Intelligent tutoring system for distance education

This study aims to develop and implement a tool called intelligent tutoring system in an online course to help a formative evaluation in order to improve student learning. According to Bloom et al. (1971,117) formative evaluation is a systematic evaluation to improve the process of teaching and learning. The intelligent tutoring system may provide a timely and high quality feedback that not only informs the correctness of the solution to the problem, but also informs students about the accuracy of the response relative to their current knowledge about the solution. Constructive and supportive feedback should be given to students to reveal the right and wrong answers immediately after taking the test. Feedback about the right answers is a form to reinforce positive behaviors. Identifying possible errors and relating them to the instructional material may help student to strengthen the content under consideration. The remedial suggestion should be given in each answer with detaileddescription with regards the materials and instructional procedures before taking next step. The main idea is to inform students about what they have learned and what they still have to learn. The open-source LMS called Moodle was extended to accomplish the formative evaluation, high-quality feedback, and the communal knowledge presented here with a short online financial math course that is being offered at a large University in Brazil. The preliminary results shows that the intelligent tutoring system using high quality feedback helped students to improve their knowledge about the solution to the problems based on the errors of their past cohorts. The results and suggestion for future work are presented and discussed.

Progettazione e Implementazione di un modulo di Power Management per Smart Environments

Progettazione ed implementazione di un modulo che gestisca il consumo di energia in uno Smart Environment, contestualizzato nell'ambito di un progetto europeo, SOFIA (Smart Object For Intelligent Applications), che ambisce ad accelerare l'integrazione di oggetti intelligenti nella vita quotidiana. Il consumo energetico da gestire e' quello di una rete di sensori; e' stato dimostrato che, riducendo le trasmissioni di dati tra sensori ed il resto della rete, le batterie durano quasi il doppio del tempo e, di conseguenza, la vita della rete e' raddoppiata, con vantaggi evidenti per l'ambiente.

Modeling systems and vis/NIR device to improve peach and nectarine pre and post-harvest fruit maturity management

During the last decade peach and nectarine fruit have lost considerable market share, due to increased consumer dissatisfaction with quality at retail markets. This is mainly due to harvesting of too immature fruit and high ripening heterogeneity. The main problem is that the traditional used maturity indexes are not able to objectively detect fruit maturity stage, neither the variability present in the field, leading to a difficult post-harvest management of the product and to high fruit losses. To assess more precisely the fruit ripening other techniques and devices can be used. Recently, a new non-destructive maturity index, based on the vis-NIR technology, the Index of Absorbance Difference (IAD), that correlates with fruit degreening and ethylene production, was introduced and the IAD was used to study peach and nectarine fruit ripening from the “field to the fork”. In order to choose the best techniques to improve fruit quality, a detailed description of the tree structure, of fruit distribution and ripening evolution on the tree was faced. More in details, an architectural model (PlantToon®) was used to design the tree structure and the IAD was applied to characterize the maturity stage of each fruit. Their combined use provided an objective and precise evaluation of the fruit ripening variability, related to different training systems, crop load, fruit exposure and internal temperature. Based on simple field assessment of fruit maturity (as IAD) and growth, a model for an early prediction of harvest date and yield, was developed and validated. The relationship between the non-destructive maturity IAD, and the fruit shelf-life, was also confirmed. Finally the obtained results were validated by consumer test: the fruit sorted in different maturity classes obtained a different consumer acceptance. The improved knowledge, leaded to an innovative management of peach and nectarine fruit, from “field to market”.

HIV-1 coreceptor usage and CXCR4-specific viral load predict clinical disease progression during combination antiretroviral therapy

