Miracle-dz/UniFAR-FTUs huggingface dataset:
Theoretical model of suppression of electron instability in hall thrusters by boundary feedback system

Among plasma instabilities in Hall thrusters, large-scale electron instability of Rayleigh type holds one of the main positions. Its arising brings about redistribution of the electrical field in the acceleration layer that can increase losses of ions on the walls of the thruster. In the paper, the possibility of suppression of this instability by a boundary feedback system (BFS) is theoretically considered. The analysis is carried out with the use of hydrodynamic approximation. The eigenvalue problem is solved in assumption that the BFS creates an azimuthal distribution of the electrical potential on the surface of the anode, which is a function of the perturbation electrical field near the anode. From the solution of the eigenvalue problem, it follows that for the suppression of the electron instability, the transformation coefficient of the BFS should lie in the region limited by both a lower value and upper value, which depend on the length of the wave and distance between the anode and a maximum of the drift velocity.
Detection of face spoofing using low-level features and shape analysis

Face as a security system has a vulnerability to the spoofing attack because by falsifying faces using certain media such as photos or videos can fool the system. In this study, we proposed a spoofing detection system on human faces that good to distinguish spoof and non- spoof face using Low-Level Feature: Speeded-Up Robust Features (SURF) and Shape Analysis: Pyramid Histogram of Oriented Gradient (PHOG) as the feature extraction. We tested our method on 2 scenarios: intra-database and cross-database, using 4 different public datasets: MSU MFSD, NUAA Imposter, CASIA FASD, and IDIAP Replay-Attack. We used Support Vector Machine (SVM) and k-Nearest Neighbors (k-NN) as classification.
Perencanaan Strategis Sistem Informasi Pada Pt. Primajasa Menggunakan Zachman Framework

Abstrak Saat ini teknologi dan sistem informasi berkembang semakin pesat, keduanya merupakan hal yang tidak terpisahkan baik untuk kalangan perusahaan besar, perusahaan menengah ataupun perusahaan kecil. Sistem informasi yang didukung dengan teknologi informasi dapat berjalan lebih baik dibandingkan dengan sistem informasi yang dikelola secara manual. Perusahaan yang melakukan perencanaan dan pengelolaan sistem informasi dengan baik akan membantu terlaksananya proses bisnis perusahaan itu sendiri. Dalam mengimplementasikan sistem informasi ini diperlukan perencanaan strategis sistem informasi untuk mengidentifikasi strategi dan teknologi yang akan digunakan sistem informasi tersebut sesuai dengan kebutuhan PT. Primajasa Perdanarayautama. Metode yang digunakan dalam menyusun perencanaan strategis sistem informasi di lingkungan PT. Primajasa Perdanarayautama adalah Zachman Framework yang merupakan salah satu cara kerja dari pemodelan enterprise architecture yang dapat mendefinisikan fungsi perancangan sistem informasi yang lengkap dari berbagai subjek dan perspektif. Kerangka kerja Zachman terdiri dari matriks 6x6 yaitu enam baris dan enam kolom yang memiliki 36 sel yang merepresentasikan deskriptif dari arsitektur enterprise berdasarkan perspektif dan abstraksinya. Hasil dari penelitian ini adalah blue print dan aplikasi hasil dari perencanaan strategis sistem informasi PT. Primajasa Perdanarayautama berdasarkan data yang diperoleh dari PT. Primajasa Perdanarayautama. Kata Kunci : Zachman Framework, Enterprise Architecture, Perencanaan Strategis sistem informasi, PT. Primajasa Perdanarayautama
Robust and window-insensitive mixture model approaches for localizing balancing selection

