Miracle-dz/UniFAR-FTUs huggingface dataset:
PENGARUH UMUR, PENGALAMAN KERJA, UPAH, TEKNOLOGI DAN LINGKUNGAN KERJA TERHADAP PRODUKTIVITAS KARYAWAN

Penelitian ini bertujuan untuk mengetahui pengaruh secara simultan dan parsial dari, umur, pengalaman kerja, upah, teknologi, dan lingkungan kerja terhadap produktivitas karyawan di Kelurahan Penarungan Kecamatan Buleleng tahun 2014. Penelitian menggunakan desain penelitian kausal. Penelitian ini termasik penelitian populasi dengan subjek karyawan pada UD Puji Jiwa Seni dan objeknya adalah variabel umur, pengalaman kerja, upah, teknologi, lingkungan kerja dan produktivitas. Data dikumpulkan dengan metode kuesioner, pencatatan dokumen dan wawancara, kemudian dianalisis dengan menggunakan analisis regresi linier berganda. Hasil penelitian menunjukkan bahwa ada pengaruh secara simultan dan parsial dari umur, pengalaman kerja, upah, teknologi dan lingkungan kerja terhadap produktivitas. Kata Kunci : umur, pengalaman kerja, upah, teknologi, lingkungan kerja dan produktivitas This study aims to determine the effect of multiple and partial of age, work experience, wage, technology and work environment on the productivity of labor in the Kelurahan Penarungan Buleleng districts in 2014. This research uses causal design. This research includes the study population with employees subject to the revlations UD Puji Jiwa Seni and it is object is age, work experience, wage, technology and work environment. Data is collected by questionnaire method, recording document, an interview then analyzed by multiple liniear regression analysis. The results showed that there are effect of multiple and partial of age, work experience, wage, technology and work environment on the productivity keyword : age, work experience, wage, technology, work environment and productivity
The Neuro-Fuzzy Controller of Reactor Installation Management of Butanol Hydrogenation

The possibility of applying the fuzzy logic apparatus for non-fully described systems with unknown dynamics is considered in the article on the example of the problem of defining the condition of management object under the date of different nature. The model of microcontroller for managing a reactor installation of butanol hydrogenation is suggested.The suggested neurofuzzy model of the reactor installation management system is proved to be adequate to real data. The designed controller model can be applied for solving the problem of managing any technological process with non-linear dependence/ Keywords— fuzzy logic, multicoherent systems, a neural network
Diversification of the orchid genus Tridactyle: Origin of endemism on the oceanic islands of São Tomé & Príncipe in the Gulf of Guinea

Oceanic islands have played an important role in our understanding of the diversification of organisms, and phylogenetic estimates have been used in this context to investigate the origin of island diversity and its relationship to the continent. Using a typical orchid genus rich in island endemics and with widespread continental relatives, we aim to compare alternative hypotheses of diversification with a focus on island endemism.
Optimal supercapacitor placement in an urban railway line

Supercapacitors (SCs) are important devices used in renewable energy storage applications on urban railways due to their high power density, good performance, and long maintenance-free lifetime. The position and capacity of supercapacitors play an essential role in increasing energy efficiency and improving the operating condition of the power supply system. This paper proposes an optimal methodology to place a supercapacitor energy storage system (SESS) for urban railway lines. The proposed method uses simulation tools to determine the level of renewable energy as well as the cycle of renewable energy occurrence at substations. Next, based on the working characteristics of the supercapacitor to calculate the accumulated energy that can be reused. Finally, the problem of the optimal siting and sizing of the SESSs is solved to maximize the economic benefits. A case study is applied to evaluate the algorithm. The simulation results demonstrate that installing the optimal SESS can increase energy efficiency, lower transient power, and the solution found is the best choice for economic goals
Mixer U-Net: An Improved Automatic Road Extraction from UAV Imagery

Automatic road extraction from unmanned aerial vehicle (UAV) imagery has been one of the major research topics in the area of remote sensing analysis due to its importance in a wide range of applications such as urban planning, road monitoring, intelligent transportation systems, and automatic road navigation. Thanks to the recent advances in Deep Learning (DL), the tedious manual segmentation of roads can be automated. However, the majority of these models are computationally heavy and, thus, are not suitable for UAV remote-sensing tasks with limited resources. To alleviate this bottleneck, we propose two lightweight models based on depthwise separable convolutions and ConvMixer inception block. Both models take the advantage of computational efficiency of depthwise separable convolutions and multi-scale processing of inception module and combine them in an encoder–decoder architecture of U-Net. Specifically, we substitute standard convolution layers used in U-Net for ConvMixer layers. Furthermore, in order to learn images on different scales, we apply ConvMixer layer into Inception module. Finally, we incorporate pathway networks along the skip connections to minimize the semantic gap between encoder and decoder. In order to validate the performance and effectiveness of the models, we adopt Massachusetts roads dataset. One incarnation of our models is able to beat the U-Net’s performance with 10× fewer parameters, and DeepLabV3’s performance with 12× fewer parameters in terms of mean intersection over union (mIoU) metric. For further validation, we have compared our models against four baselines in total and used additional metrics such as precision (P), recall (R), and F1 score.
Luxury in Emerging Markets: An Investigation of the Role of Subjective Social Class and Conspicuous Consumption

