper is a development of the basic idea stated in "Hypothesis on the Black Sea origin". The succession of events in dynamics is offered in this article. In the article, it is shown that fluctuation of the level of the World Ocean is a mirror of the basic events connected with the climate on the Earth on the one hand and hydraulic processes on the other hand. In the present article, it is come out with the assumption that at the formation of passage, there were some cycles of change in a level of the World ocean. The phase of the beginning of climate warming is characterized by an increase in the level of inland water bodies on the way of meltwater runoff and an increase in the World ocean level. The end of the warming phase is characterized by the continuation of a rise in the level of the World ocean and the drying up of inland water bodies deprived of meltwater replenishment.

Keywords: Bosporus, Ryan-Pitman hypothesis, fluctuations of the World Ocean level, the Paratethys Sea, catastrophic breakthrough

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Authors: Lethamaga Tladi, Ray Kekwaletswe

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This study sought to conceptualise a multi-level framework for the effective use of stock ordering system in small enterprises in a rural area context. The interpretive research methodology has been used to enable the researcher to analyse, in-depth, and the subjective meanings of small enterprises’ employees in using the stock ordering system. The empirical data was collected from 13 small enterprises’ employees as participants through semi-structured interviews and observations. Interpretive Phenomenological Analysis (IPA) approach was used to analyse the small enterprises’ employee’s own account of lived experiences in relations to stock ordering system use in terms of their relatedness to, and cognitive engagement with. A case study of Kgautswane, a rural area in Limpopo Province, South Africa, served as a social context where the phenomenon manifested. Technology-Organisation-Environment Theory (TOE), Technology-to-Performance Chain Model (TPC), and Representation Theory (RT) underpinned this study. In this multi-level study, the findings revealed that; At the organisational level, the effective use of stock ordering system was found to be associated with the organisational performance gains such as efficiency, productivity, quality, competitiveness, and market share. Equally so, at the individual level, the effective use of stock ordering system minimised the end-user’s efforts and time to accomplish their tasks, which yields improved individual performance. The Multi-level framework for effective use of stock ordering system was presented.

Keywords: effective use, multi-dimensions of use, multi-level of use, multi-level research, small enterprises, stock ordering system

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Authors: Adel El-Hadidy

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For any industry, the production and quality management or wastages reductions have major impingement on overall factory economy. This work discusses the quality improvement of garment industry by applying Pareto analysis, cause and effect diagram and Taguchi experimental design. The main purpose of the work is to reduce the stitching defects, which will also minimize the rejection and reworks rate. Application of Pareto chart, fish bone diagram and Process Sigma Level/and or Performance Level tools helps solving those problems on priority basis. Among all, only sewing, defects are responsible form 69.3% to 97.3 % of total defects. Process Sigma level has been improved from 0.79 to 1.3 and performance rate improved, from F to D level. The results showed that the new set of sewing parameters was superior to the original one. It can be seen that fabric size has the largest effect on the sewing defects and that needle size has the smallest effect on the stitching defects.

Keywords: garment, sewing defects, cost of rework, DMAIC, sigma level, cause and effect diagram, Pareto analysis

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Authors: K. Urukundu, K. A. Aravind, Pradeep M. Nirgude, K. Sandhya

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Transmission of bulk power over a long distance through HVDC transmission lines is gaining importance. This is because the transfer of bulk power through HVDC, from generating stations to load centers over long distances is more economical. However, these HVDC transmission lines create environmental and interference effects under the right of way of the line due to the ionization of the surrounding atmosphere in the vicinity of HVDC lines. The measurement of ground-level electric field and ionic current density is essential for the evaluation of human effects due to electromagnetic interference of the HVDC transmission line. In this paper, experimental laboratory results of the ground-level electric field under the miniature model of 800 kV monopole HVDC line of length 8 meters are presented in lateral configuration with different heights of the conductor from the ground plane. The results are compared with the simulated test results obtained through Finite Element based software.

Keywords: bundle, conductor, hexagonal, transmission line, ground-level electric field

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Authors: Omar Juhmani

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This paper examines the relation between internal corporate governance and the level of corporate compliance with mandatory IFRS disclosure requirements. The internal corporate governance is measured by board and audit committee characteristics. Using data from Bahrain Stock Exchange, the results show that board independence is positively and significantly associated with level of compliance with IFRS disclosure requirements. This suggests that internal corporate governance mechanisms are effective in the financial reporting practices by increasing the level of compliance with IFRS disclosures. Also, the results of the regression analyses indicate that two of the control variables; company size and audit firm size are significantly positively associated with the level of corporate compliance with mandatory IFRS disclosure requirements in Bahrain.

