Miracle-dz/UniFAR-FTUs huggingface dataset:
Design of dual band sawtooth patch antenna using PBG structure

In this paper, a design strategy using periodic dielectric, metallic, or composite Photonic Band Gap (PBG) structure is proposed for X-band and Ku-band (11.13 GHz to 13.88 GHz). It is observed with the help of simulation results that the bandwidth has improved 22% with return loss -34db. Microstrip PBG structures could suppress the surface wave propagating on substrate and prohibit the formation of substrate modes. Additionally it's low volume, low profile and light weight which can be manufacture easily and used widely in wireless and satellite communication. In integration, it is withal proposed that the comportment of the photonic crystals will lead to a drop in pattern side lobes resulting in amendments in radiation pattern front-to-back ratio and on the whole antenna efficiency. This research is done through systematic simulations using IE3D based on MOM method.
Fostering Cooperative Activism through Critical Design

Critical design is gaining momentum in interaction design, yet little CSCW research has focused on articulating the cooperative potentials of critical design artefacts. We address this gap by reflecting upon a design project aimed at overturning the prevailing narrative regarding dyslexia in Italy. The adversarial propositions embedded in our critical design artefacts challenged the description of dyslexia as a learning disorder putting forward the view of a learning difference. These artefacts demonstrated their capacity to bridge heterogeneous social worlds (those of teachers, children, and parents) into one cooperative entity and mobilise cooperative activism. The contribution to CSCW is two-fold. Firstly, we introduce the cooperative potentials of critical design artefacts; secondly, we propose critical design as a strategy for researchers engaging with cooperative activism.
A BAYESIAN COMBINATION METHOD FOR SHORT TERM LOAD FORECASTING

This paper presents the Bayesian Combined Predictor (BCP), a probabilistically motivated predictor for Short Term Load Forecasting (STLF) based on the combination of an artificial neural network (ANN) predictor and two linear regression (LR) predictors. The method is applied to STLF for the Greek Public Power Corporation dispatching center of the island of Crete, using 1994 data, and daily load profiles are obtained. Statistical analysis of prediction errors reveals that during given time periods the ANN predictor consistently forecasts better for certain hours of the day, while the LR predictors forecast better during for the rest. This relative prediction advantage may change over different time intervals. The combined prediction is a weighted sum of the ANN and LR predictions, where the weights are computed using an adaptive update of the Bayesian posterior probability of each predictor, based on their past predictive performance. The proposed method outperforms both ANN and LR predictions.
Image Description Using a Multiplier-Less Operator

A fast algorithm for image classification based on a computationally efficient operator forming a semigroup on real numbers is developed. The new operator does not require any multiplications. The co-difference matrix based on the new operator is defined and an image descriptor using the co-difference matrix is developed. In the proposed method, the multiplication operation of the well-known covariance method is replaced by the new operator. The proposed method is experimentally compared with the regular covariance matrix method. The proposed descriptor performs as well as the the regular covariance method without performing any multiplications. Texture recognition and licence plate identification examples are presented.
A State-Based Testing Approach Providing Data Flow Coverage in Object-Oriented Class Testing

A novel Object-Oriented class testing approach, proposed in this paper, combines functional with structural testing techniques. Based on state-based testing, test cases generated from the MACT (Method for Automatic Class Testing) tool can be used to execute functional testing. The definition-use information of data members, occur in public member functions of a class under test, is generated from MACT to facilitate data flow analysis. Testers can compute definition-use path with the information in order to ensure that the class is also satisfied with data flow coverage at intra-class level. The discussion with a queue class example to reveal that using a hybrid testing technique benefits class testing.
ANALISA PENGARUH KUALITAS PELAYANAN DAN KINERJA KARYAWAN BADAN PERTANAHAN NASIONAL KABUPATEN KERINCI TERHADAP KEPUASAN MASYARAKAT

