Search results for: Consumers Decision Making

Authors: S. K. Fasogbon, T. M. Oladosu, O. S. Osasuyi

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Plastic extrusion has been an important process of plastic production since 19^th century. Meanwhile, in plastic extrusion process, wide variation in temperature along the extrudate usually leads to scraps formation on the side of finished products. To avoid this situation, there is a need to deeply understand temperature distribution along the extrudate in plastic extrusion process. This work developed an analytical model that predicts the temperature distribution over the billet (the polymers melt) along the extrudate during extrusion process with the limitation that the polymer in question does not cover biopolymer such as DNA. The model was solved and simulated. Results for two different plastic materials (polyvinylchloride and polycarbonate) using self-developed MATLAB code and a commercially developed software (ANSYS) were generated and ultimately compared. It was observed that there is a thermodynamic heat transfer from the entry level of the billet into the die down to the end of it. The graph plots indicate a natural exponential decay of temperature with time and along the die length, with the temperature being 413 K and 474 K for polyvinylchloride and polycarbonate respectively at the entry level and 299.3 K and 328.8 K at the exit when the temperature of the surrounding was 298 K. The extrusion model was validated by comparison of MATLAB code simulation with a commercially available ANSYS simulation and the results favourably agree. This work concludes that the developed mathematical model and the self-generated MATLAB code are reliable tools in predicting temperature distribution along the extrudate in plastic extrusion process.

Keywords: ANSYS, extrusion process, MATLAB, plastic making, thermal analysis.

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Authors: N. Ravi Kumar, R. Kamalakannan

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The advancement of hybrid energy resources such as solar and wind power leading to the emergence of customer owned grid. It provides an opportunity to regulars to obtain low energy costs as well as enabling the power supplier to regulate the utility grid. There is a need to develop smart systems that will automatically submit energy demand schedule and monitors energy price signals in real-time without the prompt of customers. In this paper, a demand side energy management for a grid connected household and also smart preparation of electrical appliance have been presented. It also reduces electricity bill for the consumers in the grid. In addition to this, when production is high, the surplus energy fashioned in the customer owned grid is given to main grid or neighboring micro grids. The simulation of the entire system is presented using LabVIEW software.

Keywords: Distributed renewable energy resource, power storage devices, scheduling, smart meters, smart micro grid, electric vehicle.

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Authors: Susana Matos, António Pinto, Conceição Castilho, Paula Reis Correia, António Cardoso Monteiro

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Yogurts are prepared by fermenting milk with bacterial cultures consisting of a mixture of Streptococcus ssp. thermophilus and Lactobacillus delbrueckii ssp. bulgaricus. The main aim of this investigation was to develop a majority goat yogurt, with the addition of sheep milk in order to have a final product with good physicochemical quality properties and sensorial attributes. Four types of yogurts were prepared presenting the following proportion of goat and sheep milk respectively: C100 – 100%; C80 – 80%/20%; C60 – 60%/40%; C50 – 50%/50%. The goat milk was from the Serrana Jarmelista breed and the sheep milk from the Serra da Estrela breed. The inclusion of sheep milk improved attractiveness to consumers, and it also improved the nutritional value of the product, mainly the fatty acid and mineral contents. The C50 yogurt was preferred by 28% of the panellists, followed by the C100 with 16%  and the commercial cow yogurt was 40% of preferences.

Keywords: Goat, sheep, yogurt.

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Authors: Bernard Kumi-Boateng, Issaka Yakubu

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Forest fire, which is, an uncontrolled fire occurring in nature has become a major concern for the Forestry Commission of Ghana (FCG). The forest fires in Ghana usually result in massive destruction and take a long time for the firefighting crews to gain control over the situation. In order to assess the effect of forest fire at local scale, it is important to consider the role fire plays in vegetation composition, biodiversity, soil erosion, and the hydrological cycle. The occurrence, frequency and behaviour of forest fires vary over time and space, primarily as a result of the complicated influences of changes in land use, vegetation composition, fire suppression efforts, and other indigenous factors. One of the forest zones in Ghana with a high level of vegetation stress is the Goaso forest area. The area has experienced changes in its traditional land use such as hunting, charcoal production, inefficient logging practices and rural abandonment patterns. These factors which were identified as major causes of forest fire, have recently modified the incidence of fire in the Goaso area. In spite of the incidence of forest fires in the Goaso forest area, most of the forest services do not provide a cartographic representation of the burned areas. This has resulted in significant amount of information being required by the firefighting unit of the FCG to understand fire risk factors and its spatial effects. This study uses Remote Sensing and Geographic Information System techniques to develop a fire risk hazard model using the Goaso Forest Area (GFA) as a case study. From the results of the study, natural forest, agricultural lands and plantation cover types were identified as the major fuel contributing loads. However, water bodies, roads and settlements were identified as minor fuel contributing loads. Based on the major and minor fuel contributing loads, a forest fire risk hazard model with a reasonable accuracy has been developed for the GFA to assist decision making.

