Miracle-dz/UniFAR-FTUs huggingface dataset:
PicTouRe - A Picture-Based Tourism Recommender

We present PicTouRe – a picture-based tourism recommender. PicTouRe aims to mitigate people’s difficulties in explicitly expressing their touristic preferences, which is even more challenging in the initial phase of travel decision making. Addressing this issue, with PicTouRe we follow the idiom “a picture is worth a thousand words” and use pictures as a tool to implicitly elicit peoples’ touristic preferences. We describe the core concept of PicTouRe - the Generic Profiler, which in essence determines an explainable vector representation, i.e., touristic profile, given any picture collection as input. We showcase a user’s journey through PicTouRe and describe the steps behind. Finally, we present results of a first user study supporting our approach. PicTouRe is available under https://pictoprof.ec. tuwien.ac. at and a demo video under https://youtu.be/xZnXLPcenEs.
VeriSIM: A Learning Environment for Comprehending Class and Sequence Diagrams using Design Tracing

In this paper, we describe the design tracing strategy, which enables students to comprehend class and sequence diagrams by tracing different scenarios. In design tracing, for a given scenario, students identify relevant variables from the class diagram, relevant events from the sequence diagram and trace the flow of these data variables and events by constructing a state diagram. We have developed a web-based learning environment - VeriSIM, which trains students to apply the design tracing strategy. We conducted a study where 86 final-year undergraduates interacted with VeriSIM. Findings from the pre-test and post-test show that students are able to trace a given scenario by identifying relevant variables and events and are able to simulate change of state for these variables. A focus-group interview was also conducted with 13 participants in order to understand their perception of the usefulness of design tracing. A thematic analysis of the focus-group interview showed that students perceived design tracing helped them understand the relationship between different diagrams and identify different scenarios in the design. Interaction with VeriSIM also helped students understand the usefulness of creating class and sequence diagrams. These results show that design tracing can be a useful pedagogy to help learners form an integrated and correct understanding of class and sequence design diagrams.
No Need to Slow Down! A Head-up Display Based Warning System for Cyclists for Safe Passage of Parked Vehicles

The development of driver assistance systems and technologies for vehicle automation is pushed forward in order to increase road safety. However, there are still numerous situations that cannot (easily) be solved with on-vehicle assistance systems, particularly during the interaction of vehicles with vulnerable road users. Bicyclists, especially in urban areas, are traveling at relatively high speeds compared to pedestrians. Even on dedicated bicycle lanes, numerous accidents are caused by vehicle doors opening. Our proposed approach aims at warning cyclists of suddenly opening doors of parked vehicles when passing. We plan to conduct a user study in mixed reality, comparing the baseline (no system) to two warning concepts (visual and visual-auditory). We expect that awareness of the possible danger will let cyclists feel safer and help to prevent accidents. We estimate that the visual-auditory system leads to better reaction times and lower mental workload as the visual-only system.
JTeC: A Large Collection of Java Test Classes for Test Code Analysis and Processing

The recent push towards test automation and test-driven development continues to scale up the dimensions of test code that needs to be maintained, analysed, and processed side-by-side with pro-duction code. As a consequence, on the one side regression testing techniques, e.g., for test suite prioritization or test case selection, capable to handle such large-scale test suites become indispensable; on the other side, as test code exposes own characteristics, specific techniques for its analysis and refactoring are actively sought. We present JTeC, a large-scale dataset of test cases that researchers can use for benchmarking the above techniques or any other type of tool expressly targeting test code. JTeC collects more than 2.5M test classes belonging to 31K + GitHub projects and summing up to more than 430 Million SLOCs of ready-to-use real-world test code.
REVEAL 2020: Bandit and Reinforcement Learning from User Interactions

The REVEAL workshop1 focuses on framing the recommendation problem as a one of making personalized interventions, e.g. deciding to recommend a particular item to a particular user. Moreover, these interventions sometimes depend on each other, where a stream of interactions occurs between the user and the system, and where each decision to recommend something will have an impact on future steps and long-term rewards. This framing creates a number of challenges we will discuss at the workshop. How can recommender systems be evaluated offline in such a context? How can we learn recommendation policies that are aware of these delayed consequences and outcomes?
Polyglot and Distributed Software Repository Mining with Crossflow

Mining software repositories at a large scale typically requires substantial computational and storage resources. This creates an increasing need for repository mining programs to be executed in a distributed manner, such that remote collaborators can contribute local computational and storage resources. In this paper we present Crossflow, a novel framework for building polyglot distributed repository mining programs. We demonstrate how Crossflow offers delegation of mining jobs to remote workers and can cache their results, how such workers are able to implement advanced behavior like load balancing and rejecting jobs they either cannot perform or would execute sub-optimally, and how workers of the same analysis program can be written in different programing languages like Java and Python, executing only relevant parts of the program described in that language.
On Target Item Sampling in Offline Recommender System Evaluation

