nils-herrmann/clean_scirepeval huggingface dataset:
Towards Modelling Factors of Intention to Adopt Cloud Based M Retail Application among Textile Cyberpreneurs
Year: 2017

Nowadays, conducting retail activities through the use of mobile devices are very common among the internet entrepreneurs or cyberpreneurs in Malaysia. The emergence of various mobile applications especially social media apps have boosted the buying and selling activities due to the increasing number of mobile device users. Clothes are one of the most popular products that are being sold via Internet. Besides social media channels, textile cyberpreneurs in Malaysia use websites and m retail applications like mobile marketplace applications that utilize cloud services for conducting online business. Determining the intention to use m shopping services among the consumers was usually conducted in previous researches, but investigating the issue from retailer's perspective was rarely done. Therefore, this study intends to investigate the factors that affect the intention to use cloud based m retail application among textile cyberpreneurs for better understanding by integrating Decomposed Theory of Planned Behaviour (DTPB) with Technology Acceptance Model (TAM) Task Technology Fit (TTF) and Information System Success (ISS) models. Modelling the right factors may result in future enhancements on the current m retail applications in m commerce context based on the requirements of textile cyberpreneurs. This study can be used as a platform in understanding the needs of textile cyberpreneurs in Malaysia to adopt cloud based m retail application.
Effect of carbon dioxide pneumoretroperitoneum on bacterial translocation in an experimental retroperitoneoscopy model.
Venue: Journal of endourology
Year: 2007

To evaluate the effect of artificial CO2 pneumoretroperitoneum on bacterial translocation in an experimental retroperitoneoscopy model.  Eighteen adult male New Zealand White rabbits weighing 2.5 to 3 kg were divided into two groups. Group 1 (control group) consisted of 6 rabbits, while the remaining 12 served as the pneumoretroperitoneum group (group 2) In group 1, the left retroperitoneal space was dissected with a 50 mL balloon without CO2 insufflation, and the animals were kept under anesthesia for 3 hours with the balloons inflated. In group 2, after balloon dissection as in group 1, CO2 insufflation was applied at 1 L/min to achieve a pressure of 10 to 12 mm Hg for 3 hours. Afterward, all animals were sacrificed, and samples were taken from the blood, retroperitoneal area, lungs, liver, mesentery, heart, kidneys, ureters, bladder, colon, small intestine, and spleen and carried to the microbiology laboratory in Carry Blair medium. Bacterial growth was evaluated using standard techniques.  All animals survived the experimental procedures. None of the rabbits in the control group demonstrated any bacterial translocation in the sampled tissues. In the pneumoretroperitoneum group, one rabbit was found to have 10(2) colony forming units of E. coli in the kidney, but this was considered to be the result of contamination, not translocation.  Carbon dioxide pneumoretroperitoneum does not seem to cause bacteremia or bacterial translocation in this experimental model. Retroperitoneoscopy probably does not create any additional risk of septic complications.
Navigating the labyrinth The path to progression for senior female managers working in a foreign country
Year: 2014

