Miracle-dz/UniFAR-FTUs huggingface dataset:
Non-Linear Regression Method for Instability Problems in Haptic Rendering System

This paper addresses instability problems in 6-DoFs haptic rendering system due do the virtual stiffness technology in haptic device by using non-linear polynomial regression analysis method for haptic feedback value. The method is based on the locally optimized generalized penetration computation algorithm which computes the minimum translational and rotational motion to separate two overlapping objects. The essence of penalty-based haptic rendering method is the stability problem which is the prospect in virtual manipulation and physical experiment simulation. The algorithm which employs the virtual coupling method in order to optimize the haptic feedback value in haptic rendering system. Combining with the non-linear regression method, we get a well-distributed output and stable force feedback. The constructed rendering algorithm can process the complexity polygon-soup models and make no assumption about the underlying geometry topology. The experiment result shows the non-linear regression analysis method can make the haptic system stable and get realistic force feedback.
The Needle in the Haystack

Since the invention of the printing press, individuals have created and shared more information at increasing rates, and this has further accelerated with the proliferation of information technology and the increase in Internet accessibility. Humans' ability to absorb and process information has not evolved alongside the speed at which information can be created and shared. This chapter examines what impact this abundance of information has had on society and its ability to process, examine, and retain information. The relationship between information overload and society's ability to discern the veracity of information is discussed. The author makes recommendations for how individuals and organizations can harness their information overload and continue to discern fact from fiction and create a more truthful world.
Seleção Adaptativa de Operadores Aplicada ao Problema do Despacho Econômico de Energia Elétrica

The Economic Load Dispatch Problem is one of the most important problems in the generation and distribution of electrical energy. Differential Evolution is an efficient evolutionary algorithm for continuous optimization. Distinct Differential Evolution operators are adequate to solve problems with distinct characteristics, however the choice of which operator is more adequate is a complex task. In this work, two adaptive operator selection techniques (Adaptive Pursuit and Probability Matching) are investigated to select the most appropriate operator to solve the Economic Load Dispatch Problem during execution time. The proposed algorithms are evaluated in problems with 13 and 40 thermal generators with valve-point loading effect. The proposed methods achieved better results than recent metaheuristics, finding the best known minimum cost value for all considered systems. Resumo. O Despacho Econômico de Energia Elétrica é um dos mais importantes problemas na área de geração e distribuição de energia elétrica. A Evolução Diferencial é um algoritmo evolutivo eficiente para otimização contı́nua. Diferentes operadores da Evolução Diferencial são adequados para a resolução de problemas com caracterı́sticas diferentes, contudo a escolha do operador mais adequado é uma tarefa complexa. Neste trabalho são investigadas duas técnicas de seleção adaptativa de operadores (Adaptive Pursuit e Probability Matching) para escolher em tempo de execução qual o operador mais eficiente para a resolução do Despacho Econômico de Energia Elétrica. Os algoritmos propostos são validados em problemas de teste que consideram 13 e 40 geradores térmicos e levam em consideração efeitos de ponto de válvula. Os métodos propostos superam os resultados reportados na literatura obtidos por metaheurı́sticas modernas, sendo capazes de encontrar o melhor valor de custo mı́nimo conhecido para todos os sistemas de teste considerados.
Faktor Risiko Gangguan Pendengaran pada Skrining Pendengaran Bayi Baru Lahir di Rumah Sakit PKU Muhammadiyah Yogyakarta

