Search results for: imperialist competitive algorithm

Authors: Muhammad Abdul Basit Memon

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The importance of organizational knowledge sharing and knowledge management has been documented in numerous research studies in available literature, since knowledge sharing has been recognized as a founding pillar for superior organizational performance and a source of gaining competitive advantage. Built on this, most of the successful organizations perceive knowledge management and knowledge sharing as a concern of high strategic importance and spend huge amounts on the effective management and sharing of organizational knowledge. However, despite some very serious endeavors, many firms fail to capitalize on the benefits of knowledge sharing because of being unaware of the individual characteristics, interpersonal, organizational and contextual factors that influence knowledge sharing; simply the antecedent to knowledge sharing. The extant literature on antecedents to knowledge sharing, offers a range of antecedents mentioned in a number of research articles and research studies. Some of the previous studies about antecedents to knowledge sharing, studied antecedents to knowledge sharing regarding inter-organizational knowledge transfer; others focused on inter and intra organizational knowledge sharing and still others investigated organizational factors. Some of the organizational antecedents to KS can relate to the characteristics and underlying aspects of knowledge being shared e.g., specificity and complexity of the underlying knowledge to be transferred; others relate to specific organizational characteristics e.g., age and size of the organization, decentralization and absorptive capacity of the firm and still others relate to the social relations and networks of organizations such as social ties, trusting relationships, and value systems. In the same way some researchers have highlighted on only one aspect like organizational commitment, transformational leadership, knowledge-centred culture, learning and performance orientation and social network-based relationships in the organizations. A bulk of the existing research articles on antecedents to knowledge sharing has mainly discussed organizational or environmental factors affecting knowledge sharing. However, the focus, later on, shifted towards the analysis of individuals or personal determinants as antecedents for the individual’s engagement in knowledge sharing activities, like personality traits, attitude and self efficacy etc. For example, employees’ goal orientations (i.e. learning orientation or performance orientation is an important individual antecedent of knowledge sharing behaviour. While being consistent with the existing literature therefore, the antecedents to knowledge sharing can be classified as being individual and organizational. This paper is an endeavor to discuss a conceptual framework of the individual and organizational antecedents to knowledge sharing in the light of the available literature and empirical evidence. This model not only can help in getting familiarity and comprehension on the subject matter by presenting a holistic view of the antecedents to knowledge sharing as discussed in the literature, but can also help the business managers and especially human resource managers to find insights about the salient features of organizational knowledge sharing. Moreover, this paper can help provide a ground for research students and academicians to conduct both qualitative as well and quantitative research and design an instrument for conducting survey on the topic of individual and organizational antecedents to knowledge sharing.

Keywords: antecedents to knowledge sharing, knowledge management, individual and organizational, organizational knowledge sharing

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Authors: Rudolph Carl Barrientos, Juwaln Diego Descallar, Rainer James Palmiano

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Household Appliance Scheduling Systems (HASS) coupled with a Time-of-Use (TOU) pricing scheme, a form of Demand Side Management (DSM), is not widely utilized in the Philippines’ residential electricity sector. This paper’s goal is to encourage distribution utilities (DUs) to adopt HASS and TOU by analyzing the effect of household schedulers on the electricity price and load profile in a residential environment. To establish this, a city based on an implemented survey is generated using Monte Carlo Analysis (MCA). Then, a Binary Particle Swarm Optimization (BPSO) algorithm-based HASS is developed considering user satisfaction, electricity budget, appliance prioritization, energy storage systems, solar power, and electric vehicles. The simulations were assessed under varying levels of user compliance. Results showed that the average electricity cost, peak demand, and peak-to-average ratio (PAR) of the city load profile were all reduced. Therefore, the deployment of the HASS and TOU pricing scheme is beneficial for both stakeholders.

Keywords: appliance scheduling, DSM, TOU, BPSO, city-wide simulation, electric vehicle, appliance prioritization, energy storage system, solar power

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Authors: Zehai Yu, Hui Zhu, Linglong Lin, Huawei Liang, Biao Yu, Weixin Huang

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With the development of intelligent vehicle systems, a high-precision road map is increasingly needed in many aspects. The automatic lane lines extraction and modeling are the most essential steps for the generation of a precise lane-level road map. In this paper, an automatic lane-level road map generation system is proposed. To extract the road markings on the ground, the multi-region Otsu thresholding method is applied, which calculates the intensity value of laser data that maximizes the variance between background and road markings. The extracted road marking points are then projected to the raster image and clustered using a two-stage clustering algorithm. Lane lines are subsequently recognized from these clusters by the shape features of their minimum bounding rectangle. To ensure the storage efficiency of the map, the lane lines are approximated to cubic polynomial curves using a Bayesian estimation approach. The proposed lane-level road map generation system has been tested on urban and expressway conditions in Hefei, China. The experimental results on the datasets show that our method can achieve excellent extraction and clustering effect, and the fitted lines can reach a high position accuracy with an error of less than 10 cm.

Keywords: curve fitting, lane-level road map, line recognition, multi-thresholding, two-stage clustering

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Authors: Aneesh Babu, S. P. Anusha

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A dynamic signal control system combines traditional traffic lights with an array of sensors to intelligently control vehicle and pedestrian traffic. The present study focus on evaluating the performance of dynamic signal control systems for mixed traffic conditions. Data collected from four different approaches to a typical four-legged signalized intersection at Trivandrum city in the Kerala state of India is used for the study. Performance of three other dynamic signal control methods, namely (i) Non-sequential method (ii) Webster design for consecutive signal cycle using flow as input, and (iii) dynamic signal control using RFID delay as input, were evaluated. The evaluation of the dynamic signal control systems was carried out using a calibrated VISSIM microsimulation model. Python programming was used to integrate the dynamic signal control algorithm through the COM interface in VISSIM. The intersection delay obtained from different dynamic signal control methods was compared with the delay obtained from fixed signal control. Based on the study results, it was observed that the intersection delay was reduced significantly by using dynamic signal control methods. The dynamic signal control method using delay from RFID sensors resulted in a higher percentage reduction in delay and hence is a suitable choice for implementation under mixed traffic conditions. The developed dynamic signal control strategies can be implemented in ITS applications under mixed traffic conditions.