Many articles have been written about women and what kind of barriers they face whether it being a glass ceiling or a labyrinth as they are progressing in their careers; gender stereotyping, double binds, lack of role models, "old boys club" different leadership styles, and so forth. And many others have talked about how to navigate or mitigate any obstacles that might face women due to their gender.  This report aims to give insight into another aspect of this topic, namely through the lens of a cultural standpoint: do women that live and work abroad face yet another obstacle by being foreigners in addition to the gender specific ones that previously have been thoroughly identified in academic research.  How do successful female managers overcome attitudinal and cultural barriers in a foreign country? What strategies have they used?  The main research data was collected through in depth, semi structured, qualitative Skype interviews with women who have chosen to work and live abroad on a local level (i.e. not expats on time limited assignments) The collected empirical data was subsequently analysed using a matrix containing key words obtained from an in depth, two level academic literature search. The key words supported the discussion of the empirical findings and the analysis where the barriers were identified together with the subsequent strategies these women have used in order to progress their careers.  As the study shows, a majority of the interviewed women have experienced positive response due to them being from a foreign culture, allowing them additional lee way in making decisions that is considered to be non stereotypical or norm "because she is not from around here" or using very consciously the excuse "this is the way we do it in my home country" to overcome attitudinal [gender] barriers. Most interviewed women also acknowledge that being a woman in a male dominated environment such as a higher management position differentiates them from the "crowd" and it can be utilized as an advantage providing that you want to stand in the spotlight. A common thread among the interviewed women was that women themselves are their own worst enemies they often create their own internal barriers that prevent them from advancing their careers. However, the higher the women climb on the corporate ladder, the less advantage they have from being a foreigner and a woman, and the more they have to conform to the "norm" that in many places still is an "old boys club"
Mining Bio Medical Literature Using Ontology Based Text Mining
Year: 2014

Text mining is a new and exciting area of computer science research that tries to solve the crisis of information overload by combining techniques from data mining, machine learning, natural language processing, information retrieval, and knowledge management. Significant developments in the area of biomedical text mining during the past years have demonstrated its great promise for supporting scientists and medical practitioners in developing new knowledge from the biomedical literature. Identifying and classifying relevant medical information in short texts and finding the semantic relations among these information is a challenging task of mining Bio Medical Literature. This can be achieved by extracting information from published literatures. In order to share the vast amounts of biomedical knowledge effectively, textual evidence needs to be linked to ontologies as the main repositories of formally represented knowledge. Ontologies are conceptual models that aim to support consistent and unambiguous knowledge sharing and that provide a framework for knowledge integration.
IMPLEMENTASI PENDIDIKAN KARAKTER DALAM EKSTRAKURIKULER PRAMUKA DI SD NEGERI TEMBONGRAJA 03 KECAMATAN SALEM KABUPATEN BREBES
Year: 2018

Penelitian ini dilatarbelakangi oleh fenomena yang terjadi di SD Negeri Tembongraja 03 saat peneliti melakukan praktik mengajar. Tujuan penelitian ini untuk mendeskripsikan implementasi pendidikan karakter dalam ekstrakurikuler pramuka di SD Negeri Tembongraja 03 Kecamatan Salem Kabupaten Brebes Tahun Pelajaran 2016/2017. Jenis penelitian menggunakan kualitatif deskriftif dengan pendekataan fenomenologi, teknik keabsahan data menggunakan trianggulasi sumber dan teknik. Teknik pengumpulan data meliputi: metode observasi, wawancara, dan dokumentasi. Teknik analisis data menggunakan teknik deskriptif kualitatif melalui reduksi data, penyajian data, dan penarikan kesimpulan. Subjek penelitian terdiri dari kepala sekolah, pembina pramuka, dan siswa penggalang yang aktif mengikuti kegiatan ekstrakurikuler pramuka. Sumber terdiri dari data primer dan skunder, data primer diperoleh dari hasil wawancara dengan kepala sekolah, pembina pramuka dan siswa penggalang yang aktif mengikuti kegiatan ekstrakurikuler pramuka, data skunder diperoleh dari dokumentasi berupa data siswa yang mengikuti kegiatan ekstrakurikuler pramuka dan foto kegiatan penelitian. Hasil penelitian terlihat bagus pada karakter religius, jujur, disiplin, kerja keras, kreatif, mandiri, demokratis, rasa ingin tahu, semangat kebangsaan, cinta tanah air, menghargai prestasi, bersahabat/komunikatif, cinta damai, peduli lingkunganan, peduli sosial, dan karakter tanggung jawab sudah cukup bagus terlihat namun kurang terlihat bagus pada karakter gemar membaca. Untuk keseluruhan pendidikan karakter yang ada sudah menerapkan 18 karakter yang di canangkan kemendiknas.
Study of the deformation mechanism of the Gaoliying ground fissure
Year: 2015

