Miracle-dz/UniFAR-FTUs huggingface dataset:
Deep Few-Shot Learning for Hyperspectral Image Classification

Deep learning methods have recently been successfully explored for hyperspectral image (HSI) classification. However, training a deep-learning classifier notoriously requires hundreds or thousands of labeled samples. In this paper, a deep few-shot learning method is proposed to address the small sample size problem of HSI classification. There are three novel strategies in the proposed algorithm. First, spectral–spatial features are extracted to reduce the labeling uncertainty via a deep residual 3-D convolutional neural network. Second, the network is trained by episodes to learn a metric space where samples from the same class are close and those from different classes are far. Finally, the testing samples are classified by a nearest neighbor classifier in the learned metric space. The key idea is that the designed network learns a metric space from the training data set. Furthermore, such metric space could generalize to the classes of the testing data set. Note that the classes of the testing data set are not seen in the training data set. Four widely used HSI data sets were used to assess the performance of the proposed algorithm. The experimental results indicate that the proposed method can achieve better classification accuracy than the conventional semisupervised methods with only a few labeled samples.
Numerical Approximation of the Maximum Power Consumption in DC-MGs With CPLs via an SDP Model

This brief addresses the numerical approximation of the maximum power consumption in direct-current microgrids (DC-MGs) with constant power loads through a convex optimizing model. The convex formulation is developed via a semidefinite programming model and is solved by using a MATLAB/CVX package. For comparison purposes the exact nonlinear model is solved in a GAMS package to compare the accuracy and quality of the results obtained with the proposed convex reformulation. Numerical testing is made with a small three-node DC-MG test system as well as DC-MGs from 10 to 150 nodes.
Comparison of SVM & Naïve Bayes Algorithm for Sentiment Analysis Toward West Java Governor Candidate Period 2018-2023 Based on Public Opinion on Twitter

Opinion is a statement conveyed by a person or group of people in addressing a problem by providing predictions or expectations about the event. No guarantee that an opinion automatically will be true because it is not reinforced by the facts, it is subjective, and there is a different opinion about an event. Everyone has different views and same rights to express opinions or give opinions toward particular event. Public opinion is view of someone for certain problem comes out due to prior conversation with another person who may have an effect on the opinion given. Public opinion comes from a discussion process in addressing the problem then lead to a conclusion as a joint decision and a shared opinion. One of the media to convey public opinion is through social media like twitter. Public opinion about the election of West Java governor candidate period 2018-2023 on twitter was increasingly widespread. There are several sentiments emerged for four candidates elected on twitter accounts such as Ridwan Kamil-Uu Ruzhanul Ulum, Tubagus Hasanuddin-Anton Charliyan, Sudrajat-Ahmad Syaikhu, and Deddy Mizwar-Dedi Mulyadi. Therefore, it is necessary to classify the sentiments to the existing opinion so that it can be predicted in advance which of the governor candidate pair of West Java who has more positive and predictable sentiments will be elected as governor period 2018-2023. The data used by the researchers is tweet in Indonesian Language with keywords Rindu, Hasanah, Asyik, 2DM with datasets number is 800 tweets. There are many classification techniques commonly used for opinion sentiment analysis. This study compares two classification techniques namely Support Vector Machine Algorithm (SVM) and Naïve Bayes Classifier (NBC). The results show that the Algorithm of Naïve Bayes Classifier (NBC) has a higher accuracy level of Support Vector Machine (SVM), up to 94% for Deddy Mizwar-Dedi Mulyadi.
A Convolutional Neural Network Approach for a P300-based Brain-Computer Interface for Disabled and Healthy Subjects