Keywords: Bahrain, board and audit committee characteristics, compliance, disclosure, IFRS

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Authors: Angelo I. Aquino, Luis Ma. T. Bo-ot

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We use the Homotopy Analysis Method (HAM) to solve the system of equations modeling the two-level system and extract results which will pinpoint to turbulent behavior. We look at multi-valued solutions as indicative of turbulence or turbulent-like behavior. We take dierent specic cases which result in multi-valued velocities. The solutions are in series form and application of HAM ensures convergence in some region.

Keywords: multivalued solutions, homotopy analysis method, two-level system, equation

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Authors: Niyongabo Elyse

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Prefabricated building construction is a pioneering approach that combines design, production, and assembly to attain energy efficiency, environmental sustainability, and economic feasibility. Despite continuous development in the industry in China, the low technical maturity of standardized design, factory production, and construction assembly introduces uncertainties affecting prefabricated component production and on-site assembly processes. This research focuses on enhancing project management performance under uncertainty to help enterprises navigate these challenges and optimize project resources. The study introduces a perspective on how uncertain factors influence the implementation of prefabricated building construction projects. It proposes a theoretical model considering project process management ability, adaptability to uncertain environments, and collaboration ability of project participants. The impact of uncertain factors is demonstrated through case studies and quantitative analysis, revealing constraints on implementation time, cost, quality, and safety. To address uncertainties in prefabricated component production scheduling, a fuzzy model is presented, expressing processing times in interval values. The model utilizes a cooperative co-evolution evolution algorithm (CCEA) to optimize scheduling, demonstrated through a real case study showcasing reduced project duration and minimized effects of processing time disturbances. Additionally, the research addresses on-site assembly construction scheduling, considering the relationship between task processing times and assigned resources. A multi-objective model with fuzzy activity durations is proposed, employing a hybrid cooperative co-evolution evolution algorithm (HCCEA) to optimize project scheduling. Results from real case studies indicate improved project performance in terms of duration, cost, and resilience to processing time delays and resource changes. The study also introduces a multistage dynamic process control model, utilizing IoT technology for real-time monitoring during component production and construction assembly. This approach dynamically adjusts schedules when constraints arise, leading to enhanced project management performance, as demonstrated in a real prefabricated housing project. Key contributions include a fuzzy prefabricated components production scheduling model, a multi-objective multi-mode resource-constrained construction project scheduling model with fuzzy activity durations, a multi-stage dynamic process control model, and a cooperative co-evolution evolution algorithm. The integrated mathematical model addresses the complexity of prefabricated building construction project management, providing a theoretical foundation for practical decision-making in the field.

Keywords: prefabricated construction, project management performance, uncertainty, fuzzy scheduling

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Authors: Razul Ikmal Ramli

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Successful implementation of innovation is a key success formula of a great organization. Innovation will ensure competitive advantages as well as sustainability of organization in the long run. In public sector context, the role of innovation is crucial to resolve dynamic challenges of public services such as operating in economic uncertainty with limited resources, increasing operating expenditure and growing expectation among citizens towards high quality, swift and reliable public services. Acknowledging the prospect of innovation as a tool for achieving high-performance public sector, the Malaysian New Economic Model launched in the year 2011 intensified government commitment to foster innovation in the public sector. Since 2011 various initiatives have been implemented, however little is known about the performance of public sector innovation in Malaysia. Hence, by applying the national innovation system theory as a pillar, the formulated research objectives were focused on measuring the level of innovation capabilities, wider public sector condition for innovation, innovation activity, and innovation performance as well as to examine the relationship between the four constructs with innovation performance as a dependent variable. For that purpose, 1,000 sets of self-administrated survey questionnaires were distributed to heads of units and divisions of 22 Federal Ministry and Central Agencies in the administrative, security, social and economic sector. Based on 456 returned questionnaires, the descriptive analysis found that innovation capabilities, wider sector condition, innovation activities and innovation performance were rated by respondents at moderately high level. Based on Structural Equation Modelling, innovation performance was found to be influenced by innovation capability, wider sector condition for innovation and innovation activity. In addition, the analysis also found innovation activity to be the most important construct that influences innovation performance. The implication of the study concluded that the innovation policy implemented in the public sector of Malaysia sparked motivation to innovate and resulted in various forms of innovation. However, the overall achievements were not as well as they were expected to be. Thus, the study suggested for the formulation of a dedicated policy to strengthen innovation capability, wider public sector condition for innovation and innovation activity of the Malaysian public sector. Furthermore, strategic intervention needs to be focused on innovation activity as the construct plays an important role in determining the innovation performance. The success of public sector innovation implementation will not only benefit the citizens, but will also spearhead the competitiveness and sustainability of the country.

