Miracle-dz/UniFAR-FTUs huggingface dataset:
Outlier-robust Logistic Regression for Imbalanced Data

Logistic regression represents a widely used classification method for modeling a binary response variable. Many exemplary cases of binary logistic regression employ data sets with an imbalanced distribution of the output variable and often include outliers – atypical observations in the data. Both outliers and an imbalanced class distribution can greatly reduce the predictive power of the classifier. Therefore, such data structures require a robust method suitable for imbalanced learning problems. This thesis proposes a robust logistic regression for imbalanced data sets based on the Bianco-Yohai estimator, a highly robust method for logistic regression. The imbalance learning problem is addressed by including the cost-sensitive features in the objective function for parameter estimation. Thus, the implementation involves adapting the iterative algorithm for computing the Bianco-Yohai estimator. The paper also proposes an additional method for detecting leverage points required for the weighted version of the estimator, which significantly expands the data domain in which the Bianco-Yohai estimator is applicable. The obtained cost-sensitive forms of the Bianco-Yohai estimator, in the weighted and original versions, are compared with the corresponding non-robust and non-cost-sensitive forms. The results of the simulation experiments and the use case with the imbalanced data set employed for credit scoring indicate the following. For imbalanced data sets, the inclusion of cost significantly improves the performance of the Bianco-Yohai estimator in both the original and weighted versions. Moreover, the methods provide better performance compared to logistic regression when the data contain bad leverage points. Thus, the cost-sensitive form of the Bianco-Yohai estimator, in both its original and weighted versions, provides a statistically reliable classifier for modeling imbalanced data containing outliers. Eidesstattliche Erklärung Ich erkläre an Eides statt, dass ich die vorliegende Diplomarbeit selbstständig und ohne fremde Hilfe verfasst, andere als die angegebenen Quellen und Hilfsmittel nicht benutzt bzw. die wörtlich oder sinngemäß entnommenen Stellen als solche kenntlich gemacht habe. Wien, am 14.09. 2021 Sanja Priselac
Speedup of discrete Fourier transform by efficient modular arithmetic

The fast Fourier transform (FFT) based on modular arithmetic can compute convolution without round‐off errors, which is desirable in many applications such as computational algebra and combinatory pattern matching. One of the critical challenges of the FFT is to enhance the performance. An effective approach is to optimize the high‐cost operations. Modular reduction is one of the most frequently used high‐cost operations that is a bottleneck of the FFT using modular arithmetic. In this article, we present three modular reduction methods and apply them to the implementation of the FFT. We use the strategy of delaying the modular reduction in the first method. We apply the Montgomery reduction to the FFT in the second method. The two methods both first transform the input, and then replace the modular reductions with lightweight replacements, and apply the reverse transform in the output stage to compute the right results. In the third method, we design an efficient modular reduction for the specific form of modular used in FFT. Experiments show that the incorporation of the new modular reductions speedups the FFT based on modular arithmetic.
“APA NAMANYA”: KAJIAN SENYAPAN FRASA PENJEDA PADA PEMBICARAAN PUBLIK

Speaking is not only about using language as a medium for delivering messages from the sender to the recipient, but also activities that involve brain work. In language activities, speakers who produce language orally are also producing language structures in their brains. This working paper aims to describe the pause phrases that often appear every time there is a public conversation. In addition, the presentation will also explain about language activities outwardly which are in line with the language process that is conceptualized in the mind, namely that every conversation sometimes stops because there are certain factors such as nervousness and other psychological conditions. The method used in this research is descriptive qualitative. The data in this study is the speaking word apa namanya in the verbal communication process produced by public speakers in conducting oral presentations in a scientific forum. Data analysis using taxonomic theory expressed by Leonard Bloomfield about linguistic behaviorism. Another theory is the outer structure and inner structure proposed by Noam Chomsky. Based on the analysis carried out, it was found that the word pause emerged from public speakers in scientific forums as a form of behavior that showed a reaction to the stimulus in the mind. These stimuli include nervousness, confusion, forgetfulness, and loss of concentration. The reaction appears with language behavior in the form of the emergence of a pause word to collect scattered focus and plan the next conversation. Based on these results, the speaking pause is used by public speakers to stay in control of the forum and to stay in the flow of the conversation.
Research on the Competitive Advantages of Movie-Television Cultural and Creative Enterprises in Guangdong-Hong Kong-Macao Greater Bay Area