Keywords: dynamic signal control, intersection delay, mixed traffic conditions, RFID sensors

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Authors: Ali Zaker, Zhi Chen

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Due to the concerns about the depletion of fossil fuel sources and the deteriorating environment, the attempt to investigate the production of renewable energy will play a crucial role as a potential to alleviate the dependency on mineral fuels. One particular area of interest is the generation of bio-oil through sewage sludge (SS) pyrolysis. SS can be a potential candidate in contrast to other types of biomasses due to its availability and low cost. However, the presence of high molecular weight hydrocarbons and oxygenated compounds in the SS bio-oil hinders some of its fuel applications. In this context, catalytic pyrolysis is another attainable route to upgrade bio-oil quality. Among different catalysts (i.e., zeolites) studied for SS pyrolysis, activated chars (AC) are eco-friendly alternatives. The beneficial features of AC derived from SS comprise the comparatively large surface area, porosity, enriched surface functional groups, and presence of a high amount of metal species that can improve the catalytic activity. Hence, a sludge-based AC catalyst was fabricated in a single-step pyrolysis reaction with NaOH as the activation agent and was compared with HZSM5 zeolite in this study. The thermal decomposition and kinetics were invested via thermogravimetric analysis (TGA) for guidance and control of pyrolysis and catalytic pyrolysis and the design of the pyrolysis setup. The results indicated that the pyrolysis and catalytic pyrolysis contains four obvious stages, and the main decomposition reaction occurred in the range of 200-600°C. The Coats-Redfern method was applied in the 2nd and 3rd devolatilization stages to estimate the reaction order and activation energy (E) from the mass loss data. The average activation energy (Em) values for the reaction orders n = 1, 2, and 3 were in the range of 6.67-20.37 kJ for SS; 1.51-6.87 kJ for HZSM5; and 2.29-9.17 kJ for AC, respectively. According to the results, AC and HZSM5 both were able to improve the reaction rate of SS pyrolysis by abridging the Em value. Moreover, to generate and examine the effect of the catalysts on the quality of bio-oil, a fixed-bed pyrolysis system was designed and implemented. The composition analysis of the produced bio-oil was carried out via gas chromatography/mass spectrometry (GC/MS). The selected SS to catalyst ratios were 1:1, 2:1, and 4:1. The optimum ratio in terms of cracking the long-chain hydrocarbons and removing oxygen-containing compounds was 1:1 for both catalysts. The upgraded bio-oils with AC and HZSM5 were in the total range of C4-C17, with around 72% in the range of C4-C9. The bio-oil from pyrolysis of SS contained 49.27% oxygenated compounds, while with the presence of AC and HZSM5 dropped to 13.02% and 7.3%, respectively. Meanwhile, the generation of benzene, toluene, and xylene (BTX) compounds was significantly improved in the catalytic process. Furthermore, the fabricated AC catalyst was characterized by BET, SEM-EDX, FT-IR, and TGA techniques. Overall, this research demonstrated AC is an efficient catalyst in the pyrolysis of SS and can be used as a cost-competitive catalyst in contrast to HZSM5.

Keywords: catalytic pyrolysis, sewage sludge, activated char, HZSM5, bio-oil

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Authors: Weiming Hu, Xu Li, Xiaonan Li, Zhong Xu, Li Yuan, Xuan Dong

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Maneuver decision-making plays a critical role in high-performance intelligent driving. This paper proposes a risk assessment-based decision-making network (RADMN) to address the problem of driving strategy for the commercial vehicle. RADMN integrates two networks, aiming at identifying the risk degree of collision and rollover and providing decisions to ensure the effectiveness and reliability of driving strategy. In the risk assessment module, risk degrees of the backward collision, forward collision and rollover are quantified for hazard recognition. In the decision module, a deep reinforcement learning based on multi-objective optimization (DRL-MOO) algorithm is designed, which comprehensively considers the risk degree and motion states of each traffic participant. To evaluate the performance of the proposed framework, Prescan/Simulink joint simulation was conducted in highway scenarios. Experimental results validate the effectiveness and reliability of the proposed RADMN. The output driving strategy can guarantee the safety and provide key technical support for the realization of autonomous driving of commercial vehicles.

Keywords: decision-making strategy, risk assessment, multi-objective optimization, commercial vehicle

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Authors: Andrew Hwang

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The average American worker sits for thirteen hours a day, often with poor posture and infrequent breaks, which can lead to health issues and back problems. The Smart Cushion was created to alert individuals of their poor postures, and may potentially alleviate back problems and correct poor posture. The Smart Cushion is a portable, rectangular, foam cushion, with five strategically placed pressure sensors, that utilizes an Arduino Uno circuit board and specifically designed software, allowing it to collect data from the five pressure sensors and store the data on an SD card. The data is then compiled into graphs and compared to controlled postures. Before volunteers sat on the cushion, their levels of back pain were recorded on a scale from 1-10. Data was recorded for an hour during sitting, and then a new, corrected posture was suggested. After using the suggested posture for an hour, the volunteers described their level of discomfort on a scale from 1-10. Different patterns of sitting postures were generated that were able to serve as early warnings of potential back problems. By using the Smart Cushion, the areas where different volunteers were applying the most pressure while sitting could be identified, and the sitting postures could be corrected. Further studies regarding the relationships between posture and specific regions of the body are necessary to better understand the origins of back pain; however, the Smart Cushion is sufficient for correcting sitting posture and preventing the development of additional back pain.