Jenis ketulian neonatus yang banyak dijumpai adalah sensori. Upaya habilitasi hanya dengan memasang alat bantu dengar dan melatih dengan metode audiovisual. Habilitasi sangat efektif bila dilakukan pada periode perkembangan bicara anak sekitar usia 9 bulan sampai 3 tahun. Untuk itu perlu dideteksi dini adanya ketulian pada neonatus, dan segera dimulai habilitasi pendengaran. Penelitian ini untuk mengetahui frekuensi jenis faktor risiko yang potensial penyebab ketulian neonatal. Penelitian ini menggunakan rancang penelitian potong lintang, dengan menggunakan alat otoacoustic emission ( OAE) untuk deteksi ketulian neonatus yang lahir antara bulan Januari dan December 2014 di RS PKU Muhammadiyah. Faktor risiko di lihat dalam rekam medik, data dianalisis menggunakan chi-square . Faktor risiko ketulian yang paling banyak adalah hiperbilirubin sejumlah 44 (53.0%) kasus, prematuritas sejumlah 30 (36.1%) kasus, ventilasi mekanik sejumlah 27 (32.5%) kasus, dan BBLR sejumlah 16 (19.3%). Uji statistik chi-square menunjukkan p=0,001 pada risiko BBLR. Disimpulkan BBLR menjadi salah satu risiko gangguan pendengaran pada skrining pendengaran bayi baru lahir. T he most common congenital neonatus hearing loss is sensory disorder. The habilitation is wearing hearing aids, and audiovisual training. Effective habilitation if perform at optimal early childhood speech development around 9 month to 3 years old. For this reason need early neonatus hearing detection and habilitation. The aims t o know the frequency and potential of neonatal hearing loss risk factors. The m ethod b y cross sectional method newborns were tested with OAE screening test, between Januari 2014 and December 2014 in PKU Muhammadiyah Hospital. From medical report all risk factors data and analyzed by chi-square. Most hearing impairment risk factors are hyperbilirubinemia 44 (53.0%) cases , prematurity 30 (36.1%) cases, mechanical ventilation 27 (32.5%) cases, and low birth weight LBW 16 (19.3%) cases . By chi-square shown p=0,001 for low birth weight . LBW as one of risk factor to hearing impairment at newborn hearing screening.
ANALISA METODE SHA384 UNTUK MENDETEKSI ORISINALITAS CITRA DIGITAL

Cryptography is used to maintain the security of content or information that is personal from anyone except those who have the authority or secret key to open the information that has been encoded. Along with the development of technology and computers now, the increase in computer crime has also increased, especially in image manipulation. Many methods are used and carried out by people to manipulate images that have a detrimental effect on others. The originality of a digital image is the authenticity of the image in terms of colors, shapes, objects and information without the slightest change from the other party. Nowadays many digital images circulating on the internet have been manipulated and even images have been used for material fraud in the competition, so we need a method that can detect the image is authentic or fake like a diploma.In this study, the authors used the SHA-384 method to detect the originality of digital images, using this method an image that is still doubtful of its authenticity can be found out that the image is authentic or fake. Keywords : Originality, Citra, SHA-384
Super Kinetically Pseudocapacitive MnCo2S4 Nanourchins toward High‐Rate and Highly Stable Sodium‐Ion Storage

Improving surface morphology profiles, i.e., surface area and porosity, by nanostructure/surface engineering is effective in accommodating sodium's ionic and kinetic inadequacies. However, this strategy is limited to only activating the extrinsic pseudocapacitance in terms of improving surface‐based reactions. Herein, it is aimed to improve the sodiation performance by enhancement from both intrinsic and extrinsic pseudocapacitance to maximize sodiation potential of materials. A rarely reported but highly functional spinel MnCo2S4 (MCS), is introduced and systematically analyzed using first‐principles investigations, which exhibits energetically favorable charge‐transfer states and strong Na‐ions adsorption kinetics as well as diffusion channels (−3.65 and 0.40 eV respectively). The overall electrochemical redox profiles of the MCS nanostructure is revealed by in situ techniques, which disclose the commencing of partial and then a full conversion‐type sodiation at low discharge potentials (0.52 V vs Na/Na+) with fast Na‐ions diffusivity. Assisted by surface engineering technology on the intrinsically pseudocapacitive MCS, the urchin‐like morphology is instrumental in boosting and realizing sodium storage performance, especially the surface capacitive behavior (from 73.4% to 94.1%), prolonged cycling stability (>800 cycles), and high‐rate capability (416 mAh g−1 at 10 A g−1), as well as exhibiting remarkable full cell capability (high rate at 2 A g−1, >200 cycles at 200 mA g−1).
Corporate Governance: A Key Driver of Intellectual Capital Performance

