44 research outputs found
Antimicrobial sensitivity pattern of bacterial pathogens for uncomplicated urinary tract infection in female patients at a tertiary level hospital
No full textBackground: Urinary tract infections (UTIs) remain the common infections in outpatients as well as hospitalized patients. Antimicrobials are frequently used drugs for the treatment of UTIs. Periodic evaluation of antimicrobial activity of different antimicrobial agents is essential as the pattern of antimicrobial sensitivity may vary over period. The aim of this study was to identify the antimicrobial sensitivity pattern of the isolated uropathogens in female patients in urinary tract infection at a tertiary care hospital in Bangladesh.
Methods: This observational cross-sectional type of study was conducted in the department of pharmacology and therapeutics in collaboration with department of microbiology SBMC, outpatient department of medicine, and gynaecology and obstetrics, SBMCH, Barishal, from January 2017 to December 2017.
Results: In this study, age of the subjects ranging from 18 to 65 years, majority subjects (57.0%) belonged to age group of 31-44 years. The mean age was found 44.5±9.1 years. Out of 200 cases, 83% cases hailing from rural area and 17% from urban site. In this study microbial culture result of uncomplicated UTI revealed that 103 (51.5%) of urine samples had significant bacteriuria. E. coli was found to be the most prevalent 47 (45.6%), followed by Klebsiella pneumoniae 18 (17.4%), Proteus spp. 11 (10.6%) and Enterobacter spp. 9 (8.7%).
Conclusions: The pattern of resistance to commonly used antimicrobials for treating UTI alerts us against indiscriminate usage of antimicrobials
Robust design of CAV-Dedicated lanes considering CAV demand uncertainty and lane reallocation policy
No full textReduced headways of connected and automated vehicles (CAV) provide opportunities to address traffic congestion and environmental adversities. This benefit can be utilized by deploying CAV-dedicated lanes (CAVDL). This paper presents a bi-level optimization model that captures CAV market size uncertainty. The upper level determines the links (and number of lanes) for CAVDL deployment to minimize emissions. It considers lane reallocation policies that account for the prospect of smaller width of CAV-dedicated lane due to the smaller lateral wander of CAV tire tracks. This can increase the total number of lanes on wide highway sections. At the lower level, equilibrium and demand diffusion models capture travelers’ route and vehicle-type choices. The bi-level model is formulated as a min–max mathematical program with equilibrium conditions and solved using the cutting-plane scheme and active-set algorithm. The computational experiments indicate that the robust plans have superior performance compared to the deterministic plan in pessimistic cases.Green Open Access added to TU Delft Institutional Repository ‘You share, we take care!’ – Taverne project https://www.openaccess.nl/en/you-share-we-take-care Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public.Transport and Plannin
Robust Design of Electric Charging Infrastructure Locations under Travel Demand Uncertainty and Driving Range Heterogeneity
No full textThe rising demand for electric vehicles (EVs), motivated by their environmental benefits, is generating an increased need for EV charging infrastructure. Also, it has been recognized that the adequacy of such infrastructure helps promote EV use. Therefore, to facilitate EV adoption, governments seek guidance on continued investments in EV charging infrastructure development. Such investment decisions, which include EV charging station locations and capacities, and the timing of such investments require robust estimates of future travel demand and EV battery range constraints. This paper develops and implements a framework to establish an optimal schedule and locations for new charging stations and decommissioning gasoline refueling stations over a long-term planning horizon, considering the uncertainty in future travel demand forecasts and the driving range heterogeneity of EVs. A robust mathematical model is proposed to solve the problem by minimizing not only the worst-case total system travel cost but also the total penalty for unused capacities of charging stations. This study uses an adaptation of the cutting-plane method to solve the proposed model. Based on two key decision criteria (travelers' cost and charging supply sufficiency), the results indicate that the robust scheme outperforms its deterministic counterpart. Green Open Access added to TU Delft Institutional Repository ‘You share, we take care!’ – Taverne project https://www.openaccess.nl/en/you-share-we-take-care Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public.Transport and Plannin
New β-peptides for mimicking biomineralisation
No full textThis thesis was scanned from the print manuscript for digital preservation and is copyright the author.
Researchers can access this thesis by asking their local university, institution or public library to
make a request on their behalf. Monash staff and postgraduate students can use the link in the References field
Authorship attribution on Urdu corpus using lexical, syntactic and stylistic features
No full textAuthorship attribution has deep roots in linguistic Stylometry. Stylometry is the linguistic information to label documents whose authors are unknown by using the writing style of the possible suspects. Traditional authorship attribution systems rely on the specific vocabulary and writing style of the author.
