Search results for: using an Anisotropic Analytical Algorithm (AAA)

Authors: Parul Goel, Jyeshtharaj B. Joshi, Arun K. Nayak

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Nucleate boiling is characterized by the nucleation, growth and departure of the tiny individual vapor bubbles that originate in the cavities or imperfections present in the heating surface. It finds a wide range of applications, e.g. in heat exchangers or steam generators, core cooling in power reactors or rockets, cooling of electronic circuits, owing to its highly efficient transfer of large amount of heat flux over small temperature differences. Hence, it is important to be able to predict the rate of heat transfer and the safety limit heat flux (critical heat flux, heat flux higher than this can lead to damage of the heating surface) applicable for any given system. A large number of experimental and analytical works exist in the literature, and are based on the idea that the knowledge of the bubble dynamics on the microscopic scale can lead to the understanding of the full picture of the boiling heat transfer. However, the existing data in the literature are scattered over various sets of conditions and often in disagreement with each other. The correlations obtained from such data are also limited to the range of conditions they were established for and no single correlation is applicable over a wide range of parameters. More recently, a number of researchers have been trying to remove empiricism in the heat transfer models to arrive at more phenomenological models using extensive numerical simulations; these models require state-of-the-art experimental data for a wide range of conditions, first for input and later, for their validation. With this idea in mind, experiments with sub-cooled and saturated demineralized water have been carried out under atmospheric pressure to study the bubble dynamics- growth rate, departure size and frequencies for nucleate pool boiling. A number of heating elements have been used to study the dependence of vapor bubble dynamics on the heater surface finish and heater geometry along with the experimental conditions like the degree of sub-cooling, super heat and the heat flux. An attempt has been made to compare the data obtained with the existing data and the correlations in the literature to generate an exhaustive database for the pool boiling conditions.

Keywords: experiment, boiling, bubbles, bubble dynamics, pool boiling

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Authors: Nyeng P. Gyang

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Even though past, current and future trends suggest that multicore and cloud computing systems are increasingly prevalent/ubiquitous, this class of parallel systems is nonetheless underutilized, in general, and barely used for research on employing parallel Delaunay triangulation for parallel surface modeling and generation, in particular. The performances, of actual/physical and virtual/cloud multicore systems/machines, at executing various algorithms, which implement various parallelization strategies of the incremental insertion technique of the Delaunay triangulation algorithm, were evaluated. T-tests were run on the data collected, in order to determine whether various performance metrics differences (including execution time, speedup and efficiency) were statistically significant. Results show that the actual machine is approximately twice faster than the virtual machine at executing the same programs for the various parallelization strategies. Results, which furnish the scalability behaviors of the various parallelization strategies, also show that some of the differences between the performances of these systems, during different runs of the algorithms on the systems, were statistically significant. A few pseudo superlinear speedup results, which were computed from the raw data collected, are not true superlinear speedup values. These pseudo superlinear speedup values, which arise as a result of one way of computing speedups, disappear and give way to asymmetric speedups, which are the accurate kind of speedups that occur in the experiments performed.

Keywords: cloud computing systems, multicore systems, parallel Delaunay triangulation, parallel surface modeling and generation

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Authors: Caroline M. Spagnol, Vera L. B. Isaac, Marcos A. Corrêa, Hérida R. N. Salgado

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Phenolic compounds are abundant in the Brazilian plant kingdom and they are part of a large and complex group of organic substances. Cinnamic acids are part of this group of organic compounds, and caffeic acid (CA) is one of its representatives. Antioxidants are compounds which act as free radical scavengers and, in other cases, such as metal chelators, both in the initiation stage and the propagation of oxidative process. The tyrosinase, polyphenol oxidase, is an enzyme that acts at various stages of melanin biosynthesis within the melanocytes and is considered a key molecule in this process. Some phenolic compounds exhibit inhibitory effects on melanogenesis by inhibiting the tyrosinase enzymatic activity and therefore has been the subject of studies. However, few studies have reported the effectiveness of these products and their safety. Objectives: To assess the inhibitory activity of tyrosinase, the antioxidant activity of CA and its cytotoxic potential. The method to evaluate the inhibitory activity of tyrosinase aims to assess the reduction transformation of L-dopa into dopaquinone reactions catalyzed by the enzyme. For evaluating the antioxidant activity was used the analytical methodology of DPPH radical inhibition. The cytotoxicity evaluation was carried out using the MTT method (3-(4,5-dimethyl-2-thiazolyl)-2,5-diphenyl-2H-tetrazolium bromide), a colorimetric assay which determines the amount of insoluble violet crystals formed by the reduction of MTT in the mitochondria of living cells. Based on the results obtained during the study, CA has low activity as a depigmenting agent. However, it is a more potent antioxidant than ascorbic acid (AA), since a lower amount of CA is sufficient to inhibit 50% of DPPH radical. The results are promising since CA concentration that promoted 50% toxicity in HepG2 cells (IC50=781.8 μg/mL) is approximately 330 to 400 times greater than the concentration required to inhibit 50% of DPPH (IC50 DPPH= 2.39 μg/mL) and ABTS (IC50 ABTS= 1.96 μg/mL) radicals scavenging activity, respectively. The maximum concentration of caffeic acid tested (1140 mg /mL) did not reach 50% of cell death in HaCat cells. Thus, it was concluded that the caffeic acid does not cause toxicity in HepG2 and HaCat cells in the concentrations required to promote antioxidant activity in vitro, and it can be applied in topical products.

Keywords: caffeic acid, antioxidant, cytotoxicity, cosmetic

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Authors: Jocelyn B. Barbosa, Angeli L. Magbaril, Mariel T. Sabanal, John Paul T. Galario, Mikka P. Baldovino

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The use of technology has become ubiquitous in different areas of business today. With the advent of digital imaging and database technology, business owners have been motivated to integrate technology to their business operation ranging from small, medium to large enterprises. Technology has been found to have brought many benefits that can make a business grow. Hog or swine raising, for example, is a very popular enterprise in the Philippines, whose challenges in production monitoring can be addressed through technology integration. Swine production monitoring can become a tedious task as the enterprise goes larger. Specifically, problems like delayed and inconsistent reports are most likely to happen if counting of swine per pen of which building is done manually. In this study, we present iCount, which aims to ensure efficient swine detection and counting that hastens the swine production monitoring task. We develop a system that automatically detects and counts swine based on Sobel filter and ellipse fitting model, given the still photos of the group of swine captured in a pen. We improve the Sobel filter detection result through 8-neigbhorhood rule implementation. Ellipse fitting technique is then employed for proper swine detection. Furthermore, the system can generate periodic production reports and can identify the specific consumables to be served to the swine according to schedules. Experiments reveal that our algorithm provides an efficient way for detecting swine, thereby providing a significant amount of accuracy in production monitoring.