Intangible assets that are represented by Intellectual Capital play an essential role as the key to success and trigger the creation of company value. The current issue is companies have not yet focused on Intellectual Capital performance. Corporate Governance mechanism with a focus on Audit Committee and Ownership Structure is expected to support the performance of Intellectual Capital, to add the company values. The population in this research was Indonesia financial companies in 2016. The purposive sampling method was used in this study. The secondary data of this research was the company's annual report. Multiple linear regressions were used to examine how the Audit Committee and Ownership Structure influence Intellectual Capital performance, with considering control variables. The results of this research found that Audit Committee (Number of Audit Committees, Independent Audit Committees, Audit Committee Education Background and The Number of Audit Committee Meetings) and Ownership Structure (Managerial Ownership and Institutional Ownership) also control variable (Age, Proportion of Independent Commissioners and Company Size) were able to explain the Intellectual Capital performance in minor way. Meanwhile, the Audit Committee, Ownership Structure, and control variable did not influence Intellectual Capital performance. Advances in Economics, Business and Management Research, volume 115 17th International Symposium on Management (INSYMA 2020) Copyright © 2020 The Authors. Published by Atlantis Press SARL. This is an open access article distributed under the CC BY-NC 4.0 license (http://creativecommons.org/licenses/by-nc/4.0/). 48
Women's Empowerment and Its Impact on Reproductive Health Outcomes: Evidence from Nepal

The percentage of women utilizing maternal health care services in Nepal is relatively less than women in other South Asian countries. Moreover, large socio-economic and regional disparities have been the root causes for lower utilization of health care leading to increasing maternal mortality. Using a national representative sample of 9,475 women (2011) and 9,875 women (2016) from Nepal, I examine the impact of women empowerment in relation to prenatal care, place of delivery and postnatal care (3Ps) outcomes. A composite Women’s Empowerment Index (WEI) based upon responses is also constructed to include three empowerment domains namely, attitude toward violence, social independence, and decision-making. Control variables explaining socio-demographic and economic factors are also added to the index. Principal Component Analysis (PCA) technique is used to calculate empowerment indicators and regression results are evaluated to estimate the 3Ps. Poisson regression model is used for selected survey years of each of the countries to examine the associations between women’s empowerment and prenatal care visits controlling for other variables. Further, ordered probit model and probit model techniques are used to study the associations of women’s empowerment with place of delivery and postnatal care respectively. Findings show that a large proportion of pregnant women have at least one ANC exposure but Nepal’s average ANC coverage was 6 visits in 2011 and 7 visits in 2016, indicating that Nepal crosses the global benchmark for the minimum 4 ANC visits. Further, the trend toward significantly greater use of public health institutions is apparent with respect to several other variables. We observe much smaller effects for who makes decisions about household purchases, about woman’s health, and about her family visits. Also, relatively low incidence of postnatal visits to health care institutions was observed in the analysis. Summarizing the categories of women’s empowerment indicators in terms of linear combinations represented conveniently by a single principal component in each of the three cases, we find decision-making and independence factors to be significantly associated with postnatal visits whereas the violence factors to be insignificant in 2011 and barely significant in 2016.
From Molecular Precursors to Nanoparticles—Tailoring the Adsorption Properties of Porous Carbon Materials by Controlled Chemical Functionalization