Keywords: public sector, innovation, performance, innovation policy

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Authors: Petri Solanti, Russell Klein

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Many designers are asking for an automated path from an abstract mathematical MATLAB model to a high-quality Register-Transfer Level (RTL) hardware description. Manual transformations of MATLAB or intermediate code are needed, when the design abstraction is changed. Design conversion is problematic as it is multidimensional and it requires many different design steps to translate the mathematical representation of the desired functionality to an efficient hardware description with the same behavior and configurability. Yet, a manual model conversion is not an insurmountable task. Using currently available design tools and an appropriate design methodology, converting a MATLAB model to efficient hardware is a reasonable effort. This paper describes a simple and flexible design methodology that was developed together with several design teams.

Keywords: design methodology, high-level synthesis, MATLAB, verification

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Authors: Ali Abdrhman M. Ukasha

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Data security needed in data transmission, storage, and communication to ensure the security. The single step parallel contour extraction (SSPCE) method is used to create the edge map as a key image from the different Gray level/Binary image. Performing the X-OR operation between the key image and each bit plane of the original image for image pixel values change purpose. The Arnold transform used to changes the locations of image pixels as image scrambling process. Experiments have demonstrated that proposed algorithm can fully encrypt 2D Gary level image and completely reconstructed without any distortion. Also shown that the analyzed algorithm have extremely large security against some attacks like salt & pepper and JPEG compression. Its proof that the Gray level image can be protected with a higher security level. The presented method has easy hardware implementation and suitable for multimedia protection in real time applications such as wireless networks and mobile phone services.

Keywords: SSPCE method, image compression-salt- peppers attacks, bitplanes decomposition, Arnold transform, lossless image encryption

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Authors: Ju Peng Poh, Jun Yu Charles Lee, Jonathan Chew Hoe Khoo

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The emergence of digital twin technology, a digital replica of physical world, has improved the real-time access to data from sensors about the performance of buildings. This digital transformation has opened up many opportunities to improve the management of the building by using the data collected to help monitor consumption patterns and energy leakages. One example is the integration of predictive models for anomaly detection. In this paper, we use the GAM (Generalised Additive Model) for the anomaly detection of Air Handling Units (AHU) power consumption pattern. There is ample research work on the use of GAM for the prediction of power consumption at the office building and nation-wide level. However, there is limited illustration of its anomaly detection capabilities, prescriptive analytics case study, and its integration with the latest development of digital twin technology. In this paper, we applied the general GAM modelling framework on the historical data of the AHU power consumption and cooling load of the building between Jan 2018 to Aug 2019 from an education campus in Singapore to train prediction models that, in turn, yield predicted values and ranges. The historical data are seamlessly extracted from the digital twin for modelling purposes. We enhanced the utility of the GAM model by using it to power a real-time anomaly detection system based on the forward predicted ranges. The magnitude of deviation from the upper and lower bounds of the uncertainty intervals is used to inform and identify anomalous data points, all based on historical data, without explicit intervention from domain experts. Notwithstanding, the domain expert fits in through an optional feedback loop through which iterative data cleansing is performed. After an anomalously high or low level of power consumption detected, a set of rule-based conditions are evaluated in real-time to help determine the next course of action for the facilities manager. The performance of GAM is then compared with other approaches to evaluate its effectiveness. Lastly, we discuss the successfully deployment of this approach for the detection of anomalous power consumption pattern and illustrated with real-world use cases.

Keywords: anomaly detection, digital twin, generalised additive model, GAM, power consumption, supervised learning

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Authors: Kongrat Nokkaew

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This article assessed the surface erosion and stability of cut and fill slope in the excavation of the detention basin, Kalasin Province, Thailand. The large excavation project was built to enlarge detention basin for relieving repeated flooding and drought which usually happen in this area. However, at the end of the 1st rainstorm season, severely erosions slope failures were widespread observed. After investigation, the severity of erosions and slope failure were classified into five level from sheet erosion (Level 1), rill erosion (Level 2, 3), gully erosion (Level 4), and slope failure (Level 5) for proposing slope remediation. The preliminary investigation showed that lack of runoff control were the major factors of the surface erosions while insufficient compacted of the fill slope leaded to slopes failures. The slope stability of four selected slope failure was back calculated by using Simplified Bishop with Seep-W. The result show that factor of safety of slope located on non-plasticity sand was less than one, representing instability of the embankment slope. Such analysis agreed well with the failures observed in the field.