The Gaoliying ground fissure in Beijing has caused building cracking and road damage, and has seriously influenced city construction. Based on investigations and trenching, the influences of the fault and the variation of groundwater levels on the formation mechanism of the Gaoliying ground fissure were investigated by using FLAC3D. The results indicated that (1) the surface location of Gaoliying fissure is controlled by the underlying normal fault activity, and over pumping further exacerbates development of the ground fissure; (2) when the groundwater level declines, obvious differential settlement occurs at both sides of the ground fissure, in which greater settlement occurs in the vicinity of the hanging wall, the greater the distance from the hanging wall, the smaller the ground subsidence, however smaller ground subsidence occurs in the vicinity of the footwall, the greater the distance from the footwall, the greater the ground subsidence; (3) the vertical velocity of the ground fissure triggered by the fault activity and groundwater decline ranges from 15.5 to 18.3 mm a 1, which is basically in line with the monitoring data. The fault activity contributes about 28 39 and the groundwater contributes about 61 72 to the deformation of the ground fissure, respectively.
Nature inspired meta heuristics approaches for charging plug in hybrid electric vehicle
Venue: Wirel. Networks
Year: 2020

Currently, there is a remarkable focus on green technologies for taking steps towards more use of renewable energy sources within the sector of transportation and also decreasing pollution. At this point, employment of plug in hybrid electric vehicles (PHEVs) needs sufficient charging allocation strategy, by running smart charging infrastructures and smart grid systems. In order to daily usage of PHEVs, daytime charging stations are required and at this point, only an appropriate charging control and a management of the infrastructure can lead to wider employment of PHEVs. In this study, four swarm intelligence based optimization techniques: particle swarm optimization (PSO) gravitational search algorithm (GSA) accelerated particle swarm optimization, and hybrid version of PSO and GSA (PSOGSA) have been applied for the state of charge optimization of PHEVs. In this research, hybrid PSOGSA has performed very well in producing better results than other stand alone optimization techniques.
Selection and Assessment of Plant Growth Promoting Rhizobacteria for Biological Control of Multiple Plant Diseases.
Venue: Phytopathology
Year: 2017

A study was designed to screen individual strains of plant growth promoting rhizobacteria (PGPR) for broad spectrum disease suppression in vitro and in planta. In a preliminary screen, 28 of 196 strains inhibited eight different tested pathogens in vitro. In a secondary screen, these 28 strains showed broad spectrum antagonistic activity to six different genera of pathogens, and 24 of the 28 strains produced five traits reported to be related to plant growth promotion, including nitrogen fixation, phosphate solubilization, indole 3 acetic acid production, siderophore production, and biofilm formation. In advanced screens, the 28 PGPR strains selected in vitro were tested in planta for biological control of multiple plant diseases including bacterial spot of tomato caused by Xanthomonas axonopodis pv. vesicatoria, bacterial speck of tomato caused by Pseudomonas syringae pv. tomato, damping off of pepper caused by Rhizoctonia solani, and damping off of cucumber caused by Pythium ultimum. In all, 5 of the 28 tested strains significantly reduced three of the four tested diseases, and another 19 strains showed biological control to two tested diseases. To understand the observed broad spectrum biocontrol capacity, antiSMASH was used to predict secondary metabolite clusters of selected strains. Multiple gene clusters encoding for secondary metabolites, e.g. bacillibactin, bacilysin, and microcin, were detected in each strain. In conclusion, selected individual PGPR strains showed broad spectrum biocontrol activity to multiple plant diseases.
Sparse Binary Compression: Towards Distributed Deep Learning with minimal Communication
Venue: 2019 International Joint Conference on Neural Networks (IJCNN)
Year: 2019

