Search results for: human machine interface

Authors: Yongjiang Zhang, Kallol Barai, Umesh R. Hodeghatta, Trang Tran, Vikas Dhiman

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Detecting water stress on crops early and accurately is crucial to minimize its impact. This study aims to measure water stress in wild blueberry crops non-destructively by analyzing proximal hyperspectral data. The data collection took place in the summer growing season of 2022. A drought experiment was conducted on wild blueberries in the randomized block design in the greenhouse, incorporating various genotypes and irrigation treatments. Hyperspectral data ( spectral range: 400-1000 nm) using a handheld spectroradiometer and leaf water potential data using a pressure chamber were collected from wild blueberry plants. Machine learning techniques, including multiple regression analysis and random forest models, were employed to predict leaf water potential (MPa). We explored the optimal wavelength bands for simple differences (RY1-R Y2), simple ratios (RY1/RY2), and normalized differences (|RY1-R Y2|/ (RY1-R Y2)). NDWI ((R857 - R1241)/(R857 + R1241)), SD (R2188 – R2245), and SR (R1752 / R1756) emerged as top predictors for predicting leaf water potential, significantly contributing to the highest model performance. The base learner models achieved an R-squared value of approximately 0.81, indicating their capacity to explain 81% of the variance. Research is underway to develop a neural vegetation index (NVI) that automates the process of index development by searching for specific wavelengths in the space ratio of linear functions of reflectance. The NVI framework could work across species and predict different physiological parameters.

Keywords: hyperspectral reflectance, water potential, spectral indices, machine learning, wild blueberries, optimal bands

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Authors: Ibrahim Laro ABUBAKAR

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The study examined the Availability and Utilization of E-Learning Technologies in Teaching of Human Kinetics and Health Education courses in Nigerian Universities, specifically, Universities in Kwara State. Two purposes were formulated to guide the study from which two research questions and two hypotheses were raised. The descriptive research design was used in the research. Three Hundred respondents (100 Lecturers and 200 Students) made up the population for the study. There was no sampling, as the population of the study was not much. A structured questionnaire tagged ‘Availability and Utilization of E-Learning Technologies in Teaching and Learning Questionnaire’ (AUETTLQ) was used for data collection. The questionnaire was subjected to face and content validation, and it was equally pilot tested. The validation yielded a reliability coefficient of 0.78. The data collected from the study were statistically analyzed using frequencies and percentage count for personal data of the respondents, mean and standard deviation to answer the research questions. The null hypotheses were tested at 0.05 level of significance using the independent t-test. One among other findings of this study showed that lecturers and Student are aware of synchronous e-learning technologies in teaching and learning of Human Kinetics and Health Education but often utilize the synchronous e-learning technologies. It was recommended among others that lecturers and Students should be sensitized through seminars and workshops on the need to maximally utilize available e-learning technologies in teaching and learning of Human Kinetics and Health Education courses in Universities.

Keywords: awareness, utilization, E-Learning, technologies, human kinetics synchronous

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Authors: Deepika Christopher, Garima Anand

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To determine the best model for churn prediction in the telecom industry, this paper compares 11 machine learning algorithms, namely Logistic Regression, Support Vector Machine, Random Forest, Decision Tree, XGBoost, LightGBM, Cat Boost, AdaBoost, Extra Trees, Deep Neural Network, and Hybrid Model (MLPClassifier). It also aims to pinpoint the top three factors that lead to customer churn and conducts customer segmentation to identify vulnerable groups. According to the data, the Logistic Regression model performs the best, with an F1 score of 0.6215, 81.76% accuracy, 68.95% precision, and 56.57% recall. The top three attributes that cause churn are found to be tenure, Internet Service Fiber optic, and Internet Service DSL; conversely, the top three models in this article that perform the best are Logistic Regression, Deep Neural Network, and AdaBoost. The K means algorithm is applied to establish and analyze four different customer clusters. This study has effectively identified customers that are at risk of churn and may be utilized to develop and execute strategies that lower customer attrition.

Keywords: attrition, retention, predictive modeling, customer segmentation, telecommunications

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Authors: Housein Deli, Loui Al-Shrouf, Hammoud Al Joumaa, Mohieddine Jelali

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When forming metallic materials, fluctuations in material properties, process conditions, and wear lead to deviations in the component geometry. Several hundred features sometimes need to be measured, especially in the case of functional and safety-relevant components. These can only be measured offline due to the large number of features and the accuracy requirements. The risk of producing components outside the tolerances is minimized but not eliminated by the statistical evaluation of process capability and control measurements. The inspection intervals are based on the acceptable risk and are at the expense of productivity but remain reactive and, in some cases, considerably delayed. Due to the considerable progress made in the field of condition monitoring and measurement technology, permanently installed sensor systems in combination with machine learning and artificial intelligence, in particular, offer the potential to independently derive forecasts for component geometry and thus eliminate the risk of defective products - actively and preventively. The reliability of forecasts depends on the quality, completeness, and timeliness of the data. Measuring all geometric characteristics is neither sensible nor technically possible. This paper, therefore, uses the example of car seat rail production to discuss the necessary first step of feature selection and reduction by correlation analysis, as otherwise, it would not be possible to forecast components in real-time and inline. Four different car seat rails with an average of 130 features were selected and measured using a coordinate measuring machine (CMM). The run of such measuring programs alone takes up to 20 minutes. In practice, this results in the risk of faulty production of at least 2000 components that have to be sorted or scrapped if the measurement results are negative. Over a period of 2 months, all measurement data (> 200 measurements/ variant) was collected and evaluated using correlation analysis. As part of this study, the number of characteristics to be measured for all 6 car seat rail variants was reduced by over 80%. Specifically, direct correlations for almost 100 characteristics were proven for an average of 125 characteristics for 4 different products. A further 10 features correlate via indirect relationships so that the number of features required for a prediction could be reduced to less than 20. A correlation factor >0.8 was assumed for all correlations.