Keywords: Forest risk, GIS, remote sensing, Goaso.

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Authors: Xiaocong Liu, Huazhen Wang, Ting He, Xiaozheng Li, Weihan Zhang, Jian Chen

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The utilization of electronic medical record (EMR) data to establish the disease diagnosis model has become an important research content of biomedical informatics. Deep learning can automatically extract features from the massive data, which brings about breakthroughs in the study of EMR data. The challenge is that deep learning lacks semantic knowledge, which leads to impracticability in medical science. This research proposes a method of incorporating lexical-semantic knowledge from abundant entities into a convolutional neural network (CNN) framework for pediatric disease diagnosis. Firstly, medical terms are vectorized into Lexical Semantic Vectors (LSV), which are concatenated with the embedded word vectors of word2vec to enrich the feature representation. Secondly, the semantic distribution of medical terms serves as Semantic Decision Guide (SDG) for the optimization of deep learning models. The study evaluates the performance of LSV-SDG-CNN model on four kinds of Chinese EMR datasets. Additionally, CNN, LSV-CNN, and SDG-CNN are designed as baseline models for comparison. The experimental results show that LSV-SDG-CNN model outperforms baseline models on four kinds of Chinese EMR datasets. The best configuration of the model yielded an F1 score of 86.20%. The results clearly demonstrate that CNN has been effectively guided and optimized by lexical-semantic knowledge, and LSV-SDG-CNN model improves the disease classification accuracy with a clear margin.

Keywords: lexical semantics, feature representation, semantic decision, convolutional neural network, electronic medical record

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Authors: Ana Pauna

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The Expert Witness Testimony in the Battered Woman Syndrome Expert witness testimony (EWT) is a kind of information given by an expert specialized in the field (here in BWS) to the jury in order to help the court better understand the case. EWT does not always work in favor of the battered women. Two main decision-making models are discussed in the paper: the Mathematical model and the Explanation model. In the first model, the jurors calculate ″the importance and strength of each piece of evidence″ whereas in the second model they try to integrate the EWT with the evidence and create a coherent story that would describe the crime. The jury often misunderstands and misjudges battered women for their action (or in this case inaction). They assume that these women are masochists and accept being mistreated for if a man abuses a woman constantly, she should and could divorce him or simply leave at any time. The research in the domain found that indeed, expert witness testimony has a powerful influence on juror’s decisions thus its quality needs to be further explored. One of the important factors that need further studies is a bias called the dispositionist worldview (a belief that what happens to people is of their own doing). This kind of attributional bias represents a tendency to think that a person’s behavior is due to his or her disposition, even when the behavior is clearly attributed to the situation. Hypothesis The hypothesis of this paper is that if a juror has a dispositionist worldview then he or she will blame the rape victim for triggering the assault. The juror would therefore commit the fundamental attribution error and believe that the victim’s disposition caused the rape and not the situation she was in. Methods The subjects in the study were 500 randomly sampled undergraduate students from McGill, Concordia, Université de Montréal and UQAM. Dispositional Worldview was scored on the Dispositionist Worldview Questionnaire. After reading the Rape Scenarios, each student was asked to play the role of a juror and answer a questionnaire consisting of 7 questions about the responsibility, causality and fault of the victim. Results The results confirm the hypothesis which states that if a juror has a dispositionist worldview then he or she will blame the rape victim for triggering the assault. By doing so, the juror commits the fundamental attribution error because he will believe that the victim’s disposition, and not the constraints or opportunities of the situation, caused the rape scenario.

Keywords: bias, expert/witness testimony, attribution error, jury, rape myth

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Authors: Ali E. Abbas

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Industrial Engineering is a broad multidisciplinary field with intersections and applications in numerous areas. When designing a product, it is important to determine the appropriate attributes of value and the preference function for which the product is optimized. This paper provides some guidelines on appropriate selection of attributes for preference and value functions for engineering design.

Keywords: Decision analysis, engineering design, direct vs. indirect values.

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Authors: Dhinu Johnson, Gurdip Singh

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Sensor network applications are often data centric and involve collecting data from a set of sensor nodes to be delivered to various consumers. Typically, nodes in a sensor network are resource-constrained, and hence the algorithms operating in these networks must be efficient. There may be several algorithms available implementing the same service, and efficient considerations may require a sensor application to choose the best suited algorithm. In this paper, we present a systematic evaluation of a set of algorithms implementing the data gathering service. We propose a modular infrastructure for implementing such algorithms in TOSSIM with separate configurable modules for various tasks such as interest propagation, data propagation, aggregation, and path maintenance. By appropriately configuring these modules, we propose a number of data gathering algorithms, each of which incorporates a different set of heuristics for optimizing performance. We have performed comprehensive experiments to evaluate the effectiveness of these heuristics, and we present results from our experimentation efforts.