Keywords: surface erosion, slope stability, detention basin, cut and fill

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Authors: Ehsan Mehryaar, Seyed Armin Motahari Tabari

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Coarse-grained soils are known and commonly used in a wide range of geotechnical projects, including high earth dams or embankments for their high shear strength. The most important engineering property of these soils is friction angle which represents the interlocking between soil particles and can be applied widely in designing and constructing these earth structures. Friction angle and dilative behavior of coarse-grained soils can be estimated from empirical correlations with in-situ testing and physical properties of the soil or measured directly in the laboratory performing direct shear or triaxial tests. Unfortunately, large-scale testing is difficult, challenging, and expensive and is not possible in most soil mechanic laboratories. So, it is common to remove the large particles and do the tests, which cannot be counted as an exact estimation of the parameters and behavior of the original soil. This paper describes a new methodology to simulate particles grading distribution of a well-graded gravel sample to a smaller scale sample as it can be tested in an ordinary direct shear apparatus to estimate the stress-strain behavior, friction angle, and dilative behavior of the original coarse-grained soil considering its confining pressure, and relative density using a machine learning method. A total number of 72 direct shear tests are performed in 6 different sizes, 3 different confining pressures, and 4 different relative densities. Multivariate Adaptive Regression Spline (MARS) technique was used to develop an equation in order to predict shear strength and dilative behavior based on the size distribution of coarse-grained soil particles. Also, an uncertainty analysis was performed in order to examine the reliability of the proposed equation.

Keywords: MARS, coarse-grained soil, shear strength, uncertainty analysis

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Authors: Anna K. Wood, Terri Friedline

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In April and May 2020, the private banking industry approved over 1.7 million emergency small business loans, totaling over $650 billion in federal relief funds as part of the Paycheck Protection Program (PPP). Since the program’s rollout, the extensive evidence of discriminatory lending and misuse of funds has been revealed by investigative journalism and academic studies. This study is based on 41 interviews with frontline banking industry professionals conducted during the days and weeks of the PPP rollout, presenting a real-time narrative of the program rollout through the eyes of those in the role of a street-level bureaucrat. We present two themes from this data about the conditions under which these frontline workers experienced the PPP: Exigent Timelines and Defaulting to Existing Workplace Norms and Practices. We analyze these themes using literature on street-level organizations, bureaucratic discretion, and the differences between public and private sector logic. The results of this study present new directions for theorizing sector-level differences in street-level bureaucratic discretion in the context of mixed-sector collaboration on public service delivery, particularly under conditions of crisis and urgency.

Keywords: street level bureaucracy, social policy, bureaucratic discretion, public private partnerships

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Authors: Zhenyu Zhang, Hsi-Hsien Wei

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Highway network systems play a vital role in disaster response for disaster-damaged areas. Damaged bridges in such network systems can impede disaster response by disrupting transportation of rescue teams or humanitarian supplies. Therefore, emergency inspection and repair of bridges to quickly collect damage information of bridges and recover the functionality of highway networks is of paramount importance to disaster response. A widely used measure of a network’s capability to recover from disasters is resilience. To enhance highway network resilience, plenty of studies have developed various repair scheduling methods for the prioritization of bridge-repair tasks. These methods assume that repair activities are performed after the damage to a highway network is fully understood via inspection, although inspecting all bridges in a regional highway network may take days, leading to the significant delay in repairing bridges. In reality, emergency repair activities can be commenced as soon as the damage data of some bridges that are crucial to emergency response are obtained. Given that emergency bridge inspection and repair (EBIR) activities are executed simultaneously in the response phase, the real-time interactions between these activities can occur – the blockage of highways due to repair activities can affect inspection routes which in turn have an impact on emergency repair scheduling by providing real-time information on bridge damages. However, the impact of such interactions on the optimal emergency inspection routes (EIR) and emergency repair schedules (ERS) has not been discussed in prior studies. To overcome the aforementioned deficiencies, this study develops a routing and scheduling model for EBIR while accounting for real-time inspection-repair interactions to maximize highway network resilience. A stochastic, time-dependent integer program is proposed for the complex and real-time interacting EBIR problem given multiple inspection and repair teams at locations as set post-disaster. A hybrid genetic algorithm that integrates a heuristic approach into a traditional genetic algorithm to accelerate the evolution process is developed. Computational tests are performed using data from the 2008 Wenchuan earthquake, based on a regional highway network in Sichuan, China, consisting of 168 highway bridges on 36 highways connecting 25 cities/towns. The results show that the simultaneous implementation of bridge inspection and repair activities can significantly improve the highway network resilience. Moreover, the deployment of inspection and repair teams should match each other, and the network resilience will not be improved once the unilateral increase in inspection teams or repair teams exceeds a certain level. This study contributes to both knowledge and practice. First, the developed mathematical model makes it possible for capturing the impact of real-time inspection-repair interactions on inspection routing and repair scheduling and efficiently deriving optimal EIR and ERS on a large and complex highway network. Moreover, this study contributes to the organizational dimension of highway network resilience by providing optimal strategies for highway bridge management. With the decision support tool, disaster managers are able to identify the most critical bridges for disaster management and make decisions on proper inspection and repair strategies to improve highway network resilience.