Keywords: automatic swine counting, swine detection, swine production monitoring, ellipse fitting model, sobel filter

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Authors: Xiyang Li, Qi Yu, Lun Zhang

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In the face of natural disasters and other emergency situations, determining the optimal location of rescue centers is crucial for improving rescue efficiency and minimizing impact on affected populations. This paper proposes a method that integrates genetic algorithms (GA) and backpropagation neural networks (BPNN) to address the site selection optimization problem for emergency rescue centers. We utilize BPNN to accurately estimate the cost of delivering supplies from rescue centers to each temporary camp. Moreover, a genetic algorithm with a special partially matched crossover (PMX) strategy is employed to ensure that the number of temporary camps assigned to each rescue center adheres to predetermined limits. Using the population distribution data during the 2022 epidemic in Jiading District, Shanghai, as an experimental case, this paper verifies the effectiveness of the proposed method. The experimental results demonstrate that the BPNN-GA method proposed in this study outperforms existing algorithms in terms of computational efficiency and optimization performance. Especially considering the requirements for computational resources and response time in emergency situations, the proposed method shows its ability to achieve rapid convergence and optimal performance in the early and mid-stages. Future research could explore incorporating more real-world conditions and variables into the model to further improve its accuracy and applicability.

Keywords: emergency rescue centers, genetic algorithms, back-propagation neural networks, site selection optimization

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Authors: Mehran Barani Shikhrobat, Roger Flanagan

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The construction planning and scheduling based on using the current tools and techniques is resulted deterministic in nature (Gantt chart, CPM) or applying a very little probability of completion (PERT) for each task. However, every project embodies assumptions and influences and should start with a complete set of clearly defined goals and constraints that remain constant throughout the duration of the project. Construction planners continue to apply the traditional methods and tools of “hard” project management that were developed for “ideal projects,” neglecting the potential influence of complexity on the design and construction process. The aim of this research is to investigate the emergence and growth of complexity in project planning and to provide a model to consider the influence of complexity on the total project duration at the post-contract award pre-construction stage of a project. The literature review showed that complexity originates from different sources of environment, technical, and workflow interactions. They can be divided into two categories of complexity factors, first, project tasks, and second, project organisation management. Project tasks may originate from performance, lack of resources, or environmental changes for a specific task. Complexity factors that relate to organisation and management refer to workflow and interdependence of different parts. The literature review highlighted the ineffectiveness of traditional tools and techniques in planning for complexity. However, this research focus on understanding the fundamental causes of the complexity of construction projects were investigated through a questionnaire with industry experts. The results were used to develop a model that considers the core complexity factors and their interactions. System dynamics were used to investigate the model to consider the influence of complexity on project planning. Feedback from experts revealed 20 major complexity factors that impact project planning. The factors are divided into five categories known as core complexity factors. To understand the weight of each factor in comparison, the Analytical Hierarchy Process (AHP) analysis method is used. The comparison showed that externalities are ranked as the biggest influence across the complexity factors. The research underlines that there are many internal and external factors that impact project activities and the project overall. This research shows the importance of considering the influence of complexity on the project master plan undertaken at the post-contract award pre-construction phase of a project.

Keywords: project planning, project complexity measurement, planning uncertainty management, project risk management, strategic project scheduling

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Authors: Marvin Chibuzo Offiah, Susanne Rosenthal, Markus Borschbach

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Certain research projects in Computer Science often involve research on existing signal processing algorithms and developing improvements on them. Research budgets are usually limited, hence there is limited time for implementing the algorithms from scratch. It is therefore common practice, to use implementations provided by other researchers as a template. These are most commonly provided in a rapid development, i.e. 4th generation, programming language, usually Matlab. Rapid development is a common method in Computer Science research for quickly implementing and testing new developed algorithms, which is also a common task within agile project organization. The growing relevance of mobile devices in the computer market also gives rise to the need to demonstrate the successful executability and performance measurement of these algorithms on a mobile device operating system and processor, particularly on a smartphone. Open mobile systems such as Android, are most suitable for this task, which is to be performed most efficiently. Furthermore, efficiently implementing an interaction between the algorithm and a graphical user interface (GUI) that runs exclusively on the mobile device is necessary in cases where the project’s goal statement also includes such a task. This paper examines different proposed solutions for porting computer algorithms obtained through rapid development into a GUI-based smartphone Android app and evaluates their feasibilities. Accordingly, the feasible methods are tested and a short success report is given for each tested method.

Keywords: SMARTNAVI, Smartphone, App, Programming languages, Rapid Development, MATLAB, Octave, C/C++, Java, Android, NDK, SDK, Linux, Ubuntu, Emulation, GUI

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Authors: Alireza Rasekh, Peter Sergeant, Jan Vierendeels

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This paper copes with the numerical simulation for convective heat transfer in the stator disk of an axial flux permanent magnet (AFPM) electrical machine. Overheating is one of the main issues in the design of AFMPs, which mainly occurs in the stator disk, so that it needs to be prevented. A rotor-stator configuration with 16 magnets at the periphery of the rotor is considered. Air is allowed to flow through openings in the rotor disk and channels being formed between the magnets and in the gap region between the magnets and the stator surface. The rotating channels between the magnets act as a driving force for the air flow. The significant non-dimensional parameters are the rotational Reynolds number, the gap size ratio, the magnet thickness ratio, and the magnet angle ratio. The goal is to find correlations for the Nusselt number on the stator disk according to these non-dimensional numbers. Therefore, CFD simulations have been performed with the multiple reference frame (MRF) technique to model the rotary motion of the rotor and the flow around and inside the machine. A minimization method is introduced by a pattern-search algorithm to find the appropriate values of the reference temperature. It is found that the correlations are fast, robust and is capable of predicting the stator heat transfer with a good accuracy. The results reveal that the magnet angle ratio diminishes the stator heat transfer, whereas the rotational Reynolds number and the magnet thickness ratio improve the convective heat transfer. On the other hand, there a certain gap size ratio at which the stator heat transfer reaches a maximum.