In this manuscript, we analyze different topologies of Convolutional Neural Networks (CNN) for classifying the P300 wave from an EEG signal. Also, we propose a selection criteria in order to improve the classification accuracy. In this study, the brain signals of healthy and disabled subjects were analyzed and four architectures were tested with different numbers of filters with the same dimensions. The results of the current work indicate that the best bitrate in disabled and healthy subjects was 14.14 and 25.44 bits per minute, respectively. Using target by block evaluation, the classification accuracy of 100% was obtained in healthy and disabled subjects. This approach is compared to various machine learning algorithms so that our results outperformed others works.
Transport Critical Current Density in Single-Core Composite Ba122 Superconducting Tapes

We fabricate a 1-meter-long AgSn-stainless steel composite superconducting tape via a flat rolling process. The transport critical current density <italic>J</italic><sub>c</sub> at different temperatures and magnetic fields is substantially studied. At 4.2 K and 10 T, the <italic>J</italic><sub>c</sub> of one short sample cut from the 1-meter-long tape achieves 8 × 10<sup>4</sup> A/cm<sup>2</sup>. At 20 K and 10 T, the <italic>J</italic><sub>c</sub> is also as high as 1.4 × 10<sup>4</sup> A/cm<sup>2</sup>. Moreover, the 1-meter-long tape presents good <italic>J</italic><sub>c</sub> homogeneity with an average value of 7.3 × 10<sup>4</sup> A/cm<sup>2</sup>. We also measure the resistance and susceptibility of the tape without peeling off the sheath. Based on our results, we suggest that the high strength stainless steel not only applies high pressure to the inner core after flat-rolling, but also act as a reinforcing layer to sustain good <italic>J</italic><sub>c</sub> uniformity. We also discuss some drawbacks existing in this method and corresponding solutions.
A Review on Cloud Computing Adoption from the Perspectives of Providers and Clients

Cloud computing received a lot of interests from various organizations since the technology was introduced. The potential of cloud computing as a new IT acquisition approach that provide strategic value to businesses has been discussed broadly including looking at issues and challenges in cloud computing adoption. However, there is a dearth of prior studies to discover the issues and challenges in cloud computing adoption from the providers’ perspective as most of past researches mainly focus on the clients’ perspective. In this paper, issues and challenges of cloud computing adoption from both client’s and provider’s perspectives are discussed, based on reviewing past literature related to cloud computing adoption in various countries. The result of the review indicate that there are differences in the issues which become the main concerns of clients and providers of cloud computing services. This paper contributes towards understanding cloud computing adoption from multi-perspectives and help researchers to set future agenda.
LEER: Energy Efficient Routing Protocol for Low Energy Nodes in Wireless Sensor Networks

Nodes in Wireless Sensor Networks (WSNs) are not rechargeable. Hence, it is important to take care of low energy nodes so that they do not drain out at an early stage. In this regard, routing protocol is a prime factor for the prolonged lifetime of low energy sensor nodes. We propose a new protocol LEER (Low Energy nodes Efficient Routing) which primarily focuses on optimizing the energy consumption of low energy nodes. It has two variants namely LEER-Singlehop and LEER-Multihop. In this paper, we compared LEER with Low Energy Adaptive Clustering Hierarchy (LEACH), Threshold Sensitive Energy Efficient sensor Network (TEEN) and Pairwise Energy Efficient Routing (PEER). The performance metrics considered are network lifetime, energy efficiency, the number of dead nodes per round and the time till first node is dead. The experiments we carried out proved our protocol to be much better compared to TEEN, LEACH and PEER.
Measuring Successful Implementation of Knowledge Management System: A Case Study on Ministry of Finance of the Republic of Indonesia