This study is based on the relationship between the anxiety of social groups (especially the young) in today’s social environment and the increasingly younger and more sociable consumer groups in China’s luxury market. In combination with the new consumption characteristics of sustainable luxury goods, we rethink the factors that contribute to conspicuous consumption behavior in which social groups exhibit differences. In order to test our research hypothesis, two questionnaires were conducted through online channels. In the first survey, data from 135 valid subjects showed a significant negative correlation between subjective social class and conspicuous consumption behavior. In the second survey, data obtained from 255 valid subjects again verified the main effect hypothesis of this study, which is that subjective social class has a significant negative influence on conspicuous consumption. Additionally, it is verified that status anxiety plays a mediating role in the influence mechanism of subjective social class on conspicuous consumption, and the social comparison orientation of individual consumers moderates the influence of subjective social class on status anxiety. This study reveals the applicability of subjective social class to Chinese scenarios and finds that individuals of different social classes have different conspicuous consumption behaviors, which expands the research on the antecedents of conspicuous consumption and enriches the research on consumer psychology and social behavior. In practice, the results of this study will play a positive guiding role in rationally regulating psychology, dispelling social anxiety, reshaping the moral concept of conspicuous consumption, and promoting the sustainable development of luxury consumption at the individual or social level.
Assessing Technological Tools for Remote Learning in Early Childhood

Remote learning has been taken up by many schools and districts during the COVID-19 pandemic. In many cases, remote learning has been designed as online teaching and learning, using technology hardware and software often through web-based programs and resources. For teachers of young children, this is a big change from the role of technology and types of instruction previously used in their classrooms. Throughout the pandemic and in the changed world post pandemic, digital and technological tools for remote learning will likely continue to be used in new ways. This chapter uses the framework of developmentally appropriate practice to explore and assess the structure, activities, relationship building, and attention to development in technology used across domains of online learning.
The Resource-Based View on Project Risk Management

AbstractThe benefits of conducting risk analyses in the planning of construction projects are widely acknowledged. However, the actual implementation of procedures notably differs significantly across industry segments. Even within an organization, different units represent risks differently, depending on their primary function. As a result, a holistic picture of the risk exposure is often hard to describe and even harder to manage. The objective of this paper is to provide a link between strategic planning theory, namely the resource-based view (RBV), and project risk management. The proposed resource-based approach is based on the development of a project causal network which then allows for both data-intensive and conceptual evaluation of the project risks, primarily focusing on cost impacts. The key contribution of this paper is the capacity of the developed framework to integrate with a number of methods already used in project management practices with little to no additional data requirement. These.
Stochastic block projection algorithms with extrapolation for convex feasibility problems

The stochastic alternating projection (SP) algorithm is a simple but powerful approach for solving convex feasibility problems. At each step, the method projects the current iterate onto a random individual set from the intersection. Hence, it has simple iteration, but, usually, convergences slowly. In this paper, we develop accelerated variants of basic SP method. We achieve acceleration using two ingredients: blocks of sets and adaptive extrapolation. We propose SP-based algorithms based on extrapolated iterations of convex combinations of projections onto block of sets. Our approach is based on several new ideas and tools, including stochastic selection rules for the blocks, stochastic conditioning of feasibility problem, and novel strategies for designing adaptive extrapolated stepsizes. We prove that, under linear regularity of the sets, our stochastic block projection algorithms converge linearly in expectation, with a rate depending on the condition number of the (block) feasibility problem and on the size of the blocks. Otherwise, we prove that our methods converge sublinearly. Our convergence analysis reveals that such algorithms are most effective when a good sampling of the sets into well-conditioned blocks is given. The convergence rates also explain when algorithms combining block projections with adaptive extrapolation work better than their nonextrapolated variants.
Understanding What Informs the Choice of Agro-Processing Firm Siting: Evidence from a Developing Country