Target selection is a basic yet often implicit decision in the configuration of offline recommendation experiments. In this paper we research the impact of target sampling on the outcome of comparative recommender system evaluation. Specifically, we undertake a detailed analysis considering the informativeness and consistency of experiments across the target size axis. We find that comparative evaluation using reduced target sets contradicts in many cases the corresponding outcome using large targets, and we provide a principled explanation for these disagreements. We further seek to determine which among the contradicting results may be more reliable. Through comparison to unbiased evaluation, we find that minimum target sets incur in substantial distortion in pairwise system comparisons, while maximum sets may not be ideal either, and better options may lie in between the extremes. We further find means for informing the target size setting in the common case where unbiased evaluation is not possible, by an assessment of the discriminative power of evaluation, that remarkably aligns with the agreement with unbiased evaluation.
Tunnel emitter: tunnel diode based low-power carrier emitters for backscatter tags

Backscatter enables transmissions at orders of magnitude lower energy consumption when compared to conventional radio transmitters. Backscatter tags achieve this by the reflection or absorption of carrier signal generated from emitter devices. However, backscatter systems are limited by these emitter devices, as they are significantly energy-expensive when compared to the tags. While backscatter tags can operate without requiring batteries, relying on the minuscule amounts of energy harvested from the ambient environment. However, the emitter devices, are commonly tethered to an external power supply or operate on large batteries. We present Tunnel Emitter: a tunnel diode oscillator based system that enables the generation of carrier signals at a peak biasing power of tens of μW. Thus, for the first time, it allows battery-free emitter devices. The key enabler to the design is a phenomenon exhibited by tunnel diode oscillators that we call back injection, and we are the first to demonstrate. Back injection enables the emitter devices to amplify (up to 20 dB) and relay the backscattered signal. Our results show that Tunnel Emitter when operating together with a tag from long-range backscatter system, facilitates multi-floor communication. Tunnel Emitter, due to the back injection phenomenon, achieves this with a carrier signal that is orders of magnitude weaker than used in state-of-the-art systems. We believe Tunnel Emitter overcomes the key constraint restricting backscatter systems and thus can make backscatter systems ubiquitous.
Employing Contribution and Quality Metrics for Quantifying the Software Development Process

The full integration of online repositories in contemporary soft-ware development promotes remote work and collaboration. Apart from the apparent benefits, online repositories offer a deluge of data that can be utilized to monitor and improve the software de-velopment process. Towards this direction, we have designed and implemented a platform that analyzes data from GitHub in order to compute a series of metrics that quantify the contributions of project collaborators, both from a development as well as an op-erations (communication) perspective. We analyze contributions throughout the projects' lifecycle and track the number of coding violations, this way aspiring to identify cases of software development that need closer monitoring and (possibly) further actions to be taken. In this context, we have analyzed the 3000 most popular GitHub Java projects and provide the data to the community.
The 2nd Workshop on Localization vs. Internationalization: Impact of COVID-19 Pandemic on AutomotiveUI Activities from the View of Diversity and Inclusion

A worldwide pandemic has brought many challenges in numerous areas of everyone's life. The AutomotiveUI 2020 has also been moved to a virtual conference. Although the situation seems to be improving in some parts of the world, the impacts that the pandemic has brought to the research and academia may last long even after the pandemic is over. In the AutomotiveUI community, there is more than one aspect that should be taken into consideration. Ironically, the situation brought about both risks and opportunities including research methods, collaboration, interaction manners, and diversity and inclusion. With this background, the goal of this workshop is to discuss the impact of the COVID19 pandemic on the AutomotiveUI community from the perspective of the diversity and inclusion and to discuss the direction of collaborative activities of our community with researchers from various groups. We will organize three virtual workshop sessions accomodating different time zones.
How to reduce risk effectively in fixed price software development

In this paper we consider 20 years of software development at a medium-sized European software company (called adesso). We identify changes and trends in software project management and we name typical risks inherent to fixed price projects (beyond the common sense that unclear requirements, missing domain knowledge and breakdown of project communication are permanent risks). Fixed price projects and their related derivatives can have a huge economical upside for companies like adesso, which goes along with sometimes even larger risks. The goal of this research is to identify both risk drivers and risk reduction or even elimination strategies. On this basis, we introduce the notion of a Project Management Office (PMO) and supporting tools and mechanisms which help to identify project risks early. Experience reported is based on eight years of monitoring software development projects with these tools and mechanisms. We also give some insights how PMO at adesso has changed over time and why these changes were implemented. As key message of this paper we show the correlation between the systematic usage of the PMO tools and a decreasing overspend rate over eight years and more than 320 projects.CCS CONCEPTS• General and reference → Metrics; • Software and its engineering → Software development process management; Risk management.
Interfaces and Human Decision Making for Recommender Systems