This research applies the Knowledge Management (KM) Success Model to measure the implementation of Knowledge Learning Center (KLC) as the Knowledge Management in The Ministry of Finance of the Republic of Indonesia (MOF). Data was collected by spreading online questionnaire to KLC users. Results show that leadership and knowledge content quality have a positive effect on the perceived usefulness of KMS and user satisfaction. Moreover, perceived usefulness of KMS and user satisfaction has significant positive effect on KMS use for sharing and KMS use for retrieval. The magnitude of perceived usefulness of KMS and user satisfaction effect on KMS use for sharing is 53.9%, while perceived usefulness of KMS and user satisfaction to KMS use for retrieval is 67.5%. Because knowledge management research and implementation in Indonesian government agencies is still very rare, our study is probably the first to analyse factors that are of influence in a successful implementation of Knowledge Management System (KMS) in Indonesian government agencies. This research can be used as an insights for other Indonesian government agencies in Indonesia on how to design and implement KMS in their organizations.
Integrating the Readiness and Usability Models for Assessing the Information System Use

In the systematic view, the use of information system (IS) can be separated into three main parts, i.e., the users as the actor of the use, the use itself as a process, and the system as the used object. However, most of the usability studies focus on the process and object points. The number of scholars who study about the actor of the use is still rare. This is an interesting phenomenon how to develop a comprehensive model which combining the three parts of the above-mentioned parts of the systematic perspective. The purpose of this study was to understand the influential relationships between the readiness and usability factors towards the use of IS and to integrate the readiness and usability models in the context for assessing the use of a new IS. The proposed model was developed by adopting the Parasuraman’s readiness model and the Nielsen’s usability model, in terms of an input-process-output (IPO) logic. Besides the placement transparency of the ten variable within 25 influential relationships, the study also demonstrates coherently the definitions of the variables, its indicators, and the questions of each item measurements.
Data Quality Management Maturity Model: A Case Study in BPS-Statistics of Kaur Regency, Bengkulu Province, 2017

Data are widely used in an organization not only for operation but also for strategic level use. Poor data quality can have negative impact for an organization such as poor decision making and planning. Therefore, data quality management becomes an issue growing today not only to the academic but also professional communities. Based on this issue, this paper presents and analyzes a case study developed in a governmental agency, BPS-Statistics of Kaur Regency. For analysis, a data quality maturity model is used to measure the implementation of data quality management in the organization. The results show that for the dimension of ‘Data quality expectations’ is at a maturity of 4.25. ‘Data quality protocol’ is at a maturity of 3.50. ‘Policies’ reaches a maturity of 3.67. ‘Data quality protocol’ and ‘Data standard’ are at a maturity of 4.42. ‘Data governance’ is at a maturity of 3.00. ‘Technology’ is at a maturity 3.17. ‘Performance management’ is at a maturity of 3.33. However, this also implies that implementing these particular dimensions will lead to a direct increase in overall maturity.
Time-Domain Experimentation of NGD ActiveRC-Network Cell

A theoretical and experimental investigation of low-pass negative group delay (NGD) topology is introduced. The NGD topology is composed of a low noise amplifier (LNA) and RC-parallel series mounted lumped network. The NGD cell theoretical characterization is elaborated. The NGD properties as NGD level, cut-off frequencies and central frequency are established. The synthesis formulas as function of the expected NGD level and gain are established. The NGD proof of concept using monolithic LNA LEE-9+ manufactured by mini-circuits are designed, simulated, fabricated, and measured. The simulated and measured frequency domain results are in good agreement with the circuit theory. As expected, low-pass NGD behavior is observed with −5 ns-NGD level over 32-MHz bandwidth. The low-pass NGD function meaning is illustrated by the advance of the output pulse signal leading and trailing edges compared to the input ones.
Circular Polarized Wide Beam Elliptical Microstrip Antenna for Energy Harvesting Application

A wide beam elliptical microstrip antenna circularly polarized is proposed for RF energy harvesting applications. Circular polarization is achieved by using single coaxial-fed elliptical microstrip antenna and exciting the degenerate even and odd modes corresponding to the fundamental TM11 mode. Further, a cross-slot for perturbing the current distribution of the antenna to cause path difference corresponding to quarter wavelength. The proposed design has a 10 dB impedance bandwidth of equal to 0.1 GHz approximately and an axial ratio bandwidth of 0.02 GHz. A gain of around 3.8 dB and a wide beamwidth of 172 degrees. The overall antenna size is 70 mm x 70mm x 1.6 mm (0.58 λ0 × 0.58 λ0 × 0.013 λ0). The antenna is suitable for use in RF energy harvesting applications from WiFi, Bluetooth and other devices operating in the 2.4 GHz ISM band.
Detection of Sparse Stochastic Signals With Quantized Measurements in Sensor Networks

