Search results for: generating sets

Authors: Migena Ceyhan, Zeynep Orhan, Dimitrios Karras

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People in modern societies are continuously sharing their experiences, emotions, and thoughts in different areas of life. The information reaches almost everyone in real-time and can have an important impact in shaping people’s way of living. This phenomenon is very well recognized and advantageously used by the market representatives, trying to earn the most from this means. Given the abundance of information, people and organizations are looking for efficient tools that filter the countless data into important information, ready to analyze. This paper is a modest contribution in this field, describing the process of automatically classifying social media comments in the Turkish language into positive or negative. Once data is gathered and preprocessed, feature sets of selected single words or groups of words are build according to the characteristics of language used in the texts. These features are used later to train, and test a system according to different machine learning algorithms (Naïve Bayes, Sequential Minimal Optimization, J48, and Bayesian Linear Regression). The resultant high accuracies can be important feedback for decision-makers to improve the business strategies accordingly.

Keywords: feature selection, machine learning, natural language processing, sentiment analysis, social media reviews

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Authors: Ahmed M. Ashteyat

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Artificial Neural Network (ANN) models have been widely used in material modeling, inter-correlations, as well as behavior and trend predictions when the nonlinear relationship between system parameters cannot be quantified explicitly and mathematically. In this paper, ANN was used to predict the residual modulus of elasticity (RME) of self compacted concrete (SCC) damaged by heat. The ANN model was built, trained, tested and validated using a total of 112 experimental data sets, gathered from available literature. The data used in model development included temperature, relative humidity conditions, mix proportions, filler types, and fiber type. The result of ANN training, testing, and validation indicated that the RME of SCC, exposed to different temperature and relative humidity levels, could be predicted accurately with ANN techniques. The reliability between the predicated outputs and the actual experimental data was 99%. This show that ANN has strong potential as a feasible tool for predicting residual elastic modulus of SCC damaged by heat within the range of input parameter. The ANN model could be used to estimate the RME of SCC, as a rapid inexpensive substitute for the much more complicated and time consuming direct measurement of the RME of SCC.

Keywords: residual modulus of elasticity, artificial neural networks, self compacted-concrete, material modeling

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Authors: Srinivasarao Kondaparla, Utsab Debnath, Awakash Soni, Vasantha Rao Dola, Manish Sinha, Kumkum Kumkum Srivastava, Sunil K. Puri, Seturam B. Katti

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In a focused exploration, we have designed synthesized and biologically evaluated chiral conjugated new chloroquine (CQ) analogs with substituted piperazines as antimalarial agents. In vitro as well as in vivo studies revealed that compound 7c showed potent activity [for in vitro IC₅₀= 56.98nM (3D7), 97.76nM (K1); for in vivo (up to at the dose of 12.5 mg/kg); SI = 3510] as a new lead of antimalarial agent. Other compounds 6b, 6d, 7d, 7h, 8c, 8d, 9a, and 9c are also showing moderate activity against CQ-sensitive (3D7) strain and superior activity against resistant (K1) strain of P. falciparum. Furthermore, we have carried out docking and 3D-QSAR studies of all in-house data sets (168 molecules) of chiral CQ analogs to explain the structure activity relationships (SAR). Our new findings specified the significance of H-bond interaction with the side chain of heme for biological activity. In addition, the 3D-QSAR study against 3D7 strain indicated the favorable and unfavorable sites of CQ analogs for incorporating steric, hydrophobic and electropositive groups to improve the antimalarial activity.

Keywords: piperazines, CQ-sensitive strain-3D7, in-vitro and in-vivo assay, docking, 3D-QSAR