Keywords: disaster management, emergency bridge inspection and repair, highway network, resilience, uncertainty

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Authors: Sayed Abdallah Mohamed Dahy

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Aswan High Dam Reservoir extends for 500 km along the Nile River; it is a vast reservoir in southern Egypt and northern Sudan. It was created as a result of the construction of the Aswan High Dam between 1958 and 1970; about 95% of the main water resources for Egypt are from it. The purpose of this study is to discuss and understand the effect of the fluctuation of the water level in the reservoir on natural and human-induced environmental like earthquakes in the Aswan area, Egypt. In summary, the correlation between the temporal variations of earthquake activity and water level changes in the Aswan reservoir from 1982 to 2014 are investigated and analyzed. This analysis confirms a weak relation between the fluctuation of the water level and earthquake activity in the area around Aswan reservoir. The result suggests that the seismicity in the area becomes active during a period when the water level is decreasing from the maximum to the minimum. Behavior of the water level in this reservoir characterized by a special manner that is the unloading season extends to July or August, and the loading season starts to reach its maximum in October or November every year. Finally, daily rate of change in the water level did not show any direct relation with the size of the earthquakes, hence, it is not possible to be used as a single tool for prediction.

Keywords: Aswan high dam reservoir, earthquake activity, environmental, Egypt

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Authors: Nopadol Burananat, Kedsara Tripaichayonsak

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This research aims to study the level of expectations and participation of personnel in implementing educational quality assurance of programs in Graduate School, Rajabhat Suan Sunandha University. The sample used in this study is 60 participants. The tool used for data collection is a questionnaire constructed by the researcher. The analysis is done by frequency, percentage, mean and standard deviation. It was found that the level of expectations personnel in Graduate School, Suan Sunandha Rajabhat University in implementing educational quality assurance is at high level. The category which received the most score is Action, followed by Check, Do and Plan, respectively. For the level of participation of personnel at program level of Graduate School, Suan Sunandha Rajabhat University in implementing educational quality assurance, the overall score is at high level. The category which received the most score is Action, followed by Do, Check and Plan, respectively.

Keywords: participation, implementation of educational quality assurance, educational quality assurance, expectations and participation

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Authors: Murat Yucel, Murat Yucel, Nail Ferhat Ozturk, Halim Haldun Goktas, Cemal Gemci, Fatih Vehbi Celebi

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In this study, Brillouin gain spectrum (BGS) is experimentally analyzed in the Brillouin optical time domain reflectometry (BOTDR) and Brillouin optical time domain analyzer (BOTDA). For this purpose, the signal level of the microwave generator is varied and the effects of BGS are investigated. In the setups, 20 km conventional single mode fiber is used to both setups and laser wavelengths are selected around 1550 nm. To achieve best results, it can be used between 5 dBm to 15 dBm signal level of microwave generator for BOTDA and BOTDR setups.

Keywords: microwave signal level, Brillouin gain spectrum, BOTDA, BOTDR

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Authors: Faisal Ali, Hasssan Saad Mohammed Hilmi, Mustafa Mohamed, Shamseddin Musa

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The Gash rivers an ephemeral river, it usually flows from July to September, it has a braided pattern with high sediment content, of 15200 ppm in suspension, and 360 kg/sec as bed load. The Gash river bed has an average slope of 1.3 m/Km. The objectives of this study were: assessing the Gash River bed level patterns; quantifying the annual variations in Gash bed level; and recommending a suitable method to reduce the sediment accumulation on the Gash River bed. The study covered temporally the period 1905-2013 using datasets included the Gash river flows, and the cross sections. The results showed that there is an increasing trend in the river bed of 5 cm3 per year. This is resulted in changing the behavior of the flood routing and consequently the flood hazard is tremendously increased in Kassala city.

Keywords: bed level, cross section, gash river, sedimentation

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Authors: Rodolfo Lorbieski, Silvia Modesto Nassar

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Many supervised machine learning tasks require decision making across numerous different classes. Multi-class classification has several applications, such as face recognition, text recognition and medical diagnostics. The objective of this article is to analyze an adapted method of Stacking in multi-class problems, which combines ensembles within the ensemble itself. For this purpose, a training similar to Stacking was used, but with three levels, where the final decision-maker (level 2) performs its training by combining outputs from the tree-based pair of meta-classifiers (level 1) from Bayesian families. These are in turn trained by pairs of base classifiers (level 0) of the same family. This strategy seeks to promote diversity among the ensembles forming the meta-classifier level 2. Three performance measures were used: (1) accuracy, (2) area under the ROC curve, and (3) time for three factors: (a) datasets, (b) experiments and (c) levels. To compare the factors, ANOVA three-way test was executed for each performance measure, considering 5 datasets by 25 experiments by 3 levels. A triple interaction between factors was observed only in time. The accuracy and area under the ROC curve presented similar results, showing a double interaction between level and experiment, as well as for the dataset factor. It was concluded that level 2 had an average performance above the other levels and that the proposed method is especially efficient for multi-class problems when compared to binary problems.

