Miracle-dz/UniFAR-FTUs huggingface dataset:
Visible light communication system

The utility model discloses a visible light communication system. A start controlling and processing unit comprises an external network interface, a start processor, a start controller, a start modulation circuit, a start demodulation circuit and a reception amplifier. An optical array unit comprises a drive circuit, an infrared receiver and three sets of LED light sources formed by white light LED light sources and RBG light LED light sources, and a mobile terminal comprises a filter sheet combination, a lens, a photoelectric detector, a trans-impedance amplifier, an automatic gain circuit, a low-noise amplifier, a filter circuit, an amplitude-limited amplifier, a terminal demodulation circuit, a terminal controller, a terminal processor, a terminal modulation circuit and an infrared transmitting tube. Automatic link transfer and illumination communication among areas can be realized, so that cross-area continuity of continuous communication of a reception device, illumination compatibility and energy saving performance of green communication are ensured.
Extraction of Person Body using Appearance & Feature based Algorithms

Extraction is considered to be challenging with person body because of various conditions involved inclusive of pose space with high dimension, complex scene features, size involved with image, pose variance and variant person appearance, almost all existing work involves the vigorous training and matching of templates, the proposed method includes the algorithm which is combination of feature and appearance data involved in the complete process. The dimension and person’s color with size is considered as fact for identification along with separation among the feature and appearance. Some of the anthropometric set of constraints is being used for the skin color estimation and the combined approach is applied at different level in order to correctly estimate the person body. The feature data estimation includes detection of edge from the image and appearance data extraction including the color of image and shape of image under different illuminant condition. The segments from different regions are combined estimation of foreground and the background during search process.
Finessing filter scarcity problem in face recognition via multi-fold filter convolution

The deep convolutional neural networks for face recognition, from DeepFace to the recent FaceNet, demand a sufficiently large volume of filters for feature extraction, in addition to being deep. The shallow filter-bank approaches, e.g., principal component analysis network (PCANet), binarized statistical image features (BSIF), and other analogous variants, endure the filter scarcity problem that not all PCA and ICA filters available are discriminative to abstract noise-free features. This paper extends our previous work on multi-fold filter convolution (ℳ-FFC), where the pre-learned PCA and ICA filter sets are exponentially diversified by ℳ folds to instantiate PCA, ICA, and PCA-ICA offspring. The experimental results unveil that the 2-FFC operation solves the filter scarcity state. The 2-FFC descriptors are also evidenced to be superior to that of PCANet, BSIF, and other face descriptors, in terms of rank-1 identification rate (%).
Images, Civic Identity, and Cultural Narratives of Puerto Rico: Using Intertextual Articulation to Develop Culturally Responsive Practices

Through a collaboration between a university in the US Southeast and a university in Puerto Rico, the researchers explored the use of primary sources to challenge mainstream assumptions and views of Puerto Rico and support application of content and pedagogic approaches into early childhood and elementary classrooms among preservice teachers working in schools in a region with a growing Puerto Rican population. The researchers investigated how preservice teachers’ potential for culturally responsive teaching influenced their selection and application of primary sources, cultural narratives, and intertextual articulation as tools to counter narratives of colonialism and oppression that suppress the civic identity formation of young children. The findings suggest that preservice teachers with high potential for culturally responsive pedagogy have greater success integrating inquiry-based learning experiences to support children in challenging historical metanarratives as they synthesize information across intertextual resources. Through the act of interpretation and interrogating multiple viewpoints, children may reclaim their civic identities as they reconsider all the possibilities of meaning encapsulated by a snapshot in time.
A study on memetic computation, with applications to capacitated vehicle routing problems