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Authors: Rajkumar Ghosh

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The paper presents a comprehensive study of the structural analysis of the Chaura Thrust in Himachal Pradesh, India. The research focuses on several key aspects, including the activation timing of the Main Central Thrust (MCT) and the South Tibetan Detachment System (STDS), the identification and characterization of mylonitised zones through microscopic examination, and the understanding of box fold characteristics and their implications in the regional geology of the Himachal Himalaya. The primary objective of the study is to provide field documentation of the Chaura Thrust, which was previously considered a blind thrust with limited field evidence. Additionally, the research aims to characterize box folds and their signatures within the broader geological context of the Himachal Himalaya, document the temperature range associated with grain boundary migration (GBM), and explore the overprinting structures related to multiple sets of Higher Himalayan Out-of-Sequence Thrusts (OOSTs). The research methodology employed geological field observations and microscopic studies. Samples were collected along the Jhakri-Chaura transect at regular intervals of approximately 1 km to conduct strain analysis. Microstructural studies at the grain scale along the Jhakri-Wangtu transect were used to document the GBM-associated temperature range. The study reveals that the MCT activated in two parts, as did the STDS, and provides insights into the activation ages of the Main Boundary Thrust (MBT) and the Main Frontal Thrust (MFT). Under microscopic examination, the study identifies two mylonitised zones characterized by S-C fabric, and it documents dynamic and bulging recrystallization, as well as sub-grain formation. Various types of crenulated schistosity are observed in photomicrographs, including a rare occurrence where crenulation cleavage and sigmoid Muscovite are found juxtaposed. The study also notes the presence of S/SE-verging meso- and micro-scale box folds around Chaura, which may indicate structural upliftment. Kink folds near Chaura are visible, while asymmetric shear sense indicators in augen mylonite are predominantly observed under microscopic examination. Moreover, the research highlights the documentation of the Higher Himalayan Out-of-Sequence Thrust (OOST) in Himachal Pradesh, which activated the MCT and occurred within a zone south of the Main Central Thrust Upper (MCTU). The presence of multiple sets of OOSTs suggests a zigzag pattern of strain accumulation in the area. The study emphasizes the significance of understanding the overprinting structures associated with OOSTs. Overall, this study contributes to the understanding of the structural analysis of the Chaura Thrust and its implications in the regional geology of the Himachal Himalaya. The research underscores the importance of microscopic studies in identifying mylonitised zones and various types of crenulated schistosity. Additionally, the study documents the GBM-associated temperature range and provides insights into the activation of the Higher Himalayan Out-of-Sequence Thrust (OOST) in Himachal Pradesh. The findings of the study were obtained through geological field observations, microscopic studies, and strain analysis, offering valuable insights into the activation timing, mylonitization characteristics, and overprinting structures related to the Chaura Thrust and the broader tectonic framework of the region.

Keywords: Main Central Thrust, Jhakri Thrust, Chaura Thrust, Higher Himalaya, Out-of-Sequence Thrust, Sarahan Thrust

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Authors: Saleh Alshehri

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Thermoelectric technology is currently being used in many industrial applications for cooling, heating and generating electricity. This research mainly focuses on using thermoelectric to cool down high-speed computer chips at different operating conditions. A previously developed and validated three-dimensional model for optimizing and assessing the performance of cascaded thermoelectric and non-cascaded thermoelectric is used in this study to investigate the possibility of decreasing the hotspot temperature of computer chip. Additionally, a test assembly is built and tested at steady-state and transient conditions. The obtained optimum thermoelectric current at steady-state condition is used to conduct a number of pulsed tests (i.e. transient tests) with different shapes to cool the computer chips hotspots. The results of the steady-state tests showed that at hotspot heat rate of 15.58 W (5.97 W/cm²), using thermoelectric current of 4.5 A has resulted in decreasing the hotspot temperature at open circuit condition (89.3 °C) by 50.1 °C. Maximum and minimum hotspot temperatures have been affected by ON and OFF duration of the electrical current pulse. Maximum hotspot temperature was resulted by longer OFF pulse period. In addition, longer ON pulse period has generated the minimum hotspot temperature.

Keywords: thermoelectric generator, TEG, thermoelectric cooler, TEC, chip hotspots, electronic cooling

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Authors: Jaisridhar P.

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The present study aimed to investigate preferred teaching styles of young faculties in agricultural education among 23 constituent colleges of Tamil Nadu Agricultural University (TNAU) using Staffordshire Evaluation of Teaching Styles (SETS). An onlinesurvey was conducted among 156 young faculties of 2014 Batch working in different constituent colleges of TNAU and 73 faculties respondent to the survey. The results showed that 62.53 percent preferred “The one-off teacher” stylefollowed by62.26 percent preferring “The student centered, sensitive teacher” style.“The all-round flexible and adaptable teaching style” was preferred by 61.64 percent. The Official Curriculum Teacher” with 61.23 per cent preferring this style.58.97 per cent preferred “The Big Conference Teacher” followed by 58.08 percent of the faculties preferring “The Straight Fact no Non-sense Teacher” type of teaching style. From the results, it wasconcluded that blended teaching approach can balance a teacher’s personal strengths and interest with student’s needs, and curricular requirements enables a teacher to tailor their teaching according to the student’s needs and as per subject matter.

