nils-herrmann/clean_scirepeval huggingface dataset:
Requirements Elicitation for an Inter-Organizational Business Intelligence System for Small and Medium Retail Enterprises

Business Intelligence (BI) is on everyone's lips nowadays, since it provides businesses with the possibility to analyze their business practices and improve them. However, Small and Medium Enterprises (SME) often cannot leverage the positive effects of BI because of missing resources like personnel, knowledge, or money. Since SME pose a major form of business organization, this fact has to be overcome. As the retail industry is a substantial part of the SME branch, we propose an inter-organizational approach for a BI system for retail SME, which allows them to collaboratively collect data and perform analysis task. The aim of our ongoing research effort is the development of such a system following the Design Science Research Methodology. Within this article, the status quo of current BI practices in SME in the retail industry is analyzed through qualitative interviews with ten SME managers. Afterwards, adoption and success factors of BI systems and Inter-organizational Information Systems are worked out in a comprehensive structured literature review. Based on the status quo and the adoption and success factors, first requirements for the acceptance of an inter-organizational BI system are identified and validated in another round of qualitative interviews. This leads to nine functional requirements and three non-functional requirements, which can be used for designing and implementing an inter-organizational BI system for SME in the following research efforts.
Artificial Vision in Road Vehicles

The last few decades witnessed the birth and growth of a new sensibility to transportation efficiency. In particular, the need for efficient and improved people and goods mobility pushed researchers to address the problem of intelligent transportation systems. This paper surveys the most advanced approaches to the (partial) customization of road following task, using on-board systems based on artificial vision. The functionalities of lane detection, obstacle detection and pedestrian detection are described and classified, and their possible application on future road vehicles is discussed.
Java in the High Performance Computing arena: Research, practice and experience

The rising interest in Java for High Performance Computing ( HPC) is based on the appealing features of this language for programming multi-core cluster architectures, partic ularly the built-in networking and multithreading support , and the continuous increase in Java Virtual Machine (JVM) perfo rmance. However, its adoption in this area is being delayed by the lack of analysis of the existing programming o ptions in Java for HPC and thorough and up-to-date evaluations of their performance, as well as the unawarenes s of the current research projects in this field, whose solutions are needed in order to boost the embracement of Jav a in HPC. This paper analyzes the current state of Java for HPC, both fo r shared and distributed memory programming, presents related research projects, and finally, evaluates the performance of current Java HPC solutions and research developments on two shared memory environments and two Infin iBand multi-core clusters. The main conclusions are that: (1) the significant interest in Java for HPC has led to th e development of numerous projects, although usually quite modest, which may have prevented a higher development of Java in this field; (2) Java can achieve almost similar performance to natively compiled languages, both f r sequential and parallel applications, being an alternat ive for HPC programming; and (3) the recent advances in the e ffici nt support of Java communications on shared memory and low-latency networks are bridging the gap between Java a nd n tively compiled applications in HPC. Thus, the good prospects of Java in this area are attracting the attent ion of both industry and academia, which can take significant advantage of Java adoption in HPC.
International experiences with the Hospital Anxiety and Depression Scale--a review of validation data and clinical results.

More than 200 published studies from most medical settings worldwide have reported experiences with the Hospital Anxiety and Depression Scale (HADS) which was specifically developed by Zigmond and Snaith for use with physically ill patients. Although introduced in 1983, there is still no comprehensive documentation of its psychometric properties. The present review summarizes available data on reliability and validity and gives an overview of clinical studies conducted with this instrument and their most important findings. The HADS gives clinically meaningful results as a psychological screening tool, in clinical group comparisons and in correlational studies with several aspects of disease and quality of life. It is sensitive to changes both during the course of diseases and in response to psychotherapeutic and psychopharmacological intervention. Finally, HADS scores predict psychosocial and possibly also physical outcome.
IBOTS: Agent Control Through the User Interface

This paper describes an ibot, a specialized software agent that exists in the environment of the user interface. Such an agent interacts with applications through the same medium as a human user. Its sensors process screen contents and mouse/keyboard events to monitor the user’s actions and the responses of the environment, while its effecters can generate such events for its own contributions to the interaction. We describe the architecture of our agent and * its algorithms for image processing, event management, and state representation. We illustrate the use of the agent with a small feasibility study in the area of software logging; results are promising for future progress.
Project Success Prediction in Crowdfunding Environments