Keywords: long-term SHM, condition monitoring, machine learning, correlation analysis, component prediction, wear prediction, regressions analysis

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Authors: Julio Jesus Salazar, Julio Jesus De Lama

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the fundamental objective of hydrological studies applied to the engineering field is to determine the statistically consistent volumes or water flows that, in each case, allow us to size or design a series of elements or structures to effectively manage and develop a river basin. To determine these values, there are several ways of working within the framework of traditional hydrology: (1) Study each of the factors that influence the hydrological cycle, (2) Study the historical behavior of the hydrology of the area, (3) Study the historical behavior of hydrologically similar zones, and (4) Other studies (rain simulators or experimental basins). Of course, this range of studies in a certain basin is very varied and complex and presents the difficulty of collecting the data in real time. In this complex space, the study of variables can only be overcome by collecting and transmitting data to decision centers through the Internet of things and artificial intelligence. Thus, this research work implemented the learning project of the sub-basin of the Shullcas river in the Andean basin of the Mantaro river in Peru. The sensor firmware to collect and communicate hydrological parameter data was programmed and tested in similar basins of the European Union. The Machine Learning applications was programmed to choose the algorithms that direct the best solution to the determination of the rainfall-runoff relationship captured in the different polygons of the sub-basin. Tests were carried out in the mountains of Europe, and in the sub-basins of the Shullcas river (Huancayo) and the Yauli river (Jauja) with heights close to 5000 m.a.s.l., giving the following conclusions: to guarantee a correct communication, the distance between devices should not pass the 15 km. It is advisable to minimize the energy consumption of the devices and avoid collisions between packages, the distances oscillate between 5 and 10 km, in this way the transmission power can be reduced and a higher bitrate can be used. In case the communication elements of the devices of the network (internet of things) installed in the basin do not have good visibility between them, the distance should be reduced to the range of 1-3 km. The energy efficiency of the Atmel microcontrollers present in Arduino is not adequate to meet the requirements of system autonomy. To increase the autonomy of the system, it is recommended to use low consumption systems, such as the Ashton Raggatt McDougall or ARM Cortex L (Ultra Low Power) microcontrollers or even the Cortex M; and high-performance direct current (DC) to direct current (DC) converters. The Machine Learning System has initiated the learning of the Shullcas system to generate the best hydrology of the sub-basin. This will improve as machine learning and the data entered in the big data coincide every second. This will provide services to each of the applications of the complex system to return the best data of determined flows.

Keywords: hydrology, internet of things, machine learning, river basin

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Authors: Essang Anwana Onuntuei, Chinyere Blessing Azunwoke

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The study focused on determining the impact of multimedia systems and computer graphic design on global and local scale economies. Firstly, the study identified the major players and the world’s top five digital media distribution in the digital media market. It then examined if the Digital Media Vendor and Market Shares differ or remain the same. Also, the research studied whether the global and local desktop, mobile, and tablet markets differ. Again, the study assessed the link between the top five Digital Media and Global Market Shares. Finally, the paper observed the extent of growth rate, economic gains, major setbacks, and opportunities within the Digital Media industry amidst global and local scale economic flux. A multiple regression analysis method was used to analyse the significant influence of the top five Global Digital Media on the total market share. Furthermore, to analyse the global Digital Media Vendor Market share data, and so on, the Analysis of Variance (ANOVA) was employed. The findings were intriguing and significant.

Keywords: multimedia, systems design, computer graphics, digital media market, media vendor, global market share, user interface, social media, market size

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Authors: Wen-Jay Lee, Kuo-Ning Chiang

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The graphene binding with silicon substrate has apparently Schottky barriers property, which can be used in the application of solar cell and light source. Because graphene has only one atom layer, the atomistic structure of graphene binding with the silicon surface plays an important role to affect the properties of graphene. In this work, temperature effect on the morphology of graphene sheet attached on different crystal planes of silicon substrates are investigated by Molecular dynamics (MD) (LAMMPS, developed by Sandia National Laboratories). The results show that the covered graphene sheet would cause the structural deformation of the surface Si atoms of stubtrate. To achieve a stable state in the binding process, the surface Si atoms would adjust their position and fit the honeycomb structure of graphene after the graphene attaches to the Si surface. The height contour of graphene on different plane of silicon surfaces presents different pattern, leading the local residual stress at the interface. Due to the high density of dangling bond on the Si (111)7x7 surface, the surface of Si(111)7x7 is not matching with the graphene so well in contrast with Si(100)2x1and Si(111)2x1. Si(111)7x7 is found that only partial silicon adatoms are rearranged on surface after the attachment when the temperature is lower than 200K, As the temperature gradually increases, the deformation of surface structure becomes significant, as well as the residue stress. With increasing temperature till the 815K, the graphene sheet begins to destroy and mixes with the silicon atoms. For the Si(100)2x1 and Si(111)2x1, the silicon surface structure keep its structural arrangement with a higher temperature. With increasing temperature, the residual stress gradually decrease till a critical temperatures. When the temperature is higher than the critical temperature, the residual stress gradually increases and the structural deformation is found on the surface of the Si substrates.