Keywords: Data Centric Protocols, Shortest Paths, Sensor networks, Message passing systems.

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Authors: Eshagh Rasouli Sarabi, Mir Saeed Moosavi

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In Iran, due to abundance of energy resources, energy consumption is extraordinarily higher than international standards and transportation sector is considered to be one of the major consumers of energy. Moreover, air pollution in urban areas as a result of high dependence on private vehicle and lower standards of vehicles, high subsidies spent on fuel and time waste due to traffic congestion in urban areas all have led to speculations on new strategies and policies in order to control energy consumption in transportation sector. These strategies and policies will be introduced in this paper and their consequences will be analyzed with consideration to socio-economic factors affecting the urban society of Iran. Besides, the intention is to suggest and analyze new approaches such as broader application of public transportation system, demand management in transport sector, replacement of deteriorated vehicles, quality improvement in car manufacture and introduction of substitute fuels.

Keywords: Consumption, energy, fuel, transportation.

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Authors: Safak Isik, Ozalp Vayvay

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Strategic partnerships with suppliers play a vital role for the long-term value-based supply chain. This strategic collaboration keeps still being one of the top priority of many business organizations in order to create more additional value; benefiting mainly from supplier’s specialization, capacity and innovative power, securing supply and better managing costs and quality. However, many organizations encounter difficulties in initiating, developing and managing those partnerships and many attempts result in failures. One of the reasons for such failure is the incompatibility of members of this partnership or in other words wrong supplier selection which emphasize the significance of the selection process since it is the beginning stage. An effective selection process of strategic suppliers is critical to the success of the partnership. Although there are several research studies to select the suppliers in literature, only a few of them is related to strategic supplier selection for long-term partnership. The purpose of this study is to propose a conceptual model for the selection of strategic partnership suppliers. A two-stage approach has been used in proposed model incorporating first segmentation and second selection. In the first stage; considering the fact that not all suppliers are strategically equal and instead of a long list of potential suppliers, Kraljic’s purchasing portfolio matrix can be used for segmentation. This supplier segmentation is the process of categorizing suppliers based on a defined set of criteria in order to identify types of suppliers and determine potential suppliers for strategic partnership. In the second stage, from a pool of potential suppliers defined at first phase, a comprehensive evaluation and selection can be performed to finally define strategic suppliers considering various tangible and intangible criteria. Since a long-term relationship with strategic suppliers is anticipated, criteria should consider both current and future status of the supplier. Based on an extensive literature review; strategical, operational and organizational criteria have been determined and elaborated. The result of the selection can also be used to determine suppliers who are not ready for a partnership but to be developed for strategic partnership. Since the model is based on multiple criteria for both stages, it provides a framework for further utilization of Multi-Criteria Decision Making (MCDM) techniques. The model may also be applied to a wide range of industries and involve managerial features in business organizations.

Keywords: Kraljic’s matrix, purchasing portfolio, strategic supplier selection, supplier collaboration, supplier partnership, supplier segmentation.

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Authors: Edward A. Osifodunrin, Jose Manuel Dias Lopes

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In Nigeria, enormous efforts/resources had, over the years, been expended on promoting financial inclusion (FI); however, it is seemingly discouraging that many of its self-declared targets on FI remained unachieved, especially amongst the Rural Dwellers and Actors in the Informal Sectors (RDAIS). Expectedly, many reasons had been earmarked for these failures: low literacy level, huge informal/rural sectors etc. This study posits that in spite of these truly-debilitating factors, these FI policy failures could have been avoided or mitigated if the principles of active and better-managed citizens’ participation had been strictly followed in the (re)design/implementation of its FI policies. In other words, in a bid to mitigate the prevalent financial exclusion (FE) in Nigeria, this study hypothesizes the significant positive impact of involving the RDAIS in policy-wide decision making in the FI domain, backed by a preliminary empirical validation. Also, the study introduces the RDAIS-focused Participatory Financial Inclusion Policy (PFIP) as a major FI policy regeneration/improvement tool. The three categories of respondents that served as research subjects are FI experts in Nigeria (n = 72), RDAIS from the very rural/remote village of Unguwar Dogo in Northern Nigeria (n = 43) and RDAIS from another rural village of Sekere (n = 56) in the Southern region of Nigeria. Using survey design (5-point Likert scale questionnaires), random/stratified sampling, and descriptive/inferential statistics, the study often recorded independent consensus (amongst these three categories of respondents) that RDAIS’s active participation in iterative FI policy initiation, (re)design, implementation, (re)evaluation could indeed give improved FI outcomes. However, few questionnaire items also recorded divergent opinions and various statistically (in)significant differences on the mean scores of these three categories. The PFIP (or any customized version of it) should then be carefully integrated into the NFIS of Nigeria (and possibly in the NFIS of other developing countries) to truly/fully provide FI policy integration for these excluded RDAIS and arrest the prevalence of FE.