Keywords: Arduino Sketch Algorithm, biomedical technology, pressure sensors, Smart Cushion

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Authors: Nixon Kuruvila, H. V. Ravindra

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Wire-cut Electro Discharge Machining (WEDM) is a special form of conventional EDM process in which electrode is a continuously moving conductive wire. The present study aims at determining parametric influence and optimum process parameters of Wire-EDM using Taguchi’s Technique and Genetic algorithm. The variation of the performance parameters with machining parameters was mathematically modeled by Regression analysis method. The objective functions are Dimensional Accuracy (DA) and Material Removal Rate (MRR). Experiments were designed as per Taguchi’s L16 Orthogonal Array (OA) where in Pulse-on duration, Pulse-off duration, Current, Bed-speed and Flushing rate have been considered as the important input parameters. The matrix experiments were conducted for the material Oil Hardened Non Shrinking Steel (OHNS) having the thickness of 40 mm. The results of the study reveals that among the machining parameters it is preferable to go in for lower pulse-off duration for achieving over all good performance. Regarding MRR, OHNS is to be eroded with medium pulse-off duration and higher flush rate. Finally, the validation exercise performed with the optimum levels of the process parameters. The results confirm the efficiency of the approach employed for optimization of process parameters in this study.

Keywords: dimensional accuracy (DA), regression analysis (RA), Taguchi method (TM), volumetric material removal rate (VMRR)

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Authors: H.-H. Doh, J.-M. Yu, Y.-J. Kwon, J.-H. Shin, H.-W. Kim, S.-H. Nam, D.-H. Lee

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This paper suggests a decision tree based approach for flexible job shop scheduling with multiple process plans, i. e. each job can be processed through alternative operations, each of which can be processed on alternative machines. The main decision variables are: (a) selecting operation/machine pair; and (b) sequencing the jobs assigned to each machine. As an extension of the priority scheduling approach that selects the best priority rule combination after many simulation runs, this study suggests a decision tree based approach in which a decision tree is used to select a priority rule combination adequate for a specific system state and hence the burdens required for developing simulation models and carrying out simulation runs can be eliminated. The decision tree based scheduling approach consists of construction and scheduling modules. In the construction module, a decision tree is constructed using a four-stage algorithm, and in the scheduling module, a priority rule combination is selected using the decision tree. To show the performance of the decision tree based approach suggested in this study, a case study was done on a flexible job shop with reconfigurable manufacturing cells and a conventional job shop, and the results are reported by comparing it with individual priority rule combinations for the objectives of minimizing total flow time and total tardiness.

Keywords: flexible job shop scheduling, decision tree, priority rules, case study

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Authors: M. Dezvarei, S. Morovati

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In recent years, increasing usage of electrical energy provides a widespread field for investigating new methods to produce clean electricity with high reliability and cost management. Fuel cells are new clean generations to make electricity and thermal energy together with high performance and no environmental pollution. According to the expansion of fuel cell usage in different industrial networks, the identification and optimization of its parameters is really significant. This paper presents optimization of a proton exchange membrane fuel cell (PEMFC) parameters based on modified particle swarm optimization with real valued mutation (RVM) and clonal algorithms. Mathematical equations of this type of fuel cell are presented as the main model structure in the optimization process. Optimized parameters based on clonal and RVM algorithms are compared with the desired values in the presence and absence of measurement noise. This paper shows that these methods can improve the performance of traditional optimization methods. Simulation results are employed to analyze and compare the performance of these methodologies in order to optimize the proton exchange membrane fuel cell parameters.

Keywords: clonal algorithm, proton exchange membrane fuel cell (PEMFC), particle swarm optimization (PSO), real-valued mutation (RVM)

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Authors: Shoury Gupta

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Chatbots are a rapidly growing technological trend that has revolutionized the way businesses interact with their customers. With the advancements in artificial intelligence, chatbots can now mimic human-like conversations and provide instant and efficient responses to customer inquiries. In this research paper, we aim to explore the implications of chatbots on the future of globalization for both businesses and consumers. The paper begins by providing an overview of the current state of chatbots in the global market and their growth potential in the future. The focus is on how chatbots have become a valuable tool for businesses looking to expand their global reach, especially in areas with high population density and language barriers. With chatbots, businesses can engage with customers in different languages and provide 24/7 customer service support, creating a more accessible and convenient customer experience. The paper then examines the impact of chatbots on cross-cultural communication and how they can help bridge communication gaps between businesses and consumers from different cultural backgrounds. Chatbots can potentially facilitate cross-cultural communication by offering real-time translations, voice recognition, and other innovative features that can help users communicate effectively across different languages and cultures. By providing more accessible and inclusive communication channels, chatbots can help businesses reach new markets and expand their customer base, making them more competitive in the global market. However, the paper also acknowledges that there are potential drawbacks associated with chatbots. For instance, chatbots may not be able to address complex customer inquiries that require human input. Additionally, chatbots may perpetuate biases if they are programmed with certain stereotypes or assumptions about different cultures. These drawbacks may have significant implications for businesses and consumers alike. To explore the implications of chatbots on the future of globalization in greater detail, the paper provides a thorough review of existing literature and case studies. The review covers topics such as the benefits of chatbots for businesses and consumers, the potential drawbacks of chatbots, and how businesses can mitigate any risks associated with chatbot use. The paper also discusses the ethical considerations associated with chatbot use, such as privacy concerns and the need to ensure that chatbots do not discriminate against certain groups of people. The ethical implications of chatbots are particularly important given the potential for chatbots to be used in sensitive areas such as healthcare and financial services. Overall, this research paper provides a comprehensive analysis of chatbots and their implications for the future of globalization. By exploring both the potential benefits and drawbacks of chatbot use, the paper aims to provide insights into how businesses and consumers can leverage this technology to achieve greater global reach and improve cross-cultural communication. Ultimately, the paper concludes that chatbots have the potential to be a powerful tool for businesses looking to expand their global footprint and improve their customer experience, but that care must be taken to mitigate any risks associated with their use.