Keywords: molecular dynamics, graphene, silicon, Schottky barriers, interface

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Authors: Wanhyun Cho, Soonja Kang, Sangkyoon Kim, Soonyoung Park

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In this paper, we propose a novel inference algorithm for the multi-class Gaussian process classification model that can be used in the field of human behavior recognition. This algorithm can drive simultaneously both a posterior distribution of a latent function and estimators of hyper-parameters in a Gaussian process classification model with multi-class. Our algorithm is based on the Laplace approximation (LA) technique and variational EM framework. This is performed in two steps: called expectation and maximization steps. First, in the expectation step, using the Bayesian formula and LA technique, we derive approximately the posterior distribution of the latent function indicating the possibility that each observation belongs to a certain class in the Gaussian process classification model. Second, in the maximization step, using a derived posterior distribution of latent function, we compute the maximum likelihood estimator for hyper-parameters of a covariance matrix necessary to define prior distribution for latent function. These two steps iteratively repeat until a convergence condition satisfies. Moreover, we apply the proposed algorithm with human action classification problem using a public database, namely, the KTH human action data set. Experimental results reveal that the proposed algorithm shows good performance on this data set.

Keywords: bayesian rule, gaussian process classification model with multiclass, gaussian process prior, human action classification, laplace approximation, variational EM algorithm

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Authors: Jae-Yeong Choi, Gyu-Mok Jeon, Jong-Chun Park, Yong-Jin Cho, Seok-Tae Yoon

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When air flow is injected into water, bubbles are formed in various types inside the water pool along with the air flow rate. The bubbles are floated in equilibrium with forces such as buoyancy, surface tension and shear force. Single bubble generated at low flow rate maintains shape, but bubbles with high flow rate break up to make mixing and turbulence. In addition to this phenomenon, as the hot air bubbles are injected into the water, heat affects the interface of phases. Therefore, the main scope of the present work reveals how to proceed heat transfer between water and hot air bubbles injected into water. In the present study, a series of CFD simulation for the heat transfer of hot bubbles injected through a nozzle near the bottom in a cylindrical water column are performed using a commercial CFD software, STAR-CCM+. The governing equations for incompressible and viscous flow are the continuous and the RaNS (Reynolds- averaged Navier-Stokes) equations and discretized by the FVM (Finite Volume Method) manner. For solving multi-phase flow, the Eulerian multiphase model is employed and the interface is defined by VOF (Volume-of-Fluid) technique. As a turbulence model, the SST k-w model considering the buoyancy effects is introduced. For spatial differencing the 3th-order MUSCL scheme is adopted and the 2nd-order implicit scheme for time integration. As the results, the dynamic behavior of the rising hot bubbles with the flow rate injected and regarding heat transfer mechanism are discussed based on the simulation results.

Keywords: heat transfer, hot bubble injection, eulerian multiphase model, flow rate, CFD (Computational Fluid Dynamics)

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Authors: Angelos Kaminis, Dakotah Stirnweis

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Advances in robotic technology have driven the development of improved robotic companions in the last couple decades. However, commercially available robotic companions lack the ability to create an emotional connection with their user. By developing a companion robot that has a symbiotic relationship with a plant, an element of co-dependency is introduced into the human companion robot dynamic. This companion robot, while theoretically capable of providing most of the plant’s needs, still requires human interaction for watering, moving obstacles, and solar panel cleaning. To facilitate the interaction between human and robot, the robot is capable of limited auditory and visual communication to help express its and the plant’s needs. This paper seeks to fully describe the Autonomous Plant Care Robot system and its symbiotic relationship with its botanical ward and the plant and robot’s dependent relationship with their owner.

Keywords: symbiotic, robotics, autonomous, plant-care, companion

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Authors: Tim Bolle, Franziska Kreimendahl, Thomas Gries, Stefan Jockenhoevel

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The therapeutic treatment of extensive, deep wounds is limited. Autologous split-skin grafts are used as a so-called ‘gold standard’. Most common deficits are the defects at the donor site, the risk of scarring as well as the limited availability and quality of the autologous grafts. The aim of this project is a tissue engineered dermal-epidermal skin replacement to overcome the limitations of the gold standard. A key requirement for the development of such a three-dimensional implant is the formation of a functional capillary-like network inside the implant to ensure a sufficient nutrient and gas supply. Tailored three-dimensional warp knitted spacer fabrics are used to reinforce the mechanically week fibrin gel-based scaffold and further to create a directed in vitro pre-vascularization along the parallel-oriented pile yarns within a co-culture. In this study various three-dimensional warp knitted spacer fabrics were developed in a factorial design to analyze the influence of the machine parameters such as the stitch density and the pattern of the fabric on the scaffold performance and further to determine suitable parameters for a successful fibrin gel-incorporation and a physiological performance of the scaffold. The fabrics were manufactured on a Karl Mayer double-bar raschel machine DR 16 EEC/EAC. A fine machine gauge of E30 was used to ensure a high pile yarn density for sufficient nutrient, gas and waste exchange. In order to ensure a high mechanical stability of the graft, the fabrics were made of biocompatible PVDF yarns. Key parameters such as the pore size, porosity and stress/strain behavior were investigated under standardized, controlled climate conditions. The influence of the input parameters on the mechanical and morphological properties as well as the ability of fibrin gel incorporation into the spacer fabric was analyzed. Subsequently, the pile yarns of the spacer fabrics were colonized with Human Umbilical Vein Endothelial Cells (HUVEC) to analyze the ability of the fabric to further function as a guiding structure for a directed vascularization. The cells were stained with DAPI and investigated using fluorescence microscopy. The analysis revealed that the stitch density and the binding pattern have a strong influence on both the mechanical and morphological properties of the fabric. As expected, the incorporation of the fibrin gel was significantly improved with higher pore sizes and porosities, whereas the mechanical strength decreases. Furthermore, the colonization trials revealed a high cell distribution and density on the pile yarns of the spacer fabrics. For a tailored reinforcing structure, the minimum porosity and pore size needs to be evaluated which still ensures a complete incorporation of the reinforcing structure into the fibrin gel matrix. That will enable a mechanically stable dermal graft with a dense vascular network for a sufficient nutrient and oxygen supply of the cells. The results are promising for subsequent research in the field of reinforcing mechanically weak biological scaffolds and develop functional three-dimensional scaffolds with an oriented pre-vascularization.