Keywords: Citizens’ participation, development, financial inclusion, formal financial services, national financial inclusion strategy, participatory financial inclusion policy, rural dwellers and actors in the informal sectors.

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Authors: Mohd Fikri Azli bin Abdullah, Khairul Anwar bin Kamarul Hatta, Esther Jeganathan

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WiFi has become an essential technology that is widely used nowadays. It is famous due to its convenience to be used with mobile devices. This is especially true for Internet users worldwide that use WiFi connections. There are many location based services that are available nowadays which uses Wireless Fidelity (WiFi) signal fingerprinting. A common example that is gaining popularity in this era would be Foursquare. In this work, the WiFi signal would be used to estimate the user or client’s location. Similar to GPS, fingerprinting method needs a floor plan to increase the accuracy of location estimation. Still, the factor of inconsistent WiFi signal makes the estimation defer at different time intervals. Given so, an adaptive method is needed to obtain the most accurate signal at all times. WiFi signals are heavily distorted by external factors such as physical objects, radio frequency interference, electrical interference, and environmental factors to name a few. Due to these factors, this work uses a method of reducing the signal noise and estimation using the Nearest Neighbour based on past activities of the signal to increase the signal accuracy up to more than 80%. The repository yet increases the accuracy by using Artificial Neural Network (ANN) pattern matching. The repository acts as the server cum support of the client side application decision. Numerous previous works has adapted the methods of collecting signal strengths in the repository over the years, but mostly were just static. In this work, proposed solutions on how the adaptive method is done to match the signal received to the data in the repository are highlighted. With the said approach, location estimation can be done more accurately. Adaptive update allows the latest location fingerprint to be stored in the repository. Furthermore, any redundant location fingerprints are removed and only the updated version of the fingerprint is stored in the repository. How the location estimation of the user can be predicted would be highlighted more in the proposed solution section. After some studies on previous works, it is found that the Artificial Neural Network is the most feasible method to deploy in updating the repository and making it adaptive. The Artificial Neural Network functions are to do the pattern matching of the WiFi signal to the existing data available in the repository.

Keywords: Adaptive Repository, Artificial Neural Network, Location Estimation, Nearest Neighbour Euclidean Distance, WiFi RSSI Fingerprinting.

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Authors: Tithdanin Chav, Phichhang Ou

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The study is about the e-banking consumer behavior of five major banks in Cambodia. This work aims to examine the relationships among job relevance, trust, mobility, perceived ease of use, perceived usefulness, attitude toward using, and intention to use of internet banking and apps. Also, the research develops and tests a conceptual model of intention to use internet banking by integrating the Technology Acceptance Model (TAM) and job relevance, trust, and mobility which were supported by Theory of Reasoned Action (TRA) and Theory of Planned Behavior (TPB). The proposed model was tested using Structural Equation Modeling (SEM), which was processed by using SPSS and AMOS with a sample size of 250 e-banking users. The results showed that there is a significant positive relationship among variables and attitudes toward using internet banking, and apps are the most factor influencing consumers’ intention to use internet banking and apps with the importance level in SEM 0.82 accounted by 82%. Significantly, all six hypotheses were accepted.

Keywords: Bank Apps, consumer intention, internet banking, technology acceptance model.

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Authors: Marijana Pantić, Saša Milijić

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In Serbia as a continental country, the tourism industry relies on city-break, spa and mountain tourism, where ski resorts have primacy during the winter season. Even though the number of tourists has recently increased, the share of domestic tourists remained predominant. It is also noticed that tourists from Serbia eagerly travel abroad, which was so far researched in the context of summer holidays but not in the framework of ski resorts. Therefore, this paper examines the competitiveness of ski resorts in Serbia from the perspective of domestic tourists. A survey was used as a data collection method, covering various competitiveness dimensions. The aim is to recognize the main motives of consumers when choosing a ski resort in Serbia or abroad. The results showed that the choices of Serbian tourists are predominantly shaped by the cost of an offer – of accommodation above all others. They are attentive by estimating the value for money, which is the most common reason to choose a ski resort abroad over a domestic one. The crowd at ski resorts and ski runs appears to be a result of unbalanced accommodation capacities on the one hand and ski infrastructure on the other, which is currently the most notable competitiveness drawback of ski resorts in Serbia.