As an interactive intelligent system, recommender systems are developed to give recommendations that match users’ preferences. Since the emergence of recommender systems, a large majority of research focuses on objective accuracy criteria and less attention has been paid to how users interact with the system and the efficacy of interface designs from users’ perspectives. The field has reached a point where it is ready to look beyond algorithms, into users’ interactions, decision making processes, and overall experience. The series of workshops on Interfaces and Human Decision Making for Recommender Systems focuses on the ”human side” of recommender systems. The goal of the research stream featured at the workshop is to improve users’ overall experience with recommender systems by integrating different theories of human decision making into the construction of recommender systems and exploring better interfaces for recommender systems. In this summary, we introduce 7th Joint Workshop on Interfaces and Human Decision Making for Recommender Systems at RecSys’20, review its history, and discuss most important topics considered at the workshop.
Causal Inference for Recommender Systems

The task of recommender systems is classically framed as a prediction of users’ preferences and users’ ratings. However, its spirit is to answer a counterfactual question: “What would the rating be if we ‘forced’ the user to watch the movie? ” This is a question about an intervention, that is a causal inference question. The key challenge of this causal inference is unobserved confounders, variables that affect both which items the users decide to interact with and how they rate them. To this end, we develop an algorithm that leverages classical recommendation models for causal recommendation. Across simulated and real datasets, we demonstrate that the proposed algorithm is more robust to unobserved confounders and improves recommendation.
Improving One-class Recommendation with Multi-tasking on Various Preference Intensities

In the one-class recommendation problem, it’s required to make recommendations basing on users’ implicit feedback, which is inferred from their action and inaction. Existing works obtain representations of users and items by encoding positive and negative interactions observed from training data. However, these efforts assume that all positive signals from implicit feedback reflect a fixed preference intensity, which is not realistic. Consequently, representations learned with these methods usually fail to capture informative entity features that reflect various preference intensities. In this paper, we propose a multi-tasking framework taking various preference intensities of each signal from implicit feedback into consideration. Representations of entities are required to satisfy the objective of each subtask simultaneously, making them more robust and generalizable. Furthermore, we incorporate attentive graph convolutional layers to explore high-order relationships in the user-item bipartite graph and dynamically capture the latent tendencies of users toward the items they interact with. Experimental results show that our method performs better than state-of-the-art methods by a large margin on three large-scale real-world benchmark datasets.
Phytochemical analysis of Leucas urticifolia (Vahl) R. Br. ex Sm.: A traditional medicinal herb

The present paper shows the phytochemical analysis of the traditional medicinal plant Leucas urticifolia (Vahl) R. Br. ex Sm. belonging to family Lamiaceae. The Preliminary Phytochemical analysis revealed the presence of alkaloids, glycosides, flavonoids, tannins, terpenoids, steroids, saponins and phenolics. Alkaloids were present at low quantity but phenolics were present in high quantity as compare to flavonoids. During HPTLC analysis total 11 compounds were identified i.e., Ferulic acid, Kaempferol, pCaumarin, Cinnamic acid, Chlorogenic acid, Catechin, Myricetin, Gallic acid, Apigenin, Quercetin and Vanillic acid.
From RU 38486 towards Dissociated Antiglucocorticoid and Antiprogesterone

The aim of this paper is to describe the different structure-affinity and structure-activity relationships which led to the discovery of RU 43044, a pure antiglucocorticoid, and of the dissociated antiprogestins RU 46556 and RU 49295. Furthermore, a complete biochemical and pharmacological profile of these 3 compounds compared to that of RN 38486 will be presented
Heavy Metals Toxicity and the Environment

Heavy metals are naturally occurring elements that have a high atomic weight and a density at least 5 times greater than that of water. Their multiple industrial, domestic, agricultural, medical and technological applications have led to their wide distribution in the environment; raising concerns over their potential effects on human health and the environment. Their toxicity depends on several factors including the dose, route of exposure, and chemical species, as well as the age, gender, genetics, and nutritional status of exposed individuals. Because of their high degree of toxicity, arsenic, cadmium, chromium, lead, and mercury rank among the priority metals that are of public health significance. These metallic elements are considered systemic toxicants that are known to induce multiple organ damage, even at lower levels of exposure. They are also classified as human carcinogens (known or probable) according to the U.S. Environmental Protection Agency, and the International Agency for Research on Cancer. This review provides an analysis of their environmental occurrence, production and use, potential for human exposure, and molecular mechanisms of toxicity, genotoxicity, and carcinogenicity.
DIALECT IDENTIFICATION FROM PROSODIC CUES