Keywords: fibrin-gel, skin replacement, spacer fabric, pre-vascularization

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Authors: Carlos Gonzalez, Neil Slatcher, Marcus Properzi, Kan Seah

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In many underground mining operations, shotcrete is used for permanent rock support. Shotcrete thickness is a critical measure of the success of this process. 3D Laser Mapping, in conjunction with Jetcrete, has developed a 3D laser scanning system specifically for measuring the thickness of shotcrete. The system is mounted on the shotcrete spraying machine and measures the rock faces before and after spraying. The calculated difference between the two 3D surface models is measured as the thickness of the sprayed concrete. Typical work patterns for the shotcrete process required a rapid and automatic system. The scanning takes place immediately before and after the application of the shotcrete so no convergence takes place in the interval between scans. Automatic alignment of scans without targets was implemented which allows for the possibility of movement of the spraying machine between scans. Case studies are presented where accuracy tests are undertaken and automatic audit reports are calculated. The use of 3D imaging data for the calculation of shotcrete thickness is an important tool for geotechnical engineers and contract managers, and this could become the new state-of-the-art methodology for the mining industry.

Keywords: 3D imaging, shotcrete, surface model, tunnel stability

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Authors: Wiwat Kittinaraporn, Napat Harnpornchai, Sutja Boonyachut

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This paper deals with the application of a novel neural network technique, so-called Support Vector Machine (SVM). The objective of this study is to explore the variable and parameter of forecasting factors in the construction industry to build up forecasting model for construction quantity in Thailand. The scope of the research is to study the non-residential construction quantity in Thailand. There are 44 sets of yearly data available, ranging from 1965 to 2009. The correlation between economic indicators and construction demand with the lag of one year was developed by Apichat Buakla. The selected variables are used to develop SVM models to forecast the non-residential construction quantity in Thailand. The parameters are selected by using ten-fold cross-validation method. The results are indicated in term of Mean Absolute Percentage Error (MAPE). The MAPE value for the non-residential construction quantity predicted by Epsilon-SVR in corporation with Radial Basis Function (RBF) of kernel function type is 5.90. Analysis of the experimental results show that the support vector machine modelling technique can be applied to forecast construction quantity time series which is useful for decision planning and management purpose.

Keywords: forecasting, non-residential, construction, support vector machines

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Authors: Zunaira Zaman, David Bohannon

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This study explores the application of machine learning (ML) for detecting security vulnerabilities in source code. The research aims to assist organizations with large application portfolios and limited security testing capabilities in prioritizing security activities. ML-based approaches offer benefits such as increased confidence scores, false positives and negatives tuning, and automated feedback. The initial approach using natural language processing techniques to extract features achieved 86% accuracy during the training phase but suffered from overfitting and performed poorly on unseen datasets during testing. To address these issues, the study proposes using the abstract syntax tree (AST) for Java and C++ codebases to capture code semantics and structure and generate path-context representations for each function. The Code2Vec model architecture is used to learn distributed representations of source code snippets for training a machine-learning classifier for vulnerability prediction. The study evaluates the performance of the proposed methodology using two datasets and compares the results with existing approaches. The Devign dataset yielded 60% accuracy in predicting vulnerable code snippets and helped resist overfitting, while the Juliet Test Suite predicted specific vulnerabilities such as OS-Command Injection, Cryptographic, and Cross-Site Scripting vulnerabilities. The Code2Vec model achieved 75% accuracy and a 98% recall rate in predicting OS-Command Injection vulnerabilities. The study concludes that even partial AST representations of source code can be useful for vulnerability prediction. The approach has the potential for automated intelligent analysis of source code, including vulnerability prediction on unseen source code. State-of-the-art models using natural language processing techniques and CNN models with ensemble modelling techniques did not generalize well on unseen data and faced overfitting issues. However, predicting vulnerabilities in source code using machine learning poses challenges such as high dimensionality and complexity of source code, imbalanced datasets, and identifying specific types of vulnerabilities. Future work will address these challenges and expand the scope of the research.

Keywords: code embeddings, neural networks, natural language processing, OS command injection, software security, code properties

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Authors: Maryam Sadeghi

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Civilization and industrialization are two important factors that make people believe they are just depriving of savagery and brutality. But practical studies show exactly something different. How groups of people behave, when they are put in extreme situations is the very unpleasant truth about the human being in general. Both novels deal with the fragility of human society, no matter the people who are playing a role are children or grown-ups, who by definition should know better. Both novels have got beautiful plots in which no one enforces rules and laws on the characters, so they begin to show their true nature. The present study is undertaken to investigate the process of a journey from lack of humanity to a sort of self-consciousness which happens at the end of both Blindness by Saramago and Lord of the Flies by Golding. In order to get the best result the two novels have been studied precisely and lots of different articles and critical essays have been analyzed, which shows people drift into cruelty and savagery easily but can also drift out of it. In blindness losing sight, and being apart from society in a deserted tropical island in Lord of the Flies causes limitation. Limitation in any form makes people rebel. Although in the process of both novels, any kind of savagery, brutality, filth, and social collapse can be observable and both writers believe that human being has the potential of being animal images, but they both also want to show that the very nature of human being is divine. Children’s weeping at the end Lord of the Flies and Doctor’s remark at the end of Blindness “I don’t think we did go blind, I think we are blind, blind but seeing, blind people who can see but do not see”, show exactly the matter of insight at the end of the novels. The fact that divinity exists in the very nature of human being is the indubitable aim that makes this research truly valuable.