Nanoporous carbon materials (NCMs) provide the “function” of high specific surface area and thus have large interface area for interactions with surrounding species, which is of particular importance in applications related to adsorption processes. The strength and mechanism of adsorption depend on the pore architecture of the NCMs. In addition, chemical functionalization can be used to induce changes of electron density and/or electron density distribution in the pore walls, thus further modifying the interactions between carbons and guest species. Typical approaches for functionalization of nanoporous materials with regular atomic construction like porous silica, metal–organic frameworks, or zeolites, cannot be applied to NCMs due to their less defined local atomic construction and abundant defects. Therefore, synthetic strategies that offer a higher degree of control over the process of functionalization are needed. Synthetic approaches for covalent functionalization of NCMs, that is, for the incorporation of heteroatoms into the carbon backbone, are critically reviewed with a special focus on strategies following the concept “from molecules to materials. ” Approaches for coordinative functionalization with metallic species, and the functionalization by nanocomposite formation between pristine carbon materials and heteroatom‐containing carbons, are introduced as well. Particular focus is given to the influences of these functionalizations in adsorption‐related applications.
Eco-system oriented instrument for measuring firm technology adoption

This paper seeks to test the Firm Technology Adoption Model (F-TAM) using data from a developing country context. The data for this current study were purposively collected from four hundred (400) SMEs in the Greater Accra Region of Ghana. We used partial least squares structural equation modeling (PLS-SEM) for our data analysis. Data revealed that, whereas employee factors can lead to firm adoption, firm factors of adoption do not lead to firm adoption if societal factors, characteristics of the innovation, and employee factors do not moderate the relationship between firm factors and firm adoption. Data also reveals that societal factors do not lead to firm adoption if employee factors do not mediate it. The theoretical contribution of this study is that it challenges the dominant idea in most of the earlier models that firm adoption of innovation will be realized, without reference to factors at other levels of adoption. This positioning of the F-TAM model is a significant departure from earlier models. For industry practitioners, these findings illustrate the essence of putting a premium on recruiting technologically savvy employees if the firm intends to adopt digital technologies.
A Complex Network-Based Broad Learning System for Detecting Driver Fatigue From EEG Signals

Driver fatigue detection is of great significance for guaranteeing traffic safety and further reducing economic as well as societal loss. In this article, a novel complex network (CN) based broad learning system (CNBLS) is proposed to realize an electroencephalogram (EEG)-based fatigue detection. First, a simulated driving experiment was conducted to obtain EEG recordings in alert and fatigue state. Then, the CN theory is applied to facilitate the broad learning system (BLS) for realizing an EEG-based fatigue detection. The results demonstrate that the proposed CNBLS can accurately differentiate the fatigue state from an alert state with high stability. In addition, the performances of the four existing methods are compared with the results of the proposed method. The results indicate that the proposed method outperforms these existing methods. In comparison to directly using EEG signals as the input of BLS, CNBLS can sharply improve the detection results. These results demonstrate that it is feasible to apply BLS in classifying EEG signals by means of CN theory. Also, the proposed method enriches the EEG analysis methods.
Vitronectin and prolactin levels of cervicovaginal irrigation liquid in preterm birth risk evaluation

Aim: The objective of this study is to determine the predictive role of cervical length, cervicovaginal irrigation liquid vitronectin and prolactin levels in preterm birth. Material and Methods: A total of 73 pregnant women between 24-34th gestational week were included and the study population was divided into two groups as: term birth group (n=54) and preterm birth(n=19). Birth weeks, weight and methods were noted. The irrigation fluid has been collected from posterior fornix and vitronectin levels are detected by Enzyme-linked-immunosorbent-assay method. Results: Vitronectin were higher in preterm group as compared to controls [90 (78-98) vs 16 (9-41) ng/ml, p<0.001]. Positive predictive value for vitronectin was 78 %, negative predictive value was 100 % and accuracy ratio was 91.8%. The sensitivity of vitronectin was 100 %, specifity was 89 % with a cut-off value of 59 ng/mL. Area under curve for vitronectin was 0.96 which was compatible with ‘perfect’. When average prolactin levels have been found as 0.14 ng/mL in term and 2 ng/mL in preterm birth group, cervical length have been found as 34.5 and 24.2 mm respectively. Cut-off value for prolactin has been found as 0.088 ng/dL. Positive predictive value was 58.3 % for prolactin and 51.5 % for cervical length. Negative predictive value was 89.8% for prolactin and 95 % for cervical length. Vitronectin was strongly positively correlated with prolactin levels while it was negatively correlated with cervical length (r=0.691 and r=-0.348 respectively). Conclusion: Many trials have been done to make the most accurate prediction of preterm delivery risk. By this study, it makes us think about that vitronectin could be a valuable marker for preterm birth, and also could be independent from the gestational week.
Use of active synthesis in vibration reduction using an example of a four-storey building