Keywords: teaching styles, assistant professors, agriculture, tamil nadu

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Authors: Darsh N. Patel, Eric Olson

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Fractals can be found everywhere, whether it be the shape of a leaf or a system of blood vessels. Fractals are used to help study and understand different physical and mathematical processes; however, their artistic nature is also beautiful to simply explore. This project explores fractals generated by a cubically convergent extension to Newton's method. With this iteration as a starting point, a complex plane spanning from -2 to 2 is created with a color wheel mapped onto it. Next, the polynomial whose roots the fractal will generate from is established. From the Fundamental Theorem of Algebra, it is known that any polynomial has as many roots (counted by multiplicity) as its degree. When generating the fractals, each root will receive its own color. The complex plane can then be colored to indicate the basins of attraction that converge to each root. From a computational point of view, this project’s code identifies which points converge to which roots and then obtains fractal images. A zoom path into the fractal was implemented to easily visualize the self-similar structure. This path was obtained by selecting keyframes at different magnifications through which a path is then interpolated. Using parallel processing, many images were generated and condensed into a video. This project illustrates how practical techniques used for scientific visualization can also have an artistic side.

Keywords: fractals, cubic method, Julia programming language, basin of attraction

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Authors: Fatemeh Abdollahi, Munn-Sann Lye, Jamshid Yazdani Charati, Mehran Zarghami

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Background: In March 2020, the World Health Organization (WHO) declared the outbreak of a new coronavirus disease, COVID-19, as a public health concern and pandemic. This situation is generating psychological consequences such as stress, anxiety, depression, and intimate partner violence (IPV) throughout the population. This is a brief note on the magnitude of this threat and different ways for abused women to minimize the effects of it in their daily life. Methods: A literature review was conducted using the MEDLINE, PSYCHINFO, and SCIENCE DIRECT databases. The keywords used included intimate partner violence, abuse, victims, pandemic, quarantine, coronavirus, and COVID-19. A Google search was also conducted using these words to identify reports published in non-indexed health care and social science journals. The literature search was restricted to English language studies. Results: The prevalence of IPV and its consequences are rising during such a pandemic. Having sufficient support from healthcare workers and acquaintances is critical for women in such circumstances. Conclusion: Community members, healthcare providers, governments, and policymakers should be informed of the increased risk of IPV during such a pandemic. They should provide a supporting structure for abused women. Social networking is also a good approach that could help abusive women during this situation.

Keywords: covid-19, intimate partner violence, pandemic, women

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Authors: C. Asha Poorna, P. G. Vinod, A. R. R. Menon

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Currently increasing population and their activities like urbanization and industrialization generating the greatest environmental, issue called Waste. And the major problem in waste management is selection of an appropriate site for waste disposal. The selection of suitable site have constrains like environmental, economical and political considerations. In this paper we discuss the strategies to be followed while selecting a site for decentralized system for solid waste disposal, using Geographic Information System (GIS), the Analytical Hierarchy Process (AHP) and the remote sensing method for Thiruvananthapuram corporation area. It is located on the west coast of India near the extreme south of the mainland. It lies on the shores of Killiyar and Karamana River. Being on the basin the waste managements must be regulated with the water body. The different criteria considered for waste disposal site selection are lithology, surface water, aquifer, groundwater, land use, contours, aspect, elevation, slope, and distance to road, distance from settlement are examined in relation to land fill site selection. Each criterion was identified and weighted by AHP score and mapped using GIS technique and suitable map is prepared by overlay analysis.

Keywords: waste disposal, solid waste management, Geographic Information System (GIS), Analytical Hierarchy Process (AHP)

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Authors: Stephen Orimoloye, Jose Horrillo-Caraballo, Harshinie Karunarathna, Dominic E. Reeve

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Prediction of wave overtopping is an essential component of coastal seawall designing and management. Not only that excessive overtopping is reported for impermeable seawalls under bimodal waves, but overtopping is also showing a high sensitivity to the peakedness of the random wave propagation patterns. In the present study, we present a comprehensive analysis of the effects of peakedness of bimodal wave patterns of the overtopping of sloping seawalls. An energy-conserved bimodal spectrum with four different spectra peak periods and swell percentages was applied to estimate wave overtopping in both numerical and experimental flumes. Results of incident surface elevations and bimodal spectra were accurately captured across the flume domain using sets of well-positioned resistant-type wave gauges. Peakedness characteristics of the wave patterns were extracted to derive a relationship between the non-dimensional overtopping and the peakedness across the wave groups in the wave series. The full paper will briefly describe the development of the spectrum and present a comprehensive results analysis leading to the derivation of the relationship between dimensionless overtopping and peakedness of bimodal waves.