Keywords: chatbots, conversational AI, globalization, businesses

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Authors: Chux Gervase Iwu, Simon Nsengimane

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Entrepreneurship stimulates socio-economic development in many countries, if not all. It creates jobs and decreases unemployment and inequality. There are other benefits that are accruable from entrepreneurship, namely the empowerment of women and the promotion of better livelihoods. Innovation has become a weapon for business competition, growth, and sustainability. Paradoxically, it is a threat to businesses because products can be duplicated; new products may decrease the market share of existing ones or delete them from the market. This creates a constant competitive environment that calls for updates, innovation, and the invention of new products and services. Thus, the importance of higher education in instilling a good entrepreneurial mindset in students has become even more critical. It can be argued that the business environment is under enormous pressure from several factors, including the fourth industrial revolution, which calls for the adoption and use of information and communication technology, which is the catalyst for many innovations and organisational changes. Therefore, it is crucial that higher education students are equipped with relevant knowledge and skills to respond effectively to the needs of the business environment and create a vibrant entrepreneurship ecosystem. In South Africa, entrepreneurship education or some form of it has been a privilege for economic and management fields of study, leaving behind other fields. Entrepreneurship should not be limited to business faculties but rather extended to other fields of study. This is perhaps the reason for low levels of entrepreneurship uptake among South African graduates if they are compared with the graduates in other countries. There may be other reasons for the low entrepreneurship uptake. Some of these have been documented in extant literature to include (1) not enough time was spent teaching entrepreneurship in the business faculties, (2) the skills components in the curricula are insufficient, and (3) the overall attitudes/mindsets necessary to establish and run sustainable enterprises seem absent. Therefore, four important areas are recognised as crucial for the effective implementation of entrepreneurship education: policy, private sector engagement, curriculum development, and teacher development. The purpose of this research is to better comprehend the views, aspirations, and expectations of students and faculty members to design an entrepreneurial teaching model for higher education institutions. A qualitative method will be used to conduct a purposive interview with undergraduate and graduate students in select higher institutions. Members of faculty will also be included in the sample as well as, where possible, two or more government personnel responsible for higher education policy development. At present, interpretative analysis is proposed for the analysis of the interviews with the support of Atlas Ti. It is hoped that an entrepreneurship education model in the South African context is realised through this study.

Keywords: entrepreneurship education, higher education institution, graduate unemployment, curriculum development

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Authors: Anjali Chouksey, Riya Nimje, Jahanvi Saraf

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Online transactions have increased dramatically in this new ‘social-distancing’ era. With online transactions, Fraud in online payments has also increased significantly. Frauds are a significant problem in various industries like insurance companies, baking, etc. These frauds include leaking sensitive information related to the credit card, which can be easily misused. Due to the government also pushing online transactions, E-commerce is on a boom. But due to increasing frauds in online payments, these E-commerce industries are suffering a great loss of trust from their customers. These companies are finding credit card fraud to be a big problem. People have started using online payment options and thus are becoming easy targets of credit card fraud. In this research paper, we will be discussing machine learning algorithms. We have used a decision tree, XGBOOST, k-nearest neighbour, logistic-regression, random forest, and SVM on a dataset in which there are transactions done online mode using credit cards. We will test all these algorithms for detecting fraud cases using the confusion matrix, F1 score, and calculating the accuracy score for each model to identify which algorithm can be used in detecting frauds.

Keywords: machine learning, fraud detection, artificial intelligence, decision tree, k nearest neighbour, random forest, XGBOOST, logistic regression, support vector machine

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Authors: Zoi Konsoula

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The increasing prevalence of Alzheimer’s disease (AD) and diabetes mellitus (DM) constitutes them major global health problems. Recently, the inhibition of key enzyme activity is considered a potential treatment of both diseases. Specifically, inhibition of acetylcholinesterase (AChE), the key enzyme involved in the breakdown of the neurotransmitter acetylcholine, is a promising approach for the treatment of AD, while inhibition of α-amylase retards the hydrolysis of carbohydrates and, thus, reduces hyperglycemia. Unfortunately, commercially available AChE and α-amylase inhibitors are reported to possess side effects. Consequently, there is a need to develop safe and effective treatments for both diseases. In the present study, pomegranate peel (PP) was extracted using various solvents of increasing polarity, while two extraction methods were employed, the conventional maceration and the ultrasound assisted extraction (UAE). The concentration of bioactive phytoconstituents, such as total phenolics (TPC) and total flavonoids (TFC) in the prepared extracts was evaluated by the Folin-Ciocalteu and the aluminum-flavonoid complex method, respectively. Furthermore, the anti-neurodegenerative and anti-hyperglycemic activity of all extracts was determined using AChE and α-amylase inhibitory activity assays, respectively. The inhibitory activity of the extracts against AChE and α-amylase was characterized by estimating their IC₅₀ value using a dose-response curve, while galanthamine and acarbose were used as positive controls, respectively. Finally, the kinetics of AChE and α-amylase in the presence of the most inhibitory potent extracts was determined by the Lineweaver-Burk plot. The methanolic extract prepared using the UAE contained the highest amount of phytoconstituents, followed by the respective ethanolic extract. All extracts inhibited acetylcholinesterase in a dose-dependent manner, while the increased anticholinesterase activity of the methanolic (IC₅₀ = 32 μg/mL) and ethanolic (IC₅₀ = 42 μg/mL) extract was positively correlated with their TPC content. Furthermore, the activity of the aforementioned extracts was comparable to galanthamine. Similar results were obtained in the case of α-amylase, however, all extracts showed lower inhibitory effect on the carbohydrate hydrolyzing enzyme than on AChE, since the IC₅₀ value ranged from 84 to 100 μg/mL. Also, the α-amylase inhibitory effect of the extracts was lower than acarbose. Finally, the methanolic and ethanolic extracts prepared by UAE inhibited both enzymes in a mixed (competitive/noncompetitive) manner since the Kₘ value of both enzymes increased in the presence of extracts, while the Vmax value decreased. The results of the present study indicate that PP may be a useful source of active compounds for the management of AD and DM. Moreover, taking into consideration that PP is an agro-industrial waste product, its valorization could not only result in economic efficiency but also reduce the environmental pollution.