The current national policy strongly supports the development of the Guangdong-Hong Kong-Macao Greater Bay Area. Therefore, how can Lingnan film and television works meet the consumers' needs under the global market competition, promote the positive energy, improve the quality, and then promote the culture and art of the whole area moving towards a new realm becomes the most important issues. If Lingnan movie-television companies want to have the lasting competitive advantages, they must understand their own resources and capabilities to obtain them. This study cited the theory of competitive advantage, using literature analysis and secondary data analysis, and found three unique competitive advantages for Lingnan movie-television cultural and creative enterprises in the Greater Bay Area: the first is the innovation of the content of movie-television works, the second is the rich content of movie-television creation to satisfy consumer demand, and the third is that Lingnan movie-television cultural and creative enterprises in the Greater Bay Area welcome and apply technology heartedly. The movie-television cultural and creative industry in the Greater Bay Area can accelerate the sustainable development of the competitiveness through content innovation and industrial policy management.
Single-Fed Triple-Mode Wideband Circularly Polarized Microstrip Antennas Using Characteristic Mode Analysis

A method of triple-mode operation by capacitive slot loading is proposed for bandwidth enhancement of single-fed circularly polarized (CP) patch antennas. Instead of using even-numbered linearly polarized (LP) modes with quadrature phase, three orthogonal LP modes are used for CP bandwidth enhancement, where the middle mode is shared by two cross-polarized modes with the same polarization. The advantages include reduced constraints, lower complexity, and a higher degree of freedom for antenna design. Guided by the method, a U-slot antenna and an E-shaped antenna are proposed and designed with characteristic mode analysis (CMA). Both antennas work with a TM10-like mode and a TM01-like mode. Differently, the U-slot antenna works with an additional slot mode and the E-shaped antenna works with an additional TM11-like mode. The operating modes are manipulated by the slot loadings for creating phase difference. As a result, wideband CP radiation is achieved with a single feeding. CMA-based empirical formulas are derived for fast design. The proposed method and antennas are experimentally validated. Both antennas measure a bandwidth exceeding 21% for 10 dB return loss and 3 dB axial-ratio (AR), a significant improvement compared with conventional corner-truncated U-slot patch antennas of similar thickness or volume.
Epidemiological and Histopathological Profile of Gastric Adenocarcinoma at Brazzaville University Hospital

Introduction: Gastric adenocarcinoma is the most common gastric malignancy (over 90% of gastric cancers) and remains a global public health problem. The aim of the study was to determine the epidemiological and histopathological aspects of gastric adenocarcinoma in Brazzaville. Material and Methods: The epidemiological and histopathological profile is determined through a descriptive study, collecting retrospective data spread over a period of 11 years (January 2008- December 2018), based on consultation of the departmental histology registers. pathological anatomy and cytology. For each case, age, sex, location, pTNM stage, location and histological type were collected. Results: 93 histologically confirmed gastric adenocarcinomas were collected during the 11-year period. The mean age of the patients was 54.5 years. The sex ratio was 2 in favor of men. The antral and fundal localization were more frequent (74.2% and 20.4% respectively). Of the 2 operative parts collected, one was T2N1 and the other T1N0. Tubular adenocarcinoma was the most common histologic type (51.6%), followed by independent cell adenocarcinoma (34.4%), papillary adenocarcinoma (11.8%), and mucinous adenocarcinoma (2, 2%). Conclusion: gastric tubular adenocarcinoma was the most common histological type in Brazzaville. Key words: epidemiology, gastric adenocarcinoma, histological type.
Estimated the Requirements for Calcium and Phosphorus of Female Arab Chicken in Semi-Scavenging Systems in the Tropics

The ability of chickens to retain calcium and phosphorus at high temperatures is low, so a lot of calcium and phosphorus is wasted through feces. This study aimed to calculate the calcium and phosphorus requirements of female Arab chicken until the first age of laying eggs in a semi-scavenging system with a free choice feeding system in tropical climates. The research design was a completely randomized design with four treatments and each treatment was repeated 4 times and each replication consisted of 18-day old chick female Arab chickens. The treatments were (a) control feed, (b) high calcium high phosphorus feed and high calcium low phosphorus feed, (c) high calcium high phosphorus feed, high calcium low phosphorus feed and low calcium high phosphorus feed, and (d) high calcium high phosphorus, high calcium low phosphorus, low calcium high phosphorus, and control feed. The protein and energy content of all the feeds were based on the results of research by Adrizal et al (2017), while calcium and phosphorus were based on standards from Hy-line International in 2018. The data collected are feed consumption, calcium and phosphorus consumption, calcium, and phosphorus concentrations in the feed consumed. Data were analyzed by using ANOVA. This research has only been going on for 3 weeks. Consumption of feed was not different (P> 0.05) between treatments until week 3. Calcium intake was different (P<0.05) between treatments in weeks 2 and 3, Phosphorus intake was different (P< 0.05) between treatments in week 3. The calcium concentration of the feed consumed was significantly different (P <0.05) between treatments each week. Calcium concentration in control diets was significantly lower between treatments each week, except between T2 in week 3. Calcium concentration in T2 was lower than T3 in week 2, but it was similar to T3 dan T4 in week 3. The phosphorus concentration of T1 was lower than that of T3 and T4 in week 1 and of T2 and T3 in week 3. The body weight gain did not differ between treatments (P> 0.05) each week. It can be concluded that the concentration of calcium and phosphorus in the control diets was the limiting factor to support the growth of female Arab chicken as shown a numerically higher growth rate based on the free-choice feeding system.
Organic Cotton Clothing Purchase Behavior: A Comparative Study of Consumers in the United States and Bangladesh