Keywords: wave overtopping, peakedness, bimodal waves, swell percentages

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Authors: Manoj Kumar

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Ionization cross sections of molecules due to electron impact play an important role in chemical processes in various branches of applied physics, such as radiation chemistry, gas discharges, plasmas etching in semiconductors, planetary upper atmospheric physics, mass spectrometry, etc. In the present work, we have calculated the total ionization cross sections for Adenine (C₅H₅N₅), a biologically important molecule, by electron impact in the incident electron energy range from ionization threshold to 2 keV employing a well-known Jain-Khare semiempirical formulation based on Bethe and Möllor cross sections. In the non-availability of the experimental results, the present results are in good agreement qualitatively as well as quantitatively with available theoretical results. The present results drive our confidence for further investigation of complex bio-molecule with better accuracy. Notwithstanding, the present method can deduce reliable cross-sectional data for complex targets with adequate accuracy and may facilitate the acclimatization of calculated cross-sections into atomic molecular cross-section data sets for modeling codes and other applications.

Keywords: electron impact ionization cross-sections, oscillator strength, jain-khare semiempirical approach

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Authors: Akshay Paranjape, Nils Plettenberg, Robert Schmitt

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Producing faulty products can be costly for manufacturing companies and wastes resources. To reduce scrap rates in manufacturing, process parameters can be optimized using machine learning. Thus far, research mainly focused on optimizing specific processes using traditional algorithms. To develop a framework that enables real-time optimization based on a predictive model for an arbitrary production process, this study explores the application of reinforcement learning (RL) in this field. Based on a thorough review of literature about RL and process parameter optimization, a model based on maximum a posteriori policy optimization that can handle both numerical and categorical parameters is proposed. A case study compares the model to state–of–the–art traditional algorithms and shows that RL can find optima of similar quality while requiring significantly less time. These results are confirmed in a large-scale validation study on data sets from both production and other fields. Finally, multiple ways to improve the model are discussed.

Keywords: reinforcement learning, production process optimization, evolutionary algorithms, policy optimization, actor critic approach

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Authors: Chia-Hao Chang, Geng-Gui Wang, Jee-Cheng Wu

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The prediction of a landslide is a difficult task because it requires a detailed study of past activities using a complete range of investigative methods to determine the changing condition. In this research, first step, LiDAR 1-meter by 1-meter resolution of digital elevation model (DEM) was used to generate six environmental factors of landslide. Then, back-propagation neural networks (BPNN) was adopted to identify scarp, landslide areas and non-landslide areas. The BPNN uses 6 environmental factors in input layer and 1 output layer. Moreover, 6 landslide areas are used as training areas and 4 landslide areas as test areas in the BPNN. The hidden layer is set to be 1 and 2; the hidden layer neurons are set to be 4, 5, 6, 7 and 8; the learning rates are set to be 0.01, 0.1 and 0.5. When using 1 hidden layer with 7 neurons and the learning rate sets to be 0.5, the result of Network training root mean square error is 0.001388. Finally, evaluation of BPNN classification accuracy by the confusion matrix shows that the overall accuracy can reach 94.4%, and the Kappa value is 0.7464.

Keywords: digital elevation model, DEM, environmental factors, back-propagation neural network, BPNN, LiDAR

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Authors: Muhammad Imran Ahmad, Ruzelita Ngadiran, Mohd Nazrin Md Isa, Nor Ashidi Mat Isa, Mohd ZaizuIlyas, Raja Abdullah Raja Ahmad, Said Amirul Anwar Ab Hamid, Muzammil Jusoh

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This paper presents two technique, local feature extraction using image spectrum and low frequency spectrum modelling using GMM to capture the underlying statistical information to improve the performance of face recognition system. Local spectrum features are extracted using overlap sub block window that are mapping on the face image. For each of this block, spatial domain is transformed to frequency domain using DFT. A low frequency coefficient is preserved by discarding high frequency coefficients by applying rectangular mask on the spectrum of the facial image. Low frequency information is non Gaussian in the feature space and by using combination of several Gaussian function that has different statistical properties, the best feature representation can be model using probability density function. The recognition process is performed using maximum likelihood value computed using pre-calculate GMM components. The method is tested using FERET data sets and is able to achieved 92% recognition rates.

Keywords: local features modelling, face recognition system, Gaussian mixture models, Feret

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Authors: Rahul Mohite, Lahcen Ouarbya

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This paper focuses on the interplay between humans and computer systems and the ability of these systems to understand and respond to human emotions, including non-verbal communication. Current emotion recognition systems are based solely on either facial or verbal expressions. The limitation of these systems is that it requires large training data sets. The paper proposes a system for recognizing human emotions that combines both speech and emotion recognition. The system utilizes advanced techniques such as deep learning and image recognition to identify facial expressions and comprehend emotions. The results show that the proposed system, based on the combination of facial expression and speech, outperforms existing ones, which are based solely either on facial or verbal expressions. The proposed system detects human emotion with an accuracy of 86%, whereas the existing systems have an accuracy of 70% using verbal expression only and 76% using facial expression only. In this paper, the increasing significance and demand for facial recognition technology in emotion recognition are also discussed.