ABSTRAK - Penelitian ini bertujuan untuk menganalisis Pengaruh antara kualitas pelayanan dan kinerja karyawan Badan Pertanahan Nasional Kabupaten Kerinci terhadap kepuasan masyarakat. Metode yang digunakan dalam penelitian ini adalah teknik non probability sampling. Sedangkan jenis non probability sampling yang digunakan adalah accidental sampling. Dalam penelitian ini jumlah sampel adalah sebanyak 35 orang. Analisis data menggunakan regresi linear berganda dan koefisien determinasi. Metode pengambilan data adalah dengan menggunakan kuesioner. Teknik analisis data dalam penelitian ini adalah analisis regresi berganda. Hasil analisis menunjukkan persamaan regresi Y = 7,696 + 0,660 X1 + 0,080 X2. Nilai t tabel adalah 2,032 untuk penelitian ini (α = 5%). Variabel kualitas pelayanan memiliki nilai t hitung 4,998, dan variabel kinerja karyawan memiliki nilai t hitung 0,625, yang berarti faktor kualitas pelayanan berpengaruh signifikan dan memiliki arah hubungan positif sedangkan kinerja karyawanberpengaruh tidak signifikan. Selain itu, uji F menunjukkan nilai F hitung 15,302 sedangkan nilai F tabel 4,139, yang berarti secara bersama-sama/simultan variabel kualitas pelayanan dan kinerja karyawan Badan Pertanahan Nasional Kabupaten Kerinci berpengaruh signifikan terhadap kepuasan masyarakat. Kata kunci :Kualitas Pelayanan, Kinerja karyawan dan Kepuasan Masyarakat
Impact of Transgenic Wheat with wheat yellow mosaic virus Resistance on Microbial Community Diversity and Enzyme Activity in Rhizosphere Soil

The transgenic wheat line N12-1 containing the WYMV-Nib8 gene was obtained previously through particle bombardment, and it can effectively control the wheat yellow mosaic virus (WYMV) disease transmitted by Polymyxa graminis at turngreen stage. Due to insertion of an exogenous gene, the transcriptome of wheat may be altered and affect root exudates. Thus, it is important to investigate the potential environmental risk of transgenic wheat before commercial release because of potential undesirable ecological side effects. Our 2-year study at two different experimental locations was performed to analyze the impact of transgenic wheat N12-1 on bacterial and fungal community diversity in rhizosphere soil using polymerase chain reaction-denaturing gel gradient electrophoresis (PCR-DGGE) at four growth stages (seeding stage, turngreen stage, grain-filling stage, and maturing stage). We also explored the activities of urease, sucrase and dehydrogenase in rhizosphere soil. The results showed that there was little difference in bacterial and fungal community diversity in rhizosphere soil between N12-1 and its recipient Y158 by comparing Shannon's, Simpson's diversity index and evenness (except at one or two growth stages). Regarding enzyme activity, only one significant difference was found during the maturing stage at Xinxiang in 2011 for dehydrogenase. Significant growth stage variation was observed during 2 years at two experimental locations for both soil microbial community diversity and enzyme activity. Analysis of bands from the gel for fungal community diversity showed that the majority of fungi were uncultured. The results of this study suggested that virus-resistant transgenic wheat had no adverse impact on microbial community diversity and enzyme activity in rhizosphere soil during 2 continuous years at two different experimental locations. This study provides a theoretical basis for environmental impact monitoring of transgenic wheat when the introduced gene is derived from a virus.
Efficient low-rank supported extreme learning machine for robust face recognition

Recently, deep learning based face recognition algorithms have achieved great success in recognition performance. However, designing and training complex learning models suffer from time and labor efficiency. In this paper, we propose a novel three-layer low-rank supported extreme learning machine (LSELM) algorithm to take advantage of both robust feature representation and fast classification for efficient recognition. Every given probe sample is first clustered into a sub-class spanned by linear representation. With this sub-class, low-rank and robust features that are insensitive to disguise, noise, variant expression or illumination are recovered. These discriminative features are then coded to support a forward neural network for efficient prediction. Experimental results show that LSELM is on par with other deep learning based face recognition algorithms in recognition performance but has less time complexity on both AR and extend Yale-B datasets.
Teacher Commitment and Parent Involvement on Learner Performance: A Crucial Concerted Attribute

