Miracle-dz/UniFAR-FTUs huggingface dataset:
TopExNet: Entity-Centric Network Topic Exploration in News Streams

The recent introduction of entity-centric implicit network representations of unstructured text offers novel ways for exploring entity relations in document collections and streams efficiently and interactively. Here, we present TopExNet as a tool for exploring entity-centric network topics in streams of news articles. The application is available as a web service at https://topexnet.ifi. uni-heidelberg.de.
WSDM 2019 Tutorial on Health Search (HS2019): A Full-Day from Consumers to Clinicians

The HS2019 tutorial will cover topics from an area of information retrieval (IR) with significant societal impact --- health search. Whether it is searching patient records, helping medical professionals find best-practice evidence, or helping the public locate reliable and readable health information online, health search is a challenging area for IR research with an actively growing community and many open problems. This tutorial will provide attendees with a full stack of knowledge on health search, from understanding users and their problems to practical, hands-on sessions on current tools and techniques, current campaigns and evaluation resources, as well as important open questions and future directions.
Connective-Collective Action on Social Media: Moderated Mediation of Cognitive Elaboration and Perceived Source Credibility on Personalness of Source

Taking the logic of online connective action from an information-processing viewpoint, an online experiment (N = 208) was done to examine whether individuals’ cognitive elaboration on messages received from different sources (personal: friends, family, vs. impersonal: organization) mediates their willingness to engage in connective-type collective activities on social media (e.g., commenting, “Liking”); and whether this indirect influence is biased by perceived source credibility. Results revealed significant influence from personal sources. Cognitive elaboration positively mediates this influence and was conditionally affected by high source credibility. Direct influence from personal issue involvement and perceived self and technological efficacy was also observed. Theoretical contributions (i.e., cognitive demands at individual level) and practical implications (i.e., enhancing organizational credibility, popularity of easy-to-do acts) are discussed.
Unsupervised Methods For Subgoal Discovery During Intrinsic Motivation in Model-Free Hierarchical Reinforcement Learning

Common approaches to Reinforcement Learning (RL) are seriously challenged by large-scale applications involving huge state spaces and sparse delayed reward feedback. Hierarchical Reinforcement Learning (HRL) methods attempt to address this scalability issue by learning action selection policies at multiple levels of temporal abstraction. Abstraction can be had by identifying a relatively small set of states that are likely to be useful as subgoals, in concert with the learning of corresponding skill policies to achieve those subgoals. Many approaches to subgoal discovery in HRL depend on the analysis of a model of the environment, but the need to learn such a model introduces its own problems of scale. Once subgoals are identified, skills may be learned through intrinsic motivation, introducing an internal reward signal marking subgoal attainment. In this paper, we present a novel modelfree method for subgoal discovery using incremental unsupervised learning over a small memory of the most recent experiences (trajectories) of the agent. When combined with an intrinsic motivation learning mechanism, this method learns both subgoals and skills, based on experiences in the environment. Thus, we offer an original approach to HRL that does not require the acquisition of a model of the environment, suitable for large-scale applications. We demonstrate the efficiency of our method on two RL problems with sparse delayed feedback: a variant of the rooms environment and the first screen of the ATARI 2600 Montezuma’s Revenge game.
Linking Epidemic Models and Hawkes Point Processes for Modeling Information Diffusion

Epidemic models and Hawkes point process models are two common model classes for information diffusion. Recent work has revealed the equivalence between the two for information diffusion modeling. This allows tools created for one class of models to be applied to another. However, epidemic models and Hawkes point processes can be connected in more ways. This thesis aims to develop a rich set of mathematical equivalences and extensions, and use them to ask and answer questions in social media and beyond. Specifically, we show our plan of generalizing the equivalence of the two model classes by extending it to Hawkes point process models with arbitrary memory kernels. We then outline a rich set of quantities describing diffusion, including diffusion size and extinction probability, introduced in the fields where the models are originally designed. Lastly, we discuss some novel applications of these quantities in a range of problems such as popularity prediction and popularity intervention.
Images of the Outcast: The Urban Poor in the Cries of London

Picturing the London outcast Broadsheet Cries and British commerce Tailoring the urban poor - the ensembles of Laroon and Amigoni From representation to ridicule - Hogarth and the London Cries Retailoring the lower orders - Ensembles from 1740 to 1821 Hawkers infantalized - Cries as illustrated books Pastoral and antipastoral in the London Cries.
Living with Vitiligo: A Controlled Investigation into the Effects of Group Cognitive-Behavioural and Person-Centred Therapies