Keywords: Mountain tourism, Serbia, ski resorts, tourism competitiveness.

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Authors: G. Rezai, Z. Mohamed, M. N. Shamsudin, M. Z. Zahran

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The availability of broadband internet and increased access to computers has been instrumental in the rise of internet literacy in Malaysia. This development has led to the adoption of online shopping by many Malaysians. On another note, the Government has supported the development and production of local herbal products. This has resulted in an increase in the production and diversity of products by SMEs. The purpose of this study is to evaluate the influence of the Malaysian demographic factors and selected attitudinal characteristics in relation to the online purchasing of herbal products. In total, 1054 internet users were interviewed online and Chi-square analysis was used to determine the relationship between demographic variables and different aspects of online shopping for herbal products. The overall results show that the demographic variables such as age, gender, education level, income and ethnicity were significant when considering the online shopping antecedents of trust, quality of herbal products, perceived risks and perceived benefits.

Keywords: Demographic factors, herbal products, Malaysian consumers, online shopping, Chi-square analysis

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Authors: Alanoud Moraya Aldalan, Abdulaziz Almaleh

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A crucial part of maintaining a customer-oriented business in the telecommunications industry is understanding the reasons and factors that lead to customer churn. Competition between telecom companies has greatly increased in recent years, which has made it more important to understand customers’ needs in this strong market. For those who are looking to turn over their service providers, understanding their needs is especially important. Predictive churn is now a mandatory requirement for retaining customers in the telecommunications industry. Machine learning can be used to accomplish this. Churn Prediction has become a very important topic in terms of machine learning classification in the telecommunications industry. Understanding the factors of customer churn and how they behave is very important to building an effective churn prediction model. This paper aims to predict churn and identify factors of customers’ churn based on their past service usage history. Aiming at this objective, the study makes use of feature selection, normalization, and feature engineering. Then, this study compared the performance of four different machine learning algorithms on the Orange dataset: Logistic Regression, Random Forest, Decision Tree, and Gradient Boosting. Evaluation of the performance was conducted by using the F1 score and ROC-AUC. Comparing the results of this study with existing models has proven to produce better results. The results showed the Gradients Boosting with feature selection technique outperformed in this study by achieving a 99% F1-score and 99% AUC, and all other experiments achieved good results as well.

Keywords: Machine Learning, Gradient Boosting, Logistic Regression, Churn, Random Forest, Decision Tree, ROC, AUC, F1-score.

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Authors: Bernardo Cedano, Ahmed H. Eltom, Bob Hay, Jim Glass, Raga Ahmed

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The deployment of smart grid devices such as smart meters and smart switches (SS) supported by a reliable and fast communications system makes automated distribution possible, and thus, provides great benefits to electric power consumers and providers alike. However, more research is needed before the full utility of smart switch data is realized. This paper presents new automated switching techniques using SS within the electric power grid. A concise background of the SS is provided, and operational examples are shown. Organization and presentation of data obtained from SS are shown in the context of the future goal of total automation of the distribution network. The description of application techniques, the examples of success with SS, and the vision outlined in this paper serve to motivate future research pertinent to disturbance analysis automation.

Keywords: Disturbance automation, electric power grid, smart grid, smart switch.

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Authors: R. B. Ibrahim, M. S. Argungu, I. M. Mungadi

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It is obvious in this present time, internet has become an indispensable part of human life since its inception. The Internet has provided diverse opportunities to make life so easy for human beings, through the adoption of various channels. Among these channels are email, internet banking, video conferencing, and the like. Email is one of the easiest means of communication hugely accepted among individuals and organizations globally. But over decades the security integrity of this platform has been challenged with malicious activities like Phishing. Email phishing is designed by phishers to fool the recipient into handing over sensitive personal information such as passwords, credit card numbers, account credentials, social security numbers, etc. This activity has caused a lot of financial damage to email users globally which has resulted in bankruptcy, sudden death of victims, and other health-related sicknesses. Although many methods have been proposed to detect email phishing, in this research, the results of multiple machine-learning methods for predicting email phishing have been compared with the use of filter-wrapper feature selection. It is worth noting that all three models performed substantially but one outperformed the other. The dataset used for these models is obtained from Kaggle online data repository, while three classifiers: decision tree, Naïve Bayes, and Logistic regression are ensemble (Bagging) respectively. Results from the study show that the Decision Tree (CART) bagging ensemble recorded the highest accuracy of 98.13% using PEF (Phishing Essential Features). This result further demonstrates the dependability of the proposed model.

Keywords: Ensemble, hybrid, filter-wrapper, phishing.