BACKGROUND: Although combination antiretroviral therapy (cART) dramatically reduces rates of AIDS and death, a minority of patients experience clinical disease progression during treatment. OBJECTIVE: To investigate whether detection of CXCR4(X4)-specific strains or quantification of X4-specific HIV-1 load predict clinical outcome. METHODS: From the Swiss HIV Cohort Study, 96 participants who initiated cART yet subsequently progressed to AIDS or death were compared with 84 contemporaneous, treated nonprogressors. A sensitive heteroduplex tracking assay was developed to quantify plasma X4 and CCR5 variants and resolve HIV-1 load into coreceptor-specific components. Measurements were analyzed as cofactors of progression in multivariable Cox models adjusted for concurrent CD4 cell count and total viral load, applying inverse probability weights to adjust for sampling bias. RESULTS: Patients with X4 variants at baseline displayed reduced CD4 cell responses compared with those without X4 strains (40 versus 82 cells/microl; P = 0.012). The adjusted multivariable hazard ratio (HR) for clinical progression was 4.8 [95% confidence interval (CI) 2.3-10.0] for those demonstrating X4 strains at baseline. The X4-specific HIV-1 load was a similarly independent predictor, with HR values of 3.7 (95% CI, 1.2-11.3) and 5.9 (95% CI, 2.2-15.0) for baseline loads of 2.2-4.3 and > 4.3 log10 copies/ml, respectively, compared with < 2.2 log10 copies/ml. CONCLUSIONS: HIV-1 coreceptor usage and X4-specific viral loads strongly predicted disease progression during cART, independent of and in addition to CD4 cell count or total viral load. Detection and quantification of X4 strains promise to be clinically useful biomarkers to guide patient management and study HIV-1 pathogenesis.

Ecological study of the predictors of successful management of dyslipidemia in HIV-infected patients on ART: the Swiss HIV Cohort Study

PURPOSE: Antiretroviral therapy (ART) may induce metabolic changes and increase the risk of coronary heart disease (CHD). Based on a health care system approach, we investigated predictors for normalization of dyslipidemia in HIV-infected individuals receiving ART. METHOD: Individuals included in the study were registered in the Swiss HIV Cohort Study (SHCS), had dyslipidemia but were not on lipid-lowering medication, were on potent ART for >or= 3 months, and had >or= 2 follow-up visits. Dyslipidemia was defined as two consecutive total cholesterol (TC) values above recommended levels. Predictors of achieving treatment goals for TC were assessed using Cox models. RESULTS: Analysis included 958 individuals with median followup of 2.3 years (IQR 1.2-4.0). 454 patients (47.4%) achieved TC treatment goals. In adjusted analyses, variables significantly associated with a lower hazard of reaching TC treatment goals were as follows: older age (compared to 18-37 year olds: hazard ratio [HR] 0.62 for 45-52 year olds, 95% CI 0.47-0.82; HR 0.40 for 53-85, 95% CI 0.29-0.54), diabetes (HR 0.39, 95% CI 0.26-0.59), history of coronary heart disease (HR 0.27, 95% CI 0.10-0.71), higher baseline TC (HR 0.78, 95% CI 0.71-0.85), baseline triple nucleoside regimen (HR 0.12 compared to PI-only regimen, 95% CI 0.07-0.21), longer time on PI-only regimen (HR 0.39, 95% CI 0.33-0.46), longer time on NNRTI only regimen (HR 0.35, 95% CI 0.29-0.43), and longer time on PI/NNRTI regimen (HR 0.34, 95% CI 0.26-0.43). Switching ART regimen when viral load was undetectable was associated with a higher hazard of reaching TC treatment goals (HR 1.48, 95% CI 1.14-1.91). CONCLUSION: In SHCS participants on ART, several ART-related and not ART-related epidemiological factors were associated with insufficient control of dyslipidemia. Control of dyslipidemia in ART recipients must be further improved.

A Communication Platform for Tele-monitoring and Tele-management of Type 1 Diabetes

Type 1 diabetes mellitus is a chronic disease characterized by blood glucose levels out of normal range due to inability of insulin production. This dysfunction leads to many short- and long-term complications. In this paper, a system for tele-monitoring and tele-management of Type 1 diabetes patients is proposed, aiming at reducing the risk of diabetes complications and improving quality of life. The system integrates Wireless Personal Area Networks (WPAN), mobile infrastructure, and Internet technology along with commercially available and novel glucose measurement devices, advanced modeling techniques, and tools for the intelligent processing of the available diabetes patients information. The integration of the above technologies enables intensive monitoring of blood glucose levels, treatment optimisation, continuous medical care, and improvement of quality of life for Type 1 diabetes patients, without restrictions in everyday life activities.