Abstract The purpose of this paper was to explore the impact of teacher commitment and parent involvementon learner performance. Most teachers are traditionally restricted to their role of teaching. In recent years, therole of the teacher has undergone a significant overhaul. Teachers are now obliged to assume new roles and tasks toimprove the quality of their teaching and learning. The results of this study suggests that the performance of ateacher is supposed to reflect their quality teaching and learning abilities, communication skills, dedication to theirwork, parental involvement, sacrifice, initiative, creativity, resourcefulness, willingness to take on responsibilityand leadership qualities. This qualitative study was conducted through thematic content analysis. Data was gatheredthrough observations and focus group interviews. The paper concludes with recommendations on how parents andteachers can work together as associates in order to achieve the all-inclusive potential of the learner.
The Industry Origins of the US–Japan Productivity Gap

Abstract This paper presents a comparison of total factor productivity (TFP) levels between the US and Japan for the period 1960–2004 and allocates the gap to individual industries. We carefully distinguish the various concepts of purchasing power parity (PPP) and measure them within the framework of a US–Japan bilateral input–output table. We also measure industry-level PPPs for capital, labor, energy, and materials inputs and output for 42 industries common to the US and Japan, based on detailed estimates for 164 commodities, 33 assets, including land and inventories, and 1596 labor categories. The US–Japan productivity gap shrank during three decades of rapid Japanese economic growth, 1960–1990. The Japanese manufacturing sector achieved parity with its US counterpart by the end of the period. With the collapse of the Japanese economic bubble at the end of the 1980s, the US–Japan productivity gap reversed course and expanded to 79.5% by 2004. This can be attributed to rapid productivity growth in the IT-producing industries in the US during the late 1990s and the sharp acceleration of productivity growth in the IT-using industries in the US during 2000–2004. Wholesale and Retail Trade emerged as the largest contributor to this gap, accounting for 25.1% of the lower TFP of the Japanese economy.
International Journal of Advanced Robotic Systems An Autonomous UAV with an Optical Flow Sensor for Positioning and Navigation Regular Paper

A procedure to control all six DOF (degrees of freedom) of a UAV (unmanned aerial vehicle) without an external reference system and to enable fully autonomous flight is presented here. For 2D positioning the principle of optical flow is used. Together with the output of height estimation, fusing ultrasonic, infrared and inertial and pressure sensor data, the 3D position of the UAV can be computed, controlled and steered. All data processing is done on the UAV. An external computer with a pathway planning interface is for commanding purposes only. The presented system is part of the AQopterI8 project, which aims to develop an autonomous flying quadrocopter for indoor application. The focus of this paper is 2D positioning using an optical flow sensor. As a result of the performed evaluation, it can be concluded that for position hold, the standard deviation of the position error is 10cm and after landing the position error is about 30cm.
On the use of PDF schemes to parameterize sub‐grid clouds

Using high resolution simulations of eight well‐documented cloud cases in different climate regimes, this study investigated the statistical distributions of dynamic and thermodynamic variables in the cloud layer and examined various assumptions used by the current statistical cloud schemes. It is found that dynamic and thermodynamic variables skew differently in the cloud layer of shallow cumulus, stratocumulus, and deep convective clouds. Vertical velocity is positively skewed, but the skewed dynamic structure cannot account for the large skewness of positively skewed total mixing ratio qt and negatively skewed liquid water potential temperature θl. It is, thus, not physically sound to assume that the sub‐grid variation of different variables follows the same skewed PDF. The simulations further show that the weighted standard deviations of qt and θl have the same order of magnitude in all types of clouds, indicating that the variations of temperature and moisture are the equally important factors for sub‐grid clouds. Thus, neglecting either one of them in a statistical cloud scheme may introduce significant bias in the parameterized clouds.
Surprisingly correct: Unexpectedness of observed actions activates the medial prefrontal cortex

