Miracle-dz/UniFAR-FTUs huggingface dataset:
THE EFFECTIVENESS OF DISCOVERY LEARNING MODEL IN IMPROVING STUDENTS� FICTION WRITING

Writing skill becomes a concern nowadays since it is an important skill in communication and becomes the hallmark of a creative, imaginative, and educated nation. Yet, in fact, students� writing skills are generally low which can be seen from the lack of quality of writing produced. This is caused by some factors, including the lack of time allocation provided by the teacher to practice writing, the lack of teachers� creativity in using learning models that can stimulate students to write, and the low of students� reading habits. Hence, this study aims to identify the effectiveness of Discovery Learning (DL) model in improving students� fiction writing. This research is a quasi experimental with nonequivalent control group design. The sample of research was the fourth grader of elementary school in Purwakarta sub-district. The data in this research were collected through writing test, observation, and interview. Moreover, students� writing skills were assessed by using writing rubric which has been validated by expert lecturers. Further, the data were then analyzed by using inference statistics including normality test, homogeneity test, and t-test. The results revealed that discovery learning model is effective in improving students� fiction writing which can be seen from students� post test score. This is because discover learning model allows students to explore, classify, and utilize more data to improve their imagination, their vocabulary selection, and their creativity as well.Keywords: discovery learning model; writing skill; fiction writing.
The influence of firm performance on management earnings forecasts accuracy

This thesis aims to find the effect of firm performance on management earnings forecasts accuracy. I use Compustat North America, IBES and Thomson Reuters databases to retrieve the data necessary for this thesis. The sample for the main analysis consists of 13,070 firmyears observations with 2,583 unique firms and is spread across 17 years from 2002 until 2018. Following prior literature, I expect firm performance to have an effect on management earnings forecasts accuracy. However, the mixed evidence provided does not allow me to make a prediction about the sign of this effect. The result of this study shows that firm performance has a negative impact on forecast error. This demonstrates that forecast accuracy is increased when firm performance is increasing. I find this result for both ROA and ROE as a proxy for firm performance. I also find the same result when I create a benchmark for firm performance. I find that when a company has a ROA (or ROE) lower than the yearly industry median, the forecast error is increasing. This implies that the accuracy of the forecasts is being reduced when a firm is performing below the benchmark. Thus, I can conclude that management earnings forecasts have lower level of accuracy in times of bad performance.
The predictability of stock market volatility in emerging economies: Relative roles of local, regional, and global business cycles

This paper explores the role of business cycle proxies, measured by the output gap at the global, regional and local levels, as potential predictors of stock market volatility in the emerging BRICS nations. We observe that the emerging BRICS nations display a rather heterogeneous pattern when it comes to the relative role of idiosyncratic factors as a predictor of stock market volatility. While domestic output gap is found to capture significant predictive information for India and China particularly, the business cycles associated with emerging economies and the world in general are strongly important for the BRIC countries and weakly for South Africa, especially in the post-global financial crisis era. The findings suggest that despite the increase in the financial integration of world capital markets, emerging economies can still bear significant exposures to idiosyncratic risk factors, an issue of high importance for the profitability of global diversification strategies.
Classification of radar images with different methods of image preprocessing

This work is aimed at comparing the classification algorithms and methods of machine learning with various methods of preliminary processing of radar images. Preprocessing step includes speckle noise filtering and object orientation normalization on the image. In comparison, the following classification algorithms were considered: Decision Tree, Support Vector Machine, K Nearest-Neighbor method, Random Forest, AdaBoost where decision tree was used as a weak classifier, Convolutional Neural Network and Residual Neural Network. The principal component analysis was applied to reduce the dimension. The study was carried out on the objects from the base of radar images MSTAR.
Automation, job characteristics and job insecurity

Purpose The purpose of this paper is to analyze whether specific jobs characteristics, which experts have identified as being more automation proof, are associated with reduced job insecurity. Design/methodology/approach Data come from a recent survey providing information on sources of job insecurity as well as on detailed job characteristics. The analysis is based on various regression models. Findings People who have jobs that involve lots of personal interaction are less likely to be concerned about losing their job because of automation, or because of other reasons, and are more likely to think their job will exist 50 years from now. Having a creative job does not change these concerns. The share of respondents who fear losing their job to automation is fairly small, and those who do, typically fear other sources of job insecurity as much or even more. Practical implications Developing interpersonal skills is more likely to be an effective strategy for reducing job insecurity than developing creative skills. The findings further suggest that policies aimed at automation are unlikely to suffice for the elimination of worry over job loss, as many workers who fear automation at the same time feel there are other reasons that might lead to the loss of their job. Originality/value There are very few studies that link fear of losing one’s job to automation to a job’s characteristics. The survey used here is unique in the level of detail provided on job characteristics.
Pengaruh Kompensasi dan Kepuasan Kerja terhadap Kinerja (Studi terhadap Fakultas Keguruan dan Ilmu Pendidikan Universitas Muhammadiyah Sumatera Utara)