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Authors: Choon Ling Sia, Yani Shi, Jiaqi Yan, Huaping Chen

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With the development of the Internet, E-commerce is growing at an exponential rate, and lots of online stores are built up to sell their goods online. A major factor influencing the successful adoption of E-commerce is consumer-s trust. For new or unknown Internet business, consumers- lack of trust has been cited as a major barrier to its proliferation. As web sites provide key interface for consumer use of E-Commerce, we investigate the design of web site to build trust in E-Commerce from a design science approach. A conceptual model is proposed in this paper to describe the ontology of online transaction and human-computer interaction. Based on this conceptual model, we provide a personalized webpage design approach using Bayesian networks learning method. Experimental evaluation are designed to show the effectiveness of web personalization in improving consumer-s trust in new or unknown online store.

Keywords: Trust, Web site design, Human-ComputerInteraction, E-Commerce, Design science, Bayesian network.

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Authors: P. G. Siddheshwar, R. K. Vanishree, C. Kanchana

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A local nonlinear stability analysis using a eight-mode expansion is performed in arriving at the coupled amplitude equations for Rayleigh-Bénard-Brinkman convection (RBBC) in the presence of LTNE effects. Streamlines and isotherms are obtained in the two-dimensional unsteady finite-amplitude convection regime. The parameters’ influence on heat transport is found to be more pronounced at small time than at long times. Results of the Rayleigh-Bénard convection is obtained as a particular case of the present study. Additional modes are shown not to significantly influence the heat transport thus leading us to infer that five minimal modes are sufficient to make a study of RBBC. The present problem that uses rolls as a pattern of manifestation of instability is a needed first step in the direction of making a very general non-local study of two-dimensional unsteady convection. The results may be useful in determining the preferred range of parameters’ values while making rheometric measurements in fluids to ascertain fluid properties such as viscosity. The results of LTE are obtained as a limiting case of the results of LTNE obtained in the paper.

Keywords: Rayleigh-Bénard convection, heat transport, porous media, generalized Lorenz model, coupled Ginzburg-Landau model.

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Authors: R.M. Kainkwa

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The African Great Lakes Region refers to the zone around lakes Victoria, Tanganyika, Albert, Edward, Kivu, and Malawi. The main source of electricity in this region is hydropower whose systems are generally characterized by relatively weak, isolated power schemes, poor maintenance and technical deficiencies with limited electricity infrastructures. Most of the hydro sources are rain fed, and as such there is normally a deficiency of water during the dry seasons and extended droughts. In such calamities fossil fuels sources, in particular petroleum products and natural gas, are normally used to rescue the situation but apart from them being nonrenewable, they also release huge amount of green house gases to our environment which in turn accelerates the global warming that has at present reached an amazing stage. Wind power is ample, renewable, widely distributed, clean, and free energy source that does not consume or pollute water. Wind generated electricity is one of the most practical and commercially viable option for grid quality and utility scale electricity production. However, the main shortcoming associated with electric wind power generation is fluctuation in its output both in space and time. Before making a decision to establish a wind park at a site, the wind speed features there should therefore be known thoroughly as well as local demand or transmission capacity. The main objective of this paper is to utilise monthly average wind speed data collected from one prospective site within the African Great Lakes Region to demonstrate that the available wind power there is high enough to generate electricity. The mean monthly values were calculated from records gathered on hourly basis for a period of 5 years (2001 to 2005) from a site in Tanzania. The documentations that were collected at a height of 2 m were projected to a height of 50 m which is the standard hub height of wind turbines. The overall monthly average wind speed was found to be 12.11 m/s whereas June to November was established to be the windy season as the wind speed during the session is above the overall monthly wind speed. The available wind power density corresponding to the overall mean monthly wind speed was evaluated to be 1072 W/m2, a potential that is worthwhile harvesting for the purpose of electric generation.

Keywords: Hydro power, windy season, available wind powerdensity.

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Authors: Ali E. Abbas

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This paper highlights some of the normative issues that might result by setting independent thresholds in risk analyses and particularly with safety regions. A second objective is to explain how such regions can be specified appropriately in a meaningful way. We start with a review of the importance of setting deterministic trade-offs among target requirements. We then show how to determine safety regions for risk analysis appropriately using utility functions.

Keywords: Decision analysis, thresholds, risk, reliability.

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Authors: Charmaine du Plessis

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Arguments on a popular microblogging site were analysed by means of a methodological approach to business rhetoric focusing on the logos communication technique. The focus of the analysis was the 100 day countdown to the 2011 Rugby World Cup as advanced by the organisers. Big sporting events provide an attractive medium for sport event marketers in that they have become important strategic communication tools directed at sport consumers. Sport event marketing is understood in the sense of using a microblogging site as a communication tool whose purpose it is to disseminate a company-s marketing messages by involving the target audience in experiential activities. Sport creates a universal language in that it excites and increases the spread of information by word of mouth and other means. The findings highlight the limitations of a microblogging site in terms of marketing messages which can assist in better practices. This study can also serve as a heuristic tool for other researchers analysing sports marketing messages in social network environments.