Keywords: facial reputation, expression reputation, deep gaining knowledge of, photo reputation, facial technology, sign processing, photo type

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Authors: Ioannis Andrianakis, Manolis Falelakis, Maria Pavlidou, Konstantinos Papakonstantinou, Ermioni Avramidou, Dimitrios Kalogiannis, Nikolaos Milios, Katerina Bountakidou, Kiriakos Chatzidimitriou, Panagiotis Panagiotopoulos

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Artistic events, such as concerts and performances, are challenging to organize because they involve many people with different skill sets. Small and medium venues often struggle to afford the costs and overheads of booking and hosting remote artists, especially if they lack sponsors or subsidies. This limits the opportunities for both venues and artists, especially those outside of big cities. However, more and more research shows that audiences prefer smaller-scale events and concerts, which benefit local economies and communities. To address this challenge, our project “PerformAnts: Digital Event Manager-Organizer” aims to develop a smart digital tool that automates and optimizes the processes and costs of live shows and tours. By using machine learning, applying best practices and training users through workshops, our platform offers a comprehensive solution for a growing market, enhances the mobility of artists and the accessibility of venues and allows professionals to focus on the creative aspects of concert production.

Keywords: event organization, creative industries, event promotion, machine learning

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Authors: Patricia Helena Dos Santos Martins, Mateus Atique, Lucas Oliveira Gomes Ferreira

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There is a growing body of literature that recognizes the importance of bibliometric analysis through the evolutionary nuances of a specific field while shedding light on the emerging areas in that field. Surprisingly, its application in the manufacturing research of vitiviniculture is relatively new and, in many instances, underdeveloped. The aim of this study is to present an overview of the bibliometric methodology, with a particular focus on the Meta-Analytical Approach Theory model – TEMAC, while offering step-by-step results on the available techniques and procedures for carrying out studies about the elements associated with vitiviniculture. Where TEMAC is a method that uses metadata to generate heat maps, graphs of keyword relationships and others, with the aim of revealing relationships between authors, articles and mainly to understand how the topic has evolved over the period study and thus reveal which subthemes were worked on, main techniques and applications, helping to understand that topic under study and guide researchers in generating new research. From the studies carried out using TEMAC, it is possible to raise which are the techniques within the statistical control of processes that are most used within the wine industry and thus assist professionals in the area in the application of the best techniques. It is expected that this paper will be a useful resource for gaining insights into the available techniques and procedures for carrying out studies about vitiviniculture, the cultivation of vineyards, the production of wine, and all the ethnography connected with it.

Keywords: TEMAC, vitiviniculture, statical control of process, quality

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Authors: H. Bentarzi, A. Zitouni

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The reliability of the power grid depends on the successful operation of thousands of protective relays. The failure of one relay to operate as intended may lead the entire power grid to blackout. In fact, major power system failures during transient disturbances may be caused by unnecessary protective relay tripping rather than by the failure of a relay to operate. Adequate relay testing provides a first defense against false trips of the relay and hence improves power grid stability and prevents catastrophic bulk power system failures. The goal of this research project is to design and enhance the relay tester using a technology such as Field Programmable Gate Array (FPGA) card NI 7851. A PC based tester framework has been developed using Simulink power system model for generating signals under different conditions (faults or transient disturbances) and LabVIEW for developing the graphical user interface and configuring the FPGA. Besides, the interface system has been developed for outputting and amplifying the signals without distortion. These signals should be like the generated ones by the real power system and large enough for testing the relay’s functionality. The signals generated that have been displayed on the scope are satisfactory. Furthermore, the proposed testing system can be used for improving the performance of protective relay.

Keywords: amplifier class D, field-programmable gate array (FPGA), protective relay, tester

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Authors: Stephen J Futter, Michael I Okereke

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This paper presents an investigation of the premature in-service failure of the engine mounting towers that form part of the bedframe commonly used for industrial power generation applications. The client during a routine in-service assessment of the generator set observed that the engine mounting towers had cracked. Thus, this study has investigated in detail the origin of the crack and proffered solutions to prevent a re-occurrence. Seven step problem solving methodology was followed during this paper. The study used both experimental and numerical approaches to understand, monitor and evaluate the cause and evolution of the premature failure. Findings from this study indicated that the failure resulted from a combination of varied processes from procurement of material parts, material selection, welding processes and inaptly designed load-bearing mechanics of the generating set and its mounting arrangement. These in-field observations and experimental simulations provided insights to design and validate a numerical finite element sub-model of the cracked bedframe considering thermal cycling: designed as part of these investigations. Resulting findings led to a recommendation of several procedural changes that should be adopted by the manufacturer, in order to prevent the re-occurrence of such pre-mature failure in future industrial applications.