Long-term balancing selection typically leaves narrow footprints of increased genetic diversity, and therefore most detection approaches only achieve optimal performances when sufficiently small genomic regions (i.e., windows) are examined. Such methods are sensitive to window sizes and suffer substantial losses in power when windows are large. This issue creates a tradeoff between noise and power in empirical applications. Here, we employ mixture models to construct a set of five composite likelihood ratio test statistics, which we collectively term B statistics. These statistics are agnostic to window sizes and can operate on diverse forms of input data. Through simulations, we show that they exhibit comparable power to the best-performing current methods, and retain substantially high power regardless of window sizes. Moreover, these methods display considerable robustness to high mutation rates and uneven recombination landscapes, as well as an array of other common confounding scenarios. Further, we applied these statistics on a bonobo population-genomic dataset. In addition to the MHC-DQ genes, we uncovered several novel candidate genes, such as KLRD1, involved in viral defense, and NKAIN3, associated with sexuality. Finally, we integrated the set of statistics into open-source software named BalLeRMix, for future applications by the scientific community.
Concentration profiling using a novel acoustic backscatter system with single transducers pulsed at multiple frequencies

Acoustic backscatter systems offer a flexible technique to measure dispersion concentration and particle size, through inversion of the return echo voltage response of pulse-echo signals in the MHz range. This study explores the use of the ultrasound array research platform to measure the suspended particle attenuation constant using acoustic backscatter from glass species, and invert the voltage response to produce concentration profiles. The measurement principle is described and experimentally determined values for the particle attenuation constant are compared to theoretical values from literature. Transducer constants for each probe are determined allowing concentration profiles to be inverted from the voltage profiles, and the limits for determining the attenuation constant are explored.
The Beamline DAQ System for the T2K Experiment

The T2K (Tokai-to-Kamioka) experiment is a long baseline neutrino experiment designed to observe oscillations from mu neutrinos to electron neutrinos. Through 2013, the system showed stable operation, with 230 kW of beam power and 1.2×1014 protons per bunch, the highest intensity in the world. This manuscript describes the data acquisition system used to monitor the high-intensity proton beam that produces the neutrino beam. This paper describes the data acquisition system for the monitoring of the primary proton beam and the secondary muon beam.
Visual comparison of software architectures

Reverse engineering methods produce different descriptions of software architectures. In this article we address the task of exploring and comparing these descriptions. We present a novel visualization technique to compare architectures consisting of a decomposition of the software system and the dependencies among the code entities. This technique uses a visual representation of an adjacency matrix to provide a scalable analysis tool. Advanced layout features such as an automatic level of detail algorithm and sorting strategies improve the readability of the visualization. Using a case study, we show how this technique can be applied in practice.
Armature reaction field and inductance calculations for a permanent magnet linear synchronous machine based on subdomain model

This paper proposes an analytical technique to calculate the armature reaction field and inductance of permanent magnet linear synchronous machines (PMLSMs) based on a subdomain analytical model. The analytical expressions can be used for PMLSMs with any armature current waveform and any number of slots. The analytical solutions based on the subdomain model, in terms of a two-dimensional Cartesian coordinate system, are obtained using boundary conditions. The analytical results of the magnetic field are validated extensively with finite-element (FE) analyses. Based on these solutions, the inductance is also determined analytically. Finally, the predictions are compared with the three-dimensional FE analyses and the measured data to confirm the validity of the analysis methods presented in this paper.
Insight into physics‐based RRAM models – review

This article presents a review of physical, analytical, and compact models for oxide-based RRAM devices. An analysis of how the electrical, physical, and thermal parameters affect resistive switching and the different current conduction mechanisms that exist in the models is performed. Two different physical mechanisms that drive resistive switching; drift diffusion and redox which are widely adopted in models are studied. As for the current conduction mechanisms adopted in the models, Schottky and generalised hopping mechanisms are investigated. It is shown that resistive switching is strongly influenced by the electric field and temperature, while the current conduction is weakly dependent on the temperature. The resistive switching and current conduction mechanisms in RRAMs are highly dependent on the geometry of the conductive filament (CF). 2D and 3D models which incorporate the rupture/formation of the CF together with the variation of the filament radius present accurate resistive switching behaviour.
A Compressive Sensing Approach to Detect the Proximity Between Smartphones and BLE Beacons