Keywords: acetylcholinesterase, Alzheimer’s disease, α-amylase, diabetes mellitus, pomegranate

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Authors: Luay Jum'a

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Many challenges are facing third-party logistics (3PL) providers in the domestic and global markets which create a volatile decision making environment. All these challenges such as managing changes in consumer behaviour, demanding expectations from customers and time compressions have turned into complex problems for 3PL providers. Since the movement towards increased outsourcing outpaces movement towards insourcing, the need to achieve a competitive advantage over competitors in 3PL market increases. This trend continues to grow over the years and as a result, areas of strengths and improvements are highlighted through the analysis of the LSQ factors that lead to B2B customers’ satisfaction which become a priority for 3PL companies. Consequently, 3PL companies are increasingly focusing on the most important issues from the perspective of their customers and relying more on this value of information in making their managerial decisions. Therefore, this study is concerned with providing guidance for improving logistics service quality (LSQ) levels in the context of 3PL industry in Jordan. The study focused on the most important factors in LSQ and used a managerial tool that guides 3PL companies in making LSQ improvements based on a quadrant analysis of two main dimensions: LSQ declared importance and LSQ inferred importance. Although, a considerable amount of research has been conducted to investigate the relationship between logistics service quality (LSQ) and customer satisfaction, there remains a lack of developing managerial tools to aid in the process of LSQ improvement decision-making. Moreover, the main advantage for the companies to use 3PL service providers as a trend is due to the realised percentage of cost reduction on the total cost of logistics operations and the incremental improvement in customer service. In this regard, having a managerial tool that help 3PL service providers in managing the LSQ factors portfolio effectively and efficiently would be a great investment for service providers. One way of suggesting LSQ improvement actions for 3PL service providers is via the adoption of analysis tools that perform attribute categorisation such as Importance–Performance matrix. In mind of the above, it can be stated that the use of quadrant analysis will provide a valuable opportunity for 3PL service providers to identify improvement opportunities as customer service attributes or factors importance are identified in two different techniques that complete each other. Moreover, the data were collected through conducting a survey and 293 questionnaires were returned from business-to-business (B2B) customers of 3PL companies in Jordan. The results showed that the LSQ factors vary in their importance and 3PL companies should focus on some LSQ factors more than other factors. Moreover, ordering procedures, timeliness/responsiveness LSQ factors considered being crucial in 3PL businesses and therefore they need to have more focus and development by 3PL service providers in the Jordanian market.

Keywords: logistics service quality, managerial decisions, quadrant analysis, third party logistics service provider

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Authors: Khalid Ali, Manar Jammal

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In order to meet the stringent latency and reliability requirements of the upcoming 5G networks, Open Radio Access Networks (O-RAN) have been proposed. The virtualization of O-RAN has allowed it to be treated as a Network Function Virtualization (NFV) architecture, while its components are considered Virtualized Network Functions (VNFs). Hence, intelligent Machine Learning (ML) based solutions can be utilized to apply different resource management and allocation techniques on O-RAN. However, intelligently allocating resources for O-RAN VNFs can prove challenging due to the dynamicity of traffic in mobile networks. Network providers need to dynamically scale the allocated resources in response to the incoming traffic. Elastically allocating resources can provide a higher level of flexibility in the network in addition to reducing the OPerational EXpenditure (OPEX) and increasing the resources utilization. Most of the existing elastic solutions are reactive in nature, despite the fact that proactive approaches are more agile since they scale instances ahead of time by predicting the incoming traffic. In this work, we propose and evaluate traffic forecasting models based on the ML algorithm. The algorithms aim at predicting future O-RAN traffic by using previous traffic data. Detailed analysis of the traffic data was carried out to validate the quality and applicability of the traffic dataset. Hence, two ML models were proposed and evaluated based on their prediction capabilities.

Keywords: O-RAN, traffic forecasting, NFV, ARIMA, LSTM, elasticity

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Authors: Ashish Shrivastava, C. Pandu Rangan

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In this paper, we consider The Hospitals Residents problem with Social Stability (HRSS), where hospitals and residents can communicate only through the underlying social network. Those residents and hospitals which don not have any social connection between them can not communicate and hence they cannot be a social blocking pair with respect to a socially stable matching in an instance of hospitals residents problem with social stability. In large scale matching like NRMP or Scottish medical matching scheme etc. where set of agents, as well as length of preference lists, are very large, social stability is a useful notion in which members of a blocking pair could block a matching if and only if they know the existence of each other. Thus the notion of social stability in hospitals residents problem allows us to increase the cardinality of the matching without taking care of those blocking pairs which are not socially connected to each other. We know that finding a maximum cardinality socially stable matching, in an instance, of HRSS is NP-hard. This motivates us to solve this problem with bounded length preference lists on one side. In this paper, we have presented a polynomial time algorithm to compute maximum cardinality socially stable matching in a HRSS instance where residents can give at most two length and hospitals can give unbounded length preference list. Preference lists of residents and hospitals will be strict in nature.

Keywords: matching under preference, socially stable matching, the hospital residents problem, the stable marriage problem

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Authors: Yanni Chang, Dezhi Dai, Albert Y. Tong

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Piecewise linear interface calculation (PLIC) schemes are widely used in the volume-of-fluid (VOF) method to capture interfaces in numerical simulations of multiphase flows. Dynamic overset meshes can be especially useful in applications involving component motions and complex geometric shapes. In the present study, the VOF value of an acceptor cell is evaluated in a geometric way that transfers the fraction field between the meshes precisely with reconstructed interfaces from the corresponding donor elements. The acceptor cell value is evaluated by using a weighted average of its donors for most of the overset interpolation schemes for continuous flow variables. The weighting factors are obtained by different algebraic methods. Unlike the continuous flow variables, the VOF equation is a step function near the interfaces, which ranges from zero to unity rapidly. A geometric interpolation scheme of the VOF field in overset meshes for the PLIC-VOF method has been proposed in the paper. It has been tested successfully in quadrilateral/hexahedral overset meshes by employing several VOF advection tests with imposed solenoidal velocity fields. The proposed algorithm has been shown to yield higher accuracy in mass conservation and interface reconstruction compared with three other algebraic ones.

