Miracle-dz/UniFAR-FTUs huggingface dataset:
APLIKASI BURSA KERJA ONLINE BERBASIS WEBSITE DENGAN SISTEM REKOMENDASI MENGGUNAKAN METODE CONTENT BASED FILTERING

Salah satu pemanfaatan website adalah sebagai portal informasi lowongan pekerjaan. Sebelumnya, penyebaran dan pencarian lowongan pekerjaan dilakukan secara manual yaitu mendatangi tempat secara langsung dan mendatangi pameran lowongan kerja atau job fair. Sehingga kesulitan bagi pihak yang mempunyai lowongan dan pihak yang ingin mencari lowongan pekerjaan. Namun seiring dengan perkembangan teknologi dan internet mulai terdapat aplikasi berbasis website yang menjadi portal dalam informasi lowongan pekerjaan seperti cc.dinus. ac.id ,JobsDB, jobstreet. Namun karena informasi yang terdapat dalam website bursa kerja sangat banyak menimbulkan masalah baru yaitu para pengguna website sebagai pencari pekerjaan kesulitan dalam memilih dan mencari informasi lowongan pekerjaan yang tepat. Dalam upaya mengatasi masalah kelebihan informasi yang terdapat pada website bursa kerja dapat diatasi dengan solusi penggunaan sistem rekomendasi. Penelitian ini mengusulkan pembuatan aplikasi bursa kerja online berbasis website dengan sistem rekomendasi. Metode yang diusulkan dalam sistem rekomendasi adalah content based filtering. Metode yang diusulkan pada penelitian yaitu content based filtering telah berhasil diimplementasikan pada aplikasi bursa kerja online. Metode content based filtering dapat digunakan untuk menyarankan informasi lowongan kerja yang sesuai dengan profil pengguna atau pencari kerja sehingga mempermudah proses pencarian informasi.
AN ABSTRACT OF THE THESIS OF Sriraam Natarajan for the degree of Master of Science in Computer Science presented on June 2, 2004. Title: Multi-Criteria Average Reward Reinforcement Learning Abstract approved:

approved: Prasad Tadepalli Reinforcement learning (RL) is the study of systems that learn from interaction with their environment. The current framework of Reinforcement Learning is based on receiving scalar rewards, which the agent aims to maximize. But in many real world situations, tradeoffs must be made among multiple objectives. This necessitates the use of vector representation of values and rewards and the use of weights to represent the importance of different objectives. In this thesis, we consider the problem of learning in the presence of timevarying preferences among multiple objectives. Learning a new policy for every possible weight vector is wasteful. Instead we propose a method that allows us store a finite number of policies, choose an appropriate policy for any weight vector and improve upon it. The idea is that though there can be infinitely many weight vectors, a lot of them will have the same optimal policy. We prove this empirically in two domains: a version of the Buridan's ass problem and network routing. We show that while learning is required for the first few weight vectors, later the agent would settle for an already learnt policy and thus would converge very quickly. Redacted for Privacy Multi-Criteria Average Reward Reinforcement Learning
eu { T , S } SPLITTINGS OF RECTANGULAR MATRICES REVISITED

In this short note, {T, S} splittings of rectangular matrices are considered and derived certain convergence and comparison results. These results involve outer inverses (or {2}-inverses) with prescribed range and null space, of matrices emerge from the {T, S} splittings. AMS Subject Classification: 15A09, 47A75
Valuing improvements in urban water security: evidence of heterogeneity derived from a latent class model for eastern Australia