In my study, I have performed two experiments and compare both the experiment and discuss the outcomes. Both experiments examine the performance of the model using the combination of lexical, syntactic and stylistic features. In experiment 1, the performance of Naïve Bayes, Support Vector Machine and Random Forest is examined and in experiment 2, the deep learning model is applied and its performance is judge using the traditional approaches in experiment 1
PENERIMAAN DIRI DISABILITAS FISIK NON-BAWAAN DI UPT. REHABILITASI SOSIAL BINA DAKSA PASURUAN
No full textPeople with non-congenital physical disabilities tend to experience depression due to traumatic events that affect their physical changes. So there needs to be a process to accept one's condition so that individuals can overcome the depression they are experiencing and have a purpose in life. This research aims to determine the process of self-acceptance and the problems experienced by people with non-congenital physical disabilities at UPT RSBD Pasuruan. To obtain data for this research, the author used a descriptive qualitative approach which helped the author to explain in more detail the content of the research. In this research, researchers also used observation, interview and documentation techniques. The results of this research show that the process of self-acceptance experienced by the subject goes through the stages of Aversion, Curiosity, Tolerance, Allowing, and Friendship. Each individual has different stages. The factors that support self-acceptance include understanding themselves, realistic expectations, identification of people who are able to adapt, and supportive social behavior
AS-258 Performance of B Type Natriuretic Peptide in the Early Diagnosis of Left Ventricular Diastolic Dysfunction in High Risk Subjects
No full textANALISIS DAN PENINGKATAN KUALITAS PELAYANAN PADA JNE SUMBERSARI DENGAN METODE SERVICE QUALITY (SERVQUAL) DAN IMPORTANCE PERFORMANCE ANALYSIS (IPA)
No full textJika membutuhkan abstrak atau isi jurnal silahkan menghubungi author melalui e-mail [email protected] atau [email protected]
Dipublikasikan tanggal: 29 Desember 2023 
Mood Influences Working Memory Capacity
No full textabstract: Working memory is the cognitive system responsible for storing and maintaining information in short-term memory and retrieving cues from long-term memory. Working memory capacity (WMC) is needed for goal maintenance and to ignore task-irrelevant stimuli (Engle & Kane, 2003). Emotions are one type of task-irrelevant stimuli that could distract an individual from a task (Smallwood, Fitzgerald, Miles, & Phillips, 2009). There are studies that show there is a relation between emotions and working memory capacity. The direction of this relationship, though, is unclear (Kensinger, 2009). In this study, emotions served as a distractor and task performance was examined for differences in the effect of emotion depending on participants' working memory capacity. The participants watched a mood induction video, then were told to complete a complex-span working memory task. The mood induction was successful- participants watching the negative emotional video were in a less positive mood after watching the video than the participants that watched a neutral video. However, the results of the complex-span working memory task showed no significant difference in the results between participants in the negative versus neutral mood. These results may provide support to an alternative hypothesis: cognitive tasks can diminish the effects of emotions (Dillen, Heslenfeld, & Koole, 2009).A copy of this thesis/creative project may be available at Barrett, the Honors College at Arizona State University. If you would like to access the printed copy, please email [email protected]
Perbandingan Metode Pearson Correlation dan Spearman Correlation pada Recommender system berbasis Collaborative filtering
No full textABSTRAKSI: Perkembangan internet yang sangat pesat menyebabkan terjadinya information overload, dimana user mendapat kesulitan jika ingin mendapatkan sesuatu yang benar-benar diperlukan.. Salah satu solusi untuk mempermudah user mencari informasi yang dibutuhkan adalah Recommender System. Recommender system adalah sebuah sistem yang dapat memberikan rekomendasi berupa prediksi rating terhadap suatu item berdasarkan persamaan karakteristik user dalam memberikan informasi. Oleh karena itu, tugas akhir ini mengimplementasikan dan menganalisis user-based collaborative filtering recommender system, yang menerapkan Pearson Correlation dan Spearman Correlation. Pearson Correlation dan Spearman Correlation digunakan untuk mengolah nilai rating user. Tujuan dari tugas akhir ini adalah untuk menganalisis akurasi prediksi rating yang dihasilkan oleh recommender system setelah diimplementasikan kedua korelasi. Parameter yang digunakan dalam analisis adalah ukuran threshold co-rated items, perbandingan training set dan test set serta ukuran neighbourhood yang diukur dengan Mean Absolute Error.Hasil pengujian menunjukkan bahwa akurasi prediksi yang dihasilkan oleh Pearson Correlation dan Spearman Correlation semakin meningkat dengan bertambahnya jumlah co-rated items. Semakin besar ukuran neighbourhood, akurasi prediksi yang dihasilkan juga semakin baik. Nilai error dari prediksi semakin menurun dengan bertambahnya jumlah training set . Hasil prediksi kedua korelasi menunjukkan bahwa nilai error yang dihasilkan Pearson Correlation lebih rendah dibandingkan Spearman Correlation. Kata Kunci : recommender system, collaborative filtering, Pearson Correlation, Spearman CorrelationABSTRACT: The internet development these days with too much information cause information overload, where users have a difficulty in making decisions by the presence of too much information. One of the solution to ease the users finding the required information is recommender system. Recommender system is a system that can give recommendation in term of rating prediction of an item, based on the similarity of the user characteristic in giving information.Therefore, in this final project, the author implement and analyze user-based Collaborative Filtering Recommender System, which applies Pearson Correlation and Spearman Correlation. Pearson Correlation and Spearman Correlation is used to compute user’s rating in giving similarity. The purpose of the final project is to analyze prediction accuracy result that is given by the recommender system after both of the correlation is implemented. The parameter that is used in the analysis is the threshold co-rated items size, the neighbourhood size, and the comparison between training set and test set, measured by Mean Absolute Error. Based on the analysis, Pearson Correlation and Spearman Correlation produces prediction accuracy that increases with the increase number of co-rated items. The bigger the neighbourhood size, the better the prediction accuracy is given. The prediction accuracy also get better with the bigger of the training set size. The recommendation of both correlation shows that the differences value of error rate is relatively small, with Pearson Correlation’s error rate smaller than Spearman Correlation.Keyword: recommender system, collaborative filtering, Pearson Correlation, Spearman Correlatio
