The Application of Graph Model for Automation of the User Interface Construction

The ability of automatic graphic user interface construction is described. It is based on the building of user interface as reflection of the data domain logical definition. The submitted approach to development of the information system user interface enables dynamic adaptation of the system during their operation. This approach is used for creation of information systems based on CASE-system METAS.

Progmosis:evaluating risky individual behavior during epidemics using mobile network data

The possibility to analyze, quantify and forecast epidemic outbreaks is fundamental when devising effective disease containment strategies. Policy makers are faced with the intricate task of drafting realistically implementable policies that strike a balance between risk management and cost. Two major techniques policy makers have at their disposal are: epidemic modeling and contact tracing. Models are used to forecast the evolution of the epidemic both globally and regionally, while contact tracing is used to reconstruct the chain of people who have been potentially infected, so that they can be tested, isolated and treated immediately. However, both techniques might provide limited information, especially during an already advanced crisis when the need for action is urgent. In this paper we propose an alternative approach that goes beyond epidemic modeling and contact tracing, and leverages behavioral data generated by mobile carrier networks to evaluate contagion risk on a per-user basis. The individual risk represents the loss incurred by not isolating or treating a specific person, both in terms of how likely it is for this person to spread the disease as well as how many secondary infections it will cause. To this aim, we develop a model, named Progmosis, which quantifies this risk based on movement and regional aggregated statistics about infection rates. We develop and release an open-source tool that calculates this risk based on cellular network events. We simulate a realistic epidemic scenarios, based on an Ebola virus outbreak; we find that gradually restricting the mobility of a subset of individuals reduces the number of infected people after 30 days by 24%.

Learning user and product distributed representations using a sequence model for sentiment analysis

In product reviews, it is observed that the distribution of polarity ratings over reviews written by different users or evaluated based on different products are often skewed in the real world. As such, incorporating user and product information would be helpful for the task of sentiment classification of reviews. However, existing approaches ignored the temporal nature of reviews posted by the same user or evaluated on the same product. We argue that the temporal relations of reviews might be potentially useful for learning user and product embedding and thus propose employing a sequence model to embed these temporal relations into user and product representations so as to improve the performance of document-level sentiment analysis. Specifically, we first learn a distributed representation of each review by a one-dimensional convolutional neural network. Then, taking these representations as pretrained vectors, we use a recurrent neural network with gated recurrent units to learn distributed representations of users and products. Finally, we feed the user, product and review representations into a machine learning classifier for sentiment classification. Our approach has been evaluated on three large-scale review datasets from the IMDB and Yelp. Experimental results show that: (1) sequence modeling for the purposes of distributed user and product representation learning can improve the performance of document-level sentiment classification; (2) the proposed approach achieves state-of-The-Art results on these benchmark datasets.

A magyar hallgatók vállalkozásindító szándékát befolyásoló tényezők modellje - Ajzen tervezett magatartás elméletének kiterjesztése (Model of the Hungarian students’ business start-up intention influencing factors – Extending of Ajzen’s Theory of Planned Behavior)

A vállalkozási tevékenység a munkahelyteremtés és a gazdasági növekedés egyik döntő tényezője. Ennek a jövőbeli kedvező alakulását a fiatalok mai attitűdjei határozzák meg. Ha be tudjuk azonosítani a legfontosabb tényezőket, amelyek a fiatalok vállalkozásindítási szándékát befolyásolják, el tudjuk dönteni azt is, mely területen lehet és érdemes beavatkozni annak érdekében, hogy minél több új, életképes vállalkozás szülessen. A cikk a GUESSS kutatási projekt magyarországi adatbázisának köszönhetően közel 6000 hallgató válaszait elemezve rendszerezi a felsőoktatásban résztvevők vállalkozásindítási szándékára ható legfontosabb tényezőcsoportokat. Első lépésben Ajzen tervezett magatartás elméletének alkalmazásával vizsgálja a vállalkozásindítási szándék alakítóit, majd további tényezők, így a felsőoktatási intézmények által nyújtott szolgáltatások, a családi háttér és a demográfiai jellemzők bevonásával igyekszik minél pontosabban leírni a szándék alakulását. _____ Entrepreneurial activity is a decisive factor in the dynamics of job creation and economic growth. The future level of this activity highly depends on the attitudes of today’s youth towards this. If the most important factors influencing attitudes are identified and the entrepreneurial intentions towards entrepreneurship are determined, the fields of intervention targeting the creation of as many new and viable enterprises as possible can be defined. This article aims to systematise the most important factor groups that influence the decisions of students studying in higher education in terms of start-up activities and is based on the Hungarian database of the GUESSS research project, containing almost 6000 respondents. Firstly, it tests Ajzen’s Theory of Planned Behavior. Then such factors as supportive services provided by higher education institutions, family background and demographic factors are analysed in order to improve the explanatory power of the model.