Keywords: Engine, Premature Failure, Failure Analysis, Finite Element Model

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Authors: Nuttawoot Nupo, Sayan Panma

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A semigroup S is said to be a left (right) zero semigroup if S satisfies the equation xy=x (xy=y) for all x,y in S. In addition, the semigroup S is called a left (right) group if S is isomorphic to the direct product of a group and a left (right) zero semigroup. The Cayley digraph Cay(S,A) of a semigroup S with a connection set A is defined to be a digraph with the vertex set S and the arc set E(Cay(S,A))={(x,xa) | x∈S, a∈A} where A is any subset of S. All sets in this research are assumed to be finite. Let D be a digraph together with a vertex set V and an arc set E. Let u and v be two different vertices in V and I a nonempty subset of V. The vertices u and v are said to be independent if (u,v)∉E and (v,u)∉E. The set I is called an independent set of D if any two different vertices in I are independent. The independence number of D is the maximum cardinality of an independent set of D. Moreover, the vertices u and v are said to be path independent if there is no dipath from u to v and there is no dipath from v to u. The set I is called a path independent set of D if any two different vertices in I are path independent. The path independence number of D is the maximum cardinality of a path independent set of D. In this research, we describe a lower bound and an upper bound of the independence number of Cayley digraphs of left groups and right groups. Some examples corresponding to those bounds are illustrated here. Furthermore, the exact value of the path independence number of Cayley digraphs of left groups and right groups are also presented.

Keywords: Cayley digraphs, independence number, left groups, path independence number, right groups

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Authors: Kurotimi Maurice Fems, Abara Onu, Francis W. D. Poazi

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Scholars and development economists believe that the development of an economy depends largely on the creative and innovative ingenuity of its entrepreneurs. Others however, are of the opinion that the lack of entrepreneurs or entrepreneurial activities is not a constraint to economic development in any economy, particularly Nigeria. This paper sets out to explore the connectivity between entrepreneurship and economic development from a theoretical point of view, principally in Nigeria. A desk research approach was adopted where a conglomerate of literatures was reviewed on how entrepreneurship can spur economic growth or otherwise. The findings reveal that entrepreneurship is vital to the development of Nigeria and that, universities and other Higher Education Institutions must play the vital role of educating the people on entrepreneurship skills and competences. However, the problems and difficulties entrepreneurs face in Nigeria and the same problems suffocating the growth and development of its economy. Therefore, entrepreneurship cannot be said to be the sole cure for economic under-development in Nigeria but rather other factors such as empowering and granting the institutions autonomy and the provision of infrastructural capability, such as consistent electricity generation and supply, good system of transportation, implementing proposed economic policies in an effective and efficient manner etc., the cultural beliefs and mindset of the citizenry, was also found to be key in the development of any economy.

Keywords: economic underdevelopment, entrepreneurial, entrepreneurship, infrastructural under-development, oil boom, SMEs, unemployable

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Authors: Chusak Thanawattano, Roongroj Bhidayasiri

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This paper proposes a novel feature set utilized for classifying the Parkinson tremor and essential tremor. Ten ET and ten PD subjects are asked to perform kinetic, postural and resting tests. The empirical mode decomposition (EMD) is used to decompose collected tremor signal to a set of intrinsic mode functions (IMF). The IMFs are used for reconstructing representative signals. The feature set is composed of peak frequencies of IMFs and reconstructed signals. Hypothesize that the dominant frequency components of subjects with PD and ET change in different directions for different tests, difference of peak frequencies of IMFs and reconstructed signals of pairwise based tests (kinetic-resting, kinetic-postural and postural-resting) are considered as potential features. Sets of features are used to train and test by classifier including the quadratic discriminant classifier (QLC) and the support vector machine (SVM). The best accuracy, the best sensitivity and the best specificity are 90%, 87.5%, and 92.86%, respectively.