ABSTRACT In many Australian cities the response to drought has included the imposition of mandatory constraints over how water is used by households, often termed ‘water restrictions’. A similar rationing approach has been witnessed in California’s recent drought. The aim of water restrictions is to slow the depletion of water storage but restrictions have also been criticized for the costs they impose on specific water users. In order to gain insight into the potential magnitude of the cost of water restrictions, this study uses a choice experiment to investigate the non-market values for specific attributes associated with the outcomes of drought restrictions. This information was sought to understand the community’s willingness to pay for attributes related to the extent, frequency and duration of water restrictions. The article reports a latent class choice model for a major city in eastern Australia and investigates heterogeneity in preferences towards increasing water availability during drought. This study departs from the existing literature by conducting the choice experiment in a context where water supply is relatively abundant. This unique framing of the choice experiment allows for a useful comparison with existing studies and also raises challenges about the interpretation of the data for planning purposes.
Digital Control of an AC/DC Converter using the Power Balance Control Technique with Average Output Voltage Measurement

This paper presents a method for the digital control of a high power factor AC/DC converter employing the power balance control technique to achieve a fast response of the output voltage control. To avoid the effects of an output voltage ripple in the voltage control loop, the average output voltage is sampled and used as a feedback signal for the output voltage controller. The proposed control technique was verified by simulations using MATLAB/Simulink and its implementation was realized by a dsPIC30F4011 digital signal processor to control a CUK topology AC/DC converter with a 48V output voltage and a 250 W output power. The experimental results agree with the simulation results. The proposed control technique achieves a fast transient response with a lower line current distortion than is achieved when using a conventional proportional-integral controller and the power balance control technique with the conventional sampling method.
No . 6275 Distance , Globalization , and International Trade

For a long time globalization could be seen everywhere but in gravity estimates. We offer evidence how globalization affects manufacturing trade over the period 1986-2006 and show that, on average, the effect of distance has fallen whereas the effects of proximity and regional trade agreements have increased over time. We also document substantial cross-country heterogeneity in the extent to which distance elasticities have changed. Countries in the middle of the per-capita income distribution have seen the steepest fall in distance coefficients. At the same time, distance as a trade friction has not lost its bite for a number of low income countries, which may jeopardize their integration into global markets. We present suggestive evidence that the heterogeneous change in distance elasticities is related to secular shifts in the composition of exports. JEL-Codes: F130, F140, F160.
High Al-Content AlInGaN Devices for Next Generation Electronic and Optoelectronic Applications

Great strides have been made in the development of ultraviolet LED materials and devices. Power levels in the near UV (below 390 nm) have been improved from the 10 W to the 1 mW level through improvements in the growth and design of AlInGaN alloys. High frequency AlGaN/GaN HEMTs have been developed with ft of 65 GHz and fmax of 85 GHz, all while attaining breakdown voltage greater than 100 V. A new breakthrough in the lateral overgrowth of GaN materials promises to further improve these devices.
HETEROSKEDASTICITY-AUTOCORRELATION ROBUST STANDARD ERRORS USING THE BARTLETT KERNEL WITHOUT TRUNCATION

In this paper we analyze heteroskedasticity-autocorrelation (HAC) robust tests constructed using the Bartlett kernel without truncation. We show that while such an HAC estimator is not consistent, asymptotically valid testing is still possible. We show that tests using the Bartlett kernel without truncation are exactly equivalent to recent HAC robust tests proposed by Kiefer, Vogelsang and Bunzel (2000, Econometrica, 68, pp 695-714).
Quick PCR to detect M. tuberculosis and M. bovis in swine blood samples