The effects of attribute quality information and sources of information on consumers' perceptions and behavior: A model of Pre-purchase Information Utilization in Service Physical Environments

The search-experience-credence framework from economics of information, the human-environment relations models from environmental psychology, and the consumer evaluation process from services marketing provide a conceptual basis for testing the model of "Pre-purchase Information Utilization in Service Physical Environments." The model addresses the effects of informational signs, as a dimension of the service physical environment, on consumers' perceptions (perceived veracity and perceived performance risk), emotions (pleasure) and behavior (willingness to buy). The informational signs provide attribute quality information (search and experience) through non-personal sources of information (simulated word-of-mouth and non-personal advocate sources).^ This dissertation examines: (1) the hypothesized relationships addressed in the model of "Pre-purchase Information Utilization in Service Physical Environments" among informational signs, perceived veracity, perceived performance risk, pleasure, and willingness to buy, and (2) the effects of attribute quality information and sources of information on consumers' perceived veracity and perceived performance risk.^ This research is the first in-depth study about the role and effects of information in service physical environments. Using a 2 x 2 between subjects experimental research procedure, undergraduate students were exposed to the informational signs in a simulated service physical environment. The service physical environments were simulated through color photographic slides.^ The results of the study suggest that: (1) the relationship between informational signs and willingness to buy is mediated by perceived veracity, perceived performance risk and pleasure, (2) experience attribute information shows higher perceived veracity and lower perceived performance risk when compared to search attribute information, and (3) information provided through simulated word-of-mouth shows higher perceived veracity and lower perceived performance risk when compared to information provided through non-personal advocate sources. ^

Investigation into a best practice model for providing an integrated user experience with mobile cloud applications

Mobile Cloud Computing promises to overcome the physical limitations of mobile devices by executing demanding mobile applications on cloud infrastructure. In practice, implementing this paradigm is difficult; network disconnection often occurs, bandwidth may be limited, and a large power draw is required from the battery, resulting in a poor user experience. This thesis presents a mobile cloud middleware solution, Context Aware Mobile Cloud Services (CAMCS), which provides cloudbased services to mobile devices, in a disconnected fashion. An integrated user experience is delivered by designing for anticipated network disconnection, and low data transfer requirements. CAMCS achieves this by means of the Cloud Personal Assistant (CPA); each user of CAMCS is assigned their own CPA, which can complete user-assigned tasks, received as descriptions from the mobile device, by using existing cloud services. Service execution is personalised to the user's situation with contextual data, and task execution results are stored with the CPA until the user can connect with his/her mobile device to obtain the results. Requirements for an integrated user experience are outlined, along with the design and implementation of CAMCS. The operation of CAMCS and CPAs with cloud-based services is presented, specifically in terms of service description, discovery, and task execution. The use of contextual awareness to personalise service discovery and service consumption to the user's situation is also presented. Resource management by CAMCS is also studied, and compared with existing solutions. Additional application models that can be provided by CAMCS are also presented. Evaluation is performed with CAMCS deployed on the Amazon EC2 cloud. The resource usage of the CAMCS Client, running on Android-based mobile devices, is also evaluated. A user study with volunteers using CAMCS on their own mobile devices is also presented. Results show that CAMCS meets the requirements outlined for an integrated user experience.

A Computer Model of Drafting Effects on Collective Behavior in Elite 10,000 m Runners

Purpose Drafting in cycling influences collective behaviour of pelotons. Whilst evidence for collective behaviour in competitive running events exists, it is not clear if this results from energetic savings conferred by drafting. This study modelled the effects of drafting on behavior in elite 10,000 m runners. Methods Using performance data from a men’s elite 10,000 m track running event, computer simulations were constructed using Netlogo 5.1 to test the effects of three different drafting quantities on collective behaviour: no drafting, drafting to 3m behind with up to ~8% energy savings (a realistic running draft); and drafting up to 3m behind with up to 38% energy savings (a realistic cycling draft). Three measures of collective behaviour were analysed in each condition; mean speed, mean group stretch (distance between first and last placed runner), and Runner Convergence Ratio (RCR) which represents the degree of drafting benefit obtained by the follower in a pair of coupled runners. Results Mean speeds were 6.32±0.28m.s-1, 5.57±0.18 m.s-1, and 5.51±0.13 m.s-1 in the cycling draft, runner draft, and no draft conditions respectively (all P<0.001). RCR was lower in the cycling draft condition, but did not differ between the other two. Mean stretch did not differ between conditions. Conclusions Collective behaviours observed in running events cannot be fully explained through energetic savings conferred by realistic drafting benefits. They may therefore result from other, possibly psychological, processes. The benefits or otherwise of engaging in such behavior are, as yet, unclear.

Transtheoretical model for behavior changes: an important tool when adopting active life

Despite the worship of beauty that has ruled this globalized society and the importance of physical activity for the prevention of cardio-degenerative diseases (US.DHHS, 1996), sedentary behavior continues to increase in the population.  What strategies can be used by professionals of human movement to make the population physically active? It is at this point where the Transtheoretical Model appears as an innovative option that greatly surpasses the classic short-term biological interventions, which have focused on momentary changes produced by physiological values.  This model has great potential since it offers the theoretical basis that makes the acquisition of an active behavior possible.  This article explains the theoretical basis of the transtheoretical model, including the way to assess the stages of change and to develop different strategies to make the person active by using behavioral processes and processes of change.