Keywords: tremor, Parkinson, essential tremor, empirical mode decomposition, quadratic discriminant, support vector machine, peak frequency, auto-regressive, spectrum estimation

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Authors: Hanadi Al-Mubaraki, Michael Busler

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Both in the developed and developing countries as well as Gulf Cooperation Council (GCC), the small and medium-sized enterprises (SMEs) proven to be main drivers of jobs creation and tools to accelerate economic development and economic diversification. This paper seeks to investigate and identify the strengths and weakness of SME as a veritable tool in economic development. A survey method was used to gather data from 171 SME from Gulf Cooperation Council (GCC). The research methodology uses a quantitative approach (survey) while data were collected with a structured questionnaire and analyzed with several descriptive statistics. The results of the study, therefore, will present sets of the strengths of SME in GCC such as 1) government supported local products (59%), 2) promoting SME local products rather than international products (47%), 3) reduce the legal and administrative procedures of SME establishment (46%) and weakness of SME in GCC such as: 1) lack of funding during the initial phase of the project (46%), 2) lack of liquidity during project continuity (39%), and 3) strong competition in the domestic and global market (38%). The study findings will be guidelines for academia and practitioners such as governments, policymakers, funded organizations, universities and strategic institutions for successful implementation.

Keywords: SME, economic development, GCC, strengths and weaknesses

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Authors: Nonlapun Meenil, Pisitpong Intarapong, Thitima Wongsheree, Pranchalee Samanpiboon

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In Thailand, once pineapples are harvested, they must be classified into two classes based on their sweetness: sweet and unsweet. This paper has studied and developed the assessment of internal quality of pineapples using a low-cost compact spectroscopy sensor according to the Spectroscopy approach and Neural Network (NN). During the experiments, Batavia pineapples were utilized, generating 100 samples. The extracted pineapple juice of each sample was used to determine the Soluble Solid Content (SSC) labeling into sweet and unsweet classes. In terms of experimental equipment, the sensor cover was specifically designed to install the sensor and light source to read the reflectance at a five mm depth from pineapple flesh. By using a spectroscopy sensor, data on visible and near-infrared reflectance (Vis-NIR) were collected. The NN was used to classify the pineapple classes. Before the classification step, the preprocessing methods, which are Class balancing, Data shuffling, and Standardization were applied. The 510 nm and 900 nm reflectance values of the middle parts of pineapples were used as features of the NN. With the Sequential model and Relu activation function, 100% accuracy of the training set and 76.67% accuracy of the test set were achieved. According to the abovementioned information, using a low-cost compact spectroscopy sensor has achieved favorable results in classifying the sweetness of the two classes of pineapples.

Keywords: neural network, pineapple, soluble solid content, spectroscopy

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Authors: Marwa Hussein Mohamed, Mohamed Helmy Khafagy, Samah Ahmed Senbel

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Map Reduce is a programming model used to handle and support massive data sets. Rapidly increasing in data size and big data are the most important issue today to make an analysis of this data. map reduce is used to analyze data and get more helpful information by using two simple functions map and reduce it's only written by the programmer, and it includes load balancing , fault tolerance and high scalability. The most important operation in data analysis are join, but map reduce is not directly support join. This paper explains two-way map-reduce join algorithm, semi-join and per split semi-join, and proposes new algorithm hash semi-join that used hash table to increase performance by eliminating unused records as early as possible and apply join using hash table rather than using map function to match join key with other data table in the second phase but using hash tables isn't affecting on memory size because we only save matched records from the second table only. Our experimental result shows that using a hash table with hash semi-join algorithm has higher performance than two other algorithms while increasing the data size from 10 million records to 500 million and running time are increased according to the size of joined records between two tables.

Keywords: map reduce, hadoop, semi join, two way join

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Authors: Aliana Leong, T. C. Huan

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The purpose of Nostalgic themed tourism product is becoming popular in many countries. This study intends to investigate the role of nostalgia in destination image, experiential value and their effect on subsequent behavioral intention. The survey used stratified sampling method to include respondents from all the nearby Asian regions. The sampling is based on the data of inbound tourists provided by the Statistics and Census Service (DSEC) of government of Macau. The questionnaire consisted of five sections of 5 point Likert scale questions: (1) nostalgia, (2) destination image both before and after experience, (3) expected value, (4) experiential value, and (5) future visit intention. Data was analysed with structural equation modelling. The result indicates that nostalgia plays an important part in forming destination image and experiential value before individual had a chance to experience the destination. The destination image and experiential value share a bidirectional causal relationship that eventually contributes to future visit intention. The study also discovered that while experiential value is more effective in generating destination image, the later contribute more to future visit intention. The research design measures destination image and experiential value before and after respondents had experience the destination. The distinction between destination image and expected/experiential value can be examined because the longitudinal design of research method. It also allows this study to observe how nostalgia translates to future visit intention.