Keberhasilan pembangunan sangat ditentukan oleh faktor manusia yang kemampuan membangun. Kemampuan ini hanya dapa dibina melalui pendidikan. Untuk sumber daya manusia yang berkaulitas, pemerintah berusaha menyelenggarakan pendidikan salah satunya UMSU melalui Fakultas Keguruan dan Ilmu Pendidikan. Penelitian bertujuan untuk membuktikan secara empiris, mengenai besarnya pengaruh kompensasi terhadap kinerja dosen FKIP UMSU. Mengidentifikasi dan menganalisis besarnya pengaruh kepuasan kerja terhadap kinerja dosen FKIP UMSU. Mengindentifikasi dan menganalisis mengenai besarnya pengaruh secara simultan kompensasi dan kepuasan kerja terhadap kinerja dosen FKIP UMSU. Penelitian dilaksanakan di FKIP UMSU dengan menggunakan metode bersifat kuantitif. Objek penelitian yang diteliti yakni, kompensasi, kepuasan kerja dan kinerja dosen. Populasi berjumlah 197 dosen tetap dan tidak tetap FKIP UMSU sedangkan menggunakan Slovin yaitu sampel 65 orang responden. Teknis analisis data regresi linier berganda dengan hasil persamaan Y= 106.423+0.140+0,381+e. Hasil penelitian ini membuktikan bahwa secara parsial Kompensasi terhadap Kinerja Dosen tidak memiliki pengaruh, Kepuasan Kerja memiliki pengaruh yang signifikan terhadap Kinerja Dosen. Kompensasi dan Kepuasan Kerja, secara simultan tidak memiliki pengaruh terhadap kinerja dosen. Keyword: Kompensasi, Kepuasan kerja dan kinerja dosen
Series AC Arc Fault Detection Method Based on Hybrid Time and Frequency Analysis and Fully Connected Neural Network

The variety of arc fault induced by different load types makes residential series arc fault detection complicated and challengeable. This paper proposes a hybrid time and frequency analysis and fully connected neural network (HTFNN) based method to identify series ac arc fault. The HTFNN method recognizes samples state by broadly classifying them into resistive (Re) category, capacitive–inductive (CI) category, and switching (Sw) category according to the fundamental frequency components of series current. In each category, separate fully connected neural network (NN) with customized time and frequency indicators being the input is employed for fine class recognition and state identification. This method construction addresses the feature overlap among various cases by separate categories and enables suitable indicator selection within each category. Since the identification complexity in each category is cheaper than identifying all cases together, concise NNs are applied in this paper to reduce computing cost. The general accuracies of normal and arcing state identification in Re, CI, and Sw category are 99.64%, 100%, and 98.45%, respectively, based on 3950 test samples. Method comparison shows that HTFNN achieves higher detection precision at lower computational complexity for generalized load types. This paper also evaluates the feasibility of implementing the method in hardware for arc fault detection device application.
Divine kink: A consideration of the evidence for BDSM as spiritual ritual

This paper reviews the limited empirical research supporting BDSM as a spiritual ritual that enables distinct altered states of consciousness. It expands upon Sagarin, Lee, and Klement’s (2015) preliminary comparison of BDSM to extreme ritual by suggesting that BDSM bears in common with spiritual ritual elements of pain or ordeal, spiritual meaning, and transformative potential. An increasing interest in BDSM in the West is considered in light of the spiritual and ritual roles BDSM fulfills for many practitioners. The relevance of BDSM to transpersonal psychology is discussed and BDSM is considered as an area for further research in transpersonal psychology.
AIB1 predicts tumor response to definitive chemoradiotherapy and prognosis in cervical squamous cell carcinoma

Amplified in breast cancer 1 (AIB1) gene, has been reported to be associated with biological malignancy in several cancers. However, the molecular status of the AIB1 gene in cervical cancer and the clinicopathological/prognostic significance of AIB1 expression in chemoradiotherapy (CRT) sensitivity have not been determined. In our present study, we found that the high expression of AIB1 was frequent detected in specimens of cervical cancer patients, and this was significantly correlated with CRT response (P = 0.014), clinical stage (P = 0.003), T status (P = 0.027), N status (P = 0.021), M status (P = 0.015) and progression-free survival (P < 0.001). Moreover, the clonogenic survival fraction and cell apoptosis experiments showed that knockdown of AIB1 substantially increased cervical cancer cells sensitivity to ionizing radiation (IR) or cisplatin/5-fluorouracil. Collectively, our results demonstrated that the high expression of AIB1 in cervical cancer cells contributes to the resistance to CRT, which provides the evidence that AIB1 may be a promising predictor of aggressive cervical cancer patients with poor response to CRT.
THE EFFECT OF SHORT MESSAGE SERVICE (SMS) TEXTING ON MEDICATION ADHERENCE AMONG TUBERCULOSIS PATIENTS