Keywords: interpolation scheme, multiphase flows, overset meshes, PLIC-VOF method

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Authors: Kristine Demilou Santiago

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In a context of a developing nation, how important is the role of Corporate Social Responsibility health programs? Is there a possibility that this will render a large impact in a society where health benefits are insufficient? The Philippine government has been in an unceasing battle to provide its citizens competitive health benefits through launching various health programs. As the efforts are being claimed by the government, the numbers just show that all the health benefits being offered such as PhilHealth health cards, medical missions and other subsidized government health benefits are not effective and sufficient at the minimum level. This is a major characteristic of a developing nation which the Philippine government is focusing on addressing as it becomes a national concern under the effects of poverty. Industrial companies, through Corporate Social Responsibility, are playing an important role in the aspiration to resolve this problem on health programs as supposed to be basic services to citizens of the Philippine government. The rise of commitment by these industrial companies to render health programs to communities as part of their corporate citizenship has covered a large portion of the basic health services that the Filipino citizens are supposed to be receiving. This is the most salient subject that a developing nation should focus on determining the important contribution of industrial companies present in their country as part of the citizens’ access to basic health services. The use of survey forms containing quantitative and qualitative questions which aim to give numerical figures and support answers as to the role of CSR Health programs in helping the communities receive the basic health services they need was the methodological procedure followed in this research. A sample population in a community where the largest industrial company in a province of the Philippines was taken through simple random sampling. The assumption is that this sample population which represents the whole of the community has the highest opportunities to access both the government health services and the CSR health program services of the industrial company located in their community. Results of the research have shown a significant level of participation by industrial companies through their CSR health programs in the attainment of basic health services that should be rendered by the Philippine government to its citizens as part of the state’s health benefits. In a context of a developing nation such as the Philippines, the role of Corporate Social Responsibility is beyond the expectation of initiating to resolve environmental and social issues. It is moving deeper in the concept of the corporate industries being a pillar of the government in catering the support needed by the individuals in the community for its development. As such, the concept of the presence of an industrial company in a community is said to be a parallel progress: by which when an industrial company expands because it is becoming more profitable, so is the community gaining the same step of progress in terms of socioeconomic development.

Keywords: basic health services, CSR health program, health services in a developing nation, Philippines health benefits

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Authors: Madhushi Bandara, Dharshana Kasthurirathna, Danaja Maldeniya, Mahendra Piraveenan

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Community detection is an extremely useful technique in understanding the structure and function of a social network. Louvain algorithm, which is based on Newman-Girman modularity optimization technique, is extensively used as a computationally efficient method extract the communities in social networks. It has been suggested that the nodes that are in close geographical proximity have a higher tendency of forming communities. Variants of the Newman-Girman modularity measure such as dist-modularity try to normalize the effect of geographical proximity to extract geographically dispersed communities, at the expense of losing the information about the geographically proximate communities. In this work, we propose a method to extract geographically dispersed communities while preserving the information about the geographically proximate communities, by analyzing the ‘community network’, where the centroids of communities would be considered as network nodes. We suggest that the inter-community link strengths, which are normalized over the community sizes, may be used to identify and extract the ‘overlay communities’. The overlay communities would have relatively higher link strengths, despite being relatively apart in their spatial distribution. We apply this method to the Gowalla online social network, which contains the geographical signatures of its users, and identify the overlay communities within it.

Keywords: social networks, community detection, modularity optimization, geographically dispersed communities

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Authors: H. Mansor, S.B. Mohd-Noor, N. I. Othman, N. Tazali, R. I. Boby

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This paper presents an improved robust Proportional Derivative controller for a 3-Degree-of-Freedom (3-DOF) bench-top helicopter by using adaptive methodology. Bench-top helicopter is a laboratory scale helicopter used for experimental purposes which is widely used in teaching laboratory and research. Proportional Derivative controller has been developed for a 3-DOF bench-top helicopter by Quanser. Experiments showed that the transient response of designed PD controller has very large steady state error i.e., 50%, which is very serious. The objective of this research is to improve the performance of existing pitch angle control of PD controller on the bench-top helicopter by integration of PD controller with adaptive controller. Usually standard adaptive controller will produce zero steady state error; however response time to reach desired set point is large. Therefore, this paper proposed an adaptive with deadbeat algorithm to overcome the limitations. The output response that is fast, robust and updated online is expected. Performance comparisons have been performed between the proposed self-tuning deadbeat PD controller and standard PD controller. The efficiency of the self-tuning dead beat controller has been proven from the tests results in terms of faster settling time, zero steady state error and capability of the controller to be updated online.

Keywords: adaptive control, deadbeat control, bench-top helicopter, self-tuning control

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Authors: Aishwarya Ravindra Fursule, Shruti Kshirsagar

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In the intersection of artificial intelligence and human-centered computing, this paper delves into speech emotion recognition (SER). It presents a comparative analysis of machine learning models such as K-Nearest Neighbors (KNN),logistic regression, support vector machines (SVM), decision trees, ensemble classifiers, and random forests, applied to SER. The research employs four datasets: Crema D, SAVEE, TESS, and RAVDESS. It focuses on extracting salient audio signal features like Zero Crossing Rate (ZCR), Chroma_stft, Mel Frequency Cepstral Coefficients (MFCC), root mean square (RMS) value, and MelSpectogram. These features are used to train and evaluate the models’ ability to recognize eight types of emotions from speech: happy, sad, neutral, angry, calm, disgust, fear, and surprise. Among the models, the Random Forest algorithm demonstrated superior performance, achieving approximately 79% accuracy. This suggests its suitability for SER within the parameters of this study. The research contributes to SER by showcasing the effectiveness of various machine learning algorithms and feature extraction techniques. The findings hold promise for the development of more precise emotion recognition systems in the future. This abstract provides a succinct overview of the paper’s content, methods, and results.

Keywords: comparison, ML classifiers, KNN, decision tree, SVM, random forest, logistic regression, ensemble classifiers

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Authors: Joshi Manisha, Shivaram, Anand Vinekar, Tanya Susan Mathews, Yeshaswini Nagaraj

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Retinopathy of prematurity (ROP) is abnormal blood vessel development in the retina of the eye in a premature infant. The principal object of the invention is to provide a technique for detecting demarcation line and ridge detection for a given ROP image that facilitates early detection of ROP in stage 1 and stage 2. The demarcation line is an indicator of Stage 1 of the ROP and the ridge is the hallmark of typically Stage 2 ROP. Thirty Retcam images of Asian Indian infants obtained during routine ROP screening have been used for the analysis. A graphical user interface has been developed to detect demarcation line/ridge and to extract ground truth. This novel algorithm uses multilevel vessel enhancement to enhance tubular structures in the digital ROP images. It has been observed that the orientation of the demarcation line/ridge is normal to the direction of the blood vessels, which is used for the identification of the ridge/ demarcation line. Quantitative analysis has been presented based on gold standard images marked by expert ophthalmologist. Image based analysis has been based on the length and the position of the detected ridge. In image based evaluation, average sensitivity and positive predictive value was found to be 92.30% and 85.71% respectively. In pixel based evaluation, average sensitivity, specificity, positive predictive value and negative predictive value achieved were 60.38%, 99.66%, 52.77% and 99.75% respectively.