Keywords: AFPM, CFD, magnet parameters, stator heat transfer

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Authors: Yu-ding Du, Qi-lian Bao, Nassim Bessaad, Lin Liu

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The Global Navigation Satellite System (GNSS) is regarded as an effective approach for the purpose of replacing the large amount used track-side balises in modern train localization systems. This paper describes a method based on the data fusion of a GNSS receiver sensor and an odometer sensor that can significantly improve the positioning accuracy. A digital track map is needed as another sensor to project two-dimensional GNSS position to one-dimensional along-track distance due to the fact that the train’s position can only be constrained on the track. A model trained by BP neural network is used to estimate the trend positioning error which is related to the specific location and proximate processing of the digital track map. Considering that in some conditions the satellite signal failure will lead to the increase of GNSS positioning error, a detection step for GNSS signal is applied. An adaptive weighted fusion algorithm is presented to reduce the standard deviation of train speed measurement. Finally an Extended Kalman Filter (EKF) is used for the fusion of the projected 1-D GNSS positioning data and the 1-D train speed data to get the estimate position. Experimental results suggest that the proposed method performs well, which can reduce positioning error notably.

Keywords: multi-sensor data fusion, train positioning, GNSS, odometer, digital track map, map matching, BP neural network, adaptive weighted fusion, Kalman filter

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Authors: Ashi Gautam, Isha Shukla, Akhil Seghal

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Biosensors are analytical devices that use a biological sensing element to detect and measure a specific chemical substance or biomolecule in a sample. These devices are widely used in various fields, including medical diagnostics, environmental monitoring, and food analysis, due to their high specificity, sensitivity, and selectivity. In this research paper, a machine learning model is proposed for predicting the suitability of skin care products based on biosensor readings. The proposed model takes in features extracted from biosensor readings, such as biomarker concentration, skin hydration level, inflammation presence, sensitivity, and free radicals, and outputs the most appropriate skin care product for an individual. This model is trained on a dataset of biosensor readings and corresponding skin care product information. The model's performance is evaluated using several metrics, including accuracy, precision, recall, and F1 score. The aim of this research is to develop a personalised skin care product recommendation system using biosensor data. By leveraging the power of machine learning, the proposed model can accurately predict the most suitable skin care product for an individual based on their biosensor readings. This is particularly useful in the skin care industry, where personalised recommendations can lead to better outcomes for consumers. The developed model is based on supervised learning, which means that it is trained on a labeled dataset of biosensor readings and corresponding skin care product information. The model uses these labeled data to learn patterns and relationships between the biosensor readings and skin care products. Once trained, the model can predict the most suitable skin care product for an individual based on their biosensor readings. The results of this study show that the proposed machine learning model can accurately predict the most appropriate skin care product for an individual based on their biosensor readings. The evaluation metrics used in this study demonstrate the effectiveness of the model in predicting skin care products. This model has significant potential for practical use in the skin care industry for personalised skin care product recommendations. The proposed machine learning model for predicting the suitability of skin care products based on biosensor readings is a promising development in the skin care industry. The model's ability to accurately predict the most appropriate skin care product for an individual based on their biosensor readings can lead to better outcomes for consumers. Further research can be done to improve the model's accuracy and effectiveness.

Keywords: biosensors, data model, machine learning, skin care

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Authors: Sheikh Shams Azam, Manoj Raju, Venkatesh Pagidimarri, Vamsi Kasivajjala

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Over the past decade, there has been a steep rise in the data-driven analysis in major areas of medicine, such as clinical decision support system, survival analysis, patient similarity analysis, image analytics etc. Most of the data in the field are well-structured and available in numerical or categorical formats which can be used for experiments directly. But on the opposite end of the spectrum, there exists a wide expanse of data that is intractable for direct analysis owing to its unstructured nature which can be found in the form of discharge summaries, clinical notes, procedural notes which are in human written narrative format and neither have any relational model nor any standard grammatical structure. An important step in the utilization of these texts for such studies is to transform and process the data to retrieve structured information from the haystack of irrelevant data using information retrieval and data mining techniques. To address this problem, the authors present Q-Map in this paper, which is a simple yet robust system that can sift through massive datasets with unregulated formats to retrieve structured information aggressively and efficiently. It is backed by an effective mining technique which is based on a string matching algorithm that is indexed on curated knowledge sources, that is both fast and configurable. The authors also briefly examine its comparative performance with MetaMap, one of the most reputed tools for medical concepts retrieval and present the advantages the former displays over the latter.

Keywords: information retrieval, unified medical language system, syntax based analysis, natural language processing, medical informatics

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Authors: Yuri Melis, Mattia Resteghini, Emanuela Apicella, Eugenia Dozio, Leonardo Mendolicchio