The disease control strategies in livestock are the key areas to enhance improvement of livestock production and safety of livestock product consumers. Therefore, reliable techniques for quick detection and specific identification of disease causing agents need to be developed. In this study a nested PCR was developed using primer primier 5.0 software for primer design targeting IS1081 gene conserved regions in both M. tuberculosis and M. bovis. Two sets of primers TB-Q1/TB-Q2 and TB-B1/TB-B2, were designed to detect M. tuberculosis and M. bovis DNA extracted from blood samples. The findings were, the assay is sensitive enough to detect up to 1.35fg of the antigen DNA with 100% specificity. When compared with bovine Purified Protein Derivative skin test, it had better results in terms of sensitivity and specificity. Furthermore, an OxyR gene was targeted for another set of primers OxyRMT-2.1/OxyRMT-1 specific for M. tuber- culosis while OxyRMT-2.1/OxyRMB-2 for M. bovis. Introduction Most developing countries rely on livestock activities, but have a lot of shortcom- ings in implementing effective disease control programs, because of poor infrastructures (Blood et al, 1988). This is a hindrance for export of livestock and their products because the office Internationale des Epizooties (OIE) regulations requires that an exporting country should be free from certain diseases (OIE, 1994). The field trials of this research were done on a farm in Guangdong Province, China. As of 2001, China had a national inventory of pigs estimated at 454 million herds, as compared to that of the world of 928 million (Storburg et al, 2001). The routine tuberculin test has been used with satisfactory results in other parts of the world (Noordhuizen et al, 1997), but not enough informa- tion is available for its use in Guangdong.
Control Design and Implementation of Autonomous 2-DOF Wireless Visual Object Tracking System

Due to large scale implementation of visual detection and tracking as a mean of sensor and navigation tool, target detection and tracking using image manipulation for autonomous robotic system becomes an interesting object of study for many researchers. In addition, there have been attempts to develop a system that can detect and track a moving target by using an image or video processing in a real time condition. Despite that, visual object tracking can be a subject of noise because of image manipulation. The noise can create uncertainty on state and observation model that can lead to control instability, especially that in remote operation. Therefore, an effective filter that can tackle or reduce this noise is needed in developing a visual object tracking system. In this work, a 2-degree of freedom (2-DOF) visual object tracking system was developed with an information filter. The system consists of an image capture unit, an image processing unit, a wireless communication unit, and a manipulator. Then to observe the filter effectiveness on real time visual object tracking in remote operation, performances of this visual object tracking system with and without the filter were tested based on video simulation and real time tracking. In the live streaming test, the information filter can reduce the error of the measurement about 30% than that without it.
Incorporating Smart Sensing Technologies into the Poultry Industry

Increases in production input costs are driving innovation in the poultry industry in Ireland and worldwide. Integration of so called ‘Precision Livestock Farming’ techniques into the poultry industry supply chain will help producers to optimize management systems. This manuscript provides an overview of monitoring and performance sensor technologies within poultry production. It outlines traditional sensing methods and looks at the potential of novel performance related systems that could be incorporated into production facilities. Critical environmental parameters which are relevant to poultry production include inter alia air temperature, relative humidity, light, air speed and air quality (in particular CO2 and NH3 concentrations). Current industry practice with regard to the measurement of these parameters in addition of the effect of these parameters on bird welfare is reviewed, and improvements underpinned by novel technologies and processes are also investigated. Finally, the integration of such systems is also discussed.
Forecasting volatility with macroeconomic and financial variables using Kernel Ridge Regressions

This paper uses the nonlinear method kernel ridge regression to forecast volatilities with 38 macroeconomic and financial variables of four different asset classes, i.e. stocks, bonds, commodities and foreign exchanges. Kernels which are used in this paper are the linear, quadratic and the Gaussian kernel. Tuning parameters of this method are estimated in two ways, i.e. with principal components and on the full dataset of variables. Furthermore, the Least Angle Regression method is used to preselect variables, which are then used by the kernel ridge regression. Next to examining this nonlinear method, 3-month, 6-month and 12-month ahead forecasts are made for kernel ridge regressions and numerous of other linear models. Main findings are that kernel ridge regression performs better than simple linear models, and multi-step ahead forecasts with macroeconomic and financial variables are not better than a simple autoregressive model.
A Multifactorial GIS-Based Analytical Method to Determine the Quality of Urban Green Space and Water Bodies

