Miracle-dz/UniFAR-FTUs huggingface dataset:
DETEKSI PENYAKIT KULIT WAJAH MENGGUNAKAN TENSORFLOW DENGAN METODE CONVOLUTIONAL NEURAL NETWORK

Abstrak Masyarakat Indonesia dengan kondisi yang berbeda khususnya kulit pada wajah. Hal tersebut menyebabkan beberapa penyakit yang dapat menyerang kulit wajah. Di Indonesia, banyak wanita yang menderita penyakit kulit, hal ini dibuktikan dari profil kesehatan Indonesia tahun 2015. Masyarakat banyak yang belum mengetahui penyakit kulit dan bahaya penyakit kulit akibat keterlambatan dalam penanganan. Penelitian ini akan mendeteksi penyakit kuit wajah secara real-time, lalu sistem ini akan mengklasifikasikan penyakit kulit yang ada di wajah. Tipe jaringan saraf yang disebut Convolutional Neural Network (CNN) cocok untuk tugas berhubungan gambar. Jaringan dilatih untuk mencari fitur, seperti tepi, sudut dan perbedaan warna, diseluruh gambar dan menggabungkannya menjadi bentuk yang kompleks. Aplikasi ini hanya dapat digunakan pada android sehingga menjalankan sistem secara real-time. Hasil yang didapat menunjukkan hasil yang cukup baik dengan menggunakan metode deep learning. Kata kunci: Convolutional Neural Network (CNN), Penyakit Kulit, TensorFlow, DeepLearning, Sistem Deteksi Abstract Indonesian people have different skin conditions, especially the skin on the face. This one causes several diseases that can attack facial skin. Indonesia's 2015 health profile shows that many women suffer from skin diseases. Many people do not know about skin diseases and the dangers caused by delays in handling. This study will detect facial skin disease in real-time, then this system will classify skin diseases on the face. A type of neural network called a Convolutional Neural Network (CNN) is suitable for image-related tasks. The system is regular to look for features, such as edges, angles, and color differences across images and combine them into complex shapes. This application only on android, so it runs the system in real-time. The results obtained show passably results using the deep learning method. Keywords: Convolutional Neural Network (CNN), Penyakit Kulit, TensorFlow, DeepLearning, Sistem Deteksi
An Energy Efficient Mobility based Clustering in Wireless Sensor Networks

In wireless sensor networks, the sink mobility along a constrained path can improve the network lifetime and energy effi- ciency. Existing method used Weighted Rendezvous Planning (WRP) which an algorithm for controlling the movement of a mobile sinks in WSNs. This method focuses on a single source or sink. This leads to inefficient communication, reducing the network life- time. Because of this problem, some nodes or parts of WSN are not frequently visited. An enhanced technique is proposed in this pa- per to overcome the network lifetime reduction problem. The proposed system uses enhancing energy efficiency by using energy based clustering method which uses mobile sink nodes on energy consumption under different scale networks. In this WSN partition into many clusters. Every cluster there is a cluster head (CH) is elected based on their residual energy. Within the communication range of the cluster head the cluster members are joined into the clusters. The cluster members forwarded their data to their CH. The mobile sink can collect the data from the CH and forwarded to base station. The mobile sink only visited the cluster heads this leads to improve the network lifetime compare to other methods. Experimental results also produce better results compare to existing systems.
Integrated Model of Power Electronics, Electric Motor, and Gearbox for a Light EV