Keywords: communication technique, microblogging, rhetoric, social networking, sport event marketing

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Authors: Emily Kislik, Gabriel Mantilla Saltos, Gladys Torres, Mercy Borbor-Córdova

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The Galápagos Marine Reserve (GMR) is an internationally-recognized region of consistent upwelling events, high productivity, and rich biodiversity. Despite its high-nutrient, low-chlorophyll condition, the archipelago has experienced phytoplankton blooms, especially in the western section between Isabela and Fernandina Islands. However, little is known about how climate variability will affect future phytoplankton standing stock in the Galápagos, and no consistent protocols currently exist to quantify phytoplankton biomass, identify species, or monitor for potential harmful algal blooms (HABs) within the archipelago. This analysis investigates physical, chemical, and biological oceanic variables that contribute to algal blooms within the GMR, using 4 km Aqua MODIS satellite imagery and 0.125-degree wind stress data from January 2003 to December 2016. Furthermore, this study analyzes chlorophyll-a concentrations at varying spatial scales— within the greater archipelago, as well as within five smaller bioregions based on species biodiversity in the GMR. Seasonal and interannual trend analyses, correlations, and hotspot identification were performed. Results demonstrate that chlorophyll-a is expressed in two seasons throughout the year in the GMR, most frequently in September and March, with a notable hotspot in the Elizabeth Bay bioregion. Interannual chlorophyll-a trend analyses revealed highest peaks in 2003, 2007, 2013, and 2016, and variables that correlate highly with chlorophyll-a include surface temperature and particulate organic carbon. This study recommends future in situ sampling locations for phytoplankton monitoring, including the Elizabeth Bay bioregion. Conclusions from this study contribute to the knowledge of oceanic drivers that catalyze primary productivity and consequently affect species biodiversity within the GMR. Additionally, this research can inform policy and decision-making strategies for species conservation and management within bioregions of the Galápagos.

Keywords: Bioregions, ecological monitoring, phytoplankton, remote sensing.

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Authors: Aspasia Koutsokosta, Stefanos Katsavounis

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This paper reviews the model-based qualitative and quantitative Operations Management research in the context of Construction Supply Chain Management (CSCM). Construction industry has been traditionally blamed for low productivity, cost and time overruns, waste, high fragmentation and adversarial relationships. The construction industry has been slower than other industries to employ the Supply Chain Management (SCM) concept and develop models that support the decision-making and planning. However the last decade there is a distinct shift from a project-based to a supply-based approach of construction management. CSCM comes up as a new promising management tool of construction operations and improves the performance of construction projects in terms of cost, time and quality. Modeling the Construction Supply Chain (CSC) offers the means to reap the benefits of SCM, make informed decisions and gain competitive advantage. Different modeling approaches and methodologies have been applied in the multi-disciplinary and heterogeneous research field of CSCM. The literature review reveals that a considerable percentage of the CSC modeling research accommodates conceptual or process models which present general management frameworks and do not relate to acknowledged soft Operations Research methods. We particularly focus on the model-based quantitative research and categorize the CSCM models depending on their scope, objectives, modeling approach, solution methods and software used. Although over the last few years there has been clearly an increase of research papers on quantitative CSC models, we identify that the relevant literature is very fragmented with limited applications of simulation, mathematical programming and simulation-based optimization. Most applications are project-specific or study only parts of the supply system. Thus, some complex interdependencies within construction are neglected and the implementation of the integrated supply chain management is hindered. We conclude this paper by giving future research directions and emphasizing the need to develop optimization models for integrated CSCM. We stress that CSC modeling needs a multi-dimensional, system-wide and long-term perspective. Finally, prior applications of SCM to other industries have to be taken into account in order to model CSCs, but not without translating the generic concepts to the context of construction industry.

Keywords: Construction supply chain management, modeling, operations research, optimization and simulation.

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Authors: Brennan Lodge

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

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

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Authors: John Hadden, Ashutosh Tiwari, Rajkumar Roy, Dymitr Ruta

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The aim of this paper is to identify the most suitable model for churn prediction based on three different techniques. The paper identifies the variables that affect churn in reverence of customer complaints data and provides a comparative analysis of neural networks, regression trees and regression in their capabilities of predicting customer churn.

Keywords: Churn, Decision Trees, Neural Networks, Regression.