Memetic computation, a paradigm that uses the notion of meme(s) as units of information encoded in computational representations for the purpose of problem-solving, represents one of the frontiers in the computational intelligence research, of today’s optimization research. This dissertation takes an explorative attitude in the design of memetic computing frameworks and algorithms by leveraging the co-adaptive nature of meme complexes or memeplexes. The current research presented in this dissertation takes multi-memes and memeplexes as focal point of interest in the context of memetic computation and develop meme-centric computing frameworks for more effective problem-solving in the context of stochastic optimization of Capacitated Vehicle Routing Problems (CVRP) and Vehicle Routing Problem with Stochastic Demands (VRPSD). The presented research works follow a natural progression from multi-memes to memeplexes in simple and adaptive hybrids. Firstly, a simple hybrid with a multi-memes individual learning was developed to overcome the inherent risk associated with reliance on a single meme to be used for individual learning in memetic computation for solving CVRP. The proposed simple hybrid invests local search time budget among multiple memes with different search biases during individual learning, in order to reduce risks of failing on problems from different classes as well as make finding high quality solutions more likely. On this basis, an adaptive hybrid with the conceptual modeling of memeplexes was explored as a self-configuring methodology capable of learning and adapting multi-memes individual learning to the given problem of interests while the search progresses online. The connection topology network of the memeplex representation, credit assignment criteria for evaluating individual memes and meme co-adaptation, as well as the role of emergent memeplexes in the individual learning process were explored, with its application for solving CVRPs of diverse characteristics. Finally, a memeplex robust solution scheme which seeks to achieve greater level of adaptivity in
A Quantitative Examination of Generational Differences in e-Learning at a Hispanic-Serving Institution.

________________________________________________________________________ Cheng-Chang “Sam” Pan is Associate Professor, and Ming-Tsan Lu, Assistant Professor, in Teaching and Learning Department at The University of Texas Rio Grande Valley. Ming-Hsiu Tsai is Assistant Professor in Institute of Technological and Vocational Education at National Taipei University of Technology. Cheng-Chang “Sam” Pan can be reached at Sam.Pan@utrgv.edu. A Quantitative Examination of Generational Differences in e-Learning at A Hispanic-Serving Institution
Information technology -- Biometric data interchange formats -- 19794-Part 7: Signature/sign time series data - Second Edition

ISO/IEC 19794-7:2014 specifies data interchange formats for signature/sign behavioural data captured in the form of a multi-dimensional time series using devices such as digitizing tablets or advanced pen systems. The data interchange formats are generic, in that they may be applied and used in a wide range of application areas where handwritten signs or signatures are involved. No application-specific requirements or features are addressed in ISO/IEC 19794-7:2014.
Framework for pedagogical learning analytics

Learning analytics is an emergent technological practice and a multidisciplinary scientific discipline, which goal is to facilitate effective learning and knowledge of learning. In this design science research, I combine knowledge discovery process, concept of pedagogical knowledge, ethics of learning analytics and microservice architecture. The result is a framework for pedagogical learning analytics. The framework is applied and evaluated in the context of agency analytics. The framework contributes to the practical use of learning analytics.
Flexural properties of three-dimensional printed continuous wire polymer composites

ABSTRACT Recently, continuous fibre reinforcement has been combined with three-dimensional (3D) printing to create stiffer printed components. This study investigates the effect of wire volume fraction, type of polymer matrix, and wire treatment on the flexural properties of 3D printed continuous wire polymer composites (CWPCs) through a design of experiment study. CWPC samples were printed using a modified, open-source 3D printer. The flexural properties were measured and compared to non-reinforced samples. An analytical model was developed to describe the stress distribution across unidirectional CWPCs as a function of the geometrical printing parameters, reinforcement dimensions, and material properties. Sample failure analysis was performed to investigate failure modes and offer insight into further enhancement of the composite’s properties.
Automatic Versus Manual Forwarding in Web Surveys