This study presents a model of a drivetrain for an integrated design of a light electric vehicle (EV). For the drivetrain of each front wheel of the single-person, battery-powered EV tricycle consists of a battery, an inverter, and an outer rotor permanent magnet synchronous motor (PMSM), which is connected to an in-wheel gearbox. The efficiency of the inverter, motor, and gearbox is analyzed over the New European Driving Cycle. To calculate the losses and efficiency of the PMSM, the power electronics in the inverter and gearbox are used. The analytical models provide a fast, but less accurate result, useful for optimization purposes. To accurately predict the efficiency of the PMSM, a finite element model is used. The models are validated by test setups. Correspondingly, a good agreement between the measurements and the calculated results is achieved. A parameter study is performed to investigate the influence of the detailed component parameters (i.e., outer rotor radius, gear ratio, and number of pole pairs and stator slots) on the average efficiency of the drivetrain.
STATUS KARBON ORGANIK DAN NITROGEN TOTAL TANAH SERTA PERTUMBUHAN JAGUNG (Zea mays L.) AKIBAT APLIKASI FUNGI SELULOLITIK INDIGENOUS DAN JERAMI PADI PADA INCEPTISOL ACEH

Abstrak. Produktivitas Inceptisol sebagai lahan budidaya dibatasi oleh rendahnya kadar bahan organik dan ketersediaan beberapa unsur hara makro. Penelitian ini menggunakan rancangan acak kelompok dengan tiga ulangan untuk menguji pengaruh aplikasi fungi selulolitik indigenous yang berasal dari Inceptisol Aceh (tanpa fungi selulolitik, Talaromyces pinophilus strain MR107 dan Purpureocillium lilacinum isolate PIGD23i) dan jerami padi (tanpa jerami padi, 10 t ha-1 dan 20 t ha-1) terhadap karbon (C-organik) dan nitrogen (N-total) tanah serta berat basah dan berat kering berangkasan atas tanaman pada Inceptisol. Hasil penelitian menunjukkan bahwa inokulasi kedua inokulan fungi selulolitik indigenous dan jerami padi pada berbagai dosis aplikasi memberikan pengaruh yang sama terhadap status C-organik dan N-total tanah serta pertumbuhan jagung pada Inceptisol Aceh.The Statuses Soil organic carbon and total nitrogen due to application of indigenous cellulolytic fungi and rice straw on Inceptisol’s AcehAbstract. The productivity of Inceptisols as cultivated land has problems in low organic matter and macronutrients. This study arranged in a randomized block design and three replications to examine the effect of indigenous cellulolytic fungi from Inceptisol Aceh and rice straw on soil organic carbon (SOC) and total nitrogen (total-N) and the weight of the upper part of the plant on Inceptisol. The cellulolytic fungi treatments were no cellulolytic fungi, Talaromyces pinophilus strain MR107 and Purpureocillium lilacinum isolate PIGD23i. The rice straw application consisted of without rice straw, 10 t ha-1, and 20 t ha-1. The results showed that both indigenous cellulolytic fungi and rice straw at various dose applications gave the same effect on the soil C-organic and N-total status and the maize growth on Inceptisols Aceh.
The Assimilation of Knowledge Platforms in Organizations: An Empirical Investigation

ability to integrate dispersed pockets of expertise and in- stitute an organizational repository of knowledge is considered to be vital for sustained effectiveness in contemporary business environments. Information technologies provide cost-effective functionalities for building knowledge platforms through sys- tematic acquisition, storage, and dissemination of organiza- tional knowledge. However, in order to gain the value-adding potential of organizational knowledge, it is not sufficient to sim- ply adopt and deploy IT-enabled knowledge platforms. These platforms must be assimilated into the ongoing work processes in organizations. Yet, theories of technology innovation and use suggest that a variety of institutional, social, and political factors blend together in influencing the extent to which complex in- formation technologies are actually assimilated into organiza- tional practice. Therefore, this research addresses a significant question: What forces influence the assimilation of knowledge platforms in organization? Given the significant gap between the adoption and actual assimilation of complex technologies into organizations, this is an important question. Empirical evi- dence is generated by examining the forces influencing the as- similation of CASE technologies in systems development pro- jects in organizations. CASE is considered to be one of the most mature knowledge platforms in contemporary organizations. The empirical evidence sheds light on the role of institutional forces that influence the rate of assimilation of the technology. The findings have significant implications for further research and practice. (Knowledge Management ; Technology Assimilation; In- stitutional Theories)
Driver Vital Signs Monitoring Using Millimeter Wave Radio