The study was conducted to examine the effect of Short Message Service (SMS) Texting on medication adherence among tuberculosis patients. 68 persons diagnosed with tuberculosis and registered in the public health center in Klari, Karawang, West Java, Indonesia, were randomly appointed to an experimental or control group; 34 persons assigned to each group. Participants in the experimental group received routine SMS Texting, while those in the control group receive none. Data were analyzed using Dependent t-test and Independent t-test. The results indicated that after participating by receiving SMS texting, there was a significant improvement in medication adherence in TB patients in the experimental group, which was shown by significant difference in mean score of medication adherence. In addition, after participating in the program, there was a meaningful difference in mean scores of medication adherence between the experimental group (X=6.38, SD=0.85) and the control group (X=3.64, SD=1.04), p<0.01. The SMS Texting method appears to be effective in improving medication adherence among TB patients.
How State-Controlled Media Can Set the Agenda on the Internet: Coverage of Three Tragedies on Different Types of Russian Media

Abstract:December 19, 2016, witnessed three tragedies that could not go unnoticed by the Russian media: dozens of people died as a result of a surrogate alcohol poisoning in Irkutsk, a Russian ambassador was killed in Turkey, and a terrorist attack took place at the Christmas market in Berlin. In this article, we use the network agenda-setting theory to analyze how these tragedies were covered by different types of mass media. We show that ties between the tragedy and a network of other acute issues are more important than objective circumstances, such as the number of victims or the geography of the event. The context in which the events were examined led to greater attention to the killing of the ambassador and less attention to the surrogate alcohol poisoning. We believe that the state can exercise indirect control over the agenda by creating a network of events that will correctly guide discussions about tragedies.
Mechanical Performances of Green Engineered Cementitious Composites Incorporating Various Types of Sand

This paper evaluates the mechanical performances of green engineered cementitious composites (ECC) by means of compressive strength and flexural behaviour. Green ECC made of cement, ground granulated blast-furnace slag (GGBS), river sand or recycled concrete fine (RCF), polypropylene (PP) fiber, water and superplasticizer (SP) was employed in this study. Compression test result implies that green ECC incorporating either sieved river sand or sieved RCF (below 600 μm) in series G60 and G70 exhibited greater compressive strength compared with green ECC with unsieved river sand. In series G80, compressive strength of green ECC was not affected by RCF content. Flexural stress-mid deflection curves demonstrated that all green ECC specimens performed more ductile compared to normal concrete as they undergone large deformation capacity after the first cracking strength. Both compression and flexural tests suggested that mixture G80SRCF0.4 containing large amount of sieved RCF and least amount of cement is the best green ECC mixture in this study.
An interactional view of social presence: Making the virtual other “real”

In IS research, social presence is generally defined as the perceived capacity of a communication medium to convey contextual cues normally available in face‐to‐face settings. However, theorizing social presence as a property of the technology has been challenged for decades. The objective of this paper is to develop a more contemporary, interactional view of social presence. To this end, this paper develops a new conceptualization of how participants form the sense that each other is present. We characterize the development of this sense as a skilful accomplishment that entails interactants' joint construction of each other as “real. ” Viewing social presence as contingent on social practice, we seek to answer the following research question: “How is social presence accomplished in virtual environments? ” To explicate how virtual others are perceived as becoming socially present, that is, emotionally and psychologically “real” to someone interacting with them, we draw from Goffman's work, particularly his concepts of involvement and involvement obligation. Detailing two examples of social interaction in the virtual world Second Life, our analysis highlights the key role that this moral obligation, intrinsic to everyday social interaction, plays in virtual others becoming perceived as psychoemotionally “there. ” By outlining a model of how the sense of a virtual other as “real” is produced in and through social interaction, our work contributes a sociological perspective to the construct of social presence and underscores some of the material and social conditions necessary for users to perceive virtual others as present.
Joining the crowd: The career anchors of information technology workers participating in crowdsourcing

As technology platforms and online communities evolve, the nature of the relationship between workers and firms is changing. Crowdsourcing is an emerging phenomenon that exemplifies the changing relationship between workers and firms. Although significant research has been conducted on worker motivation within the traditional firm‐worker relationship, relatively little work has examined motivation in crowdsourcing engagements. This study utilizes the revealed causal mapping methodology to conduct an exploratory analysis of the motivations and career outcomes of technology workers based in the United States who participate in compensation‐based technology crowdsourcing platforms such as oDesk or Rent‐a‐coder. The findings reveal ways in which the career anchors of technology workers participating in crowdsourcing are evolving in the face of the emerging dynamics in the information technology (IT) employment marketplace
Does political connectedness determine stock returns in Indonesia?