Several authors and software vendors advocate the benefits of auto forwarding in web surveys, but there is little empirical research on this approach. We experimentally tested automatic versus manual forwarding (MF) under different levels of cognitive effort. We manipulated information accessibility (IA; low vs. high) and consistency requirements (CRs; yes vs. no), along with auto forwarding (AF) versus MF in two studies conducted among students in Finland. We find that an AF survey takes less time to complete, but only for those completing a survey on personal computers or tablets; no time advantage is found for smartphone users. We also find that respondents in both AF and MF conditions return more often to items with higher cognitive burden (low IA or a CR). MF respondents change answers more often than AF respondents. AF appears to reduce straightlining slightly. We find no difference in response consistency between two behavioral items between AF and MF, but a slight advantage for AF for two attitude items. Finally, respondents reported more positive experiences with the AF version. Auto forwarding appears to be somewhat more efficient and easy to use but may decrease the quality of responses to cognitively demanding questions.
Mathematical problem-solving by high-achieving students: Interaction of mathematical abilities and the role of the mathematical memory

The present study deals with the interaction of mathematical abilities and the role of the mathematical memory in the problem-solving process. To examine those phenomena, the study investigates the behaviour of high-achieving students from secondary school when solving new and challenging problems. Although the mathematical memory accounts for a small part of the problem-solving process, it has a critical role in the choice of problem-solving methods. The study shows that if the initially selected methods do not lead to the desired outcome, the students find it very difficult to modify them. The study also shows that students who use algebraic problem-solving methods perform better than those who use numerical methods.
Religious beliefs, patient–doctor interaction and resilience as predictors for treatment decisions and health outcomes of heart patients

ABSTRACT Treatment decision-making in chronic illness poses long-lasting effects on the health status of patients. In Western individualistic cultures, they are independently taken by the individual in collaboration with doctors contrary to the collectivistic Indian context, where it’s decided by families with little or no involvement of patients. Religious beliefs, patient–doctor interaction, and resilience measures of 100 CAD patients were used to assess their religious beliefs, patient–doctor interaction, and resilience (predictors). Hierarchical Regression Analysis was conducted to test for the significance of the proposed model. Religious beliefs, patient–doctor interaction, and resilience collectively predicted the significant change in decision-making styles, somatic symptoms, anxiety, social dysfunctions, depression, and general health total of the participants. While the treatment decision-making is heavily contingent upon the social factors namely – religious beliefs, patient–doctor interaction, and resilience, there may yet be some underlying psychological factors that have not been explored in the present study.
Easy, Breezy, Risky: Lay Investors Fail to Diversify Because Correlated Assets Feel More Fluent and Less Risky

Abstract Why do people fail to diversify risk in their investment portfolios? We study how lay investors (people with low financial literacy) invest in financial assets whose past or expected returns are provided. Although investing in assets with negatively correlated returns reduces portfolio risk (i.e., reduces portfolio fluctuations), we find that lay investors instead prefer investing in assets with positively correlated returns, which results in less diversified and riskier investment portfolios than intended. Using a mixed-method approach, we find that lay investors rely on a lay perception of portfolio risk: assets with positively correlated returns feel more fluent (more familiar, simple, and predictable), and thus are erroneously perceived as less risky. We find that lay investors succeed in forming diversified, lower-risk portfolios when they are provided with aggregate portfolio returns, or when—paradoxically—they are encouraged to take more risk.
Project Planning and Development of The Health Educational Module (Hem) on Childhood Obesity Management (Com) For Primary School Children In Malaysia: Conceptual Framework

In-Text Citation: (Said, Nor, Habidin, Buhari, & Sharoni, 2019) To Cite this Article: Said, N. , Nor, N. M. , Habidin, N. F. , Buhari, S. , & Sharoni, S. K. A. (2019). Project Planning and Development of The Health Educational Module (Hem) on Childhood Obesity Management (Com) For Primary School Children In Malaysia: Conceptual Framework. International Journal of Academic Research in Business and Social Sciences, 9(2), 1193 – 1209.
International Handbook of Trade Unions

This Handbook is an authoritative and invaluable reference tool, uniquely analysing the forces governing unionism, union behaviour and union impact from a variety of perspectives, both theoretical and empirical. The 14 chapters are written in an accessible style by acknowledged leading specialists from the fields of economics and industrial relations. They offer a truly international perspective on this important subject.
Displacement amplification ratio modeling of bridge-type nano-positioners with input displacement loss