Crowdfunding has gained widespread attention in recent years. Despite the huge success of crowdfunding platforms, the percentage of projects that succeed in achieving their desired goal amount is only around 40%. Moreover, many of these crowdfunding platforms follow "all-or-nothing" policy which means the pledged amount is collected only if the goal is reached within a certain predefined time duration. Hence, estimating the probability of success for a project is one of the most important research challenges in the crowdfunding domain. To predict the project success, there is a need for new prediction models that can potentially combine the power of both classification (which incorporate both successful and failed projects) and regression (for estimating the time for success). In this paper, we formulate the project success prediction as a survival analysis problem and apply the censored regression approach where one can perform regression in the presence of partial information. We rigorously study the project success time distribution of crowdfunding data and show that the logistic and log-logistic distributions are a natural choice for learning from such data. We investigate various censored regression models using comprehensive data of 18K Kickstarter (a popular crowdfunding platform) projects and 116K corresponding tweets collected from Twitter. We show that the models that take complete advantage of both the successful and failed projects during the training phase will perform significantly better at predicting the success of future projects compared to the ones that only use the successful projects. We provide a rigorous evaluation on many sets of relevant features and show that adding few temporal features that are obtained at the project's early stages can dramatically improve the performance.
Fourier Transform Decoding of Non-Binary LDPC Codes

Binary low-density parity-check (LDPC) codes have recently emerged as a promising alternative to turbo codes and have been shown to achieve excellent coding gains in AWGN channels. Non-binary LDPC codes have demonstrated improved performance over binary LDPC codes but their decoding is computationally intensive. Fourier transform decoding can reduce the decoding complexity but has a number of problems which can be avoided by implementing this algorithm in the log domain. In this paper Fourier transform decoding of non-binary LDPC codes in the log domain is described. The computational complexity and performance of this algorithm is then discussed. Differential evolution is then used to search for optimal binary and non-binary LDPC codes and it is shown by simulation that non-binary LDPC codes are superior.
The Evolving Role of Information Systems and Technology in Organizations : A Strategic Perspective

Most organizations in all sectors of industry, commerce, not‐for‐profit, and government are now fundamentally dependent on their information systems (IS) and information technology (IT). In industries such as telecommunications, media, entertainment, gambling and financial services, where the product is already, or is being increasingly, digitized, the very existence of an organization depends on the effective application of IS/IT. With the commercialization of the Internet, the use of technology has become the expected way of conducting many aspects of business and some businesses exist purely online. Governments and public administrations have launched many digital services. The ubiquity of mobile devices and new forms of social media are raising consumer demands for immediacy of access and speed of response. The increasing pervasiveness of smart connected devices and ‘things’ of all kinds is opening up opportunities for new products and services, further operational efficiencies and new types of businesses and business models. While organizations want to develop a more ‘strategic’ approach to harnessing and exploiting IS/IT, most have arrived at their current situation as a result of many short‐term, ‘tactical’ decisions. Many would no doubt like to rethink their investments, or even begin again with a ‘clean sheet’, but unfortunately have a ‘legacy’ resulting from a less than strategic approach to IS/IT in the past; many organizations including banks, insurance companies and public administrations O U T L I N E
I feel your pain: emotional closeness modulates neural responses to empathically experienced rejection.

Empathy is generally thought of as the ability to share the emotional experiences of others. In scientific terms, this is usually operationalized as an ability to vicariously feel others' mental and emotional experiences. Supporting this account, research demonstrates that watching others experience physical pain activates similar brain regions to the actual experience of pain itself. First-hand experience of social rejection also activates this network. The current work extends these findings by examining whether the "pain" network is similarly implicated in witnessing rejection, and whether emotional closeness modulates this response. We provide evidence for each of these suppositions, demonstrating: (a) that the pain network is activated when watching a friend suffer social rejection, and (b) that interpersonal closeness with that friend modulates this response. Further, we found that the inferior frontal gyrus, critical for representing others' mental and emotional states, mediates the relationship between emotional closeness and neural responses to watching the rejection of a friend.
Artificial intelligence applied to computer forensics