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Aim: This retrospective study was created to analyze the psychometric, anthropometric and body composition values in patients at the beginning and the discharge of their of hospitalization in the residential care clinic for eating and feeding disorders (EFD’s). Method: The sample was composed by (N=59) patients with mean age N= 33,50, divided in subgroups: Anorexia Nervosa (AN) (N=28), Bulimia Nervosa (BN) (N=13) and Binge Eating Disorders (BED) (N=14) recruited from a residential care clinic for eating and feeding disorders. The psychometrics level was measured with self-report questionnaires: Eating Disorders Inventory-3 (EDI-3) The Body Uneasiness Test (BUT), Minnesota Multiphasic Personality Inventory (MMPI – 2). The anthropometric and nutritional values was collected by Body Impedance Assessment (B.I.A), Body mass index (B.M.I.). Measurements were made at the beginning and at the end of hospitalization, with an average time of recovery of about 8,6 months. Results: The all data analysis showed a statistical significance (p-value >0,05 | power size N=0,950) in variation from T0 (start of recovery) to T1 (end of recovery) in the clinical scales of MMPI-2, AN group (Hypocondria T0 64,14 – T1 56,39) (Depression T0 72,93 – T1 59,50) (Hysteria T0 61,29 – T1 56,17) (Psychopathic deviation T0 64,00 – T1 60,82) (Paranoia T0 63,82 – T1 56,14) (Psychasthenia T0 63,82 – T1 57,86) (Schizophrenia T0 64,68 – T1 60,43) (Obsessive T0 60,36 – T1 55,68); BN group (Hypocondria T0 64,08 – T1 47,54) (Depression T0 67,46 – T1 52,46) (Hysteria T0 60,62 – T1 47,84) (Psychopathic deviation T0 65,69 – T1 58,92) (Paranoia T0 67,46 – T1 55,23) (Psychasthenia T0 60,77 – T1 53,77) (Schizophrenia T0 64,68 – T1 60,43) (Obsessive T0 62,92 – T1 54,08); B.E.D groups (Hypocondria T0 59,43 – T1 53,14) (Depression T0 66,71 – T1 54,57) (Hysteria T0 59,86 – T1 53,82) (Psychopathic deviation T0 67,39 – T1 59,03) (Paranoia T0 58,57 – T1 53,21) (Psychasthenia T0 61,43 – T1 53,00) (Schizophrenia T0 62,29 – T1 56,36) (Obsessive T0 58,57 – T1 48,64). EDI-3 report mean value is higher than clinical cut-off at T0, in T1, there is a significant reduction of the general mean of value. The same result is present in the B.U.T. test in the difference between T0 to T1. B.M.I mean value in AN group is (T0 14,83 – T1 18,41) BN group (T0 20 – T1 21,33) BED group (T0 42,32 – T1 34,97) Phase Angle results: AN group (T0 4,78 – T1 5,64) BN (T0 6 – T1 6,53) BED group (T0 6 – T1 6,72). Discussion and conclusion: The evident presence that on the whole sample, we have an altered serious psychiatric and clinic conditions at the beginning of recovery. The interesting conclusions that we can draw from this analysis are that a multidisciplinary approach that includes the entire care of the subject: from the pharmacological treatment, analytical psychotherapy, Psychomotricity, nutritional rehabilitation, and rehabilitative, educational activities. Thus, this Multidisciplinary treatment allows subjects in our sample to be able to restore psychopathological and metabolic values to below the clinical cut-off.

Keywords: feeding and eating disorders, anorexia nervosa, care clinic treatment, multidisciplinary treatment

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Authors: Dileep Kumar Gupta, Rajendra Prasad, Pradeep Kumar, Varun Narayan Mishra, Ajeet Kumar Vishwakarma, Prashant K. Srivastava

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An approach was evaluated for the retrieval of soil moisture of bare soil surface using bistatic scatterometer data in the angular range of 200 to 700 at VV- and HH- polarization. The microwave data was acquired by specially designed X-band (10 GHz) bistatic scatterometer. The linear regression analysis was done between scattering coefficients and soil moisture content to select the suitable incidence angle for retrieval of soil moisture content. The 250 incidence angle was found more suitable. The support vector regression analysis was used to approximate the function described by the input-output relationship between the scattering coefficient and corresponding measured values of the soil moisture content. The performance of support vector regression algorithm was evaluated by comparing the observed and the estimated soil moisture content by statistical performance indices %Bias, root mean squared error (RMSE) and Nash-Sutcliffe Efficiency (NSE). The values of %Bias, root mean squared error (RMSE) and Nash-Sutcliffe Efficiency (NSE) were found 2.9451, 1.0986, and 0.9214, respectively at HH-polarization. At VV- polarization, the values of %Bias, root mean squared error (RMSE) and Nash-Sutcliffe Efficiency (NSE) were found 3.6186, 0.9373, and 0.9428, respectively.

Keywords: bistatic scatterometer, soil moisture, support vector regression, RMSE, %Bias, NSE

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Authors: Arwa Alzughaibi

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Human Motion detection is a challenging task due to a number of factors including variable appearance, posture and a wide range of illumination conditions and background. So, the first need of such a model is a reliable feature set that can discriminate between a human and a non-human form with a fair amount of confidence even under difficult conditions. By having richer representations, the classification task becomes easier and improved results can be achieved. The Aim of this paper is to investigate the reliable and accurate human motion detection models that are able to detect the human motions accurately under varying illumination levels and backgrounds. Different sets of features are tried and tested including Histogram of Oriented Gradients (HOG), Deformable Parts Model (DPM), Local Decorrelated Channel Feature (LDCF) and Aggregate Channel Feature (ACF). However, we propose an efficient and reliable human motion detection approach by combining Histogram of oriented gradients (HOG) and local phase quantization (LPQ) as the feature set, and implementing search pruning algorithm based on optical flow to reduce the number of false positive. Experimental results show the effectiveness of combining local phase quantization descriptor and the histogram of gradient to perform perfectly well for a large range of illumination conditions and backgrounds than the state-of-the-art human detectors. Areaunder th ROC Curve (AUC) of the proposed method achieved 0.781 for UCF dataset and 0.826 for CDW dataset which indicates that it performs comparably better than HOG, DPM, LDCF and ACF methods.

Keywords: human motion detection, histograms of oriented gradient, local phase quantization, local phase quantization

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Authors: Misganaw Abebe Baye, Ji-Woo Park, Beom-Soo Kang

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The product quality of multi-point dieless forming (MDF) is identified to be dependent on the process parameters. Moreover, a certain variation of friction and material properties may have a substantially worse influence on the final product quality. This study proposed on how to compensate the MDF product defects by minimizing the sensitivity of noise parameter variations. This can be attained by reliability-based robust optimization (RRO) technique to obtain the optimal process setting of the controllable parameters. Initially two MDF Finite Element (FE) simulations of AA3003-H14 saddle shape showed a substantial amount of dimpling, wrinkling, and shape error. FE analyses are consequently applied on ABAQUS commercial software to obtain the correlation between the control process setting and noise variation with regard to the product defects. The best prediction models are chosen from the family of metamodels to swap the computational expensive FE simulation. Genetic algorithm (GA) is applied to determine the optimal process settings of the control parameters. Monte Carlo Analysis (MCA) is executed to determine how the noise parameter variation affects the final product quality. Finally, the RRO FE simulation and the experimental result show that the amendment of the control parameters in the final forming process leads to a considerably better-quality product.