Learning software-maintenance tasks in offshoring projects: a cognitive-load perspective

Individual learning is central to the success of the transition phase in software mainte-nance offshoring projects. However, little is known on how learning activities, such as on-the-job training and formal presentations, are effectively combined during the tran-sition phase. In this study, we present and test propositions derived from cognitive load theory. The results of a multiple-case study suggest that learning effectiveness was highest when learning tasks such as authentic maintenance requests were used. Con-sistent with cognitive load theory, learning tasks were most effective when they imposed moderate cognitive load. Our data indicate that cognitive load was influenced by the expertise of the onsite coordinator, by intrinsic task complexity, by the degree of specifi-cation of tasks, and by supportive information. Cultural and semantic distances may in-fluence learning by inhibiting supportive information, specification, and the assignment of learning tasks.

Semantic Methods for Intelligent Distributed Design Environments

Continuous advancements in technology have led to increasingly comprehensive and distributed product development processes while in pursuit of improved products at reduced costs. Information associated with these products is ever changing, and structured frameworks have become integral to managing such fluid information. Ontologies and the Semantic Web have emerged as key alternatives for capturing product knowledge in both a human-readable and computable manner. The primary and conclusive focus of this research is to characterize relationships formed within methodically developed distributed design knowledge frameworks to ultimately provide a pervasive real-time awareness in distributed design processes. Utilizing formal logics in the form of the Semantic Web’s OWL and SWRL, causal relationships are expressed to guide and facilitate knowledge acquisition as well as identify contradictions between knowledge in a knowledge base. To improve the efficiency during both the development and operational phases of these “intelligent” frameworks, a semantic relatedness algorithm is designed specifically to identify and rank underlying relationships within product development processes. After reviewing several semantic relatedness measures, three techniques, including a novel meronomic technique, are combined to create AIERO, the Algorithm for Identifying Engineering Relationships in Ontologies. In determining its applicability and accuracy, AIERO was applied to three separate, independently developed ontologies. The results indicate AIERO is capable of consistently returning relatedness values one would intuitively expect. To assess the effectiveness of AIERO in exposing underlying causal relationships across product development platforms, a case study involving the development of an industry-inspired printed circuit board (PCB) is presented. After instantiating the PCB knowledge base and developing an initial set of rules, FIDOE, the Framework for Intelligent Distributed Ontologies in Engineering, was employed to identify additional causal relationships through extensional relatedness measurements. In a conclusive PCB redesign, the resulting “intelligent” framework demonstrates its ability to pass values between instances, identify inconsistencies amongst instantiated knowledge, and identify conflicting values within product development frameworks. The results highlight how the introduced semantic methods can enhance the current knowledge acquisition, knowledge management, and knowledge validation capabilities of traditional knowledge bases.

A survey of paediatric HIV programmatic and clinical management practices in Asia and sub-Saharan Africa--the International epidemiologic Databases to Evaluate AIDS (IeDEA)

INTRODUCTION There are limited data on paediatric HIV care and treatment programmes in low-resource settings. METHODS A standardized survey was completed by International epidemiologic Databases to Evaluate AIDS paediatric cohort sites in the regions of Asia-Pacific (AP), Central Africa (CA), East Africa (EA), Southern Africa (SA) and West Africa (WA) to understand operational resource availability and paediatric management practices. Data were collected through January 2010 using a secure, web-based software program (REDCap). RESULTS A total of 64,552 children were under care at 63 clinics (AP, N=10; CA, N=4; EA, N=29; SA, N=10; WA, N=10). Most were in urban settings (N=41, 65%) and received funding from governments (N=51, 81%), PEPFAR (N=34, 54%), and/or the Global Fund (N=15, 24%). The majority were combined adult-paediatric clinics (N=36, 57%). Prevention of mother-to-child transmission was integrated at 35 (56%) sites; 89% (N=56) had access to DNA PCR for infant diagnosis. African (N=40/53) but not Asian sites recommended exclusive breastfeeding up until 4-6 months. Regular laboratory monitoring included CD4 (N=60, 95%), and viral load (N=24, 38%). Although 42 (67%) sites had the ability to conduct acid-fast bacilli (AFB) smears, 23 (37%) sites could conduct AFB cultures and 18 (29%) sites could conduct tuberculosis drug susceptibility testing. Loss to follow-up was defined as >3 months of lost contact for 25 (40%) sites, >6 months for 27 sites (43%) and >12 months for 6 sites (10%). Telephone calls (N=52, 83%) and outreach worker home visits to trace children lost to follow-up (N=45, 71%) were common. CONCLUSIONS In general, there was a high level of patient and laboratory monitoring within this multiregional paediatric cohort consortium that will facilitate detailed observational research studies. Practices will continue to be monitored as the WHO/UNAIDS Treatment 2.0 framework is implemented.