Background: Vitiligo is a progressive condition involving a loss of pigmentation in the skin. It can be disfiguring and no fully effective treatment or cure exists. Although medical effects of vitiligo have been studied extensively, less attention has been paid to its psychological impact. Methods: This research compared the efficacy of group cognitive-behavioural therapy (CBT) and group personcentred therapy with respect to ameliorating the disabling effects of the condition. Participants were randomly allocated to either the control group, the CBT treatment group or the person-centred treatment group. Participants underwent 8 consecutive weeks of therapy and psychological and physiological gains were recorded before therapy, after therapy and at 6 and 12-month follow-up. The study used a mixed factorial design for the questionnaire analysis. The independent factor was the three different experimental conditions; control, CBT and person-centred therapy and the repeated measures factor was assessment point; pre-treatment, post-treatment, 6-month follow-up and 12-month follow-up. Results: Unlike previous work with different psychotherapy formats, little psychosocial or physiological benefits were gained as a result of the two group therapy programmes. Conclusion: This research helps us to understand more fully the efficacy of psychological therapy with a vitiligo population and will help direct health professionals to the most appropriate format for future use.
Praxeology ‐ a cybernetic application

To make decisions has long been considered an art more than a science. Today the area has been formalized under the name of praxeology and includes the use of computers as decision aids. In this paper some basic decision models are analysed together with some psychological phenomena often connected to them. Managerial problems and needs are examined and related to available computer decision support. The military command, control, communication, and intelligence structure is presented and compared to the corresponding civilian framework. The conclusion was that computer support in decision making now is firmly established among middle level decision makers. Top level managers, on the other hand, were found to derive no major benefit from such systems. Here good intuition, good guesses and a certain feeling for the task were the most important tools.
MathOptimizer : A nonlinear optimization package for Mathematica users

Mathematica is an advanced software system that enables symbolic computing, numerics, program code development, model visualization and professional documentation in a unified framework. Our MathOptimizer software package serves to solve global and local optimization models developed using Mathematica . We introduce MathOptimizer ’s key features and discuss its usage options that support a range of operational modes. The numerical capabilities of the package are illustrated by simple and more advanced examples, pointing towards a broad range of potential applications.
A comprehensive part model and graphical schema representation for object-oriented databases

Part-whole modeling plays an important role in the development of database schemata in data-intensive application domains such as manufacturing, design, computer graphics, text document processing, and so on. Object-oriented databases (OODBs) have been targeted for use in such areas. Thus, it is essential that OODBs incorporate a part relationship as one of their modeling primitives. In this dissertation, we present a comprehensive OODB part model which expands the boundaries of OODB part-whole modeling along three fronts. First, it identifies and codifies new semantics for the OODB part relationship. Second, it provides two novel realizations for part relationships and their associated modeling constructs in the context of OODB data models. Third, it provides an extensive graphical notation for the development of OODB schemata. The heart of the part model is a part relationship that imposes part-whole interaction on the instances of an OODB. The part relationship is divided into four characteristic dimensions: (1) exclusive/shared, (2) cardinality/ordinality, (3) dependency, and (4) value propagation. The latter forms the basis for the definition of derived attributes in a part hierarchy. To demonstrate the viability of our part model, we present two novel realizations for it in the context of existing OODBs. The first realizes the part relationship as an object class and utilizes only a basic set of OODB constructs. The second realization, an implementation of which is described in this dissertation, uses the unique metaclass mechanism of the VODAK Model Language (VML). This implementation shows that our part model can be incorporated into an existing OODB without having to rewrite a substantial subsystem of the OODB, and it also shows that the VML metaclass facility can indeed support extensions in terms of new semantic relationships. To facilitate the creation of part-whole schemata, we introduce an extensive graphical notation for the part relationship and its associated constructs. This notation complements our more general OODB graphical schema representation which includes symbols for classes, attributes, methods, and a variety of relationships. OO-dini, a graphical schema editor that employs our notation and supports conversion of the graphical schema into textual formats, is also discussed.
Design of a Biped Robot Capable of Dynamic Maneuvers