This study aims to investigate the influences of political connection on stock returns in Indonesia. We develop a comprehensive database of firm-level political connectedness among Indonesian firms from 2010 to 2017. Our sample is non-financial Indonesian listed firms that are selected in the Kompas 100 index for 16 consecutive periods, with a total of 448 firm-year observations. This study employs panel data regressions to estimate this relationship, then mitigate possible endogeneity issues using two-stage least square with fixed-effects. The finding of this study shows that political connectedness is associated with lower stock returns, more prominently in agriculture and consumer goods industries. Moreover, state-owned enterprises are more likely to earn lower stock returns. In summary, our result suggests that investing in politically connected firms could be a risky investment. The finding holds using alternative estimation methods
The Influence of a Firm’s Capability and Dyadic Relationship of the Knowledge Base on Ambidextrous Innovation in Biopharmaceutical M&As

In recent years, technological mergers and acquisitions (M&As) have become important strategic tools for enterprises to access and utilize new external knowledge. In particular, in the biopharmaceutical industry, M&A activities are actively being progressed due to an increase in new drug development costs, a decrease in R&D productivity, and the patent expiration of blockbuster drugs. However, there is a lack of research on the integrated view of (1) the acquirer’s capability and (2) the dyadic relationship of the knowledge base between the acquirer and target on the innovation performance of the acquirer. Furthermore, there are few empirical studies on the impact of these factors on ambidextrous innovation; that is, exploitative and explorative innovation. Therefore, with this integrated view in mind, this study analyzed the effect of each factor on the exploitative and exploratory innovation performance of the acquirer. A negative binomial regression was conducted using patent data to measure the innovation outcome of the acquirer after M&A. The findings suggest that (1) the acquisition experience of the acquirer and (2) the technological commonness between the acquirer and the target both had a significant impact on the exploitation and exploration innovation performance.
New evidence on the relationship between public and private investment in India

The purpose of this paper is to examine the long run relationship between public investment and private investment in India. To this end, we employ the autoregressive distributed lag (ARDL) â€“ bounds test approach, using data for the period 1980-81 to 2015-16. Finally, an error correction model is estimated to show the short-run dynamics along with the speed of adjustment to the equilibrium relationship among the variables. The estimated results suggest that public investment crowds in private investment in India. Furthermore, the speed of adjustment parameter indicates that adjustment process towards long run equilibrium is relatively high and CUSUM and CUSUMSQ tests confirmed that the models are stable over the sample period.
E-Business Readiness in Indonesian Small Medium Size Travel Agencies

—The development of world tourism, especially in the tour and travel business is influenced by Information Communication Technology (ICT). The effective use of ICT added values to products and services that continue to develop business electronically (e-business). By doing e-business, companies tend to have effective and efficient operations. The e-business adoption in small medium size travel agents encounter rapid changes in technology and the raise of online travel agent. The aim of the research is to understand the readiness of small medium size travel agents in doing e-business. Three variables developed were technology readiness, organization readiness, and external environment. All the respondents were small medium size travel agents operating in West Java, Indonesia. Interviews were conducted during June-August 2018 with 61 persons from travel agents, consisting of managers, supervisor, owners, commissioners, and staffs. Content analysis was used to analyze data. Results showed that all small medium size travel agents are keen to run e-business. The technology infrastructure and organizational readiness support the travel agents to apply e-business. The external markets which were already online become potential market in supporting e-business. Differences between cities and suburb areas in terms of e-business adoption revealed that in suburb areas travel agents had less infrastructure, lacked staff competencies, and relied innovation on the free application available. However, suburb area travel agents faced high opportunities to take more costumers in purchasing airline and hotel tickes due to the low ability of the customers to use available distribution system.
Application of Altman Bankruptcy prediction model in Ghana

The study examined the applicability of the Altman Z-score model in predicting bankrupt companies or financially distressed companies on the Ghana Stock Exchange. A sample 10 listed firms were selected and one other company to be used for validation purposes. The validation process involved data for 2016 and 2017 for Aluworks which represented a distressed company and GOIL Ghana Limited which represented non-distressed company. The final analysis was based on a random sample of 10 listed firms using their 2017 financial statement. The results of the initial prediction showed 50 percent of the companies were correctly predicted whiles the others were misclassified. Additional analyses showed that the size of the company influence the probability of bankruptcy whiles the nature of the business does not. The conclusion drawn shows that the Altman Z-score cannot accurately predict financially distressed firms in Ghana but can still be useful in giving signals.