Keywords: brutality, lack of humanity, savagery, Blindness

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Authors: Iliya Ibrahim Gimba

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Human beings or groups over the world have a traditional and cultural practices which guide and direct their ways of life. They value and promote these practices not minding the attitude of others towards them. In spite of the place of culture which is an embodiment of these practices in every human society some people still reduce the understanding of culture to idolatry and other archaic and anachronistic arts good perhaps only for the museum. Others consider culture to be just drumming and dancing. Whether a culture is “good” or “bad”, civilized or barbaric, it can be reformed for the betterment of the society. Hence, this paper focuses on reforming traditional and cultural practices in Nigeria for enhancing development in the 21st century using the Jukun people as a case study. Relevant literatures from journals, reports, published books among others will be consulted.

Keywords: Jukun, traditional and cultural practices, sustainable development, human

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Authors: Wei-Jong Yang, Wei-Hau Du, Pau-Choo Chang, Jar-Ferr Yang, Pi-Hsia Hung

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The demands of smart visual thing recognition in various devices have been increased rapidly for daily smart production, living and learning systems in recent years. This paper proposed a visual thing recognition system, which combines binary scale-invariant feature transform (SIFT), bag of words model (BoW), and support vector machine (SVM) by using color information. Since the traditional SIFT features and SVM classifiers only use the gray information, color information is still an important feature for visual thing recognition. With color-based SIFT features and SVM, we can discard unreliable matching pairs and increase the robustness of matching tasks. The experimental results show that the proposed object recognition system with color-assistant SIFT SVM classifier achieves higher recognition rate than that with the traditional gray SIFT and SVM classification in various situations.

Keywords: color moments, visual thing recognition system, SIFT, color SIFT

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Authors: J. K. Adedeji, M. O. Oyekanmi

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This paper has critically examined the use of Machine Learning procedures in curbing unauthorized access into valuable areas of an organization. The use of passwords, pin codes, user’s identification in recent times has been partially successful in curbing crimes involving identities, hence the need for the design of a system which incorporates biometric characteristics such as DNA and pattern recognition of variations in facial expressions. The facial model used is the OpenCV library which is based on the use of certain physiological features, the Raspberry Pi 3 module is used to compile the OpenCV library, which extracts and stores the detected faces into the datasets directory through the use of camera. The model is trained with 50 epoch run in the database and recognized by the Local Binary Pattern Histogram (LBPH) recognizer contained in the OpenCV. The training algorithm used by the neural network is back propagation coded using python algorithmic language with 200 epoch runs to identify specific resemblance in the exclusive OR (XOR) output neurons. The research however confirmed that physiological parameters are better effective measures to curb crimes relating to identities.

Keywords: biometric characters, facial recognition, neural network, OpenCV

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Authors: Katarzyna Piwowar-Sulej

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The functioning of a project-oriented organisation creates new and different, from the traditional ones, conditions for human resources management. In the analysed case HRM is primarily characterized by a double-track nature – on the one hand within the framework of permanent structures (departments) and, on the other, within the area of particular projects. The purpose of the article is to present the dilemmas associated with the development of selected HRM areas in project-oriented organisations. Theoretical discussion was supplemented by the results of empirical research.

Keywords: human resources management, tracks of HRM, project, project-oriented organisation

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Authors: Bachir Chemani, Rachid Halfaoui

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The aim of study was to evaluate pressure distribution characteristics of the elastic textile bandages using two instrumental techniques: a prototype Instrument and a load Transference. The prototype instrument which simulates shape of real leg has pressure sensors which measure bandage pressure. Using this instrument, the results show that elastic textile bandages presents different pressure distribution characteristics and none produces a uniform distribution around lower limb. The load transference test procedure is used to determine whether a relationship exists between elastic textile bandage structure and pressure distribution characteristics. The test procedure assesses degree of load, directly transferred through a textile when loads series are applied to bandaging surface. A range of weave fabrics was produced using needle weaving machine and a sewing technique. A textile bandage was developed with optimal characteristics far superior pressure distribution than other bandages. From results, we find that theoretical pressure is not consistent exactly with practical pressure. It is important in this study to make a practical application for specialized nurses in order to verify the results and draw useful conclusions for predicting the use of this type of elastic band.

Keywords: textile, cotton, pressure, venous ulcers, elastic

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Authors: M. Mueller, M. Kuehn, M. Voelker