High-speed, dynamic maneuvers, such as running, jumping, and turning, allow humans and animals to adapt naturally to their surroundings. Biped robots could take full advantage of their legged mobility by executing these dynamic maneuvers for obstacle avoidance without sacrificing speed and stability. While there has been some research into dynamic maneuvers in robotics, the efforts are far from comprehensive. The objective of this thesis is to design an experimental biped robot that can be used to evaluate and validate different control approaches for performing dynamic maneuvers, focusing specifically on running and jumping. The experimental biped, named KURMET, is a 5-degree-of-freedom (DOF) planar robot with two articulated legs and a torso. The hip and knee joints are each actuated with an identical series-elastic actuator (SEA), which uses a compliant element in series with a geared brushless dc motor to drive the joint. KURMET is constrained to the wall with a long boom that restricts motion to the sagittal plane. The control electronics and motor amplifiers are mounted on the top of the torso and connect to the off-board power supply with an umbilical cord. A simplified dynamic model of KURMET performing a jump maneuver was developed to aid in the biped design process. It is anticipated that optimizing the biped design for vertical jumping will produce a system capable of the large accelerations necessary to execute a wide range of dynamic maneuvers. A motor thermal model and an alternative SEA design equation were also developed for the design process. ii The biped model design variables, which define the system’s configuration and performance, were mapped to a set of five critical parameters that included the brushless dc motor, the gearbox, the motor amplifier, the spring constant, and the leg segment length. Each parameter set was evaluated by comparing the jump height and the normalized jump height results from the dynamic model among all the possible sets. The final selected parameter set consisted of the Maxon EC-30 powermax 200W motor, the AMC ZBDC12A 12-A motor amplifier, a gear ratio of 126:1, a leg segment length of 0.25 m, and a spring constant of 30 N·m/rad. KURMET’s component level design was broken into the major subsystems, which are the SEA mechanism, the thigh segment, the shank segment, and the torso. The SEA mechanism utilizes an innovative spiral torsion spring design and a unidirectional-SEA concept to achieve series-elasticity in a compact and efficient package. A novel foot design allows ground contact to be sensed by a momentary switch even in extreme off-axis loading conditions. Many of the components were designed using finite element techniques or classical stress equations. The final biped assembly has a total mass of 14.9 kg. A full support documentation package was developed for KURMET, including a bill of materials and assembly procedures, to aid in the system maintenance.
HVL evaluation of orthovoltage X-ray machine using EGSnrc code of simulation

Background: Making use of the orthovoltage machines in Radiotherapy, is one of the rouƟ ne methods for the treatment of the superficial lesions. In this study, an important determinant of X-ray quality, the HVL (Half Value Layer), has been evaluated. Materials and Methods: The HVLs of a orthovoltage X- ray machine in 120 and 180 kVp are measured, using an empirical method, in which the HVLs are derived from the absorpƟ on curves. The measured HVLs are compared with calculated (Monte Carlo simulaƟ on) HVLs. Using the BEAMDP code of simulaƟ on, the output spectra are obtained and employed for the measurement of the HVLs. Results: Comparing the calculated and measured HVL values, the results show that the highest and lowest differences between the two are 4.96% and 2.27%, respecƟ vely, which are, in fairly good agreement with those obtained in the former studies. Conclusion: This study shows that the EGSnrc simulaƟ on code is capable of being used for the extracƟ on of the quality indices for the superficial X-ray radiotherapy machines. It seems that, the menƟ oned code, with the menƟ oned experimental method, can be employed as a rouƟ ne clinical test tool for every superficial radiotherapy department.
Improvements on Fidge logical clocks

A logical clock mechanism has been developed for maintaining the partial ordering of events in distributed systems. The mechanism handles events in an ad hoc way and its comparison rule is not quite simple. Two major improvements on the mechanism are presented. General maintenance rules are developed to handle various kinds of interprocess events, and the comparison rule is simplified by maintaining the clocks with a new technique called two-phase update. These improvements make the logical clock mechanism more general and efficient for supporting distributed system development. <<ETX>>
Middleware for Next-generation Network Games

Middleware serves the varying needs of game genres and developers. This paper reviews major 3D game engines in the industry and discusses the functional decomposition of current game middleware. We also identify the requirements for middleware in game development processes. In particular, the paper proposes the design of a next-generation game middleware for massively multiplayer online games based on service- oriented peer-to-peer (P2P) networks, which facilitates data and resource sharing in heterogeneous P2P networks.
Deep neural models to represent news events

The thesis is dedicated to the background linking tasks for news articles, utilizing the deep neural network models. The goal is to retrieve similar articles based on the news story currently viewed. We examined neural and non-neural representations for raw text and discussed notions of similarity a good model should identify and retrieve. We covered various deep neural network models and highlighted their advantages and disadvantages. Inspired by deep neural architectures in the area of Information Retrieval we adjusted the Deep Semantic Similarity model to the background linking task. Our refactored DSSM architecture employs a convolutional neural network with multiple filters and regularization techniques. This convolutional network acts as an auto-encoder and learns the compressed representations of news articles and news stories. Cosine similarity is used as the proximity metric to retrieve related news articles. Experimental results prove that our adjusted DSSM model is applicable for the background linking task, and overperforms the baseline SVM model. We discovered that corpora distributions affect the performance of the model. A model trained on news corpus containing mostly political and social news will perform poorly on news corpus about sport and entertainment news. Grid search and hyperparameter tuning are also important. Deep neural network architectures are powerful tools which can be used to solve complicated tasks and approximate nearly any function. Having a good quality dataset is half of the success. The DSSM model is planned to be adjusted to various news corpora and applied to different tasks; such as automatic linking of news articles to Wikipedia pages and linking news articles to news events. We assume this model can be extended to learn representations of a sequence of events for the task of linking background events.
Comprehensive Care: A Daily Challenge for Family Physicians