As automobiles have become an essential part to facilitate our daily life, advanced driver assistance systems (ADASs) have been gaining more and more interest in assisting drivers to enhance both safety and convenience. To respond timely in case of an emergency, ADAS needs to keep track of the driver’s health/consciousness, which is generally achieved by monitoring the driver’s vital signs, including respiration rate (RR), heart rate (HR), and heart rate variability (HRV). However, most of the state-of-art solutions need to assume that the human is stationary, which does not hold in practical driving scenarios. To tackle the problem, we propose a novel system, which can estimate driver’s RR, HR, and interbeat intervals (IBIs) in the presence of driver’s motion artifacts using commercial millimeter-wave (mmWave) radio. The system consists of two key components. First, to extract the reflection signals containing vital signals, the motion artifacts are first removed by a novel motion compensation module, followed by the periodicity check to identify the components with vital signals. Second, the respiration and heartbeat signals are reconstructed by jointly optimizing the decomposition of all the extracted compound vital signals over different range-azimuth bins. We evaluate the system performance in a real driving environment and investigate the impact of different parameters, including the device locations, pavement conditions, and motion types. The experimental results show that the proposed system can achieve a median error of 0.16 respiration per minute (RPM), 0.82 beat per minute (BPM), and 46 ms for RR, HR, and IBI estimations, corresponding to the relative accuracy of 99.17%, 98.94%, and 94.11%, respectively.
The Analysis of Implementation of Stunting Prevention Program Case Study at the Air Beliti Community Health Center, Tuah Negeri District, Musi Rawas Regency, 2021

The purpose of this study was to determine the performance or success rate of stunting prevention program implementation related to the characteristics of the institution structure, network and communication, community culture, community needs, and external networks at the Air Beliti Community Health Center, Musi Rawas Regency. The method of this research is quantitative research. The research was conducted at the Air Beliti Community Health Center, Tuah Negri District, Musi Rawas Regency. It was carried out from March to May 2021. The number of samples of the stunting program working team at the Air Beliti Community Health Center was 43. The results of research on factors related to the success of the stunting program at the Air Beliti Community Health Center, Musi Rawas Regency, were the characteristic variables of the institution's structure, network and communication, and community needs. The factors that are not related to the success of the stunting program are organizational culture and external networks. The conclusion of the implementation of the stunting prevention program at the Air Beliti Community Health Center, Musi Rawas Regency in general, has been going well, with positive community responses. Stunting program implementation factors that can affect the success of the stunting program are the characteristics of the institution structure, network and communication, and community needs.
Analysis, simulation, and applications of passive devices on conductive substrates

The wireless communication revolution has spawned a revival of interest in the design and optimization of radio transceivers. Passive elements such as inductors, capacitors, and transformers have the potential to improve the performance of key RF building blocks. Their use, though, not only necessitates proper modeling of electrostatic and magnetostatic effects, but also electromagnetic parasitic substrate coupling. This work focuses on the analysis and application of such passive devices. From Maxwell's equations, an accurate and efficient technique is developed to model the device over a wide frequency range. In particular, we demonstrate techniques for calculating the loss when such devices are fabricated in the vicinity of conductive substrates such as silicon. Energy couples to a conductive substrate through several mechanisms, such as through electrically induced displacement and conductive currents, and by magnetically induced eddy currents. Green functions for Poisson's equation and the eddy current partial differential equations are derived and employed to account for the various loss mechanisms. Numerical techniques are developed to efficiently and accurately compute the underlying Green functions. These techniques have been compiled in a user-friendly software tool, ASITIC, “Analysis and Simulation of Inductors and Transformers for Integrated Circuits”. This tool allows circuit and process engineers to design and optimize the geometry of passive devices and the process parameters to meet electrical specifications. Two key RF building block applications, a 4.4 GHz voltage controlled oscillator (VCO) and a distributed amplifier, are presented. In the VCO, the center-tapped monolithic inductor is at the heart of the resonant tank, a key component in determining the phase noise and power dissipation in the VCO. In the distributed amplifier, lumped inductors and capacitors, or on-chip transmission lines, allow broadband operation. The losses in the passive devices determine the achievable gain and power dissipation. Optimization of such passive devices is thus integral in the design of such building blocks.
A new chemical compound with an unusual ratio of number of carbon and nitrogen atoms – C(N12): quantum-chemical modelling