The article presents a method of active vibration reduction of vibrating mechanical systems. This method is based on the properties of positive rational functions, which in the case of discrete dynamical systems correspond to the characteristic function describing such systems. The method formalized uses methods for decomposing positive rational functions. The advantage of this approach is taking into account the analytical form of a characteristic function of the system being tested and the vibration-reducing force, as well as the conditions that the system should meet in the event of an active vibration-reducing force. In addition, in the proposed method, the desired dynamic properties of the system and the vibration-reducing force can be defined in such a way that the determined parameters of the active force affect all forms of the natural vibrations of the examined system. Based on the formalized methodology, the force reducing the vibrations of a four-storey frame to the desired displacement amplitude was determined. The impact of the place of application of the specific active force on the reduction of vibration of the tested object was also taken into account. The vibrations of the tested structure’s model were caused by kinematic excitation with a harmonic course and an amplitude corresponding to an earthquake of a magnitude of 5 on the Richter scale. To verify the determined force reducing the vibrations of the object and to create a visualisation of the analysed phenomenon, a dynamic analysis of the building structure was carried out using PLM Siemens NX 12 software.
Wellness Policy Awareness Among School Leaders and the Impact on Written Policy Scores

iv Chapter 1: THESIS INTRODUCTION.1 Chapter 2: LITERATURE REVIEW.2 Table 1: Federal Regulations.2 Table 2: Implementation of School Wellness Policies.5 Table 3: School Characteristics in relation to School Wellness Policies.9 Table 4: Assessment of School Wellness Policies.12 Table 5: Table 5. Model School Wellness Policies.14 Chapter 3: MANUSCRIPT.15 INTRODUCTION.15 METHODS.16 RESULTS.18 DISCUSSION.19 LIMITATIONS.21 CONCLUSION.22 TABLES.23 Table 1: WellSAT 2.0 Item Numbers and Items within each Section.23 Table 2: WellSAT-I Item Number and Question within each Section.27 Table 3: Principal knowledge of SWP as compared to WellSAT 2.0 scores.32 FIGURES.33 Figure 1: Principal knowledge of SWP and WellSAT 2.0 scores.33 REFERENCES.34
Deep Embedded Complementary and Interactive Information for Multi-View Classification

Multi-view classification optimally integrates various features from different views to improve classification tasks. Though most of the existing works demonstrate promising performance in various computer vision applications, we observe that they can be further improved by sufficiently utilizing complementary view-specific information, deep interactive information between different views, and the strategy of fusing various views. In this work, we propose a novel multi-view learning framework that seamlessly embeds various view-specific information and deep interactive information and introduces a novel multi-view fusion strategy to make a joint decision during the optimization for classification. Specifically, we utilize different deep neural networks to learn multiple view-specific representations, and model deep interactive information through a shared interactive network using the cross-correlations between attributes of these representations. After that, we adaptively integrate multiple neural networks by flexibly tuning the power exponent of weight, which not only avoids the trivial solution of weight but also provides a new approach to fuse outputs from different deterministic neural networks. Extensive experiments on several public datasets demonstrate the rationality and effectiveness of our method.