Abstract-A well balanced dataset is very important for creating a good prediction model. Medical datasets are often not balanced in their class labels. Most existing classification methods tend to perform poorly on minority class examples when the dataset is extremely imbalanced. This is because they aim to optimize the overall accuracy without considering the relative distribution of each class. In this paper we examine the performance of over-sampling and under-sampling techniques to balance cardiovascular data. Well known over-sampling technique SMOTE is used and some under-sampling techniques are also explored. An improved under sampling technique is proposed. Experimental results show that the proposed method displays significant better performance than the existing methods.

A telemedicine model enables timely access to surgical care and permits considerable savings among select VHA patients with head and neck cancer. © 2016 Wiley Periodicals, Inc. Head Neck 38: 925-929, 2016.

As a widely known chronic disease, diabetes mellitus is called a silent killer. It makes the body produce less insulin and causes increased blood sugar, which leads to many complications and affects the normal functioning of various organs, such as eyes, kidneys, and nerves. Although diabetes has attracted high attention in research, due to the existence of missing values and class imbalance in the data, the overall performance of diabetes classification using machine learning is relatively low. In this paper, we propose an effective Prediction algorithm for Diabetes Mellitus classification on Imbalanced data with Missing values (DMP_MI). First, the missing values are compensated by the Naïve Bayes (NB) method for data normalization. Then, an adaptive synthetic sampling method (ADASYN) is adopted to reduce the influence of class imbalance on the prediction performance. Finally, a random forest (RF) classifier is used to generate predictions and evaluated using comprehensive set of evaluation indicators. Experiments performed on Pima Indians diabetes dataset from the University of California at Irvine, Irvine (UCI) Repository, have demonstrated the effectiveness and superiority of our proposed DMP_MI.

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This paper presents a developing concept of mind defined in terms of external and internal niches. This perspective on mind is described primarily in terms of the niche space of control states and the design space of processes that may support such phenomena. A developing agent architecture, that can support motivation and other control states associated with mind, is presented. Different aspects of agent research are discussed in terms of three categories of agents. Each agent category is characterized primarily in terms of their task-related competencies and internal behaviors and discussed in terms of our taxonomy of control states. The concept of complete agents is then introduced. Goals are described in terms of their generation across a number of computational layers. Experimental analysis is provided on how these differing forms of behaviors can be cleanly integrated. This leads into a discussion on the nature of motivational states and the mechanisms used for making decisions and managing the sometimes-competitive nature of processes internal to a complex agent. The difficulty of evaluating complete agents is discussed from a number of perspectives. The paper concludes by considering future directions related to the computational modeling of emotions and the concept of synthetic mind.

This study compares the results of cephalometric analyses using manual and interactive computer graphics methods. Results are statistically in favour of the interactive computer system. This study provides a basis for ongoing research into alternative methods of cephalometric analyses. such as digitization and automatic landmark identification using sophisticated computer vision systems.

Motivation is a central concept in the development of autonomous agents and robots. This paper describes an architecture that uses a psychological BDI model of reasoning, combined with a distributed multi-level model of motivation. The robot controlling architecture makes use of a generic set of deliberative components plus an environment task-centred set of reactive components that reflect the architecture's embodiment. The architecture has been used in a number of simulated environments and here is used to control a mobile robot. A theoretical framework for motivation and affect is given, and related to the nature of autonomy and embodiment. A BDI model, based on a psychological model of reasoning in a 5 year old child, is described in terms of the nature of motivation and affect within the architecture. Finally, criteria for judging the nature of an agent's motivation are introduced, and used to validate the motivational constructs implemented within the architecture. Experimental results lead to a comparative discussion.

The design of coordination sites around lanthanide ions has a strong impact on the sensitization of their luminescent signal. An imidodiphosphonate anionic binding site is attractive as it can be functionalized with "remote" sensitizer units, such as phenoxy moieties, namely, HtpOp, accompanied by an increased distance of the lanthanide from the ligand high-energy stretching vibrations which quench the luminescence signal, hence providing flexible shielding of the lanthanide. We report the formation and isolation of Ln(tpOp)3 complexes where Ln = Er, Gd, Tb, Dy, Eu, and Yb and the Y(tpOp)3 diamagnetic analogue. The complexes are formed from reaction of KtpOp and the corresponding LnCl3•6H2O salt either by titration and in situ formation or by mixing and isolation. All complexes are seven-coordinated by three tpOp ligand plus one ethanol molecule, except for Yb(tpOp)3 which has no solvent coordinated. Phosphorus NMR shows characteristic shifts to support the coordination of the lanthanide complexes. The complexes display visible and near-infrared luminescence with long lifetimes even for the near-infrared complexes which range from 3.3 μs for Nd(tpOp)3 to 20 μs for Yb(tpOp)3. The ligand shows more efficient sensitization than the imidodiphosphinate analogues for all lanthanide complexes with a notable quantum yield of the Tb(tpOp)3 complex at 45%. We attribute this to the properties of the remote sensitizer unit and its positioning further away from the lanthanide, eliminating quenching of high energy C−H vibrations from the ligand shell. Calculations of the ligand shielding support the photophysical properties of the complexes. These results suggest that these binding sites are promising in the further development of the lanthanide complexes in optoelectronic devices for telecommunications and new light emitting materials.