"Comprehensive care: The availability of a wide range of services in and their appropriate provision across the entire spectrum of types of needs for all but the most uncommon problems in the population [5]. " According to the WONCA Europe definition, "a comprehensive approach includes the ability to manage multiple complaints and pathologies simultaneously, promote health and well-being by applying disease prevention strategies appropriately and manage and coordinate health promotion, prevention, cure, care, palliation, and rehabilitation [6]. "
A JIT Algorithm for Offshore Rig Assembly Sequencing

Lean principles in production are synonymous with the Toyota motor company, probably the most productive and innovative car manufacturer in the world. However, in a construction environment Lean principles are not so easy or obvious. The major difference between a production and a construction environment is the synchronicity of the work and the longer time horizons. In the production environment the product stages are often short, whereas in the construction environment they are long. Constructing offshore rigs is a long process involving many stages where the correct assembly sequence is paramount. Offshore rigs are composed of units, referred to a blocks. The building of the block involves sub-blocks; each sub-block differs in size, shape and construction time. At the block level, with more than one team of workers constructing the sub-blocks, it is possible to apply Lean principles to the sub-block work so that they arrive at the block assembly point with the minimum of waiting time. A number of Greedy based sequencing algorithms have been developed by way of a compare and contrast. The Greedy sequencing algorithm augmented with back-tracking coupled with post schedule allocation reordering has proved to be a good one within the bounds of the random nature of the data.
Bidirectional Smart Net-Meter

Now a day’s the gap between energy generation and demand is increasing. To overcome this problem, the use of generation of energy from renewable sources will satisfy the consumers need. This system also helps to reduce monthly energy bill and also generate error free bill. In this paper, we are using energy which is generated by renewable energy sources and whatever surplus energy is export to the grid. This will reduce the monthly energy bill of consumer by crediting the exported energy charges. The proposed bidirectional smart net metering consists of voltage and current measurement circuit. This measures the instantaneous voltage and current respectively. Then aurdino calculates the net energy by using measured values of voltage and current also the net output energy displayed through LCD. This is interfaced with aurdino at regular interval. Experimental result shows the accuracy in calculating the net energy of system.
IoT Structured Long-Term Wearable Social Sensing for Mental Wellbeing

Long-term wellbeing monitoring is an underlying theme for evaluating health status by collecting physiological signs through behavioral traits. In alignment with Internet of Things (IoT), nonintrusive and trustworthy wearable social sensing technology holds a potential way for researchers to find and establish the interrelationships between unobtrusive social cues and physical mental health. This paper implements an IoT structured wearable social sensing platform with the integration of privacy audio feature, behavior monitoring, and environment sensing in a naturalistic environment. Particularly, four privacy protected audio-wellbeing features are embedded into the platform to automatically evaluate speech information without preserving raw audio data. Four weeks of long-term monitoring experimental studies have been conducted. A series of well-being questionnaires in conjunction with a group of students are engaged to objectively investigate the relationships between physical and mental health by utilizing the feature fusion strategy from speech, behavioral activities, and ambient factors.
Investigation of the Relation between Emotional State and Acoustic Parameters in the Context of Language

Acoustic analysis is the most basic method used for speech emotion recognition. Speech records are digitized by signal processing methods, and various acoustic features of speech are obtained by acoustic analysis methods. The relationship between acoustic features and emotion has been investigated in many studies. However, studies have mostly focused on emotion recognition success or the effects of emotions on acoustic features. The effect of spoken language on speech emotion recognition has been investigated in a limited number. The purpose of this study is to investigate the variability of the relationship between acoustic features and emotions according to the spoken language. For this purpose, three emotions (anger, fear and neutral) of three different spoken languages (English, German and Italian) were used. In these data sets, the change in acoustic features according to spoken language was investigated statistically. According to the results obtained, the effect of anger on the acoustic features does not change according to the spoken language. For fear, change in spoken language shows a high similarity in Italian and German, but low similarity in English.