To be able to examine large amounts of data in a timely manner in search of important evidence during crime investigations is essential to the success of computer forensic examinations. The limitations in time and resources, both computational and human, have a negative impact in the results obtained. Thus, better use of the resources available are necessary, beyond the capabilities of the currently used forensic tools. Herein, we describe the use of Artificial Intelligence in computer forensics through the development of a multiagent system and case-based reasoning. This system is composed of specialized intelligent agents that act based on the experts knowledge of the technical domain. Their goal is to analyze and correlate the data contained in the evidences of an investigation and based on its expertise, present the most interesting evidence to the human examiner, thus reducing the amount of data to be personally analyzed. The correlation feature helps to find links between evidences that can be easily overlooked by a human expert, specially due to the amount of data involved. This system has been tested using real data and the results were very positive when compared to those obtained by the human expert alone performing the same analysis.
The Effect of Synonym Substitution on Search Results

Synonyms or other semantic associations can be used in web search in query substitution to improve or augment the query to retrieve more relevant search results. The value of substitution depends on how well the synonyms preserve semantic meaning, as any attrition in meaning can result in semantic drift of query results. Many synonyms are not synonyms in the traditional, thesaurus sense, but are semantic associations discovered automatically from online data, with the risk of semantic drift in substitution. This discovery of synonyms or other semantic associations arises from different methods applied over web search logs, and in this paper we review the candidate synonym pairs of words or phrases generated from three different methods applied over the same web search logs. The suitability of the candidate synonym pairs for the purpose of query substitution is evaluated in an experiment where 68 subjects assessed the search results generated by both the original query and the substituted query. It was found that two of the discovery methods returned significantly worse results with the substitution than were returned by the original query for the majority of queries, with only around 20-22% of substituted queries generating either improved or equally-relevant results. The third method however returned a very similar level of superior results as the original query, and saw over 71% of substituted queries generating either improved or equally-relevant results. These results indicate that even when candidate synonym pairs are confirmed as being semantically associated using other methods, they still may not be suitable for query substitution, depending on the method of synonym discovery.
MIMO for ATSC 3.0

This paper provides an overview of the optional multiple-input multiple-output (MIMO) antenna scheme adopted in ATSC 3.0 to improve robustness or increase capacity via additional spatial diversity and multiplexing by sending two data streams in a single radio frequency channel. Although it is not directly specified, it is expected in practice to use cross-polarized 2×2 MIMO (i.e., horizontal and vertical polarization) to retain multiplexing capabilities in line-of-sight conditions. MIMO allows overcoming the channel capacity limit of single antenna wireless communications in a given channel bandwidth without any increase in the total transmission power. But in the U.S. MIMO can actually provide a larger comparative gain because it would be allowed to increase the total transmit power, by transmitting the nominal transmit power in each polarization. Hence, in addition to the MIMO gains (array, diversity, and spatial multiplexing), MIMO could exploit an additional 3 dB power gain. The MIMO scheme adopted in ATSC 3.0 re-uses the single-input single-output antenna baseline constellations, and hence it introduces the use of MIMO with non-uniform constellations.
Insulin detemir versus insulin glargine for type 2 diabetes mellitus.

Chronically elevated blood glucose levels are associated with significant morbidity and mortality. Many diabetes patients will eventually require insulin treatment to maintain good glycaemic control. There are still uncertainties about the optimal insulin treatment regimens for type 2 diabetes, but the long-acting insulin analogues seem beneficial. Several reviews have compared either insulin detemir or insulin glargine to NPH insulin, but research directly comparing both insulin analogues is limited.



To assess the effects of insulin detemir and insulin glargine compared with each other in the treatment of type 2 diabetes mellitus.


SEARCH STRATEGY
We searched MEDLINE, EMBASE, The Cochrane Library, online registries of ongoing trials and abstract books. Date of last search was January 2011.



All randomised controlled trials comparing insulin detemir with insulin glargine with a duration of 12 weeks or longer were included.



Two authors independently selected the studies and extracted the data. Pooling of studies by means of random-effects meta-analysis was performed.



This review examined four trials lasting 24 to 52 weeks involving 2250 people randomised to either insulin detemir or glargine. Overall, risk of bias of the evaluated studies was high. Insulin glargine was dosed once-daily in the evening. Insulin detemir was initiated once-daily in the evening with the option of an additional dose in the morning in three studies and initiated twice-daily in one study. Of randomised patients 13.6% to 57.2% were injecting insulin detemir twice-daily at the end of trial.Glycaemic control, measured by glycosylated haemoglobin A1c (HbA1c) and HbA1c equal to or less than 7% with or without hypoglycaemia, did not differ statistically significantly between treatment groups.The results showed no significant differences in overall, nocturnal and severe hypoglycaemia between treatment groups.Insulin detemir was associated with less weight gain. Treatment with insulin glargine resulted in a lower daily basal insulin dose and a lower number of injection site reactions.There was no significant difference in the variability of FPG or glucose values in 24-hour profiles between treatment groups. It was not possible to draw conclusions on quality of life, costs or mortality. Only one trial reported results on health-related quality of life and showed no significant differences between treatment groups.