A NATURALISTIC COMPUTATIONAL MODEL OF HUMAN BEHAVIOR IN NAVIGATION AND SEARCH TASKS

Planning, navigation, and search are fundamental human cognitive abilities central to spatial problem solving in search and rescue, law enforcement, and military operations. Despite a wealth of literature concerning naturalistic spatial problem solving in animals, literature on naturalistic spatial problem solving in humans is comparatively lacking and generally conducted by separate camps among which there is little crosstalk. Addressing this deficiency will allow us to predict spatial decision making in operational environments, and understand the factors leading to those decisions. The present dissertation is comprised of two related efforts, (1) a set of empirical research studies intended to identify characteristics of planning, execution, and memory in naturalistic spatial problem solving tasks, and (2) a computational modeling effort to develop a model of naturalistic spatial problem solving. The results of the behavioral studies indicate that problem space hierarchical representations are linear in shape, and that human solutions are produced according to multiple optimization criteria. The Mixed Criteria Model presented in this dissertation accounts for global and local human performance in a traditional and naturalistic Traveling Salesman Problem. The results of the empirical and modeling efforts hold implications for basic and applied science in domains such as problem solving, operations research, human-computer interaction, and artificial intelligence.

Critical behavior in the site-diluted three-dimensional three-state Potts model

We have studied numerically the effect of quenched site dilution on a weak first-order phase transition in three dimensions. We have simulated the site diluted three-states Potts model studying in detail the secondorder region of its phase diagram. We have found that the n exponent is compatible with the one of the three-dimensional diluted Ising model, whereas the h exponent is definitely different.

A multiscale multisurface constitutive model for the thermo-plastic behavior of polyethylene

We present a multiscale model bridging length and time scales from molecular to continuum levels with the objective of predicting the yield behavior of amorphous glassy polyethylene (PE). Constitutive pa- rameters are obtained from molecular dynamics (MD) simulations, decreasing the requirement for ad- hoc experiments. Consequently, we achieve: (1) the identification of multisurface yield functions; (2) the high strain rate involved in MD simulations is upscaled to continuum via quasi-static simulations. Validation demonstrates that the entire multisurface yield functions can be scaled to quasi-static rates where the yield stresses are possibly predicted by a proposed scaling law; (3) a hierarchical multiscale model is constructed to predict temperature and strain rate dependent yield strength of the PE.

Biofilm And Saliva Affect The Biomechanical Behavior Of Dental Implants.

Friction coefficient (FC) was quantified between titanium-titanium (Ti-Ti) and titanium-zirconia (Ti-Zr), materials commonly used as abutment and implants, in the presence of a multispecies biofilm (Bf) or salivary pellicle (Pel). Furthermore, FC was used as a parameter to evaluate the biomechanical behavior of a single implant-supported restoration. Interface between Ti-Ti and Ti-Zr without Pel or Bf was used as control (Ctrl). FC was recorded using tribometer and analyzed by two-way Anova and Tukey test (p<0.05). Data were transposed to a finite element model of a dental implant-supported restoration. Models were obtained varying abutment material (Ti and Zr) and FCs recorded (Bf, Pel, and Ctrl). Maximum and shear stress were calculated for bone and equivalent von Misses for prosthetic components. Data were analyzed using two-way ANOVA (p<0.05) and percentage of contribution for each condition (material and FC) was calculated. FC significant differences were observed between Ti-Ti and Ti-Zr for Ctrl and Bf groups, with lower values for Ti-Zr (p<0.05). Within each material group, Ti-Ti differed between all treatments (p<0.05) and for Ti-Zr, only Pel showed higher values compared with Ctrl and Bf (p<0.05). FC contributed to 89.83% (p<0.05) of the stress in the screw, decreasing the stress when the FC was lower. FC resulted in an increase of 59.78% of maximum stress in cortical bone (p=0.05). It can be concluded that the shift of the FC due to the presence of Pel or Bf is able to jeopardize the biomechanical behavior of a single implant-supported restoration.

Keratoconus prediction using a finite element model of the cornea with local biomechanical properties

PURPOSE: The ability to predict and understand which biomechanical properties of the cornea are responsible for the stability or progression of keratoconus may be an important clinical and surgical tool for the eye-care professional. We have developed a finite element model of the cornea, that tries to predicts keratoconus-like behavior and its evolution based on material properties of the corneal tissue. METHODS: Corneal material properties were modeled using bibliographic data and corneal topography was based on literature values from a schematic eye model. Commercial software was used to simulate mechanical and surface properties when the cornea was subject to different local parameters, such as elasticity. RESULTS: The simulation has shown that, depending on the corneal initial surface shape, changes in local material properties and also different intraocular pressures values induce a localized protuberance and increase in curvature when compared to the remaining portion of the cornea. CONCLUSIONS: This technique provides a quantitative and accurate approach to the problem of understanding the biomechanical nature of keratoconus. The implemented model has shown that changes in local material properties of the cornea and intraocular pressure are intrinsically related to keratoconus pathology and its shape/curvature.