Currently, progressively larger deep neural networks are trained on ever growing data corpora. In result, distributed training schemes are becoming increasingly relevant. A major issue in distributed training is the limited communication bandwidth between contributing nodes or prohibitive communication cost in general. To mitigate this problem we propose Sparse Binary Compression (SBC) a compression framework that allows for a drastic reduction of communication cost for distributed training. SBC combines existing techniques of communication delay and gradient sparsification with a novel binarization method and optimal weight update encoding to push compression gains to new limits. By doing so, our method also allows us to smoothly trade off gradient sparsity and temporal sparsity to adapt to the requirements of the learning task. Our experiments show, that SBC can reduce the upstream communication on a variety of convolutional and recurrent neural network architectures by more than four orders of magnitude without significantly harming the convergence speed in terms of forward backward passes. For instance, we can train ResNet50 on ImageNet in the same number of iterations to the baseline accuracy, using x3531 less bits or train it to a 1% lower accuracy using x37208 less bits. In the latter case, the total upstream communication required is cut from 125 terabytes to 3.35 gigabytes for every participating client.
Self Optimizing control for wind turbine generators
Year: 2016

The fast development of the wind power technology is leading to larger and more expensive wind turbines which require increasingly advance control systems to achieve optimal or near optimal operation. However, the increased optimality of complex operation schemes, like real time optimization approaches, incur in high implementation and maintenance costs. Furthermore, while the wind speed is a key variable for the wind turbine control, using it as a direct input leads to a poor response of the power control. This makes the industry focus on simpler control structures, considering wind as a disturbance  Nevertheless, baseline control laws, which perform a deterministic control, require that complex aerodynamic properties are wellknown to achieve the desired performance. But in practice, variability bounds the efficiency of the energy capture. Thus, a constrained self optimizing control is proposed to regulate the wind turbine operation coping with wind speed uncertainty. A data driven self optimizing control is proposed for the wind turbine control region where power is maximized (region 2) Operational data is extracted from a model offline to examine the structure of the optimal solution. This insight is then transformed into a simple control structure capable of keeping the wind turbine to an optimal operation, in terms of maximizing power output. However, at high wind speed, wind turbine power output has to be maintained at its nominal rate. Thus, a cascade control structure for self optimizing and constrained control is incorporated. The control structure is implemented in Simulink using as a model FAST v8 5MW onshore wind turbine model. The proposed self optimizing control learns the structure of the optimal solution offline and then performs the optimization strategy, adjusting both torque and pitch to maximize energy capture. This control approach leads to an increase in power output when comparing it with the deterministic baseline control. Moreover, this heuristic control approach has the potential to take into account a higher number of inputs without compromising reliability. This property allows its future application for more advance control strategies.
Bayesian state prediction of wind turbine bearing failure
Year: 2018

A statistical approach to abstract and predict turbine states in an online manner has been developed. Online inference is performed on temperature measurement residuals to predict the failure state D n steps ahead of time. In this framework a case study is performed showing the ability to predict bearing failure 33 days, on average, ahead of time. The approach is based on the separability of the sufficient statistics and a hidden variable, namely the state length. The predictive probability is conditioned on the data available, as well as the state variables. It is shown that the predictive probability can be calculated by a model for the samples and a hazard function describing the probability for undergoing a state transition. This study is concerned with the prior training of the model, for which run to failure time series of bearing measurements are used. For the sample model prediction is conditioned on prior information and predict the next D n samples from a feature space spanned by the prior samples. By assuming that the feature space can be described by a multivariate Gaussian distribution, the prediction is treated as a Gaussian process over the feature space.
Understanding the User Experience of Customer Service Chatbots: What Can We Learn from Customer Satisfaction Surveys?
Venue: CONVERSATIONS
Year: 2020