The purpose of this research was to evaluate the differences and similarities of organic cotton clothing (OCC) purchase behaviors of the consumers who lie at the top and the bottom of the apparel supply chain. The influences of consumers’ sustainability knowledge and social norms on consumers’ attitudes and purchase intentions were examined to understand within the framework of the Theory of Reasoned Action (TRA). Sample data were collected from the United States and Bangladesh and, finally, 136 useable responses were used for the data analysis. Among the useable responses, 85 samples were from the US (containing 91.76% female participants and 4.71% male participants) and 51 responses were from the Bangladesh sample (containing 7.84% female participants and 88.24% male participants). A structural equation model was conducted to test the proposed hypotheses. Findings showed that for US consumers, sustainability knowledge was a powerful predictor of positive attitudes towards OCC, while for Bangladeshi consumers, it was not. In the context of social norms, Bangladeshi consumers demonstrated a strong positive attitudes formation whereas American consumers were found to display less strong relationships. OCC marketers and retailers should concentrate on educating consumers about the real benefits of organic cotton consumption by disseminating proper information about organic cotton fiber and its processing.
A Systematic Literature Review of Student’ Performance Prediction Using Machine Learning Techniques

Educational Data Mining plays a critical role in advancing the learning environment by contributing state-of-the-art methods, techniques, and applications. The recent development provides valuable tools for understanding the student learning environment by exploring and utilizing educational data using machine learning and data mining techniques. Modern academic institutions operate in a highly competitive and complex environment. Analyzing performance, providing high-quality education, strategies for evaluating the students’ performance, and future actions are among the prevailing challenges universities face. Student intervention plans must be implemented in these universities to overcome problems experienced by the students during their studies. In this systematic review, the relevant EDM literature related to identifying student dropouts and students at risk from 2009 to 2021 is reviewed. The review results indicated that various Machine Learning (ML) techniques are used to understand and overcome the underlying challenges; predicting students at risk and students drop out prediction. Moreover, most studies use two types of datasets: data from student colleges/university databases and online learning platforms. ML methods were confirmed to play essential roles in predicting students at risk and dropout rates, thus improving the students’ performance.
Uma Abordagem de Fatiamento de Rede entre Múltiplos Sistemas Autônomos

O fatiamento de rede é fundamental para suportar a coexistência de requisitos divergentes sobre o mesmo recurso de rede. O fatiamento de rede foi amplamente explorado no processo de especificação e padronização da arquiteturas de redes móveis de quinta geração (5G). Por isso, as propostas da literatura concentram-se predominantemente em prover fatiamento de rede nesse segmento de rede. As abordagens que propuseram realizar o fatiamento de rede para além de redes móveis mostraram-se funcionalmente incapazes de prover fatiamento de rede entre múltiplos Sistemas Autônomos (SAs). Nesse sentido, essa pesquisa buscou de construir um método de fatiamento de rede entre múltiplos SAs, baseando-se nos algoritmos de roteamento da Internet. Experimentos realizados em cenário significativos constataram a aplicabilidade, pertinência e desempenho do método proposto em contraste com os tradicionais do estado da arte.
The impact of parasitoids on diamondback moth in Europe: a life table approach

Abstract Diamondback moth, Plutella xylostella (Linnaeus) (Lepidoptera: Plutellidae), was first recorded in North America from Europe about 150 years ago and can be a significant pest of canola in Western Canada. Because parasitism of P. xylostella in Canada is generally low, the introduction of one or more additional exotic parasitoids from Europe is being considered to increase the suppression of P. xylostella populations. Life table studies to determine the impact of parasitoids on diamondback moth populations in Europe were conducted in northwestern Switzerland in 2014–2016. Net reproductive rates were found to be less than one in seven out of eight life tables, suggesting that P. xylostella populations in Switzerland are mostly driven by immigration and recolonisation. In total, seven primary parasitoid species and one hyperparasitoid were associated with diamondback moth. Pupal parasitism by D. collaris reached up to 30%, but because generational mortality was mainly driven by abiotic mortality factors and predation of larvae, the overall contribution of pupal parasitism was low (< 6%). In regions of Canada, where P. xylostella may have increasing populations and low larval mortality, the addition of D. collaris may be a promising approach. Life table studies across Canada are necessary to determine the need for such intervention.
ToFU: Topology functional units for deep learning