Fuzzy Web Knowledge Aggregation, Representation, and Reasoning for Online Privacy and Reputation Management

A social Semantic Web empowers its users to have access to collective Web knowledge in a simple manner, and for that reason, controlling online privacy and reputation becomes increasingly important, and must be taken seriously. This chapter presents Fuzzy Cognitive Maps (FCM) as a vehicle for Web knowledge aggregation, representation, and reasoning. With this in mind, a conceptual framework for Web knowledge aggregation, representation, and reasoning is introduced along with a use case, in which the importance of investigative searching for online privacy and reputation is highlighted. Thereby it is demonstrated how a user can establish a positive online presence.

A Conceptual Model to Combine Creativity Techniques with Fuzzy Cognitive Maps for Enhanced Knowledge Management

This chapter introduces a conceptual model to combine creativity techniques with fuzzy cognitive maps (FCMs) and aims to support knowledge management methods by improving expert knowledge acquisition and aggregation. The aim of the conceptual model is to represent acquired knowledge in a manner that is as computer-understandable as possible with the intention of developing automated reasoning in the future as part of intelligent information systems. The formal represented knowledge thus may provide businesses with intelligent information integration. To this end, we introduce and evaluate various creativity techniques with a list of attributes to define the most suitable to combine with FCMs. This proposed combination enables enhanced knowledge management through the acquisition and representation of expert knowledge with FCMs. Our evaluation indicates that the creativity technique known as mind mapping is the most suitable technique in our set. Finally, a scenario from stakeholder management demonstrates the combination of mind mapping with FCMs as an integrated system.

Relating goal scheduling, precedence, and memory management in and-parallel execution of logic programs

The interactions among three important issues involved in the implementation of logic programs in parallel (goal scheduling, precedence, and memory management) are discussed. A simplified, parallel memory management model and an efficient, load-balancing goal scheduling strategy are presented. It is shown how, for systems which support "don't know" non-determinism, special care has to be taken during goal scheduling if the space recovery characteristics of sequential systems are to be preserved. A solution based on selecting only "newer" goals for execution is described, and an algorithm is proposed for efficiently maintaining and determining precedence relationships and variable ages across parallel goals. It is argued that the proposed schemes and algorithms make it possible to extend the storage performance of sequential systems to parallel execution without the considerable overhead previously associated with it. The results are applicable to a wide class of parallel and coroutining systems, and they represent an efficient alternative to "all heap" or "spaghetti stack" allocation models.

Efficient management of backtracking in and-parallelism

A backtracking algorithm for AND-Parallelism and its implementation at the Abstract Machine level are presented: first, a class of AND-Parallelism models based on goal independence is defined, and a generalized version of Restricted AND-Parallelism (RAP) introduced as characteristic of this class. A simple and efficient backtracking algorithm for R A P is then discussed. An implementation scheme is presented for this algorithm which offers minimum overhead, while retaining the performance and storage economy of sequent ial implementations and taking advantage of goal independence to avoid unnecessary backtracking ("restricted intelligent backtracking"). Finally, the implementation of backtracking in sequential and AND-Parallcl systems is explained through a number of examples.

Energy- and environmentally efficient road management: The case of the Spanish motorway network

Transport is responsible for 41% of CO2 emissions in Spain, and around 65% of that figure is due to road traffic. Tolled motorways are currently managed according to economic criteria: minimizing operational costs and maximizing revenues from tolls. Within this framework, this paper develops a new methodology for managing motorways based on a target of maximum energy efficiency. It includes technological and demand-driven policies, which are applied to two case studies. Various conclusions emerge from this study. One is, that the use of intelligent payment systems is recommended; and another, is that the most sustainable policy would involve defining the most efficient strategy for each motorway section, including the maximum use of its capacity, the toll level which attracts the most vehicles, and the optimum speed limit for each type of vehicle.