Based on the results of a quantum chemical calculation using the DFT B3PW91/TZVP, MP2/TZVP and MP3/TZVP levels, the possibility of the existence of carbon–nitrogen compounds having the unusual carbon : nitrogen ratio 1 : 12, which is unknown for these elements at present, was shown. Data on the structural parameters are presented; it was shown that all CN4 groupings are strictly planar. In addition, the bond lengths formed by nitrogen atoms and a C atom are equal to each other, and the bond angles formed by nitrogen atoms and a C atom are equal to 90.0°, or practically do not differ from this value. Thermodynamical parameters, NBO analysis data and HOMO/LUMO images for this compound are presented, too. Good agreement was found between the calculated data obtained using the above three quantum-chemical methods.
Integrating the Development of Employability Skills into a Civil Engineering Core Subject through a Problem-Based Learning Approach*

Institutions of higher learning are expected to design their programmes to meet the needs of industry to ensure that students acquire the skills, both technical and non-technical, that will be used in future employment. Thus academic institutions have to develop teaching strategies to meet these demands. This paper presents a strategy in teaching, utilising the problem-based learning approach, which allows for the development of non-technical skills in a civil engineering core subject. The teaching strategy is based on the assumption that, by using the active knowledge base in a particular subject with specific application strategies, both technical and non-technical applicable skills can be developed in an integrated manner. An example is provided to illustrate the teaching strategy, and student perceptions of the strategy are also presented.
WRITING RECOUNT TEXT USING COOPERATIVE SCRIPT: STUDENTS' DIFFICULTIES

The objective of the research is to find out the students' difficulties in learning writing recount text using the cooperative script. This research used a qualitative method and the design was descriptive qualitative. The respondents of the research were 15 tenth grade students of Senior High School in Cikadu. The data were obtained from tests and interviews. The results of the research show that the students' difficulties in learning writing recount text using the cooperative script in mechanics, such as punctuation and capital letter. Implies that mechanic aspect tends to be ignored in learning. Keywords : Cooperative Script, Writing, Students’ Difficulties
The Belle II DEPFET pixel detector

The existing Japanese Flavour Factory (KEKB) is currently being upgraded and is foreseen to be comissioned by 2014. The new e+e? collider (SuperKEKB) will have an instantaneous luminosity of 8 ? 1035cm-2s-1, 40 times higher than the current world record set by KEKB. In order to handle the increased event rate and the higher background and provide high data quality, the Belle detector is upgraded to Belle II. The increased particle rate requires a new vertex pixel detector with high granularity. This silicon detector will be based on DEPFET technology and will consist of two layers of active pixel sensors. By integrating a field effect transistor into every pixel on top of a fully depleted bulk, the DEPFET technology combines detection and in-pixel amplification. This technology allows good signal to noise performance with a very low material budget.
Comparing mental health and well-being of US undergraduate and graduate students during the early stages of the COVID-19 pandemic