Keywords: stacking, multi-layers, ensemble, multi-class

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Authors: Ranjit Kumar Sahu, Ramakar Jha

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Urban Water Management is the practice of managing freshwater, waste water, and storm water as components of a basin-wide management plan. It builds on existing water supply and sanitation considerations within an urban settlement by incorporating urban water management within the scope of the entire river basin. The pervasive problems generated by urban development have prompted, in the present work, to study the spatial extent of urbanization in Golden Triangle of Odisha connecting the cities Bhubaneswar (20.2700° N, 85.8400° E), Puri (19.8106° N, 85.8314° E) and Konark (19.9000° N, 86.1200° E)., and patterns of periodic changes in urban development (systematic/random) in order to develop future plans for (i) urbanization promotion areas, and (ii) urbanization control areas. Remote Sensing, using USGS (U.S. Geological Survey) Landsat8 maps, supervised classification of the Urban Sprawl has been done for during 1980 - 2014, specifically after 2000. This Work presents the following: (i) Time series analysis of Hydrological data (ground water and rainfall), (ii) Application of SWMM (Storm Water Management Model) and other soft computing techniques for Urban Water Management, and (iii) Uncertainty analysis of model parameters (Urban Sprawl and correlation analysis). The outcome of the study shows drastic growth results in urbanization and depletion of ground water levels in the area that has been discussed briefly. Other relative outcomes like declining trend of rainfall and rise of sand mining in local vicinity has been also discussed. Research on this kind of work will (i) improve water supply and consumption efficiency (ii) Upgrade drinking water quality and waste water treatment (iii) Increase economic efficiency of services to sustain operations and investments for water, waste water, and storm water management, and (iv) engage communities to reflect their needs and knowledge for water management.

Keywords: Storm Water Management Model (SWMM), uncertainty analysis, urban sprawl, land use change

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Authors: Linyu Wang, Liguo Qiao, Jianhong Xiang, Hao Xu

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In semantic communication, the existing joint Source Channel coding (JSCC) wireless communication system without pilot has unstable transmission performance and can not effectively capture the global information and location information of images. In this paper, a pilot-free image transmission system of joint source channel based on multi-level semantic information (Multi-level JSCC) is proposed. The transmitter of the system is composed of two networks. The feature extraction network is used to extract the high-level semantic features of the image, compress the information transmitted by the image, and improve the bandwidth utilization. Feature retention network is used to preserve low-level semantic features and image details to improve communication quality. The receiver also is composed of two networks. The received high-level semantic features are fused with the low-level semantic features after feature enhancement network in the same dimension, and then the image dimension is restored through feature recovery network, and the image location information is effectively used for image reconstruction. This paper verifies that the proposed multi-level JSCC algorithm can effectively transmit and recover image information in both AWGN channel and Rayleigh fading channel, and the peak signal-to-noise ratio (PSNR) is improved by 1~2dB compared with other algorithms under the same simulation conditions.

Keywords: deep learning, JSCC, pilot-free picture transmission, multilevel semantic information, robustness

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Authors: Saira Iqbal

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Occupational Health and Safety issues nowadays have become an important esteem in the context of Industrial Production. This study is designed to measure the workplace hazards at Kohinoor Energy Limited. Mainly focused hazards were Heat Stress, Noise Level, Light Level and Ergonomics. Measurements for parameters like Wet, Dry, Globe, WBGTi and RH% were taken directly by visiting the Study Area. The temperature in Degrees was recoded at Control Room and Engine Hall. Highest Temperature was recoded in Engine Hall which was about 380C. Efforts were made to record emissions of Noise Levels from the main area of concern like Engines in Engine hall, parking area, and mechanical workshop. Permissible level for measuring Noise is 85 and its Unit of Measurement is dB (A). In Engine Hall Noise was very high which was about 109.6 dB (A) and that level was exceeding the limits. Illumination Level was also recorded at different areas of Power Plant. The light level was though under permissible limits but in some areas like Engine Hall and Boiler Room, level of light was very low especially in Engine Hall where the level was 29 lx. Practices were performed for measuring hazards in context of ergonomics like extended reaching, deviated body postures, mechanical stress, and vibration exposures of the worker at different units of plants by just observing workers during working hours. Since KEL is ISO 8000 and 14000 certified, the researcher found no serious problems in the parameter Ergonomics however it was a common scenario that workers were reluctant to apply PPEs.