Bluetooth low energy (BLE) beacons have been widely deployed to deliver proximity-based services (PBSs) to user’s smartphones when users are in the proximity of a beacon. Conventional proximity detection simply uses the received signal strength (RSS) to infer the proximity, and then retrieves the PBS by mapping the beacon ID with the corresponding service in the cloud database. Such an approach suffers two major issues: 1) the severe RSS fluctuation might confuse the smartphone during the detection and 2) a malicious PBS can be delivered by manipulating the same beacon ID. This paper proposes RF fingerprinting to label a beacon with an <inline-formula> <tex-math notation="LaTeX">$N$ </tex-math></inline-formula>-dimensional fingerprint vector, which consists of <inline-formula> <tex-math notation="LaTeX">$N$ </tex-math></inline-formula> RSS values from <inline-formula> <tex-math notation="LaTeX">$N$ </tex-math></inline-formula> deployed beacons. The contribution of our proposed method is twofold: 1) we infer the proximity based on the fingerprint vector instead of relying solely on the single RSS value and 2) we retrieve the PBS by mapping the fingerprint vector instead of the hard-coded beacon ID. The challenge with our proposed approach is the incomplete fingerprint observation during real-time detection, resulting in an underdetermined proximity detection problem. To this end, we exploit the compressive sensing (CS) approach based on the differential evolutional algorithm to address such an underdetermined problem. Extensive simulations with real-world datasets show that our proposed approach outperforms the legacy machine learning techniques with substantial performance gains.
Estimation of Individual Failure Rates for Power System Components Based on Risk Functions

The failure rate is essential in power system reliability assessment and thus far, it has been commonly assumed as constant. This is a basic approach that delivers reasonable results. However, this approach neglects the heterogeneity in component populations, which has a negative impact on the accuracy of the failure rate. This paper proposes a method based on risk functions, which describes the risk behavior of condition measurements over time, to compute individual failure rates within populations. The method is applied to a population of 12 power transformers on transmission level. The computed individual failure rates depict the impact of maintenance and that power transformers with long operation times have a higher failure rate. Moreover, this paper presents a procedure based on the proposed approach to forecast failure rates. Finally, the individual failure rates are calculated over a specified prediction horizon and depicted with a 95% confidence interval.
A systematic comparison of spatial search strategies for open government datasets

Datasets produced or collected by governments are being made publicly available for re-use. Open government data portals help realize such reuse by providing list of datasets and links to access those datasets. This ensures that users can search, inspect and use the data easily. With the rapidly increasing size of datasets in open government data portals, just like it is the case with the web, finding relevant datasets with a query of few keywords is a challenge. Furthermore, those data portals not only consist of textual information but also georeferenced data that needs to be searched properly. Currently, most popular open government data portals like the data.gov. uk and data.gov. ie lack the support for simultaneous thematic and spatial search. Moreover, the use of query expansion hasn’t also been studied in open government datasets. In this study we have assessed different spatial search strategies and query expansions’ performance and impact on user relevance judgment. To evaluate those strategies we harvested machine readable spatial datasets and their metadata from three English based open government data portals, performed metadata enhancement, developed a prototype and performed theoretical and user evaluation. According to the results from the evaluations keyword based search strategy returned limited number of results but the highest relevance rating. In the other hand aggregated spatial and thematic search improved the number of results of the baseline keyword based strategy with a 1 second increase in response time and but decreased relevance rating. Moreover, strategies based on WordNet Synonyms query expansion exhibited the highest relevance rated first seven results than all other strategies except the keyword based baseline strategy in three out of the four query terms. Regarding the use of Hausdorff distance and area of overlap, since documents were returned as results only if they overlap with the query, the number of results returned were the same in both spatial similarities. But strategies using Hausdorff distance were of higher relevance rating and average mean than area of overlap based strategies in three of the four queries. In conclusion, while the spatial search strategies assessed in this study can be used to improve the existing keyword based OGDs search approaches, we recommend OGD developers to also consider using WordNet Synonyms based query expansion and hausdorff distance as a way of improving relevant spatial data discovery in open government datasets using few keywords and tolerable response time.
SERUM FIBRONECTIN: AN INDICATOR OF NUTRITIONAL STATUS