Keywords: dimpling, multi-point dieless forming, reliability-based robust optimization, shape error, variation, wrinkling

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Authors: Oluremi I. Bamgbade, Oluwayomi Babatunde

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Governments and nonprofits have been in the support of sustainability as the goal of businesses especially in the construction industry because of its considerable impacts on the environment, economy, and society. However, to measure the degree to which an organisation is being sustainable or pursuing sustainable growth can be difficult as a result of the clear sustainability strategy required to assume their commitment to the goal and competitive advantage. This research investigated the influence of organisational culture and organisational structure in achieving sustainable construction among South African construction firms. A total of 132 consultants from the nine provinces in South Africa participated in the survey. The data collected were initially screened using SPSS (version 21) while Partial Least Squares Structural Equation Modeling (PLS-SEM) algorithm and bootstrap techniques were employed to test the hypothesised paths. The empirical evidence also supported the hypothesised direct effects of organisational culture and organisational structure on sustainable construction. Similarly, the result regarding the relationship between organisational culture and organisational structure was supported. Therefore, construction industry can record a considerable level of construction sustainability and establish suitable cultures and structures within the construction organisations. Drawing upon organisational control theory, these findings supported the view that these organisational internal factors have a strong contingent effect on sustainability adoption in construction project execution. The paper makes theoretical, practical and methodological contributions within the domain of sustainable construction especially in the context of South Africa. Some limitations of the study are indicated, suggesting opportunities for future research.

Keywords: organisational culture, organisational structure, South African construction firms, sustainable construction

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Authors: Bertha Korang Gyimah, Obed Asamoah, Kenross, T. Asamoah

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In every human community, crimes or offenses cannot be eliminated, but as crimes are expected, there should be bodies that will control and prevent the crimes. There has been an increasing rate of crime, such as armed robbery, kidnapping, murder, and other forms of violence in the country. Community participation in crime control cannot be left out in Ghana. Several works have been conducted to deal with the importance of community participation in policing, but the causes of communities not fully participating in community policing have been left out. The main aim of the research was to assess the impact of community policing and why the communities are reluctant to partake in community policing to help control crime in Bia West. There have been perceptions about Police that, they expose informant after they give the police tip-off which put the whistleblower life in danger. This has made the community not to get involved in security issues in the community they live in. This situation has posed a serious threat to the Ghana Police Service and its ability to position itself strategically in order to carry out a perfect investigation to bring the perpetrators into custody and to protect their lives and property, as well as the maintenance of law and order. Due to less data on community participation in the Ghana Police Service, the research adopted an interpretative framework to assess the meaning connoted to community policing from the perspectives of the stakeholders themselves. The qualitative research method was used. There was an engagement of the police and community where focus group discussions and individual in-depth interviews were organized in the randomly selected communities in the district. Key informant interviews were used to solicit views of the people why they are reluctant to give information to the police to help them take the perpetrators to book. In the data collected, it was observed that most of the people have been under threats of offenders after they come back from the prisons, it was also observed that some of the unprofessional police personnel’s expose the whistleblowers who put their lives in danger. The data obtained were analyzed using simple Analytical tool SPSS and Excel. Based on the analysis, it was observed that a high number of people in the communities contacted had not made their mind to participate in any security issues. Based on the views of the community, there should be a high level of professionalism in the recruitment system of the Ghana police service to come out with professional police officers who can abide by the rules and regulations governing the profession.

Keywords: community, bia west, Ghana, participation, police

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Authors: Edokpa Idemudia Waziri, Salisu S. Umar

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The Hotellng’s T^2 is a well-known statistic for detecting a shift in the mean vector of a multivariate normal distribution. Control charts based on T have been widely used in statistical process control for monitoring a multivariate process. Although it is a powerful tool, the T statistic is deficient when the shift to be detected in the mean vector of a multivariate process is small and consistent. The Multivariate Exponentially Weighted Moving Average (MEWMA) control chart is one of the control statistics used to overcome the drawback of the Hotellng’s T statistic. In this paper, the probability distribution of the Average Run Length (ARL) of the MEWMA control chart when the quality characteristics exhibit substantial cross correlation and when the process is in-control and out-of-control was derived using the Markov Chain algorithm. The derivation of the probability functions and the moments of the run length distribution were also obtained and they were consistent with some existing results for the in-control and out-of-control situation. By simulation process, the procedure identified a class of ARL for the MEWMA control when the process is in-control and out-of-control. From our study, it was observed that the MEWMA scheme is quite adequate for detecting a small shift and a good way to improve the quality of goods and services in a multivariate situation. It was also observed that as the in-control average run length ARL0¬ or the number of variables (p) increases, the optimum value of the ARL0pt increases asymptotically and as the magnitude of the shift σ increases, the optimal ARLopt decreases. Finally, we use the example from the literature to illustrate our method and demonstrate its efficiency.

Keywords: average run length, markov chain, multivariate exponentially weighted moving average, optimal smoothing parameter

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Authors: G. Shahzadi, A. Soulaimani

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This research work aims to identify the physical parameters of the constitutive soil model in the design of a rockfill dam by inverse analysis. The best parameters of the constitutive soil model, are those that minimize the objective function, defined as the difference between the measured and numerical results. The Finite Element code (Plaxis) has been utilized for numerical simulation. Polynomial and neural network-based response surfaces have been generated to analyze the relationship between soil parameters and displacements. The performance of surrogate models has been analyzed and compared by evaluating the root mean square error. A comparative study has been done based on objective functions and optimization techniques. Objective functions are categorized by considering measured data with and without uncertainty in instruments, defined by the least square method, which estimates the norm between the predicted displacements and the measured values. Hydro Quebec provided data sets for the measured values of the Romaine-2 dam. Stochastic optimization, an approach that can overcome local minima, and solve non-convex and non-differentiable problems with ease, is used to obtain an optimum value. Genetic Algorithm (GA), Particle Swarm Optimization (PSO) and Differential Evolution (DE) are compared for the minimization problem, although all these techniques take time to converge to an optimum value; however, PSO provided the better convergence and best soil parameters. Overall, parameter identification analysis could be effectively used for the rockfill dam application and has the potential to become a valuable tool for geotechnical engineers for assessing dam performance and dam safety.