This article investigates the complexity of factors that influence the location choice for agro-processing firms from a developing country and SME perspective. It further examines the underpinning role of government policies regarding the siting, operation and effectiveness of agro-processing firms. Using a quantitative methods research design, 124 randomly sampled agro-processing firms were surveyed. The collected data was analysed using exploratory factor analysis and logistic regression analysis. It emerged that business support, economic and socio-cultural factors had a direct impact on decisions regarding the siting of agro-processing firms. Also, the availability of raw materials and cheap labour equally contributes to such decisions. Government policies turned out to be ineffective in influencing decisions on the siting of agro-processing firms. In terms of policy, there is a need to refocus efforts to incentivise agro-entrepreneurs, open up access to sustainable funding options and build the innovative capacity of agro-processing firms. This is critical to attracting agro-processing investments to remote areas such as Northern Ghana to revamp the local economy. This article highlights the impact of policy on the location of agro businesses in developing countries and also demonstrates the nexus between the location of a business and its performance.
Aerial to Street View Image Translation using Cascaded Conditional GANs

Cross view image translation is a challenging case of viewpoint translation which involves generating the street view image when the aerial view image is given and vice versa. As there is no overlap in the two views, a single stage generation network fails to capture the complex scene structure of objects in these two views. Our work aims to tackle the task of generating street level view images from aerial view images on the benchmarking CVUSA dataset by a cascade pipeline consisting of three smaller stages: street view image generation, semantic segmentation map generation, and image refinement, trained together in a constrained manner in a Conditional GAN (CGAN) framework. Our contributions are twofold: (1) The first stage of our pipeline examines the use of alternate architectures ResNet, ResUnet++ in a framework similar to the current State-of-the-Art (SoA), leading to useful insights and comparable or improved results in some cases. (2) In the 3rd stage, ResUNet++ is used for the first time for image refinement. U-net performs the best for street view image generation and semantic map generation as a result of the skip connections between encoders and decoders, while ResU-Net++ performs the best for image refinement because of the presence of the attention module in the decoders. Qualitative and quantitative comparisons with existing methods show that our model outperforms all others on the KL Divergence metric and ranks amongst the best for other metrics.
New Zealand national weeds distribution database : a feasibility study

1. EXECUTIVE SUMMARY 3 2. INTRODUCTION 5 3. BENEFITS AND STOCK TAKE SURVEY 5 3.1 What are the benefits of a database on weed distribution? 7 3.2 Which weeds? 8 3.3 How are the sites chosen? 8 3.4 Data collection procedures in the field 8 3.5 In office data storage 10 3.6 In office data usage 12 3.7 Data sharing 12 4. RESOURCE REQUIREMENTS 13 4.1 Initiatives already underway 13 4.2 Expected Costs 14 4.3 Compulsory data to be collected 15 5. DISCUSSION AND CONCLUSION 15 5.1 Recommendations 16 5.2 The future – true absences and densities 16 6. ACKNOWLEDGEMENTS 17 7. REFERENCES 17
Problematic online gaming, subjective health complaints, and depression among adolescent gamers from the United States: the role of console-gaming aggression

ABSTRACT The purpose of this study was to examine the longitudinal relationship between problematic online gaming and subjective health complaints and depressive symptoms, and the moderation of console-gaming aggression (i.e. verbal aggression, camping, trolling) in this relationship. Participants were 202 adolescents (86% boys; M age = 12.99 years) in the 7th or 8th grade who played first-person shooter games. They completed questionnaires on problematic online gaming, console-gaming aggression, subjective health complaints, and depressive symptoms. Six months later (Time 2), they completed questionnaires on subjective health complaints and depressive symptoms again. Findings revealed that problematic online gaming and console-gaming aggression were positive predictors of Time 2 subjective health complaints and depressive symptoms, while controlling for Time 1 levels and gender. Moderating effects were found as well, indicating that high levels of console-gaming aggression increased the positive relationship between problematic online gaming and depressive symptoms. These effects were also replicated for verbal aggression, problematic online gaming, and subjective health complaints. These findings suggest the importance of considering the implications of console-gaming aggression and problematic online gaming for the physical and mental health of adolescents. Impact Summary Prior State of Knowledge: Problematic online gaming and aggressive behaviors are linked to negative outcomes, including depression and subjective health complaints. Longitudinal research further supports this connection for depression, but not for subjective health complaints or various types of aggression via console games. Novel Contributions: Few studies have focused on various types of aggression and the longitudinal associations among problematic online gaming, depression, and subjective health complaints, while controlling for previous levels of depression and subjective health complaints. The present research addresses these gaps. Practical Implications: Findings of the present research has implications for clinicians and researchers concerned with identifying adolescents who might be at risk for negative outcomes.
RRAM electronics and Switching Mechanism