Understanding and improving user experience is key to strengthening uptake and realizing the potential of chatbots for customer service. In this paper, we investigate customer satisfaction surveys as a source of insight into such user experience. A total of 5,687 customer satisfaction reports on users' interactions with a customer service chatbot, and the corresponding chatbot interactions, are analyzed. The findings demonstrate that customer satisfaction reports are closely associated with the degree to which the problems motivating users' chatbot interactions are resolved. Furthermore, the findings show substantial variation in the performance of different chatbot intents in terms of customer satisfaction and problem resolution. This implies that user experience varies substantially depending on the problems motivating users to interact with the chatbot. Finally, we identify key characteristics of the intents associated with particularly high or low customer experience, suggesting paths towards efficient improvement of chatbot user experience. Based on the findings, we point to key implications for theory and practice and suggest directions for future research.
Burnout, Perceived Efficacy, and Job Satisfaction: Perception of the Educational Context in High School Teachers
Venue: BioMed research international
Year: 2019

Burnout is closely related to personal and contextual variables, especially job satisfaction and commitment, and other less studied psychological variables, such as perception of teaching efficacy or educational context.  The general objective of this study was to examine the relationships of burnout with perceived educational context, perceived teaching efficacy (personal and collective) and job satisfaction and commitment.  A battery of instruments was administered to 500 high school teachers at different schools in several Italian provinces.  The cluster analysis found that one third of high school teachers had high burnout. Evidence was also found associating elevated burnout with low scores in perceived efficacy (personal and collective) low job satisfaction, and low professional commitment. Furthermore, perception of the educational context is less positive when the teachers experience high levels of burnout. Finally, the results showed the mediating effect of perceived personal efficacy on the relationship between burnout and job satisfaction.  The results are discussed from the perspective of developing teaching autonomy on improving personal efficacy, decreasing burnout, and increasing job satisfaction in an educational system which reinforces individual and collective competence.
Annual report readability, agency costs, firm performance: an investigation of Oman's financial sector
Year: 2021

The readability of annual reports is an important feature that determines the quality of communication between a firm and its stakeholders. Extant literature has demonstrated that readability characteristics of annual reports are crucial in facilitating the investor's ability to process and analyze information, resulting in higher firm performance and lower agency costs. This study examines the relationship between annual report readability, agency costs and the firm performance of listed financial sector companies in Oman.,Using a sample of 150 firm year observations of listed financial sector companies on the Muscat Securities Market (MSM) over the period 2014 to 2018, a panel regression analysis is used, along with the system generalized method of moments (GMM) estimation to address endogeneity concerns. The readability of annual reports is proxied by the length of the annual report, the Flesch reading ease and the Flesch Kincaid index.,The ordinary least squares (OLS) results suggest that readability proxied by the length of the annual report has no significant relationship with agency cost, return on assets (ROA) or stock returns. The OLS results are confirmed through the system GMM estimation model for agency costs, Tobin's Q and stock returns. Easier to read annual reports measured by the Flesch reading ease demonstrate high asset utilization ratio and Tobin's Q. These results emphasize Flesch reading ease measure in explaining the economic significance of agency cost and Tobin's Q. In contrast, difficult to read annual reports are observed for firms with high ROA.,The study is limited to the financial sector. Its generalizability could be extended to a similar sector or countries with features similar to Oman. Future studies on readability could be extended to other sectors of Oman, and financial firms with easier to read annual reports show a high Tobin's Q, which reflects the confidence of investors in the stock market. These findings may encourage policymakers to regulate the readability features of annual reports and influence the reporting quality of financials and disclosures also including cross country comparisons.,Financial firms with easier to read annual reports show a high Tobin's Q, which reflects the confidence of investors in the stock market. These findings may encourage policymakers to regulate the readability features of annual reports and influence the reporting quality of financials and disclosures.,While the study extends prior literature on readability, agency costs and firm performance, it is also one of the first to examine the financial sector of an emerging country, namely, Oman. The study supports the obfuscation hypothesis through the association of readability measure with agency cost. Unlike prior research that has focused on common computational linguistic literature, this study uses three proxies for readability to assess information quality.