We propose ToFU, a new trainable neural network unit with a persistence diagram dissimilarity function as its activation. Since persistence diagrams are topological summaries of structures, this new activation measures and learns the topology of data to leverage it in machine learning tasks. We showcase the utility of ToFU in two experiments: one involving the classification of discrete-time autoregressive signals, and another involving a variational autoencoder. In the former, ToFU yields competitive results with networks that use spectral features while outperforming CNN architectures. In the latter, ToFU produces topologically-interpretable latent space representations of inputs without sacrificing reconstruction fidelity.
Fast SAR Image Segmentation With Deep Task-Specific Superpixel Sampling and Soft Graph Convolution

Since the number of superpixels is lower than that of pixels, superpixels can substantially speed up subsequent processing steps and have been widely used in synthetic aperture radar (SAR) image segmentation. However, in most of the existing superpixel-wise segmentation algorithms, superpixel prediction is an isolated preprocessing step and is independent of the segmentation task. The performance of the segmentation results is determined by the accuracy of superpixels. Once superpixels are generated, their shape cannot be changed in the following segmentation stage, even if the same superpixels contain pixels of different landcovers. To address this, we propose an end-to-end trainable superpixel-wise segmentation method for single-polarization SAR images. First, we design a differentiable boundary-ware clustering method for estimating task-specific superpixels. Instead of the hard association between pixels and superpixels in the existing superpixel algorithms, this method introduces the soft association map to make the clustering differentiable. Hence, it can be implemented using a simple deep fully convolutional network. In the segmentation part, we propose a novel soft graph convolution network (Soft-GCN), which takes the association map as input and performs superpixel-wise segmentation. The advantage of our method is that superpixel generation and graph convolution parts can be trained under a unified framework, until two parts obtain the optimum parameters. In the training process, it can adaptively adjust the shape of the superpixels according to the segmentation results, ensuring the superpixels correctly adhere the boundaries. Experimental results with simulated and real SAR images demonstrate that our method outperforms other state-of-the-art segmentation algorithms, while also being faster.
The common places of alternative finance: assemblages, stoppages, and the political mobilisation of space

ABSTRACT This article reflects on the role of physical settings in the inculcation of militant practices consonant with specific discourses. To do so, it draws on firsthand empirical information derived from a multi-sited ethnographic case study of an international cooperative that formed in Europe in the aftermath of the Euro crisis and deployed decentralised cryptocurrencies and alternative digital banking. Here, space is viewed as a relevant material resource that can be occupied and organised to enable the telling of a particular story of revolution, redistribution, and horizontality, while simultaneously helping to actualise that story. The materiality of space is thus related to its expressivity and seen as contributing to both an experience of militancy and the recurrence of the underlying political tale. This approach stresses reminiscence rather than becoming; the existential dimensions of interaction and affection rather than the ontological one of ever-evolving sociotechnical assemblages. On such grounds, the article proposes the concept of stoppage to account for the repetition of specific spatial dispositions that configure extra-institutional immersive environments.
Phenylboronic Acid Conjugated to Doxorubicin for the Treatment of Hepatocellular Carcinoma Through Transcatheter Arterial Chemoembolization

Background: Anticancer strategies using nanocarrier systems via the enhanced permeability and retention (EPR) effect and tumor targeting have been explored in various cancers. In previous studies, the anticancer effect of polymerized phenylboronic acid-conjugated doxorubicin (pPBA-Dox) nanocomplexes was confirmed in various cancers, and their anticancer effect and tumor targeting ability was confirmed in hepatocellular carcinoma (HCC). This study aimed to determine the anticancer effect and changes in the liver immune cell population and function after pPBA-Dox nanocomplex infusion through transcatheter arterial chemoembolization (TACE), which is a locoregional therapy (LRT), in HCC. TACE was performed in a rat liver cancer model, and the anticancer effects, immune cell populations and functional changes were confirmed after 1 week. Magnetic resonance imaging (MRI) and flow cytometry (FACS) were performed to analyze the anticancer effect and immune cell population and function. Results: In HCC, the infusion of pPBA-Dox nanocomplexes through TACE had a stronger anticancer effect than conventional doxorubicin (Dox) and it promoted the infiltration and activation of CD4+ and CD8+ T cells in the liver. Conclusions: This study provides insight into novel targeted therapies using nanocomplexes for the treatment of HCC.