Keywords: workplace hazards, heat hazard, noise hazard, illumination, ergonomics

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Authors: Alexander Guzman Urbina, Atsushi Aoyama

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The sustainability of traditional technologies employed in energy and chemical infrastructure brings a big challenge for our society. Making decisions related with safety of industrial infrastructure, the values of accidental risk are becoming relevant points for discussion. However, the challenge is the reliability of the models employed to get the risk data. Such models usually involve large number of variables and with large amounts of uncertainty. The most efficient techniques to overcome those problems are built using Artificial Intelligence (AI), and more specifically using hybrid systems such as Neuro-Fuzzy algorithms. Therefore, this paper aims to introduce a hybrid algorithm for risk assessment trained using near-miss accident data. As mentioned above the sustainability of traditional technologies related with energy and chemical infrastructure constitutes one of the major challenges that today’s societies and firms are facing. Besides that, the adaptation of those technologies to the effects of the climate change in sensible environments represents a critical concern for safety and risk management. Regarding this issue argue that social consequences of catastrophic risks are increasing rapidly, due mainly to the concentration of people and energy infrastructure in hazard-prone areas, aggravated by the lack of knowledge about the risks. Additional to the social consequences described above, and considering the industrial sector as critical infrastructure due to its large impact to the economy in case of a failure the relevance of industrial safety has become a critical issue for the current society. Then, regarding the safety concern, pipeline operators and regulators have been performing risk assessments in attempts to evaluate accurately probabilities of failure of the infrastructure, and consequences associated with those failures. However, estimating accidental risks in critical infrastructure involves a substantial effort and costs due to number of variables involved, complexity and lack of information. Therefore, this paper aims to introduce a well trained algorithm for risk assessment using deep learning, which could be capable to deal efficiently with the complexity and uncertainty. The advantage point of the deep learning using near-miss accidents data is that it could be employed in risk assessment as an efficient engineering tool to treat the uncertainty of the risk values in complex environments. The basic idea of using a Near-Miss Deep Learning Approach for Neuro-Fuzzy Risk Assessment in Pipelines is focused in the objective of improve the validity of the risk values learning from near-miss accidents and imitating the human expertise scoring risks and setting tolerance levels. In summary, the method of Deep Learning for Neuro-Fuzzy Risk Assessment involves a regression analysis called group method of data handling (GMDH), which consists in the determination of the optimal configuration of the risk assessment model and its parameters employing polynomial theory.

Keywords: deep learning, risk assessment, neuro fuzzy, pipelines

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Authors: Youjeong Hwang

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Purpose: Insulin-like growth factor-I (IGF-I) promotes B-cell development, immunoglobulin formation, and interleukin-6 (IL-6) production, then regulate the immune response and inflammation. As IGF-I and their receptor also exist in the periodontal tissue, they may affect the immune response caused by periodontal pathogens in aggressive periodontitis (AgP) patients. The function of IGF is regulated by IGF binding proteins (IGFBPs), and IGFBP-3 is known to most abundant in plasma. The aim of the present study was to assess the concentration of IGF-I and IGFBP-3 in plasma and gingival crevicular fluid (GCF) in AgP patients and to find out their association. Methods: Nine patients with AgP (test group) and nine healthy subjects (control group) were included in this study. None of the subjects had a history of systemic disease, smoking or steroids medication. GCF samples were collected by microcapillary pipettes and plasma samples were obtained by venipuncture. Probing pocket depth (PD), clinical attachment level (CAL) and bleeding on probing (BOP) were recorded. Samples were assayed for IGF-I and IGFBP-3 levels using ELISA. Results: Mean IGF-I level in GCF was higher in the test group than control. Mean IGF-I level in plasma and IGFBP-3 level in GCF and plasma in control group were higher than that of the test group. However, there was no statistical significance (p > 0.05). The mean level of IGF-I and IGFBP-3 in GCF was lower than those in plasma. Mean IGF-I level in plasma showed a negative correlation with PD and CAL (p < 0.05) in both groups. The levels of IGF-I and IGFBP-3 in GCF seemed to be negatively correlated with BOP in the test group (p < 0.05). Conclusions: The difference in the level of IGF-I and IGFBP-3 between AgP and healthy subjects was not significant. Further studies that explain the mechanism of the protective role of IGF-I with more samples are needed.

Keywords: aggressive periodontitis, pathogenesis, insulin-like growth factor, insulin-like growth factor binding protein

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Authors: Mubarack Ahmed, Gabriele Gradoni, Stephen C. Creagh, Gregor Tanner