In this paper, we consider the problem of detection of sparse stochastic signals with quantized measurements in sensor networks. The observed sparse signals are assumed to follow the Bernoulli–Gaussian distribution. Due to the limited bandwidth in sensor networks, the local sensors are required to send quantized measurements to the fusion center. First, we propose a detector using the locally most powerful test (LMPT) strategy, called the quantized LMPT detector, for the problem of distributed detection of sparse signals with quantized measurements. Then, the local quantizers are designed to guarantee the near optimal detection performance of the proposed quantized LMPT detector. When the designed quantization thresholds are applied at the local sensors, we show that 1) the proposed 1-bit LMPT detector with 3.3L sensors achieves approximately the same detection performance as the clairvoyant LMPT detector with L sensors; 2) the proposed LMPT detector with 3-bit measurements can achieve detection performance comparable to the clairvoyant LMPT detector. Simulation results demonstrate the performance of the proposed quantized LMPT detector and corroborate our theoretical analysis.
A BaTiO3-Based Electro-Optic Pockels Modulator Monolithically Integrated on an Advanced Silicon Photonics Platform

To develop a new generation of high-speed photonic modulators on silicon-technology-based photonics, new materials with large Pockels coefficients have been transferred to silicon substrates. Previous approaches focus on realizing stand-alone devices on dedicated silicon substrates, incompatible with the fabrication process in silicon foundries. In this work, we demonstrate monolithic integration of electro-optic modulators based on the Pockels effect in barium titanate (BTO) thin films into the back-end-of-line of a photonic integrated circuit (PIC) platform. Molecular wafer bonding allows fully PIC-compatible integration of BTO-based devices and is, as shown, scalable to 200 mm wafers. The PIC-integrated BTO Mach–Zehnder modulators outperform conventional Si photonic modulators in modulation efficiency, losses, and static tuning power. The devices show excellent VπL (0.2 Vcm) and VπLα (1.3 VdB), work at high speed (25 Gbps), and can be tuned at low-static power consumption (100 nW). Our concept demonstrates the possibility of monolithic integration of Pockels-based electro-optic modulators in advanced silicon photonic platforms.
Extending the End-user Computing Satisfaction with Security Measures

Security issues have been undeniably increasingly becoming a consideration for end users since the early era of internet technology. Despite the issues have indicated practically its influences towards the end-user computing satisfaction (EUCS), but scholars who adopted clearly the construct in the EUCS research model is still rare to be found in the IS research field. This study aims to determine the EUCS status towards the sampled IS implementation and examine the factors that affect the satisfaction. The survey study was done by involving approximately 230 respondents who are selected based on the stratified purposive sampling. The partial least square-structural equation model (PLS-SEM) method the SmartPLS version 3.0 was then employed in the analysis stage. The study revealed that besides EUCS level of the sampled system is currently at a fairly satisfied level, three of the eleven influential paths are rejected. Besides the practical consideration for stakeholders of the sampled IS, the study findings may also become the theoretical considerations for the future studies.
Escherichia coli - gfp biosensors used to monitor the biological activity of carmustine residues in surface water