Abstract. This paper presents an improved modeling method for bridge-type mechanism by taking the input displacement loss into consideration, and establishes an amplification ratio model of bridge-type mechanism according to compliance matrix method and elastic beam theory. Moreover, the amplification ratio of the designed bridge-type nano-positioner is obtained by taking the guiding mechanism as the external load of bridge-type mechanism. Comparing with existing methods, the proposed model is more accurate, which is further verified by finite element analysis(FEA) and experimental test. The consistency of the results obtained from theoretical model, FEA and experimental testing indicates that the proposed model can accurately predict the amplification characteristics of nano-positioners, which helps the analysis and design of bridge-type nano-positioners in practical applications.
Oppositional Gravitational Search Algorithm and Artificial Neural Network-based Classification of Kidney Images

Abstract Ultrasound (US) imaging has been broadly utilized as part of kidney diagnosis because of its ability to show structural abnormalities like cysts, stones, and infections as well as information about kidney function. The main aim of this research is to effectively classify normal and abnormal kidney images through US based on the selection of relevant features. In this study, abnormal kidney images were classified through gray-scale conversion, region-of-interest generation, multi-scale wavelet-based Gabor feature extraction, probabilistic principal component analysis-based feature selection and adaptive artificial neural network technique. The anticipated method is executed in the working platform of MATLAB, and the results were analyzed and contrasted. Results show that the proposed approach had 94% accuracy and 100% specificity. In addition, its false-acceptance rate is 0%, whereas that of existing methods is not <27%. This shows the precise prediction level of the proposed approach, compared with that of existing methods.
A Nonlinear Framework for Facial Animation

A Nonlinear Framework for Facial Animation Hanieh Bastani Master of Science Graduate Department of Computer Science University of Toronto 2007 This thesis researches techniques for modelling static facial expressions, as well as the dynamics of continuous facial motion. We demonstrate how static and dynamic properties of facial expressions can be represented within a linear and nonlinear context, respectively. These two representations do not act in isolation, but are mutually reinforcing in conceding a cohesive framework for the analysis, animation, and manipulation of expressive faces. We derive a basis for the linear space of expressions through Principal Components Analysis (PCA). We introduce and formalize the notion of expression manifolds, manifolds residing in PCA space that model motion dynamics for semantically similar expressions. We then integrate these manifolds into an animation workflow by performing Nonlinear Dimensionality Reduction (NLDR) on the expression manifolds. This operation yields expression maps that encode a wealth of information relating to complex facial dynamics, in a low dimensional space that is intuitive to navigate and efficient to manage.
Relationships among Personal Life Stories, Vicarious Life Stories about Mothers and Fathers, and Well-being

ABSTRACT We examined whether vicarious life stories about mothers and fathers differed in their relationships with personal life stories and well-being. Seventy-six emerging adults completed scales measuring well-being and described three chapters in their personal, mothers’, and fathers’ life stories. Chapters were self-rated and content coded for emotional tone and positive/negative person change. Characteristics of personal life stories were positively correlated with characteristics of vicarious life stories for mothers and fathers. Personal life stories were higher on positive person change than vicarious life stories about mothers and fathers. Higher well-being was related to rating all three life stories as more positive, but results for content coding were more mixed. The results indicate that vicarious life stories for mothers and fathers are related in similar ways to personal life stories and well-being.
FIELD DEPENDENCE/INDEPENDENCE, LEARNING STRATEGIES, LEARNING STYLES, and FOREIGN LANGUAGE ACHIEVEMENT