Abstract Objective: This study explored how COVID-related mental health and well-being varied between undergraduate and graduate students. Relationships with physical health behaviors were also examined. Participants: Undergraduate (n = 897) and graduate (n = 314) students were recruited from three US universities between mid-April and late-May 2020. Methods: Participants in this cross-sectional survey self-reported perceived stress, financial stress, resilience, repetitive negative thinking, mood, anxiety, diet, sleep, and physical activity using validated instruments. Results: Undergraduate students reported more perceived stress, more repetitive negative thinking, less positive mood, and less support from professors than graduate students. Perceived stress, repetitive negative thinking, negative mood, and anxiety increased among all students (p < .05 for all). Correlations between mental health outcomes and physical health behaviors were weak to moderate (r = .08 to .49). Conclusions: College students, particularly undergraduates, perceived negative mental health impacts during COVID. Creative approaches for meeting student needs are necessary.
SVM-Based Switching Filter Hardware Design for Mixed Noise Reduction in Digital Images Using High-Level Synthesis Tools

Impulse and Gaussian are the two most common types of noise that affect digital images due to imperfections in the imaging process, compression, storage, and communication. The conventional filtering approaches, however, reduce the image quality in terms of sharpness and resolution while suppressing the effects of noise. In this work, a machine learning-based filtering structure has been proposed that preserves the image quality while effectively removing the noise. Specifically, a support vector machine classifier is employed to detect the type of noise affecting each pixel to select an appropriate filter. The choice of filters includes median and bilateral filters of different kernel sizes. The classifier is trained using example images with known noise parameters. The proposed filtering structure has been shown to perform better than the conventional approaches in terms of image quality metrics. Moreover, the design has been implemented as a hardware accelerator on an FPGA device using high-level synthesis tools.
Early Cardiovascular Health Outreach SMS (ECHOS): A Preventive Health Text Messaging Program Pilot Study

Context: Early adoption of healthy habits has shown reduced cardiovascular morbidity and mortality later in life. Providing heart-healthy information while encouraging positive lifestyle changes in adolescents and young adults is challenging but important preventive health goal. Objective: We hypothesized text messaging may be an effective method of increasing preventive health knowledge among young people. Early Cardiovascular Health Outreach SMS (ECHOS) evaluated the effectiveness and feasibility of text messaging to promote awareness and encourage positive lifestyle behaviours using elements of “nudge theory. ” Design: We performed a prospective cohort study in 3 phases. Setting: Community-based. Participants: Individuals between 13 and 25 years of age. Intervention: Over periods of 30 to 90 days, participants received daily to weekly text messages educating them on cardiovascular health and encouraging engagement in various heart-healthy behaviours. Main outcome measures: Knowledge about heart health and health behaviours were assessed pre- and post- intervention using 5-point Likert scales. Results: In Phase 1 the ECHOS program resulted in both increased knowledge about heart health and self-efficacy surrounding preventive health behaviours. Phase 2 addressed sleep quantity and quality and we observed improvement in both parameters. Phase 3 focused on stress management. Results showed improvement within certain lifestyle domains associated with stress but lack of improvement in others. Conclusion: These data suggest that text messaging interventions based on “nudge theory” are a feasible and scalable mode of communication promoting heart health among adolescents and young adults. Positive feedback and high satisfaction from ECHOS participants suggest that similar digital health interventions may be an effective approach to improving cardiovascular health in this population.
GENETIC LEARNING OF DISTRIBUTED CONTROL RULES FOR POSTURE ADAPTATION OF VARIABLE GEOMETRY TRUSSES

Genetic algorithms are search procedures based on restricted models of natural selection and genetics.This paper uses a class of genetic based learning and adaptive algorithms called Genetic Programming (GP) to derive optimal control rules for adaptive structures, so called variable geometry truss(VGT) structures. The adaptive structures are controlled structures that contain sensors and actuators, and have structural functionality in addition to control functionality. The integration of control logic and electronics with the structure provides the cognitive element of a distributed or hierarchical control architecture. This paper proposes the first report from an application of using the genetic programming paradigm for learning optimal rules of such adaptive structures. The results achieved for a 10 module VGT structure for learning rules to produce a maximum stiffness posture starting from any random given initial posture. The evoluted control rules are verified their effectiveness by numerical examples.