The property of PCMO RRAM memory devices have been studied in terms of electrical pulse width, Pulse polarity, voltage ramping, film thickness, resistivity distribution, and temperature dependent of resistance. The PCMO material is deposited using MOD, PVD, or PLD process. The experimental results clearly indicated the resistance increase is due to localization of valence electrons. The narrow pulse induced resistance increase near the cathode indicated the localization of valence electrons is the effect of high density of excessive non-equilibrium electrons through the well known Jahn-Teller effect. High density of non-equilibrium electrons may also be induced by any other means such as displacement current, space charge limited current, SCLC, and radiation. High field intensity collapses the localized valence electrons and returns the device to the low resistance state. This is the intrinsic property of transition metal oxides. We expect all doped and un-doped transition metal oxides to exhibit resistance switching property.
Classification of Histopathological Images of Penile Cancer using DenseNet and Transfer Learning

Penile cancer is a rare tumor that accounts for 2% of cancer cases in men in Brazil. Histopathological analyzes are commonly used in its diagnosis, making it possible to assess the degree of the disease, its evolution, and its nature. About a decade ago, scientific works in the field of deep learning were developed to help pathologists make decisions quickly and reliably, opening up possibilities for new contributions to improve such a complex and time-consuming activity for these professionals. In this work, we present the development of a method that uses a DenseNet to diagnose penile cancer in histopathological images, and the construction of a dataset (via the Legal Amazon Penis Cancer Project) used to validate this method. In the experiments performed, an F1-Score of up to 97.39% and a sensitivity of up to 98.33% were achieved in this binary classification problem (normal or squamous cell carcinoma).
Design of Voltage Charge Pump Phase Locked Loop (PLL)

This paper analyses the design and simulation of a charge-pump based phase locked loop using a 130 nm process. Each block has been studied and simulated with a circuit simulator. This design replaces the conventional current based charge pump with a voltage based one. It also discusses the frequency range at which its performance can be optimized and the other technologies which can be used to make the circuitry more efficient.
DNA Hypomethylation Is Associated with the Overexpression of INHBA in Upper Tract Urothelial Carcinoma

Urothelial carcinoma includes upper urinary tract cancer (UTUC) and bladder cancer. Although nephroureterectomy is the standard treatment for UTUC, the recurrence rate is approximately half and the tumor is associated with poor prognoses. Metastases are the most devastating and lethal clinical situation in urothelial carcinoma. Despite its clinical importance, few potential diagnostic biomarkers are suitable for early UC detection. We compared high-stage/high-grade urothelial carcinoma tissues to adjacent normal urothelial tissues using methyl-CpG binding domain protein capture for genome-wide DNA methylation analysis. Based on our findings, inhibin βA (INHBA) might be associated with carcinogenesis and metastasis. Further, clinical UC specimens had significant INHBA hypomethylation based on pyrosequencing. INHBA was detected by real-time PCR and immunohistochemistry staining, and was found to be highly expressed in clinical tissues and cell lines of urothelial carcinoma. Further, INHBA depletion was found to significantly reduce BFTC-909 cell growth and migration by INHBA-specific small interfering RNA. Interestingly, a positive correlation was found between SMAD binding and extracellular structure organization with INHBA using gene set enrichment analysis and gene ontology analysis. Together, these results are the first evidence of INHBA promoter hypomethylation and INHBA overexpression in UTUC. INHBA may affect urothelial carcinoma migration by reorganizing the extracellular matrix through the SMAD pathway.
The Supporting Actor in Enterprise Executives' Decision-making: A Competitive Intelligence Perspective

The purpose of this study is to investigate empirically how competitive intelligence (CI) impact executives' decision-making support and how decision-making subsequently influence strategic benefit s expansion in organization. A questionnaire survey was conducted from 126 enterprise executives in Taiwan. Results indicate that competitive intelligence comprises three separate constructs: the process of CI, the pr oduct of CI and prior knowledge. This study is the first effort to examine empirically on a key aspect of CI. It provides a concept to both academicians and practitioners on how to conduct a comprehensive quantitative strand in terms of competitors, competitive environment, situation and strategy through proactive CI activities.
Position Tracking of a Pneumatic Actuator Using Backstepping-Sliding Mode Control With Adaptive Friction Observer

In this paper, an enhanced sliding mode control (SMC)-based controller known as backstepping-sliding mode control (B-SMC) with an adaptive friction observer is proposed for position tracking control of pneumatic actuators. The adverse effect of friction encountered in the pneumatic actuators which play a major role in pneumatic servo system is highlighted and a solution to rectify this is proposed using an adaptive LuGre-based friction observer for friction compensation. The B-SMC is experimentally applied, for the first time, on a double-acting single-rod industrial pneumatic cylinder. Comprehensive derivation as well as stability proof of the controller is presented. The performance of B-SMC with and without the friction observer is experimentally investigated. From the results, it is clearly observed that the B-SMC with the adaptive friction observer performs better (i.e. reduces the tracking as well steady-state errors of up to 30%) than the one without friction observer. Thus, the adaptive friction observer of B-SMC is identified as the key element that improved the control performance by compensating the adverse effect of friction during the position tracking tasks. © 2013 ASME