The type, size, and spatial distribution of public green spaces and water bodies are key factors for the microclimatic quality of urban areas, particularly within densely built-up districts, where they influence the quality of life. The analytical method presented in this paper looks at entire cities in a GIS-based approach that identifies potential critical areas of the city (with regard to heat stress or the accessability of green spaces) and quantifies their size and location in relation to green space and water bodies. The advantage of this method is that analysing the urban environment can be largely automated by the use of available geo base data. This requires the application of algorithms from the field of landscape ecology to the urban environment. The method is based on multifactorial evaluation. Comparisons between cities are made possible by extremum normalisation. Densely built-up areas as well as all green spaces and water bodies within settlements are quantified in the form of areal indicators. Thus the proximity of densely built-up areas to green space or water bodies is measured by the indicator “Euclidian distance. ” By correlating the resulting potential heat islands with population data from the 2011 National Census, it is possible to determine the likely number of residents affected. The method presented, which has been tested on seven cities in Germany, is part of a wide-ranging investigation into urban densities aimed at improving efficiency and environmental quality.
FORMULATION AND EVALUATION OF PARACETAMOL SUSPENSION BY USING NATURAL SUSPENDING AGENT EXTRACTED FROM BANANA PEELS

The present work was aimed to formulate and evaluate a new, cheap and effective natural suspending agent that can be used as an effective alternative for traditional suspending agent. The study procedure involved extraction of suspending agent from the Musa paradisica (Banana) fruit peels, determination of swelling index, phytochemical testing, Micromeritic properties of mucilage like Bulk density, Tapped density, Carr’s index, Hausner’s ratio, Angle of repose, Calibration of paracetamol, preparation of paracetamol suspensions and evaluated for pH determination, determination of sedimentation volume, redispersibility, determination of flow rate, measurement of viscosity, effect of temperature, drug content, particle size determination and In-vitro dissolution studies. The study showed that the extraction of suspending agent from banana fruit peels. The swelling index was found to be 40%. The photochemical test showed contains carbohydrates. As the concentration of suspending agent increases therefore viscosity of suspension increases which ultimately reduces the sedimentation of suspension.
International Evidence on Industrial Diversification and Asymmetric Information across Different Ownership Structures

This paper examines the effect of industrial diversification on asymmetric information based on global samples. We use the international data from 28 countries in America, Europe and Asia during the period between 2000 and 2006 to test how corporate diversification affects the degree of asymmetric information across different ownership structures. The empirical results show that diversification will raise information asymmetry. In general, the increase of ownership of managing owners raises the levels of asymmetric information, but the marginal effect varies across the ownership structure.For the marginal effect of diversification, the level of asymmetric information is significantly higher for the diversified firms when the ownership of managing owners is lower than a certain level (10% or 30%). This suggests that there are more entrenchment effects for diversified firms. In contrast, the level of asymmetric information is significantly lower for the diversified firms when the ownership is more than a certain level (30%). In this case, there are alignment effects.
The ‘ what-do-you-mean syndrome ’ . A taxonomy of misunderstandings in Harold PinteÑ plays

Harold Pinter’ s plays usually display situations in which citaracters misunderstand eacit otiter. Titis paper applies a pragniatic (mainly relevance-theoretic) taxonomy of misunderstandings to te different varieties of miscommunication titat can be found in titese plays. The result of titis application is that, quite unexpectedly, many conversational excitanges in which tite speaker relies on very explicitly communicated information in orden to guarantee successful communication, systematically end up in misunderstanding. Titis unexpected abundance of misunderstandings can be explained from two points of view: one discursive, in which titese misunderstandings are regarded simply as adding to tite lack of communication titat is felt in tite plays, and the other on a more connotative level, in witich misunderstandings are, ratiter, linguistic exponents of ideological battles of aggression and defensiveness in everyday conversational excitanges between characters.
Static temperature analysis and compensation of MEMS gyroscopes