Keywords: Rockfill dam, parameter identification, stochastic analysis, regression, PLAXIS

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Authors: Saeed Farivar, Mohsen Kahrom

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The purpose of this work is to develop a physical simulation model for the purpose of studying the effect of various design parameters on the performance of packaged-liquid chillers. This paper presents a steady-state model for predicting the performance of package-Liquid chiller over a wide range of operation condition. The model inputs are inlet conditions; geometry and output of model include system performance variable such as power consumption, coefficient of performance (COP) and states of refrigerant through the refrigeration cycle. A computer model that simulates the steady-state cyclic performance of a vapor compression chiller is developed for the purpose of performing detailed physical design analysis of actual industrial chillers. The model can be used for optimizing design and for detailed energy efficiency analysis of packaged liquid chillers. The simulation model takes into account presence of all chiller components such as compressor, shell-and-tube condenser and evaporator heat exchangers, thermostatic expansion valve and connection pipes and tubing’s by thermo-hydraulic modeling of heat transfer, fluids flow and thermodynamics processes in each one of the mentioned components. To verify the validity of the developed model, a 7.5 USRT packaged-liquid chiller is used and a laboratory test stand for bringing the chiller to its standard steady-state performance condition is build. Experimental results obtained from testing the chiller in various load and temperature conditions is shown to be in good agreement with those obtained from simulating the performance of the chiller using the computer prediction model. An entropy-minimization-based optimization analysis is performed based on the developed analytical performance model of the chiller. The variation of design parameters in construction of shell-and-tube condenser and evaporator heat exchangers are studied using the developed performance and optimization analysis and simulation model and a best-match condition between the physical design and construction of chiller heat exchangers and its compressor is found to exist. It is expected that manufacturers of chillers and research organizations interested in developing energy-efficient design and analysis of compression chillers can take advantage of the presented study and its results.

Keywords: optimization, packaged liquid chiller, performance, simulation

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Authors: V. Sai Geethika, Sai Snehitha Yadavalli, Swati Ghosh Acharyya

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This study involves a single element and simultaneous electrochemical detection of heavy metal ions through square wave anodic stripping voltammetry. A glassy carbon electrode was used to detect and quantify heavy metals such as As(III), Hg(II), Cr(VI) ions in water. Under optimized conditions, peak separation was obtained by varying concentrations, scan rates, and temperatures. As (III), Hg (II), Cr (III) were simultaneously detected with GCE. Several analytical methods, such as inductively coupled plasma mass spectroscopy (ICP-MS), atomic absorption spectroscopy (AAS), were used previously to detect heavy metal ions, which are authentic but are not good enough for online monitoring due to the bulkiness of the equipment. The study provides a good alternative that is simple, more efficient, and low-cost, involving a portable potentiostat. Heavy metals having different oxidation states can be detected by anodic stripping voltammetry. This method can be easily integrated with electronics. Square wave Anodic stripping voltammetry is used with a potential range of -2.5 V – 2.5 V for single ion detection by a three-electrode cell consisting of silver/silver chloride(Ag/AgCl) as reference and platinum (Pt) counter and glassy carbon (GCE) working electrodes. All three ions are optimized by varying the parameters like concentration, scan rate, pH, temperature, and all these optimized parameters were used for studying the effects of simultaneous detection. The procedure involves preparing an electrolyte using deionized water, cleaning the surface of GCE, depositing the ions by applying the redox potentials obtained from cyclic voltammetry (CV), and then detecting by applying oxidizing potential, i.e., stripping voltage. So this includes ASV techniques such as open-circuit voltage (OCV), chronoamperometry (CA), and square wave voltammetry (SWV). Firstly, the concentration of the ions varied from 50 ppb to 5000 ppb, and an optimum concentration was determined where the three ions were detected. A concentration of 400 ppb was used while varying the temperatures in the range of 25°C – 45°C. Optimum peak intensity was obtained at a temperature of 30°C with a low scan rate of 0.005 V-s⁻¹. All the parameters were optimized, and several effects have been noticed while three ions As(II), Cr(III), Hg(II) were detected alone and simultaneously.

Keywords: Arsenic(III), Chromium(III), glassy carbon electrode, Mercury (II), square wave anodic stripping voltammetry

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Authors: Iwan Cony Setiadi, Aulia M. T. Nasution

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The multispectral imaging (MSI) technique has been used for skin analysis, especially for distant mapping of in-vivo skin chromophores by analyzing spectral data at each reflected image pixel. For ergonomic purpose, our multispectral imaging system is decomposed in two parts: a light source compartment based on LED with 11 different wavelenghts and a monochromatic 8-Bit CCD camera with C-Mount Objective Lens. The software based on GUI MATLAB to control the system was also developed. Our system provides 11 monoband images and is coupled with a software reconstructing hyperspectral cubes from these multispectral images. In this paper, we proposed a new method to build a hyperspectral reflectance cube based on artificial neural network algorithm. After preliminary corrections, a neural network is trained using the 32 natural color from X-Rite Color Checker Passport. The learning procedure involves acquisition, by a spectrophotometer. This neural network is then used to retrieve a megapixel multispectral cube between 380 and 880 nm with a 5 nm resolution from a low-spectral-resolution multispectral acquisition. As hyperspectral cubes contain spectra for each pixel; comparison should be done between the theoretical values from the spectrophotometer and the reconstructed spectrum. To evaluate the performance of reconstruction, we used the Goodness of Fit Coefficient (GFC) and Root Mean Squared Error (RMSE). To validate reconstruction, the set of 8 colour patches reconstructed by our MSI system and the one recorded by the spectrophotometer were compared. The average GFC was 0.9990 (standard deviation = 0.0010) and the average RMSE is 0.2167 (standard deviation = 0.064).

Keywords: multispectral imaging, reflectance cube, spectral reconstruction, artificial neural network

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Authors: Lavanya Ratnabala, Robinroy Peter, E. Y. A. Charles

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This research paper addresses the challenges of exploration and navigation in unknown environments from an evolutionary swarm robotics perspective. Path formation plays a crucial role in enabling cooperative swarm robots to accomplish these tasks. The paper presents a method called the sub-goal-based path formation, which establishes a path between two different locations by exploiting visually connected sub-goals. Simulation experiments conducted in the Argos simulator demonstrate the successful formation of paths in the majority of trials. Furthermore, the paper tackles the problem of inter-collision (traffic) among a large number of robots engaged in path formation, which negatively impacts the performance of the sub-goal-based method. To mitigate this issue, a task allocation strategy is proposed, leveraging local communication protocols and light signal-based communication. The strategy evaluates the distance between points and determines the required number of robots for the path formation task, reducing unwanted exploration and traffic congestion. The performance of the sub-goal-based path formation and task allocation strategy is evaluated by comparing path length, time, and resource reduction against the A* algorithm. The simulation experiments demonstrate promising results, showcasing the scalability, robustness, and fault tolerance characteristics of the proposed approach.