Keywords: nostalgia, destination image, experiential value, future visit intention

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Authors: Liang-Hsuan Chen, Sheng-Shing Nien

Abstract:

This study aims to develop approaches to formulate intuitionistic fuzzy regression (IFR) models for many decision-making applications in the fuzzy environments using intuitionistic fuzzy observations. Intuitionistic fuzzy numbers (IFNs) are used to characterize the fuzzy input and output variables in the IFR formulation processes. A mathematical programming problem (MPP) is built up to optimally determine the IFR parameters. Each parameter in the MPP is defined as a couple of alternative numerical variables with opposite signs, and an intuitionistic fuzzy error term is added to the MPP to characterize the uncertainty of the model. The IFR model is formulated based on the distance measure to minimize the total distance errors between estimated and observed intuitionistic fuzzy responses in the MPP resolution processes. The proposed approaches are simple/efficient in the formulation/resolution processes, in which the sign of parameters can be determined so that the problem to predetermine the sign of parameters is avoided. Furthermore, the proposed approach has the advantage that the spread of the predicted IFN response will not be over-increased, since the parameters in the established IFR model are crisp. The performance of the obtained models is evaluated and compared with the existing approaches.

Keywords: fuzzy sets, intuitionistic fuzzy number, intuitionistic fuzzy regression, mathematical programming method

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Authors: Siti Salbiah Samsudin, Hamzah Arof, Ainuddin Wahid Abdul Wahab, Mohd Yamani Idna Idris

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Standard X-ray spine images produced by conventional screen-film technique have a limited field of view. This limitation may obstruct a complete inspection of the spine unless images of different parts of the spine are placed next to each other contiguously to form a complete structure. Another solution to producing a whole spine image is by assembling the digitized x-ray images of its parts automatically using image stitching. This paper presents a new Medical Image Stitching (MIS) method that utilizes Minimum Average Correlation Energy (MACE) filters to identify and merge pairs of x-ray medical images. The effectiveness of the proposed method is demonstrated in two sets of experiments involving two databases which contain a total of 40 pairs of overlapping and non-overlapping spine images. The experimental results are compared to those produced by the Normalized Cross Correlation (NCC) and Phase Only Correlation (POC) methods for comparison. It is found that the proposed method outperforms those of the NCC and POC methods in identifying both the overlapping and non-overlapping medical images. The efficacy of the proposed method is further vindicated by its average execution time which is about two to five times shorter than those of the POC and NCC methods.

Keywords: image stitching, MACE filter, panorama image, scoliosis

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Authors: M. Mazraehli, F. Mehrabani, S. Zare

Abstract:

In general, mechanical and hydraulic processes are not independent of each other in jointed rock masses. Therefore, the study on hydro-mechanical coupling of geomaterials should be a center of attention in rock mechanics. Rocks in their nature contain discontinuities whose presence extremely influences mechanical and hydraulic characteristics of the medium. Assuming this effect, experimental investigations on intact rock cannot help to identify jointed rock mass behavior. Hence, numerical methods are being used for this purpose. In this paper, water inflow into a tunnel under significant water table has been estimated using hydro-mechanical discrete element method (HM-DEM). Besides, effects of geomechanical and geometrical parameters including constitutive model, friction angle, joint spacing, dip of joint sets, and stress factor on the estimated inflow rate have been studied. Results demonstrate that inflow rates are not identical for different constitutive models. Also, inflow rate reduces with increased spacing and stress factor.

Keywords: distinct element method, fluid flow, hydro-mechanical coupling, jointed rock mass, underground excavations

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Authors: Branden Heng, Harsheni Siddharthan, Allison Tseng, Paul Toprac, Sarah Abraham, Etienne Vouga

Abstract:

The goal of this project was to evaluate and document the capabilities and limitations of AI tools for empowering small teams to create high-budget, high-profile (AAA) 3D games typically developed by large studios. Two teams of novice game developers attempted to create two different games using AI and Unreal Engine 5.3. First, the teams evaluated 60 AI art, design, sound, and programming tools by considering their capability, ease of use, cost, and license restrictions. Then, the teams used a shortlist of 12 AI tools for game development. During this process, the following tools were found to be the most productive: (i) ChatGPT 4.0 for both game and narrative concepts and documentation; (ii) Dall-E 3 and OpenArt for concept art; (iii) Beatoven for music drafting; (iv) ChatGPT 4.0 and Github Copilot for generating simple code and to complement human-made tutorials as an additional learning resource. While current generative AI may appear impressive at first glance, the assets they produce fall short of AAA industry standards. Generative AI tools are helpful when brainstorming ideas such as concept art and basic storylines, but they still cannot replace human input or creativity at this time. Regarding programming, AI can only effectively generate simple code and act as an additional learning resource. Thus, generative AI tools are, at best, tools to enhance developer productivity rather than as a system to replace developers.

Keywords: AAA games, AI, automation tools, game development

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