Few techniques exist to evaluate nutritional status in infants and children. We determined serum fibronectin, prealbumin, and albumin values in 27 malnourished children (ages 1 mo - 21/2 yr) to assess serum fibronectin as a biochemical marker of nutritional state. Height, weight, estimated weight for age/height for age, head circumference to mid-humeral circumference ratio, and skinfold thickness measurements were obtained on admission to the study and serially. Patients' nutritional status was categorized as severe or mild-moderately malnourished or "nutritionally restored" by anthropometry;Prealbumin and serum fibronectin were significantly decreased in patients with severe malnutrition compared to mild-moderate malnutrition or "nutritionally restored" patients. There was no sigificant difference in prealbumin and serum fibronectin concentrations in study patients with mild-moderate malnutrition compared to "nutritionally restored" patients (prealbumin p = .24, fibronectin p = .06). Albumin concentrations were higher in the better nourished patient group, however, no significant increases were seen. Serum fibronectin significantly correlated (R = 0.64, p <.01) with prealbumin (all groups compared concomitantly). Serum fibronectin may be a sensitive indicator of nutritional adequacy.
Postgraduate Students’ Satisfaction with Library Services at the Federal University of Agriculture, Abeokuta, Nigeria

The study investigated the responses of post graduate students on the extent of utilization and accessibility of library resources as well as level of satisfaction with the quality of services provided in the Federal University of Agriculture, Abeokuta library. A descriptive survey design was used to investigate the study and random sampling technique was used to select the respondents. Questionnaire was used to gather information from PG students in all the ten faculties in the university. Out of 100 copies of questionnaire administered, 86 were returned and found usable for the analysis. The result revealed that collections of the library are adequate in term of resources; Books and Newspapers are highly accessible but Newspapers are not utilized by the PG students. Electronic journals were highly utilized by the PG students. The study also revealed that students were mostly using personal modem for internet service. On the level of satisfaction with the service quality; students were not satisfied with the Accessibility to electronic databases, and the way information needs of users are being met. Also the students were not satisfied with the Provision of timeliness and promptness of information to users and lastly with the way information are being disseminated to users. Study recommends that the library management should train staff on human behavior in library administration and also improve on the services where students are not satisfied.
FAKTOR-FAKTOR YANG BERHUBUNGAN DENGAN PERSEPSI DAN KESIAPAN DOSEN FAKULTAS KEDOKTERAN UNIVERSITAS DIPONEGORO TERHADAP INTERPROFESSIONAL EDUCATION (IPE)

Latar belakang Kualitas pelayanan kesehatan sangat ditentukan oleh kemampuan berkolaborasi, kerjasama dan komunikasi antar profesi tenaga kesehatan yang dapat ditingkatkan melalui program Interprofessional Education (IPE). Persepsi dan kesiapan dosen pembimbing adalah bagian penting dalam pelaksanaan program IPE. Penelitian ini bertujuan untuk menganalisis gambaran persepsi dan kesiapan, faktor-faktor yang berhubungan dengan persepsi dan kesiapan, dan hubungan antara persepsi dan kesiapan dosen FK Undip terhadap IPE. Metode : Penelitian deskriptif analitik dengan rancangan cross sectional. Pengambilan sampel menggunakan teknik total sampling pada dosen Fakultas Kedokteran Universitas Diponegoro yang telah bertugas sebagai dosen pembimbing lapangan (DPL) IPE tahun 2018. Responden terdiri dari 14 dosen Kedokteran, 10 dosen Ilmu Keperawatan, dan 11 dosen Ilmu Gizi. Data diambil menggunakan kuesioner Interprofessional Education Perceptions Scale (IEPS) untuk menilai persepsi dosen terhadap IPE dan Readiness Interprofessional Learning Scale (RIPLS) dimodifikasi untuk menilai kesiapan dosen terhadap IPE. Teknik analisis data yang digunakan adalah uji korelasi Pearson untuk menguji hubungan persepsi dan kesiapan dosen terhadap IPE. Hasil : Mayoritas dosen FK Undip memiliki persepsi (68.6%) dan kesiapan (82,9 %) dalam kategori baik terhadap IPE. Terdapat perbedaan bermakna (p = 0,005) kesiapan dosen terhadap IPE berdasarkan karakteristik jurusan. Terdapat hubungan positif yang sedang (p = 0,000 ; r = 0.570) antara persepsi dan kesiapan dosen FK Undip terhadap IPE. Simpulan : Terdapat faktor yang berhubungan dengan kesiapan dosen terhadap IPE. Persepsi dosen terhadap IPE berhubungan dengan kesiapan dosen terhadap IPE. Kata kunci : IPE, Persepsi, Kesiapan.
Carrier frequency offset estimation for OFDM systems with null subcarriers