Keywords: swarm, path formation, task allocation, Argos, exploration, navigation, sub-goal

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Authors: Khalid Hussein, Waleed Abdalati, Pakorn Petchprayoon, Khaula Alkaabi

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In this study, we integrated ASTER thermal data with an area-based spatial insolation model to identify and delineate geothermally active areas in Yellowstone National Park (YNP). Two pairs of L1B ASTER day- and nighttime scenes were used to calculate land surface temperature. We employed the Emissivity Normalization Algorithm which separates temperature from emissivity to calculate surface temperature. We calculated the incoming solar radiation for the area covered by each of the four ASTER scenes using an insolation model and used this information to compute temperature due to solar radiation. We then identified the statistical thermal anomalies using land surface temperature and the residuals calculated from modeled temperatures and ASTER-derived surface temperatures. Areas that had temperatures or temperature residuals greater than 2σ and between 1σ and 2σ were considered ASTER-modeled thermal anomalies. The areas identified as thermal anomalies were in strong agreement with the thermal areas obtained from the YNP GIS database. Also the YNP hot springs and geysers were located within areas identified as anomalous thermal areas. The consistency between our results and known geothermally active areas indicate that thermal remote sensing data, integrated with a spatial-based insolation model, provides an effective means for identifying and locating areas of geothermal activities over large areas and rough terrain.

Keywords: thermal remote sensing, insolation model, land surface temperature, geothermal anomalies

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Authors: Yudia Mailani Putri, Martalena Purba, B. J. Istiti Kandarina

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Background: Obesity has been recognized as a global health problem. Individuals classified as overweight and obese are increasing at an alarming rate. This condition is associated with psychological and physiological problems. as a person reaches adulthood, somatic growth ceases. At this stage, the human body has developed fully, to a stable state. As the capital of Riau Province in Indonesia, Pekanbaru is dominated by Malay ethnic population habitually consuming cholesterol-rich fatty foods as a daily menu, a trigger to the onset of obesity resulting in high prevalence of degenerative diseases. Research objectives: The aim of this study is elaborating the relationship between high-fat consumption pattern, stress level, physical activity and the incidence of obesity in adult women in Pekanbaru city. Research Methods: Among the combined research methods applied in this study, the first stage is quantitative observational, analytical cross-sectional research design with adult women aged 20-40 living in Pekanbaru city. The sample consists of 200 women with BMI≥25. Sample data is processed with univariate, bivariate (correlation and simple linear regression) and multivariate (multiple linear regression) analysis. The second phase is qualitative descriptive study purposive sampling by in-depth interviews. six participants withdrew from the study. Results: According to the results of the bivariate analysis, there are relationships between the incidence of obesity and the pattern of high fat foods consumption (energy intake (p≤0.000; r = 0.536), protein intake (p≤0.000; r=0.307), fat intake (p≤0.000; r=0.416), carbohydrate intake (p≤0.000; r=0.430), frequency of fatty food consumption (p≤0.000; r=0.506) and frequency of viscera foods consumption (p≤0.000; r=0.535). There is a relationship between physical activity and incidence of obesity (p≤0.000; r=-0.631). However, there is no relationship between the level of stress (p=0.741; r=0.019-) and the incidence of obesity. Physical activity is a predominant factor in the incidence of obesity in adult women in Pekanbaru city. Conclusion: There are relationships between high-fat food consumption pattern, physical activity and the incidence of obesity in Pekanbaru city whereas physical activity is a predominant factor in the occurrence of obesity, supported by the unchangeable pattern of high-fat foods consumption.

Keywords: obesity, adult, high in fat, stress, physical activity, consumption pattern

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Authors: Huijie Wang, Bin Zhang

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In China, the middle reaches of the Yangtze River are well-developed, boasting a wealth of different types of watershed landscape. In this regard, landscape character assessment (LCA) can serve as a basis for protection, management and planning of trans-regional watershed landscape types. For this study, we chose the middle reaches of the Yangtze River in Wuhan metropolitan area as our study site, wherein the water system consists of rich variety in landscape types. We analyzed trans-regional data to cluster and identify types of landscape characteristics at two levels. 55 basins were analyzed as variables with topography, land cover and river system features in order to identify the watershed landscape character types. For watershed landscape, drainage density and degree of curvature were specified as special variables to directly reflect the regional differences of river system features. Then, we used the principal component analysis (PCA) method and hierarchical clustering algorithm based on the geographic information system (GIS) and statistical products and services solution (SPSS) to obtain results for clusters of watershed landscape which were divided into 8 characteristic groups. These groups highlighted watershed landscape characteristics of different river systems as well as key landscape characteristics that can serve as a basis for targeted protection of watershed landscape characteristics, thus helping to rationally develop multi-value landscape resources and promote coordinated development of trans-regions.

Keywords: GIS, hierarchical clustering, landscape character, landscape typology, principal component analysis, watershed

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Authors: Ahmet Erten, Adil Mustafa, Ayşenur Eser, Özlem Yalçın

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We present a new viscometer based on a microfluidic chip with elastic high aspect ratio micropillar arrays. The displacement of pillar tips in flow direction can be used to analyze viscosity of liquid. In our work, Computational Fluid Dynamics (CFD) is used to analyze pillar displacement of various micropillar array configurations in flow direction at different viscosities. Following CFD optimization, micro-CNC based rapid prototyping is used to fabricate molds for microfluidic chips. Microfluidic chips are fabricated out of polydimethylsiloxane (PDMS) using soft lithography methods with molds machined out of aluminum. Tip displacements of micropillar array (300 µm in diameter and 1400 µm in height) in flow direction are recorded using a microscope mounted camera, and the displacements are analyzed using image processing with an algorithm written in MATLAB. Experiments are performed with water-glycerol solutions mixed at 4 different ratios to attain 1 cP, 5 cP, 10 cP and 15 cP viscosities at room temperature. The prepared solutions are injected into the microfluidic chips using a syringe pump at flow rates from 10-100 mL / hr and the displacement versus flow rate is plotted for different viscosities. A displacement of around 1.5 µm was observed for 15 cP solution at 60 mL / hr while only a 1 µm displacement was observed for 10 cP solution. The presented viscometer design optimization is still in progress for better sensitivity and accuracy. Our microfluidic viscometer platform has potential for tailor made microfluidic chips to enable real time observation and control of viscosity changes in biological or chemical reactions.