Our analyses suggest that there is no clinically relevant difference in efficacy or safety between insulin detemir and insulin glargine for targeting hyperglycaemia. However, to achieve the same glycaemic control insulin detemir was often injected twice-daily in a higher dose but with less weight gain, while insulin glargine was injected once-daily, with somewhat fewer injection site reactions.
High-Power Pulse Generator With Flexible Output Pattern

This paper presents a high-voltage bipolar rectangular pulse generator using a solid-state boosting front-end and an H-bridge output stage. The topology generates rectangular pulses with fast enough rise time and allows easy step-up input voltage. In addition, the circuit is able to adjust positive or negative pulsewidth, dead time between two pulses, and operating frequency. The topology can also be controlled to produce unipolar pulses and other pulse patterns without changing its configuration. With an appropriate dc source, the output voltage can also be adjusted to requirements of different applications. The intended application for such a circuit is algal cell membrane rupture for oil extraction, although additional applications, include biotechnology and plasma sciences, medicine, and food industry. A 1 kV/200 A bipolar solid-state pulse generator was fabricated to validate the theoretical analysis presented in this paper. In addition, to validate the analysis with simulations and prototype tests, biological test were conducted in order to examine the technical value of the proposed circuit. These evaluations seem to suggest that oil production rate from bipolar pulses may double that of an equivalent process with unipolar pulses.
Illumination compensation and normalization for robust face recognition using discrete cosine transform in logarithm domain

This paper presents a novel illumination normalization approach for face recognition under varying lighting conditions. In the proposed approach, a discrete cosine transform (DCT) is employed to compensate for illumination variations in the logarithm domain. Since illumination variations mainly lie in the low-frequency band, an appropriate number of DCT coefficients are truncated to minimize variations under different lighting conditions. Experimental results on the Yale B database and CMU PIE database show that the proposed approach improves the performance significantly for the face images with large illumination variations. Moreover, the advantage of our approach is that it does not require any modeling steps and can be easily implemented in a real-time face recognition system.
Features for Measuring Credibility on Facebook Information

Nowadays social media information, such as news, links, images, or VDOs, is shared extensively. However, the effectiveness of disseminating information through social media lacks in quality: less fact checking, more biases, and several rumors. Many researchers have investigated about credibility on Twitter, but there is no the research report about credibility information on Facebook. This paper proposes features for measuring credibility on Facebook information. We developed the system for credibility on Facebook. First, we have developed FB credibility evaluator for measuring credibility of each post by manual human’s labelling. We then collected the training data for creating a model using Support Vector Machine (SVM). Secondly, we developed a chrome extension of FB credibility for Facebook users to evaluate the credibility of each post. Based on the usage analysis of our FB credibility chrome extension, about 81% of users’ responses agree with suggested credibility automatically computed by the proposed system.
When symbolism overtakes quality : Materialists consumers disregard product quality when faced with luxury brands

Consumers use extrinsic and intrinsic cues to set preferences and make purchase decisions. However, the extent to which luxury-related extrinsic cues determine consumer preferences and whether the relative weighting of extrinsic vs. intrinsic cues depends on consumers’ values is still unclear. We investigated how luxury vs. non-luxury brands affect consumer preferences, and how this impact is moderated by consumers’ materialistic values. Results from Experiment 1 showed that materialistic and non-materialistic participants similarly appreciated products with luxurious brands. However, compared with non-materialistic participants, materialistic participants devaluated products that were tagged as non-luxurious brands. In Experiment 2, we investigated how product quality interacts with brands and whether materialistic values moderated this interaction. Materialistic participants paid more attention to brand-related cues than to qualityrelated cues, whereas non-materialistic participants considered these cues similarly. Taken together, the results of these two studies suggest that materialism influences the way extrinsic (i.e., brand) and intrinsic (i.e., quality) information is combined during product evaluation. These results highlight the importance of materialism in consumer decision-making, especially in the context of luxury consumption.