Bireylerin bilissel bicemlerinin egitim ortamlarinda etkili unsurlar oldugu kabul goren bir fikirdir. Nicel ve deneysel olmayan bir arastirma yontemini benimsemis bu calismanin amaci, alan bagimli/bagimsiz bilissel bicemlerinin bireylerin benimsedikleri ogrenme stratejilerini, tercih ettikleri ogrenme bicemlerini ve Akademik Amacli Ingilizce baglaminda, Ingilizcedeki farkli becerilerdeki basarilarini etkileyip etkilemedigini kesfetmektir. Calismanin orneklemi, egitim dili Ingilizce olan bir yuksekogretim kurumunda okumakta olan ve Ingilizceyi yabanci dil olarak ogrenen 123 kisilik cokturel bir ogrenci grubunu kapsamaktadir. Veri toplama araclari olarak Grup Sakli Şekiller Testi, Rebecca Oxford tarafinan gelistirilen Dil Ogrenme Stratejileri Envanteri ve BIG16 Ogrenme Bicemleri Envanteri kullanilmistir. Katilimcilarin dil becerindeki basari verileri, kendilerinden yazili izinleri alinmak suretiyle calismaya dahil edilmistir. Betimsel ve kestirimsel analizler, alan bagimsizlik ile bilissel, ust-bilissel ve tamamlayici stratejiler ve okuma, yazma ve dinleme becerilerindeki basari seviyeleri arasinda istatistiksel olarak anlamli iliskiler ortaya koyarken, alan bagimlilik ile konusma berisi arasinda anlamli bir iliski bulunmustur. Yapilan analizler, katilimcilarin alan bagimlilik ve bagimsizlik bilissel bicemleri ile bellek, sosyal ve duyussal stratejiler ve tercih ettikleri ogrenme bicemleri arasinda istatistiki olarak anlamli olabilecek herhangi bir iliski tespit etmemistir.
PENGEMBANGAN MIKROKONTROLER SEBAGAI REMOTE CONTROL BERBASIS ANDROID

ABSTRAK Remote kontrol diciptakan untuk memudahkan komunikasi antar peralatan yang memiliki perangkat penghubung. Alat komunikasi yang dapat dihubungkan adalah perangkat smartphone android yang berkomunikasi dengan alat lain seperti mikrokontroler. Salah satu jenis mikrokontroler adalah ATMega 16 yang dapat diprogram menggunakan bahasa Bascom AVR sehingga dapat mengendalikan perangkat lainnya untuk bergerak yaitu motor servo. Motor servo ini diintegrasikan dengan mikrokontroler dalam menggerakkan media pintu gerbang rumah. Dalam melakukan penelitian ini menggunakan metode eksperimental yaitu mengintegrasikan smartphone android, mikrokontroler ATMega 16, dan prototipe gerbang rumah yang dihubungkan dengan motor servo sebagai penggerak utama gerbang. Dari penelitian yang dilakukan mendapatkan kesimpulan bahwa prototipe ini telah berhasil dirancang dan antar alat dapat berkomunikasi dengan baik sehingga pergerakan pintu gerbang rumah sepenuhnya mampu dikontrol oleh smartphone android. ABSTRACT Remote controls are created to facilitate communication between devices with connecting devices. Communication tools that can be connected are android smartphone devices that communicate with other devices such as microcontrollers. One type of microcontroller is ATMega 16 which can be programmed using Bascom AVR language so it can control other devices to move the servo motor. Servo motor is integrated with the microcontroller in moving the media gate home. In doing this research using experimental method that is integrating android smartphone, microcontroller ATMega 16, and prototype gate home which connected with servo motor as main gate drive. From the research conducted to get the conclusion that the prototype has been successfully designed and inter-tool can communicate well so that the movement of the home gate is fully capable of being controlled by android smartphone. How To Cite : Sumarsono, Saptaningtyas, D.W. (2018). PENGEMBANGAN MIKROKONTROLER SEBAGAI REMOTE CONTROL BERBASIS ANDROID . Jurnal Teknik Informatika, 11(1), 67-74. doi 10.15408/jti.v11i1. 6293 Permalink/DOI: http://dx.doi. org/10.15408/jti.v11i1. 6293