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Authors: Yi-Chun Kuo, Jo-Chieh Lin

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The objective of a supply chain strategy is to reduce waste and increase efficiency to attain cost benefits, and to guarantee supply chain flexibility when facing the ever-changing market environment in order to meet customer requirements. Strategy implementation aims to fulfill common goals and attain benefits by integrating upstream and downstream enterprises, sharing information, conducting common planning, and taking part in decision making, so as to enhance the overall performance of the supply chain. With the rise of outsourcing and globalization, the increasing dependence on suppliers and customers and the rapid development of information technology, the complexity and uncertainty of the supply chain have intensified, and supply chain vulnerability has surged, resulting in adverse effects on supply chain performance. Thus, this study aims to use supply chain vulnerability as a moderating variable and apply structural equation modeling (SEM) to determine the relationships among supply chain strategy, supply chain integration, and supply chain performance, as well as the moderating effect of supply chain vulnerability on supply chain performance. The data investigation of this study was questionnaires which were collected from the management level of enterprises in Taiwan and China, 149 questionnaires were received. The result of confirmatory factor analysis shows that the path coefficients of supply chain strategy on supply chain integration and supply chain performance are positive (0.497, t= 4.914; 0.748, t= 5.919), having a significantly positive effect. Supply chain integration is also significantly positively correlated to supply chain performance (0.192, t = 2.273). The moderating effects of supply chain vulnerability on supply chain strategy and supply chain integration to supply chain performance are significant (7.407; 4.687). In Taiwan, 97.73% of enterprises are small- and medium-sized enterprises (SMEs) focusing on receiving original equipment manufacturer (OEM) and original design manufacturer (ODM) orders. In order to meet the needs of customers and to respond to market changes, these enterprises especially focus on supply chain flexibility and their integration with the upstream and downstream enterprises. According to the observation of this research, the effect of supply chain vulnerability on supply chain performance is significant, and so enterprises need to attach great importance to the management of supply chain risk and conduct risk analysis on their suppliers in order to formulate response strategies when facing emergency situations. At the same time, risk management is incorporated into the supply chain so as to reduce the effect of supply chain vulnerability on the overall supply chain performance.

Keywords: Supply chain integration, supply chain performance, supply chain vulnerability, structural equation modeling.

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Authors: P. H. Tee, S. M. Zamri, K. M. Kasim, S. K. Tiew

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This study evaluates the management of osteoporosis in a tertiary care government hospital in Malaysia. As the number of admitted patients having osteoporotic fractures is on the rise, osteoporotic medications are an increasing financial burden to government hospitals because they account for half of the orthopedic budget and expenditure. Comprehensive knowledge among practitioners is important to detect early and avoid this preventable disease and its serious complications. The purpose of this study is to evaluate the awareness, knowledge, and practices in managing osteoporosis among practitioners in Hospital Tengku Ampuan Rahimah (HTAR), Klang. A questionnaire from an overseas study in managing osteoporosis among primary care physicians is adapted to Malaysia’s Clinical Practice Guideline of Osteoporosis 2012 (revised 2015) and international guidelines were distributed to all orthopedic practitioners in HTAR Klang (including surgeons, orthopedic medical officers), endocrinologists, rheumatologists and geriatricians. The participants were evaluated on their expertise in the diagnosis, prevention, treatment decision and medications for osteoporosis. Collected data were analyzed for all descriptive and statistical analyses as appropriate. All 45 participants responded to the questionnaire. Participants scored highest on expertise in prevention, followed by diagnosis, treatment decision and lastly, medication. Most practitioners stated that own-initiated continuing professional education from articles and books was the most effective way to update their knowledge, followed by attendance in conferences on osteoporosis. This study confirms the importance of comprehensive training and education regarding osteoporosis among tertiary care physicians and surgeons, predominantly in pharmacotherapy, to deliver wholesome care for osteoporotic patients.

Keywords: Awareness, knowledge, osteoporosis, practices.

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Authors: Mónika Bartalné-Berceli, Eszter Izsó, Szilveszter Gergely, András Salgó

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Presently a significant portion of the Earth's population does not have access to healthy food. Either because they cannot afford it or because they do not know which one are they. The aim of the VII th Framework Chance project (Nr. 266331) supported by the European Union has been to develop relatively cheap food with favourable nutritional value and it should have acceptable quality for consumers. As one task of the project we manufactured bread products as a basic food. We examined the enrichment of bread products with four kinds of bran, with a special milling product of grain industry (aleurone-rich flour) and with a soy-based sprouted additive. The applied concentration of the six mentioned additives has been optimized and the physical properties of the bread products were monitored. The weight/density of the enriched breads increased a bit, however the volume and height decreased slightly compared to the corresponding data of the control bread. The optimized composition of the final product is favourably affected by these additives having highly preferred composition from nutritional point of view.

Keywords: Aleurone-rich flour, Brans, Bread products, Sprouted soybean, YASO.

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