Keywords: ROP, ridge, multilevel vessel enhancement, biomedical

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Authors: Najrullah Khan, Athar Ali Khan

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The Topp-Leone distribution was introduced by Topp- Leone in 1955. In this paper, an attempt has been made to fit Topp-Leone Generalized exponential (TPGE) distribution. A real survival data set is used for illustrations. Implementation is done using R and JAGS and appropriate illustrations are made. R and JAGS codes have been provided to implement censoring mechanism using both optimization and simulation tools. The main aim of this paper is to describe and illustrate the Bayesian modelling approach to the analysis of survival data. Emphasis is placed on the modeling of data and the interpretation of the results. Crucial to this is an understanding of the nature of the incomplete or 'censored' data encountered. Analytic approximation and simulation tools are covered here, but most of the emphasis is on Markov chain based Monte Carlo method including independent Metropolis algorithm, which is currently the most popular technique. For analytic approximation, among various optimization algorithms and trust region method is found to be the best. In this paper, TPGE model is also used to analyze the lifetime data in Bayesian paradigm. Results are evaluated from the above mentioned real survival data set. The analytic approximation and simulation methods are implemented using some software packages. It is clear from our findings that simulation tools provide better results as compared to those obtained by asymptotic approximation.

Keywords: Bayesian Inference, JAGS, Laplace Approximation, LaplacesDemon, posterior, R Software, simulation

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Authors: George Adomako Kumi

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The response of structural members, when subjected to various forms of non-proportional loading, plays a major role in the overall stability and integrity of a structure. This research seeks to present the outcome of a finite element investigation conducted by the use of finite element programming software ABAQUS to validate the experimental results of elastic and inelastic behavior and strength of beam-columns subjected to axial loading, biaxial bending, and torsion under ambient temperature conditions. The application of the rigorous and highly complicated ABAQUS finite element software will seek to account for material, non-linear geometry, deformations, and, more specifically, the contact behavior between the beam-columns and support surfaces. Comparisons of the three-dimensional model with the results of actual tests conducted and results from a solution algorithm developed through the use of the finite difference method will be established in order to authenticate the veracity of the developed model. The results of this research will seek to provide structural engineers with much-needed knowledge about the behavior of steel beam columns and their response to various non-proportional loading conditions under ambient temperature conditions.

Keywords: beam-columns, axial loading, biaxial bending, torsion, ABAQUS, finite difference method

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Authors: Ehsan Gholamalizadeh, Jae Dong Chung

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Solar chimney power plant is a feasible solar thermal system which produces electricity from the Sun. The objective of this study is to investigate buoyancy-driven flow and heat transfer through a built pilot solar chimney system called 'Kerman Project'. The system has a chimney with the height and diameter of 60 m and 3 m, respectively, and the average radius of its solar collector is about 20 m, and also its average collector height is about 2 m. A three-dimensional simulation was conducted to analyze the system, using computational fluid dynamics (CFD). In this model, radiative transfer equation was solved using the discrete ordinates (DO) radiation model taking into account a non-gray radiation behavior. In order to modelling solar irradiation from the sun’s rays, the solar ray tracing algorithm was coupled to the computation via a source term in the energy equation. The model was validated with comparing to the experimental data of the Manzanares prototype and also the performance of the built pilot system. Then, based on the numerical simulations, velocity and temperature distributions through the system, the temperature profile of the ground surface and the system performance were presented. The analysis accurately shows the flow and heat transfer characteristics through the pilot system and predicts its performance.

Keywords: buoyancy-driven flow, computational fluid dynamics, heat transfer, renewable energy, solar chimney power plant

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Authors: William Sigvardsson, Christoffer Alenius, Jenny Lindblom, Andreas Johansson, Marcus Sandberg

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This article covers a study focusing on a subarctic greenhouse located in Nikkala, Sweden. Through a visit and the creation of a CFD model, the study investigates the differences in energy demand with high pressure sodium (HPS) lights and light emitting diode (LED) lights in combination with an air-carried and water-carried heating system accordingly. Through an IDA ICE model, the impact of insulating the parts of the greenhouse without active cultivation was also investigated. This, with the purpose of comparing the current system in the greenhouse to state-of-the-art alternatives and evaluating if an investment in either a water-carried heating system in combination with LED lights and insulating the non-cultivating parts of the greenhouse could be considered profitable. Operating a greenhouse in the harsh subarctic climate found in the northern parts of Sweden is not an easy task and especially if the operation is year-round. With an average temperature of under -5 °C from November through January, efficient growing techniques are a must to ensure a profitable business. Today the most crucial parts of a greenhouse are the heating system, lighting system, dehumidifying measures, as well as thermal screen, and the impact of a poorly designed system in a sub-arctic could be devastating as the margins are slim. The greenhouse studied uses a pellet burner to power their air- carried heating system which is used. The simulations found the resulting savings amounted to just under 14 800 SEK monthly or 18 % of the total cost of energy by implementing the water-carrying heating system in combination with the LED lamps. Given this, a payback period of 3-9 years could be expected given different scenarios, including specific time periods, financial aids, and the resale price of the current system. The insulation of the non-cultivating parts of the greenhouse was found to have possible savings of 25 300 SEK annually or 46 % of the current heat demand resulting in a payback period of just over 1-2 years. Given the possible energy savings, a reduction in emitted CO2 equivalents of almost 1,9 tonnes could be achieved annually. It was concluded that relatively inexpensive investments in modern greenhouse equipment could make a significant contribution to reducing the energy consumption of the greenhouse resulting in a more competitive business environment for sub-arctic greenhouse owners. New parts of the greenhouse should be built with the water-carried heating system in combination with state-of-the-art LED lights, and all parts which are not housing active cultivation should be insulated. If the greenhouse in Nikkala is eligible for financial aid or finds a resale value in the current system, an investment should be made in a new water-carried heating system in combination with LED lights.