Keywords: Computational Fluid Dynamics (CFD), high aspect ratio, micropillar array, viscometer

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Authors: Rajesh Karki, Safal Bhattarai, Saket Adhikari

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Reliable and economic operation of power systems are becoming extremely challenging with large scale integration of renewable energy sources due to the intermittency and uncertainty associated with renewable power generation. It is, therefore, important to make a quantitative risk assessment and explore the potential resources to mitigate such risks. Probabilistic models for different energy storage systems (ESS), such as the flywheel energy storage system (FESS) and the compressed air energy storage (CAES) incorporating specific charge/discharge performance and failure characteristics suitable for probabilistic risk assessment in power system operation and planning are presented in this paper. The proposed methodology used in FESS modelling offers flexibility to accommodate different configurations of plant topology. It is perceived that CAES has a high potential for grid-scale application, and a hybrid approach is proposed, which embeds a Monte-Carlo simulation (MCS) method in an analytical technique to develop a suitable reliability model of the CAES. The proposed ESS models are applied to a test system to investigate the economic and reliability benefits of the energy storage technologies in system operation and planning, as well as to assess their contributions in facilitating wind integration during different operating scenarios. A comparative study considering various storage system topologies are also presented. The impacts of failure rates of the critical components of ESS on the expected state of charge (SOC) and the performance of the different types of ESS during operation are illustrated with selected studies on the test system. The paper also applies the proposed models on the test system to investigate the economic and reliability benefits of the different ESS technologies and to evaluate their contributions in facilitating wind integration during different operating scenarios and system configurations. The conclusions drawn from the study results provide valuable information to help policymakers, system planners, and operators in arriving at effective and efficient policies, investment decisions, and operating strategies for planning and operation of power systems with large penetrations of renewable energy sources.

Keywords: flywheel energy storage, compressed air energy storage, power system reliability, renewable energy, system planning, system operation

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Authors: Rafsan Al Mamun, Md. Motaharul Islam, Rabana Tajrin, Nabiha Noor, Shafinaz Qader

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In an attempt to enrich the lives of billions of people by providing proper information, security and a way of communicating with others, the need for efficient and improved satellites is constantly growing. Thus, there is an increasing demand for better error detection and correction (EDAC) schemes, which are capable of protecting the data onboard the satellites. The paper is aimed towards detecting and correcting such errors using a special algorithm called the Hamming Code, which uses the concept of parity and parity bits to prevent single-bit errors onboard a satellite in Low Earth Orbit. This paper focuses on the study of Low Earth Orbit satellites and the process of generating the Hamming Code matrix to be used for EDAC using computer programs. The most effective version of Hamming Code generated was the Hamming (16, 11, 4) version using MATLAB, and the paper compares this particular scheme with other EDAC mechanisms, including other versions of Hamming Codes and Cyclic Redundancy Check (CRC), and the limitations of this scheme. This particular version of the Hamming Code guarantees single-bit error corrections as well as double-bit error detections. Furthermore, this version of Hamming Code has proved to be fast with a checking time of 5.669 nanoseconds, that has a relatively higher code rate and lower bit overhead compared to the other versions and can detect a greater percentage of errors per length of code than other EDAC schemes with similar capabilities. In conclusion, with the proper implementation of the system, it is quite possible to ensure a relatively uncorrupted satellite storage system.

Keywords: bit-flips, Hamming code, low earth orbit, parity bits, satellite, single error upset

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Authors: Pawel Albrycht, Monika Ksiezopolska-Gocalska, Robert Holyst

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Surface Enhanced Raman Spectroscopy (SERS) is a technique of growing importance not only in purely scientific research related to analytical chemistry. It finds more and more applications in broadly understood testing - medical, forensic, pharmaceutical, food - and everywhere works perfectly, on one condition that SERS substrates used for testing give adequate enhancement, repeatability, and homogeneity of SERS signal. This is a problem that has existed since the invention of this technique. Some laboratories use as SERS amplifiers colloids with silver or gold nanoparticles, others form rough silver or gold surfaces, but results are generally either weak or unrepeatable. Furthermore, these structures are very often highly specific - they amplify the signal only of a small group of compounds. It means that they work with some kinds of analytes but only with those which were used at a developer’s laboratory. When it comes to research on different compounds, completely new SERS 'substrates' are required. That underlay our decision to develop universal substrates for the SERS spectroscopy. Generally, each compound has different affinity for both silver and gold, which have the best SERS properties, and that's what depends on what signal we get in the SERS spectrum. Our task was to create the platform that gives a characteristic 'fingerprint' of the largest number of compounds with very high repeatability - even at the expense of the intensity of the enhancement factor (EF) (possibility to repeat research results is of the uttermost importance). As specified above SERS substrates are offered by SERSitive company. Applied method is based on cyclic potentiodynamic electrodeposition of silver or silver-gold nanoparticles on the conductive surface of ITO-coated glass at controlled temperature of the reaction solution. Silver nanoparticles are supplied in the form of silver nitrate (AgNO₃, 10 mM), gold nanoparticles are derived from tetrachloroauric acid (10 mM) while sodium sulfite (Na₂O₃, 5 mM) is used as a reductor. To limit and standardize the size of the SERS surface on which nanoparticles are deposited, photolithography is used. We secure the desired ITO-coated glass surface, and then etch the unprotected ITO layer which prevents nanoparticles from settling at these sites. On the prepared surface, we carry out the process described above, obtaining SERS surface with nanoparticles of sizes 50-400 nm. The SERSitive platforms present highly sensitivity (EF = 10⁵-10⁶), homogeneity and repeatability (70-80%).

Keywords: electrodeposition, nanoparticles, Raman spectroscopy, SERS, SERSitive, SERS platforms, SERS substrates

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