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In small and medium-sized enterprises (SMEs), the challenge is to create a well-grounded and reliable basis for process analysis, optimization and planning due to a lack of data. SMEs have limited access to methods with which they can effectively and efficiently analyse processes and identify cause-and-effect relationships in order to generate the necessary database and derive optimization potential from it. The implementation of digitalization within the framework of Industry 4.0 thus becomes a particular necessity for SMEs. For these reasons, the abstract presents an analysis methodology that is subject to the objective of developing an SME-appropriate methodology for efficient, temporarily feasible data collection and evaluation in flexible production and logistics systems as a basis for process analysis and optimization. The overall methodology focuses on retrospective, event-based tracing and analysis of material flow objects. The technological basis consists of Bluetooth low energy (BLE)-based transmitters, so-called beacons, and smart mobile devices (SMD), e.g. smartphones as receivers, between which distance data can be measured and derived motion profiles. The distance is determined using the Received Signal Strength Indicator (RSSI), which is a measure of signal field strength between transmitter and receiver. The focus is the development of a software-based methodology for interpretation of relative movements of transmitters and receivers based on distance data. The main research is on selection and implementation of pattern recognition methods for automatic process recognition as well as methods for the visualization of relative distance data. Due to an existing categorization of the database regarding process types, classification methods (e.g. Support Vector Machine) from the field of supervised learning are used. The necessary data quality requires selection of suitable methods as well as filters for smoothing occurring signal variations of the RSSI, the integration of methods for determination of correction factors depending on possible signal interference sources (columns, pallets) as well as the configuration of the used technology. The parameter settings on which respective algorithms are based have a further significant influence on result quality of the classification methods, correction models and methods for visualizing the position profiles used. The accuracy of classification algorithms can be improved up to 30% by selected parameter variation; this has already been proven in studies. Similar potentials can be observed with parameter variation of methods and filters for signal smoothing. Thus, there is increased interest in obtaining detailed results on the influence of parameter and factor combinations on data quality in this area. The overall methodology is realized with a modular software architecture consisting of independently modules for data acquisition, data preparation and data storage. The demonstrator for initialization and data acquisition is available as mobile Java-based application. The data preparation, including methods for signal smoothing, are Python-based with the possibility to vary parameter settings and to store them in the database (SQLite). The evaluation is divided into two separate software modules with database connection: the achievement of an automated assignment of defined process classes to distance data using selected classification algorithms and the visualization as well as reporting in terms of a graphical user interface (GUI).

Keywords: event-based tracing, machine learning, process classification, parameter settings, RSSI, signal smoothing

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Authors: Emeka Thaddues Njoku

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Since 2009, the Nigerian Government has established diverse counter-terrorism legislations and practices in response terrorism in North Eastern part of the country. However, these measures have hampered not only the ability of civil society organizations to sustain the autonomous spaces that define/locate them at the intersection between the state and public but also the balance between freedom and security. Hence, this study examines the various elements associated with the interface between the counter terrorism security framework of the government and the capacity of civil society organizations to carry out their mandates in Nigeria. In order to achieve this, the survey research of the ex-post facto type will be adopted using the multi-stage sampling technique. A total of two hundred (200) copies of questionnaire will be administered to members of the civil society organizations and 24 In-Depth Interviews (IDI) will be conducted for officials of security agencies, Ministry of Defence and operators of civil society organizations. Fifty respondents will be drawn from each civil society organisations in the areas of humanitarian assistance, human rights Advocacy, development-oriented, peace-building. Moreover, 24 interviewees drawn from the key members of the security agencies (6), Ministry of Defence (6) and 12 operators of civil society organizations-three respondents each will represent the four civil society organizations mentioned above. Also, secondary data will be used to complement In-depth Interview (IDI) sessions. All collected data will be coded and analysed using descriptive statistics of frequency counts and simple percentage in the Statistical Package for Social Science (SPSS). Content analysis will be used for the In-depth interview and secondary data.

Keywords: counter-terrorism, civil society organizations, freedom, terrorism

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Authors: Mridula Devi

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Trafficking of women is a slur on human dignity and a shameful act to human civilization and development. Trafficking of women is one of worst brazen abuses which violate the women’s human rights. In India, more particularly in Assam, human trafficking and infringement of human rights of individual includes mainly the women and girl child of the State. Trafficking in North East region of India, more particularly in Assam occurs in two different ways – one is the internal trafficking of women and girl child from conflict affected rural areas of Assam for domestic work and prostitution. Secondly, there is trafficking of women to other south-East Asiatic countries like Bangladesh, Bhutan, Bangkok, Myanmar (Burma) for various purposes such as drug trafficking, labor, bar girl and prostitution.Historically, trafficking in human beings is associated with slavery and bonded or forced labor. Since the period of Roman Civilization, there was the practice of traffic in persons in the form of slave trade among the nations. With the rise of new imperialism, slavery had become an integral part of the colonial system of European Countries. With time, it almost became synonymous with prostitution or commercial sexual exploitation. Finally, the United Nation adopted the Convention for the Suppression of the Traffic in Persons and of the Prostitution of others, 1949 by the G.A.Res.No.-317(iv). The Convention totally denounces the traffic in persons for the purpose of prostitution. However, it is important to note that, now a days trafficking is not confined to commercial sexual exploitation of women and children alone. It has myriad forms and the number of victims has been steadily on the rise over the past few decades. In Assam, it takes place through and for marriage, sexual exploitation, begging, organ trading, militancy conflicts, drug padding and smuggling, labour, adoption, entertainment, and sports. In this paper, empirical methodology has been used. The study is based on primary and secondary sources. Data’s are collected from different books, publications, newspaper, journals etc. For empirical analysis, some random samples are collected and systematized for better result. India suffers from the ignominy of being one of the biggest hubs of women trafficking in the world. Over the years, Assam: the north east part of India has been bearing the brunt of the rapidly rising evil of trafficking of women which threaten the life, dignity and human rights of women. Though different laws are adopted at international and national level to restore trafficking, still the menace of trafficking of women in Assam is not decreased, rather it increased. This causes a serious violation of women’s human right in Assam. Human trafficking or women’s trafficking is a serious crime against society. To curb this in Assam it is required to take some effective and dedicated measure at state level as well as national and international level.

Keywords: Assam, human trafficking, sexual exploitation, India

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Authors: O. Mohamed Amine, A. Khireddine

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Telecoms operators are always looking to meet their share of the other customers, they try to gain optimum utilization of the deployed equipment and network optimization has become essential. This project consists of optimizing UMTS network, and the study area is an urban area situated in the center of Algiers. It was initially questions to become familiar with the different communication systems (3G) and the optimization technique, its main components, and its fundamental characteristics radios were introduced.