Three genetic constructs with transcriptional fusion of recA, kat G and sodA genotoxin and genotoxin sensitive promoters with green fluorescent protein (gfp) reporter gene in Escherichia coli have been used for assessment of cytotoxic and genotoxic activity of carmustine in surface water. For experiments, the drug was used at concentrations of 0,01; 0,001; 0,0001; 0,00001 and 0,000001 mg/ml. Bacteria strains were incubated with carmustine for 3 and 24 hours. Experimental data showed different sensitivity of applied promoters for the same concentrations of carmustine. Obtained results indicated that, recA::gfpmut2, katG::gfpmut2 and sodA::gfpmut2 genetic systems were sensitive to carmustine, especially at the concentrations of 0,001; 0,0001 and 0,00001 mg/ml. The strongest reactivity was noticed for recA promoter (FI = 14,64). The results indicated that gfp E. coli strains with recA, katG and sodA could be potentially useful for monitoring of cytoand genotoxic effect of pharmacist residues in surface water.
A Complex Relationship between Freshwater Discharge and Oyster Fishery Catch Per Unit Effort in Apalachicola Bay, Florida: an Evaluation from 1960 to 2013

ABSTRACT Freshwater input is thought to be a critical factor influencing estuaries through multiple direct and indirect pathways. In this study, findings of a key 1992 paper on Apalachicola Bay oyster fishery data and Apalachicola River discharge data from 1960 to 1984 were recreated, and the analysis extended to 1987 to 2013, to evaluate whether relationships previously reported between river discharge and oyster fishery catch per unit effort (CPUE) persist. The originally reported relationship between low river discharge and lower oyster landings 2 y later was confirmed, but when these same relationships for data from 1987 to 2013 were examined, correlation coefficients relating river discharge metrics to oyster fishery CPUE that were significant with 1960 to 1984 data did not persist with data from 1987 to 2013. Combining all available data (1960 to 2013, excluding 1985 to 1986), previously reported significant correlation coefficients were found to have generally persisted or strengthened and the total number of significant correlations increased. A surprising result is the general lack of association between river discharge and oyster fishery landings from 1987 to 2013, a period of frequent drought and generally lower annual river discharge compared with 1960 to 1984. There are multiple possible explanations for the observed relationships between river discharge and oyster fishery landings including (1) counterintuitive changes in oyster fishery landings due to a change in reporting requirements between the two epochs, (2) hyperstable relationship between oyster abundance and fishery CPUE, (3) failure of the Apalachicola Bay oyster population to recover after Hurricane Elena, and (4) ecosystem changes possibly related to nonstationary river discharge levels altering Apalachicola River or Bay ecosystem dynamics in unknown ways. The absence of simple relationships between freshwater input and oyster fishery responses complicates ongoing management and restoration decisions for Apalachicola Bay, and this work demonstrates that, even within the same system, the relationship between freshwater discharge and response by a key estuarine ecosystem constituent is uncertain.
IMPACT OF CUSTOMER SATISFACTION ON CUSTOMER LOYALTY IN UPSCALE ETHNIC RESTAURANTS.

The purpose of this article is to investigate the impact of the service quality factors and the customer satisfaction on customers’ loyalty and positive behavioral intensions in the context of the restaurant industry. The literature review part of the study has analyzed the key concepts of the quality, its dimensions and important features of the service sector. Moreover, the researcher has broadly examined the nature of the customer loyalty, its conceptualizations and segmentations. Reviewing the previous research papers on the topic of study assisted the author to identify that food quality, service quality, physical environment, perceived price and value have direct influence on customers’ satisfaction with their dining experience. Moreover, it was found out that the customer satisfaction is one of the core determinants of the behavioral and attitudinal loyalty. The author has chosen the Good Earth restaurant as a case for the current study and conducted a survey among the randomly selected sample of customers. The findings of the primary research depict that the most of customers visit the restaurant once in two week and spend about 20 – 50 GBP per check per person. It was also found out that the current service and food quality, price, perceived value and physical environment of the restaurant are in satisfactory level. Moreover, the cross-tabulation analysis revealed that the customers who were satisfied with service quality and overall dining experience, showed high response rate for intention to revisit the restaurant in future and recommend it to others.