Not only committing errors, but also observing errors has been shown to activate the dorsal medial prefrontal cortex, particularly BA 8 and adjacent rostral cingulate zone (RCZ). Currently, there is a debate on whether this activity reflects a response to the incorrectness of the committed action or to its unexpectedness. This article reports two studies investigating whether activity in BA 8/RCZ is due to the unexpectedness of observed errors or the incorrectness of the specific observed action. Both studies employed an action observation paradigm reliant on the observation of an actor tying sailing knots. The reported behavioral experiment delivered evidence that the paradigm successfully induced the expectation of incorrect actions as well as the expectation of correct actions. The functional magnetic resonance imaging study revealed that unexpectedly correct as well as unexpectedly incorrect actions activate the BA 8/RCZ. The same result was confirmed for a coordinate in the vicinity that has been previously reported to be activated in separate studies either by the error observation or by the unexpectedness of committed errors, and has been associated with the error‐related negativity. The present results suggest that unexpectedness has an impact on the medial prefrontal correlate of observed errors. Hum Brain Mapp 35:1615–1629, 2014. © 2013 Wiley Periodicals, Inc.
Using entropy for dimension reduction of tactile data

Tactile sensing arrays for robotic applications become more and more popular these days. This allows us to equip robots with sensing abilities similar to those of our human skin. This paper presents an approach to tactile-based recognition of objects and evaluates the utility of various feature extractors for tactile processing. Extracting these features from a tactile database, we describe a system that combines a discretization step with the well-known C4.5 algorithm in an object classification task. We analyse the usefulness of the features in terms of entropy-based considerations taking into account the generated decision trees and report our results that give important hints for feature selection.
Classification of gothic and baroque architectural elements

Architectural elements are the components and details of buildings. Their unique set, combination, design, construction technique form the architectural style of buildings. Building facade classification by architectural styles is viewed as a task of classifying separate architectural structural elements. In the scope of building facade architectural style classification the current paper targets the problem of classification of Gothic and Baroque architectural elements called tracery, pediment and balustrade. Since certain gradient directions dominate on the shape of each architectural element, discrimination between dominating gradients means classification of architectural elements and thus architectural styles. We use local features to describe gradient directions. Our approach is based on clustering and learning of local features and yields a high classification rate.
Técnicas de Elicitação de Conhecimento Tácito Coletivo: um estudo de caso aplicado a uma Empresa do Ramo Metalúrgico

O presente trabalho apresenta a teoria e a aplicacao de algumas tecnicas de elicitacao de conhecimento tacito adaptadas a realidade da empresa estudada para explicitar o conhecimento de um grupo de mecânicos de producao de uma empresa metalurgica do ramo de embalagens metalicas. Apos a elicitacao dos conhecimentos, os mesmos foram representados em forma de regras de producao (algoritmos simbolicos) elaboradas para auxiliar na forma de identificacao de causas de defeitos no processo produtivo. Para estruturar a pesquisa e sequencia logica da aplicacao das tecnicas de elicitacao de conhecimento, foi utilizada a tecnica da Sistemografia, que preconiza o pensamento sistemico como forma de observacao de fenomenos complexos e modelagem de objetos nas organizacoes. Destaca-se que a metodologia de elicitacao de conhecimento tacito coletivo obteve exito, pois a partir desta aplicacao, foram elaboradas 76 regras de producao para o processo de soldagem da embalagem e 65 regras de producao para o processo de aplicacao de vedante, totalizando 141 regras de producao. Estas regras de producao configuram em uma base de conhecimento explicito, o que antes nao existia na organizacao.
A leg configuration sensory system for dynamical body state estimates in a hexapod robot

We report on a novel leg strain sensory system for the autonomous robot RHex [Saranli U. et al., 2001] implemented upon a cheap, high performance local wireless network [H. Komsuoglu, 2002]. We introduce a model for RHex's 4-bar legs [E.Z. Moore, 2001] relating leg strain to leg kinematic configuration in the body coordinate frame. We compare against ground truth measurement the performance of the model operating on real-time leg strain data generated under completely realistic operating conditions. We introduce an algorithm for computing six degree of freedom body posture measurements in world frame coordinates from the outputs of the six leg configuration models, together with a priori information about the ground. We discuss the manner in which such stance phase configuration estimates will be fused with other sensory data to develop the continuous time full body state estimates for RHex.
A DESIGN FOR A GROUP MEMORY SYSTEM USING ONTOLOGIES