Keywords: energy efficiency, sub-arctic greenhouses, energy measures, greenhouse climate control, greenhouse technology, CFD

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Authors: Shahrokh Barati, Reza Ramezani

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Due to the countries growing attention to the renewable energy producing, the demand for energy from renewable energy has gone up among the renewable energy sources; wind energy is the fastest growth in recent years. In this regard, in order to increase the availability of wind turbines, using of Fault Detection and Isolation (FDI) system is necessary. Wind turbines include of various faults such as sensors fault, actuator faults, network connection fault, mechanical faults and faults in the generator subsystem. Although, sensors and actuators have a large number of faults in wind turbine but have discussed fewer in the literature. Therefore, in this work, we focus our attention to design a sensor and actuator fault detection and isolation algorithm and Fault-tolerant control systems (FTCS) for Wind Turbine. The aim of this research is to propose a comprehensive fault detection and isolation system for sensors and actuators of wind turbine based on data-driven approaches. To achieve this goal, the features of measurable signals in real wind turbine extract in any condition. The next step is the feature selection among the extract in any condition. The next step is the feature selection among the extracted features. Features are selected that led to maximum separation networks that implemented in parallel and results of classifiers fused together. In order to maximize the reliability of decision on fault, the property of fault repeatability is used.

Keywords: FDI, wind turbines, sensors and actuators faults, renewable energy

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Authors: Linda D. F. Bambara, Marie Sawadogo

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Jatropha curcas (jatropha) is the plant that has been the most studied for biofuel production in West Africa. There exist however other plants such as Balanites aegyptiaca (balanites) that have been targeted as a potential feedstock for biofuel production. This biomass could be an alternative feedstock for the production of straight vegetable oil (SVO) at costs lower than jatropha-based SVO production costs. This study aims firstly to determine, through an MILP model, the optimal organization that minimizes the costs of the oilseeds supply of two biomass conversion units (BCU) exploiting respectively jatropha seeds and the balanitès seeds. Secondly, the study aims to carry out a comparative study of these costs obtained for each BCU. The model was then implemented on two theoretical cases studies built on the basis of the common practices in Burkina Faso and two scenarios were carried out for each case study. In Scenario 1, 3 pre-processing locations ("at the harvesting area", "at the gathering points", "at the BCU") are possible. In scenario 2, only one location ("at the BCU") is possible. For each biomass, the system studied is the upstream supply chain (harvesting, transport and pre-processing (drying, dehulling, depulping)), including cultivation (for jatropha). The model optimizes the area of land to be exploited based on the productivity of the studied plants and material losses that may occur during the harvesting and the supply of the BCU. It then defines the configuration of the logistics network allowing an optimal supply of the BCU taking into account the most common means of transport in West African rural areas. For the two scenarios, the results of the implementation showed that the total area exploited for balanites (1807 ha) is 4.7 times greater than the total area exploited for Jatropha (381 ha). In both case studies, the location of pre-processing “at the harvesting area” was always chosen for scenario1. As the balanites trees were not planted and because the first harvest of the jatropha seeds took place 4 years after planting, the cost price of the seeds at the BCU without the pre-processing costs was about 430 XOF/kg. This cost is 3 times higher than the balanites's one, which is 140 XOF/kg. After the first year of harvest, i.e. 5 years after planting, and assuming that the yield remains constant, the same cost price is about 200 XOF/kg for Jatropha. This cost is still 1.4 times greater than the balanites's one. The transport cost of the balanites seeds is about 120 XOF/kg. This cost is similar for the jatropha seeds. However, when the pre-processing is located at the BCU, i.e. for scenario2, the transport costs of the balanites seeds is 1200 XOF/kg. These costs are 6 times greater than the transport costs of jatropha which is 200 XOF/kg. These results show that the cost price of the balanites seeds at the BCU can be competitive compared to the jatropha's one if the pre-processing is located at the harvesting area.

Keywords: Balanites aegyptiaca, biomass conversion, Jatropha curcas, optimization, post-harvest operations

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Authors: Hanee Ryu

Abstract:

The supporting policies for renewable energy have been designed to deploy renewable energy technology targeting domestic market. The government encourages market creation through obligations such as FIT or RPS on an energy supplier. With these policy measures, the securing vast market needs to induce technology development. Furthermore, it is crucial that ensuring developing market can make the environment nurture the renewable energy industry. Overseas expansion to countries being in demand is essential under immature domestic market. Extending its business abroad can make the domestic company get the knowledge through learning-by-doing. Besides, operation in the countries to be rich in renewable resources such as weather conditions helps to develop proven track record required for verifying technologies. This paper figures out the factor to hamper the global market entry and build up the strategies to overcome difficulties. Survey conducted renewable energy company having overseas experiences at least once. Based on the survey we check the obstacle against exporting home goods and services. As a result, securing funds is salient fact to proceed to business. It is difficult that only private bank or investment agencies participate in the project under uncertainty which renewable energy development project bears inherently. These uncertainties need public fund such as ODA to encourage private sectors to start a business. Furthermore, international organizations such as IRENA or multilateral development banks as WBG play a role to guarantee the investment including risk insurance against uncertainty. It can also manage excavation business cooperating with developing countries and supplement inadequate government funding involved. With survey results strategies to obtain the order, the international organization places are categorized according to the type of getting a contract. This paper suggests 3 types approaching to the international organization project (going through international competitive bidding, using ODA and project financing) and specifies the role of government to support the domestic firms with running out of funds. Under renewable energy industry environment where hard to being created as a spontaneous market, government policy approach needs to motivate the actors to get into the business. It is one of the good strategies that countries with the low demand of renewable energies participate in the project international agencies order in the developing countries having abundant resources. This provides crucial guidance for the formulation of renewable energy development policy and planning with consideration of business opportunities and funding.

Keywords: exporting strategies, multilateral development banks, promoting in developing countries, renewable energy technologies

Procedia PDF Downloads 500