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High-frequency cables commonly connect modern devices and sensors. Interestingly, the proportion of electric components is rising fast in an attempt to achieve lighter and greener devices. Modelling the propagation of signals through these cable networks in the presence of parameter uncertainty is a daunting task. In this work, we study the response of high-frequency cable networks using both Transmission Line and Quantum Graph (QG) theories. We have successfully compared the two theories in terms of reflection spectra using measurements on real, lossy cables. We have derived a generalisation of the vertex scattering matrix to include non-uniform networks – networks of cables with different characteristic impedances and propagation constants. The QG model implicitly takes into account the pseudo-chaotic behavior, at the vertices, of the propagating electric signal. We have successfully compared the asymptotic growth of eigenvalues of the Laplacian with the predictions of Weyl law. We investigate the nearest-neighbour level-spacing distribution of the resonances and compare our results with the predictions of Random Matrix Theory (RMT). To achieve this, we will compare our graphs with the generalisation of Wigner distribution for open systems. The problem of scattering from networks of cables can also provide an analogue model for wireless communication in highly reverberant environments. In this context, we provide a preliminary analysis of the statistics of communication capacity for communication across cable networks, whose eventual aim is to enable detailed laboratory testing of information transfer rates using software defined radio. We specialise this analysis in particular for the case of MIMO (Multiple-Input Multiple-Output) protocols. We have successfully validated our QG model with both TL model and laboratory measurements. The growth of Eigenvalues compares well with Weyl’s law and the level-spacing distribution agrees so well RMT predictions. The results we achieved in the MIMO application compares favourably with the prediction of a parallel on-going research (sponsored by NEMF21.)

Keywords: eigenvalues, multiple-input multiple-output, quantum graph, random matrix theory, transmission line

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Authors: Novita Verayanti Manalu, Alvin Salim

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Background: Palliative care is caring holistically for patients and families to improve their quality of life. Experts stated that palliative care could be applied not only for terminally ill cases but also for acute illnesses. Therefore, this study wants to find out the level of knowledge about palliative care of the nurses along with the relationship with attitude and performance. Method: This study applies a cross-sectional survey design and allows the respondents to fill two questionnaires to determine the level of knowledge and attitude toward palliative care, while one questionnaire is filled out by the head nurse to evaluate nurses’ performance. The relationship was analyzed by Spearman rho’s correlation in alpha < 0,05 by SPSS. Results: The majority of respondents were females, aged above 25 years old, and married. Most of the nurses are staff nurses and the ratio of education level is not significantly different. The knowledge level is poor, while the attitude and performance are at an adequate level. Knowledge may affect attitude, but it doesn’t happen toward performance. Conclusion: There is a need for increased knowledge about palliative care to improve attitude and work performance. Future researchers might use this finding as a reference to conduct further study in improving knowledge of palliative care.

Keywords: knowledge, attitude, work performance, palliative care

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Authors: Mazharuddin Syed Ahmed

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This research presents a framework used to develop The Ara Polytechnic College of Architecture Studies building “Kahukura” which is Green Building certified. This framework integrates the development of a smart building digital twin by utilizing Building Information Modelling (BIM) and its BIM maturity levels, including Levels of Development (LOD), eight dimensions of BIM, Heritage-BIM (H-BIM) and Facility Management BIM (FM BIM). The research also outlines a structured approach to building performance analysis and integration with the circular economy, encapsulated within a five-level digital twin framework. Starting with Level 1, the Descriptive Twin provides a live, editable visual replica of the built asset, allowing for specific data inclusion and extraction. Advancing to Level 2, the Informative Twin integrates operational and sensory data, enhancing data verification and system integration. At Level 3, the Predictive Twin utilizes operational data to generate insights and proactive management suggestions. Progressing to Level 4, the Comprehensive Twin simulates future scenarios, enabling robust “what-if” analyses. Finally, Level 5, the Autonomous Twin, represents the pinnacle of digital twin evolution, capable of learning and autonomously acting on behalf of users.

Keywords: building information modelling, circular economy integration, digital twin, predictive analytics

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Authors: Koninika Tanzim

Abstract:

The gaseous pollutants, SO2, NO2, CO and O3 affect the environment of Dhaka City. These pollutants are mainly released from stationary sources, like, fossil-fueled, power plants, industrial units and brickfields around the city. Suspended particulate matters including PM10 and PM2.5 are also contributing to air pollution in Dhaka City. SO2, NO2 and O3 are determined by using UV and visible spectrophotometry. The sensor type devised has been used for the determination of CO in ambient air. Lead in the suspended particulate matter was determined by using atomic absorption spectrometry. The samples were collected at ground level and on the roof of a seven-storied building. For all the criteria pollutants, the concentration at the roof was found to the lower than that at the ground level. The average concentration of PM10 and PM2.5 were found to the 241.5 and 81.1 mg/m3 at the ground level. On the roof of a 7 storied building was however 49.99 mg/m3 and 25.88 mg/m3 for PM10 and PM2.5 respectively. The concentration of Pb varied from 0.011 to 0.04 mg/m3 at the ground level. The values for Pb at the roof level were significantly lower. The values for SO2, NO2, CO and O3 were found to be higher than the USEPA values.

Keywords: gaseous air pollutant, PM, lead, gravimetry, spectrophotometry, atomic absorption, ambient air quality

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