Keywords: UMTS, UTRAN, WCDMA, optimization

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Authors: Vivek Garg, Brajendra S. Sengar, Gaurav Siddharth, Nisheka Anadkat, Amitesh Kumar, Shailendra Kumar, Shaibal Mukherjee

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CuInGaSe (CIGSe) is the dominant thin film solar cell technology. The band alignment of Buffer/CIGSe interface is one of the most crucial parameters for solar cell performance. In this article, the valence band offset (VBOff) and conduction band offset (CBOff) values of Cu(In0.70Ga0.30)Se/ 1 at.% Ga: Mg0.25Zn0.75O (GMZO) heterojunction, grown by dual ion beam sputtering system (DIBS), are calculated to understand the carrier transport mechanism at the heterojunction for the realization of all sputtered buffer-less solar cells. To determine the valence band offset (VBOff), ∆E_V at GMZO/CIGSe heterojunction interface, the standard method based on core-level photoemission is utilized. The value of ∆E_V can be evaluated by considering common core-level peaks. In our study, the values of (Valence band onset)VBOn, obtained by linear extrapolation method for GMZO and CIGSe films are calculated to be 2.86 and 0.76 eV. In the UPS spectra peak positions of Se 3d is observed in UPS spectra at 54.82 and 54.7 eV for CIGSe film and GMZO/CIGSe interface respectively, while the peak position of Mg 2p is observed at 50.09 and 50.12 eV for GMZO and GMZO/CIGSe interface respectively. The optical band gap of CIGSe and GMZO are obtained from absorption spectra procured from spectroscopic ellipsometry are 1.26 and 3.84 eV respectively. The calculated average values of ∆E_v and ∆E_C are estimated to be 2.37 and 0.21 eV, respectively, at room temperature. The calculated positive conduction band offset termed as a spike at the absorber junction is the required criterion for the high-efficiency solar cells for the efficient charge extraction from the junction. So we can conclude that the above study confirms GMZO thin films grown by the dual ion beam sputtering system are the suitable candidate for the CIGSe thin films based ultra-thin buffer-less solar cells. We investigated the band-offset properties at the GMZO/CIGSe heterojunction to verify the suitability of the GMZO for the realization of the buffer-less solar cells. The calculated average values of ∆E_V and ∆E_C are estimated to be 2.37 and 0.21 eV, respectively, at room temperature. The calculated positive conduction band offset termed as a spike at the absorber junction is the required criterion for the high-efficiency solar cells for the efficient charge extraction from the junction. So we can conclude that the above study confirms GMZO thin films grown by the dual ion beam sputtering system are the suitable candidate for the CIGSe thin films based ultra-thin buffer-less solar cells. Acknowledgment: We are thankful to DIBS, EDX, and XRD facility equipped at Sophisticated Instrument Centre (SIC) at IIT Indore. The authors B.S.S and A.K acknowledge CSIR and V.G acknowledge UGC, India for their fellowships. B.S.S is thankful to DST and IUSSTF for BASE Internship Award. Prof. Shaibal Mukherjee is thankful to DST and IUSSTF for BASE Fellowship and MEITY YFRF award. This work is partially supported by DAE BRNS, DST CERI, and DST-RFBR Project under India-Russia Programme of Cooperation in Science and Technology. We are thankful to Mukul Gupta for SIMS facility equipped at UGC-DAE Indore.

Keywords: CIGSe, DIBS, GMZO, solar cells, UPS

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Authors: Nadia Allouache

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Solar radiation is by far the largest and the most world’s abundant, clean and permanent energy source. The amount of solar radiation intercepted by the Earth is much higher than annual global energy use. The energy available from the sun is greater than about 5200 times the global world’s need in 2006. In recent years, many promising technologies have been developed to harness the sun's energy. These technologies help in environmental protection, economizing energy, and sustainable development, which are the major issues of the world in the 21st century. One of these important technologies is the solar cooling systems that make use of either absorption or adsorption technologies. The solar adsorption cooling systems are good alternative since they operate with environmentally benign refrigerants that are natural, free from CFCs, and therefore they have a zero ozone depleting potential (ODP). A numerical analysis of thermal and solar performances of an adsorption solar refrigerating system using different adsorbent/adsorbate pairs such as activated carbon AC35 and activated carbon BPL/Ammoniac; is undertaken in this study. The modeling of the adsorption cooling machine requires the resolution of the equation describing the energy and mass transfer in the tubular adsorber that is the most important component of the machine. The Wilson and Dubinin- Astakhov models of the solid-adsorbat equilibrium are used to calculate the adsorbed quantity. The porous medium is contained in the annular space and the adsorber is heated by solar energy. Effect of key parameters on the adsorbed quantity and on the thermal and solar performances are analysed and discussed. The performances of the system that depends on the incident global irradiance during a whole day depends on the weather conditions: the condenser temperature and the evaporator temperature. The AC35/methanol pair is the best pair comparing to the BPL/Ammoniac in terms of system performances.