Organisations recognise the importance of managing what they consider their most valuable asset: Knowledge. Our work is a contribution towards that end, proposing a system for representing, recording, using, retrieving, and managing knowledge. This paper begins by briefly outlining the concept of an Organisational Memory. It will then discuss the high-level conceptual taxonomy that could be used for the design of an Organisational Memory System based on a form of knowledge representation used in Artificial Intelligence: Ontologies. The paper will then discuss a specific implementation of an Organisational Memory System: a Group Memory System using Design Rationale Systems and Case-Based Reasoning. Examples to illustrate the application of such a Group Memory System in a real organisational setting are provided.
A reduced‐complexity quadratic structure for the detection of stochastic signals

Quadratic detection of discrete‐time stochastic signals in additive stationary Gaussian noise is considered. A banded‐quadratic detector structure is introduced to reduce the multiplicative complexity and data storage requirements of the optimum full‐quadratic detector, and the optimization of this reduced‐complexity structure is studied. The issue of performance versus complexity is explored for the specific problems of detecting wide‐sense Markov and triangularly correlated signals in white noise, with the conclusion that performance of the reduced complexity detector can be very close to optimum if an adequate quadratic‐form bandwidth is chosen.
Feature-preserving anisotropic smoothing for meshes with large-scale noise

This paper presents a smoothing method which preserves features for a triangular mesh even when large-scale noise are included because of measurement errors. First, scale-dependent discrete Laplacian is introduced along with boundary Laplacian to deal with an open mesh. Then, a method for feature detection which uses the values by these Laplacians is constructed. Furthermore, anisotropic diffusion is proposed which determines suitable parameters from the values for preserving features. Finally a method is presented which discriminates features from large-scale noise by generating graph of feature lines. Effectiveness of the methods is shown by the experiment results of well-smoothed meshes with their features preserved.
Promiscuous Binding in a Selective Protein: The Bacterial Na+/H+ Antiporter

The ability to discriminate between highly similar substrates is one of the remarkable properties of enzymes. For example, transporters and channels that selectively distinguish between various solutes enable living organisms to maintain and control their internal environment in the face of a constantly changing surrounding. Herein, we examine in detail the selectivity properties of one of the most important salt transporters: the bacterial Na/H antiporter. Selectivity can be achieved at either the substrate binding step or in subsequent antiporting. Surprisingly, using both computational and experimental analyses synergistically, we show that binding per se is not a sufficient determinant of selectively. All alkali ions from Li to Cs were able to competitively bind the antiporter's binding site, whether the protein was capable of pumping them or not. Hence, we propose that NhaA's binding site is relatively promiscuous and that the selectivity is determined at a later stage of the transport cycle.
Normative Influences on Adolescents’ Self-Reported Pro-Environmental Behaviors: The Role of Parents and Friends

Pro-environmental behavioral patterns are influenced by relevant others’ actions and expectations. Studies about the intergenerational transmission of environmentalism have demonstrated that parents play a major role in their children’s pro-environmental actions. However, little is known about how other social agents may shape youth’s environmentalism. This cross-sectional study concentrates on the role that parents and peers have in the regulation of 12- to 19-year-olds’ pro-environmental behaviors. We also consider the common response bias effect by examining the associations between parents, peers, and adolescents’ pro-environmentalism in two independent data sets. Data Set 1 (N = 330) includes adolescents’ perceptions of relevant others’ behaviors. Data Set 2 (N = 152) includes relevant others’ self-reported pro-environmental behavior. Our results show that parents’ and peers’ descriptive and injunctive norms have a direct effect on adolescents’ pro-environmental behavior and an indirect one, through personal norms. Adolescents seem to be accurate in the perception of their close ones’ environmental actions.