It is a well known fact that dialects differ in prosodic features as well as segmental features. Though few studies have focused on prosody, existing research provides evidence of distinct differences in the intonation pattern between African-American English (AAE) and Mainstream American English (MAE). This study examines how speakers use such prosodic cues to differentiate AAE from MAE. It was hypothesized that dialect identification is easiest in cases where the intonation pattern of an utterance is dialect-specific and does not vary across speakers within a dialect group. It was also hypothesized that the degree of exposure to AAE is positively correlated with the accuracy rate for identifying AAE. Results show that neither sex nor race alone had an effect on accuracy in dialect identification, but exposure to AAE had a measurable effect on performance in terms of both accuracy and confidence in identification.
Common errors while applying design of experimentation in special reference to aromatic and medicinal plant

Statistical science is concerned with the aspect of theory of design of experiments and sample investigation and drawing valid inferences from using various statistical methods. The statisticians design the experiments, trials and analyze the data and interpret the facts. The statisticians design the experiments, trials and analyze the data and interpret the facts. Statistical design and technique helps to describe the involvement of complex phenomena and behaviour of agricultural growth. The impact of associated factor can be analyzed with the help of simple statistical design, sampling techniques with inferential statistics. The techniques of drawing valid interpretation depend on how the data has been gathered and also depending upon the research objective. This paper describes the basic concept of statistical research design of design of experiment and techniques used for analysis and interpretation of investigations and also discuss the experimental.
HERBAL DISINFECT PRODUCTION AGAINST BACTERIA SPECIES FOUND IN THE SCHOOL ENVIRONMENT

In our project, it is aimed to identify the bacteria species found in the environments in which students spend most of their time in school and to produce herbal disinfectant against these bacteria types. During the research phase, microorganism samples were taken from the school environment and some bacteria species that could threaten health were identified. In the school environment, as a result of the cultivation of microorganisms in the living spaces of the students (window handle, stair railing, classroom door handle, cabinet interior, handle, bottom of the desks, siphon, etc.), 5 different types of bacteria have been identified and a herbal antiseptic mixture has been created against these bacteria types. Bacteria samples were taken from the school environment with the swabs at the experimental stage of the project, inoculated in petri dishes and bacteria species were determined by Gram staining method. After detecting bacteria species, disinfectant material was obtained by extraction method from herbal substances showing antibacterial properties. Inhibition diameters of plant extracts on bacteria were observed by disc diffusion method. According to the findings; Gram (+) bacteria were detected on the bottom of the desk, classroom window handle, corridor handles, computer keyboard-mouse and classroom smartboard. S. pyogenes GSJ: Volume 8, Issue 5, May 2020 ISSN 2320-9186 1117 GSJ© 2020 www.globalscientificjournal. com bacteria were detected on the bottom of the desk and S. epidermidis bacteria in other areas including window handle, handrail, computer mouse and keyboard, class smart board were detected. Extracts of chamomile, clove, cinnamon, tea tree, orange peel and rose plants, which have antibacterial properties, were applied to bacteria mediums. While both species of bacteria form the greatest inhibition diameters against clove and chamomile plants; they created a small amount of zones in the cinnamon and tea tree. No inhibition diameter was observed in rose and orange peel extracts. According to the overall results obtained from the project, we recommend to analyze the possibility of shifting the research area to different areas due to the capture of pathogenic features in bacteria in the environment, and since the extracts of chamomile and cloves are effective alone, they can also be effective in their combination.
Identity of Two Earthworms Used in Vermiculture and Vermicomposting in Korea

Two vermiculture earthworms, Eisenia andrei Bouche, 1972 and Perionyx excavatus Perrier, 1872 are newly recorded to Korean fauna. E.andrei has no pale stripe on the intersegmental furrow zone and P.excavatus has clitellum in xiii-xvi. Descriptions of the species are provided in this paper, including illustrations of the ventral view, male pore region, and spermathecae.
Non-enzymatic antioxidant defense system in plants

The defense system in plants have efficient complex enzymatic and non-enzymatic antioxidant defense systems to avoid the toxic effects of free radicals. Chloroplasts and mitochondria are the two main powerhouses and sites of reactive oxygen species (ROS) generation within plant cells AA is the most abundant and the most extensively studied antioxidant compound. It is can donate electrons to a wide range of enzymatic and non-enzymatic reactions. Majority of AA in plant cells is the result of Smirnoff-Wheeler pathway, catalyzed by L-galactano-γ-lactone dehydrogenase in the plant mitochondria, with the remaining being generated from D-galacturonic acid. Vitamin E (α-tocopherol), is an efficient lipid soluble antioxidant that functions as a ‘chain breaker’ during lipid peroxidation in cell membranes and various lipid particles including low-density lipoprotein (LDL). It functions to intercept lipid peroxyl radicals (LOO) and to terminate the lipid peroxidation chain.