In this paper, we propose an iterative CFO estimator using a specific pattern of alternating pilots and null subcarriers in training OFDM block. One major advantage of the proposed estimator is its simple structure. The proposed method estimates the CFO in an iterative fashion based on the signals at the null subcarriers and use of the estimated CFO to correct the carrier frequency for the next iteration. It is found that with the proposed scheme, the final estimation accuracy depends only on the signal to noise ratio and is insensitive to the initial frequency offset. Simulation results demonstrate that the algorithm can achieve relatively high estimation accuracy within a few iterations in frequency-selective fading channels.
In Vivo Bioluminescence Imaging of Transplanted Mesenchymal Stem Cells as a Potential Source for Pancreatic Regeneration

Stem cell therapy has been studied intensively as a promising therapeutic strategy toward a cure for diabetes. To study the effect of mesenchymal stem cell (MSC) transplantation for pancreatic regeneration, we monitored the localization and distribution of transplanted MSCs by bioluminescence imaging in a mouse model. Bone marrow MSCs were isolated and transfected with a highly sensitive firefly luciferase reporter gene. To assess the efficiency of MSC transplantation, a partially pancreatectomized (PPx) mouse model was used. Transplanted MSCs were monitored by confocal microscopy and in vivo bioluminescence imaging. Daily blood glucose levels and glucose tolerance were measured. Insulin-secreting beta cells were immunostained, and insulin levels were measured via enzyme-linked immunosorbent assay. Bioluminescence signals were clearly detected from the transplanted MSCs in the pancreatic region regardless of injection route. However, locally injected MSCs exhibited more rapid proliferation than ductally injected MSCs. PPx mice harboring transplanted MSCs gradually recovered from impaired glucose tolerance. Although insulin secretion was not observed in MSCs, transplanted MSCs facilitate the injured pancreas to recover its function. In vivo optical imaging of transplanted MSCs using a highly sensitive luciferase reporter enables the assessment of MSC transplantation efficiency in a PPx mouse model.
Efficient Algorithms for Knowledge-Enhanced Supertree and Supermatrix Phylogenetic Problems.

Phylogenetic inference is a computationally difficult problem, and constructing high quality phylogenetic trees that can build upon existing phylogenetic knowledge and synthesize insights from new data remains a major challenge. We introduce knowledge-enhanced phylogenetic problems for both supertree and supermatrix phylogenetic analyses. These problems seek an optimal phylogenetic tree that can only be assembled from a user-supplied set of, possibly incompatible, phylogenetic relationships. We describe exact polynomial time algorithms for the knowledge-enhanced versions of the NP-hard Robinson Foulds, gene duplication, duplication and loss, and deep coalescence supertree problems. Further, we demonstrate that our algorithms can rapidly improve upon results of local search heuristics for these problems. Finally, we introduce a knowledge-enhanced search heuristic that can be applied to discrete character data sets using the maximum parsimony (MP) phylogenetic problem. Although this approach is not guaranteed to find exact solutions, we show that it also can improve upon parsimony solutions from commonly used MP heuristics.