MEMS gyroscopes as a kind of angular rate sensor have been widely used, but their accuracy tends to be low in practical applications, especially under temperature influence, and they generally require error compensation. Based on the analysis of gyroscope operating principle, this paper has shown that the resonant frequency and measuring precision of the gyroscope are dependent on temperature and temperature gradients. The paper has thus proposed a compensation model based on temperature and temperature gradients. The experimental results have demonstrated that the thermal drift of zero bias can be effectively suppressed, and the accuracy can be improved by one order of magnitude after compensation. Compared with compensation methods only based on temperature, the new method gives significantly better performance. The new error compensation model has not only integrated the differences under different temperature conditions, but also reduced the repeatability errors. It provides a theoretical basis for accurate compensation of the gyroscope thermal error in practical applications and is applicable to other MEMS gyroscopes.
An Investigation of Orthogonal Frequency Division Multiplexing Modulation Technique as a Candidate for Cognitive Radio Networks

As the development of modern wireless communication techniques is increasing very fast in recent years, the demand for reliable high data rate transmission has also increased significantly. These have led to the problem of spectrum scarcity and cognitive radio technology is seen as a potential solution to increase spectrum usage efficiency. Cognitive radio however requires an adaptive physical layer in order to perform its cognitive capabilities efficiently. Orthogonal Frequency Division Multiplexing (OFDM) is the most favoured modulation technique being used nowadays for high speed data communications. In this article, orthogonal frequency division multiplexing OFDM as a modulation technique for cognitive radio networks is discussed and the challenges that arises from its employment. OFDM is also compared with four other modulation techniques DFT-spread OFDM (DFTS-OFDM), Constant Envelope OFDM (CE-OFDM) and Filter Bank Multi Carrier (FDMC) to show each technique’s sensitivity to various impairments and why OFDM is employed by cognitive radio will be investigated.
Developing of module challenge based learning in environmental material to empower the critical thinking ability

This research aimed to compile a product development, knowing the feasibility and knowing the effectiveness of challenge-based learning (CBL) modules in an environment al material to empower the critica l thinking ability. The research wa s a research & development model of Borg & Gall. Validation the product was done b y material expert, expert of development and design module, expert of device and evaluation of learning , a linguist and practitioner of learning of Biology. S ubject of th e research wa s a student of grade X MIA Islamic State Senior High School Karanganyar. This research result s are : (1) m odule in the form of product module for teachers and students CBL based on environmental material was developed based on CBL syntax and indicators of Fascione ’s critical think ing that visualized i n the objective, material , activities , and evaluation items ; (2) appropriateness of module for teachers and student based on CBL environment material according to the validation results of qualified as good until very good; (3) Modules based CBL environment al material is effectiv e to improve the ability of student critical thinking.
Analyticity of the generalized two-dimensional fractional cosine transform

Fourier transform can be generalized into the fractional Fourier transform (FRFT), Linear Canonical Transform (LCT) and simplified fractional Fourier transform (SFRFT). They extend the utilities of original Fourier transform, and can solve many problems that can't solved well by original Fourier transform. In this paper, we study distributional generalized two-dimensional fractional Cosine transform. Testing function space and distributional two-dimensional fractional Cosine transform is defined. Analyticity of the generalized two-dimensional fractional Cosine transform is proved.
Flow separation and resuspension beneath shoaling nonlinear internal waves

[1] Laboratory observations are presented showing the structure and dynamics of the turbulent bottom boundary layer beneath nonlinear internal waves (NLIWs) of depression shoaling upon sloping topography. The adverse pressure gradient beneath the shoaling waves causes the rear face to steepen, flow separation to occur, and wave-induced near-bottom vortices to suspend bed material. The resuspension is directly attributed to the near-bed viscous stress and to near-bed patches of elevated positive Reynolds stress generated by the vortical structures. These results are consistent with published field observations of resuspension events beneath shoaling NLIWs. Elevated near-bed viscous stresses are found throughout the domain at locations that are not correlated to the resuspension events. Near-bed viscous stress is thus required for incipient sediment motion but is not necessarily a precursor for resuspension. Resuspension is dependent on the vertical velocity field associated with positive Reynolds stress and is also found to occur where the mean (wave-averaged) vertical velocity is directed away from the bed. The results are interpreted by analogy to the eddy-stress and turbulent bursting resuspension models developed for turbulent channel flows.