Keywords: activated carbon-methanol pair, activated carbon-ammoniac pair, adsorption, performance coefficients, numerical analysis, solar cooling system

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Authors: Saugata Bose, Ritambhra Korpal

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The internet has increased the copy-paste scenarios amongst students as well as amongst researchers leading to different levels of plagiarized documents. For this reason, much of research is focused on for detecting plagiarism automatically. In this paper, an initiative is discussed where Natural Language Processing (NLP) techniques as well as supervised machine learning algorithms have been combined to detect plagiarized texts. Here, the major emphasis is on to construct a framework which detects external plagiarism from monolingual texts successfully. For successfully detecting the plagiarism, n-gram frequency comparison approach has been implemented to construct the model framework. The framework is based on 120 characteristics which have been extracted during pre-processing the documents using NLP approach. Afterwards, filter metrics has been applied to select most relevant characteristics and then supervised classification learning algorithm has been used to classify the documents in four levels of plagiarism. Confusion matrix was built to estimate the false positives and false negatives. Our plagiarism framework achieved a very high the accuracy score.

Keywords: lexical matching, shallow NLP, supervised machine learning algorithm, word n-gram

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Authors: Cagri Baris Kasap

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In this study, how interface designers can be viewed as producers of culture in the current era will be interrogated from a critical theory perspective. Walter Benjamin was a German Jewish literary critical theorist who, during 1930s, was engaged in opposing and criticizing the Nazi use of art and media. ‘The Author as Producer’ is an essay that Benjamin has read at the Communist Institute for the Study of Fascism in Paris. In this article, Benjamin relates directly to the dialectics between base and superstructure and argues that authors, normally placed within the superstructure should consider how writing and publishing is production and directly related to the base. Through it, he discusses what it could mean to see author as producer of his own text, as a producer of writing, understood as an ideological construct that rests on the apparatus of production and distribution. So Benjamin concludes that the author must write in ways that relate to the conditions of production, he must do so in order to prepare his readers to become writers and even make this possible for them by engineering an ‘improved apparatus’ and must work toward turning consumers to producers and collaborators. In today’s world, it has become a leading business model within Web 2.0 services of multinational Internet technologies and culture industries like Amazon, Apple and Google, to transform readers, spectators, consumers or users into collaborators and co-producers through platforms such as Facebook, YouTube and Amazon’s CreateSpace Kindle Direct Publishing print-on-demand, e-book and publishing platforms. However, the way this transformation happens is tightly controlled and monitored by combinations of software and hardware. In these global-market monopolies, it has become increasingly difficult to get insight into how one’s writing and collaboration is used, captured, and capitalized as a user of Facebook or Google. In the lens of this study, it could be argued that this criticism could very well be considered by digital producers or even by the mass of collaborators in contemporary social networking software. How do software and design incorporate users and their collaboration? Are they truly empowered, are they put in a position where they are able to understand the apparatus and how their collaboration is part of it? Or has the apparatus become a means against the producers? Thus, when using corporate systems like Google and Facebook, iPhone and Kindle without any control over the means of production, which is closed off by opaque interfaces and licenses that limit our rights of use and ownership, we are already the collaborators that Benjamin calls for. For example, the iPhone and the Kindle combine a specific use of technology to distribute the relations between the ‘authors’ and the ‘prodUsers’ in ways that secure their monopolistic business models by limiting the potential of the technology.

Keywords: interface designer, cultural producer, Walter Benjamin, materialist aesthetics, dialectical thinking

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Authors: Burcu Uçan

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The certification approach differs in civil and military projects in aviation. Sets of criteria and standards created by airworthiness authorities for the determination of certification basis are distinct. While the civil standards are more understandable and clear because of not only include detailed specifications but also the help of guidance materials such as Advisory Circular, military criteria do not provide this level of guidance. Therefore, specifications that are more negotiable and sometimes more difficult to reconcile arise for the certification basis of a military aircraft. This study investigates a method of how to develop a military specification set by taking advantage of civil standards, regarding the European Military Airworthiness Criteria (EMACC) that establishes the airworthiness criteria for aircraft systems. Airworthiness Certification Criteria (MIL-HDBK-516C) is a handbook published for guidance that contains qualitative evaluation for military aircrafts meanwhile Certification Specifications (CS-29) is published for civil aircrafts by European Union Aviation Safety Agency (EASA). This method intends to compare and contrast specifications that MIL-HDBK-516C and CS-29 contain within the scope of Human Factors. Human Factors supports human performance and aims to improve system performance by encompassing knowledge from a range of scientific disciplines. Human Factors focuses on how people perform their tasks and reduce the risk of an accident occurring due to human physical and cognitive limitations. Hence, regardless of whether the project is civil or military, the specifications must be guided at a certain level by taking into account human limits. This study presents an advisory method for this purpose. The method in this study develops a solution for the military certification process by identifying the CS requirement corresponding to the criteria in the MIL-HDBK-516C by means of EMACC. Thus, it eases understanding the expectations of the criteria and establishing derived requirements. As a result of this method, it may not always be preferred to derive new requirements. Instead, it is possible to add remarks to make the expectancy of the criteria and required verification methods more comprehensible for all stakeholders. This study contributes to creating a certification basis for military aircraft, which is difficult and takes plenty of time for stakeholders to agree due to gray areas in the certification process for military aircrafts.

Keywords: human factors, certification, aerospace, requirement

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Authors: Dammar Bahadur Adhikari

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Mathematics teaching begins with human civilization. The rular used to choose mathematician as prime adviser in many tribes and country. Mathematics was powerful tool for understanding economial situation and strength of rular. In ancient Nepal teaching of mathematics starts with informal education provided by religious leaders there after in modern education system seems to follow the world’s educational system. The aim of this paper is to present a brief historical background of the Nepalese mathematicians up to nineteenth century and highlight the transformation in mathematical science in the line with modern world. Secondary data and formal papers and informal publications were studied to explore the present situation of education. The study concluded that there is remarcable change in quality of education and there are sufficient human powers in the mathematical sciences in Nepal.

Keywords: human development, mathematics, Nepal, science, traditional

Procedia PDF Downloads 375