There is considerable evidence that a person’s gait is affected by cognitive load. Research in this field has implications for understanding the relationship between motor control and neurological conditions in aging and clinical populations. Accordingly, this pilot study evaluates the cognitive load based on gait accelerometry measurements of the walking patterns of ten healthy individuals (18–35 years old). Data points were collected using six triaxial accelerometer sensors and treadmill pressure reports. Stride and window extraction methods were used to process these data points and separate into statistical features. A binary classification was created by using logistic regression, support vector machine, random forest, and learning vector quantization to classify cognitive load vs. no cognitive load. Within and between subjects, a cognitive load was predicted with accuracy values ranged of 0.93–1 by all four models. Various feature selection methods demonstrated that only 2–20 variables could be used to achieve similar levels of accuracies. Coupling sensors with machine learning algorithms to detect the most minute changes in gait patterns, most of which are too subtle to identify with the human eye, may have a remarkable impact on the potential to detect potential neuromotor illnesses and fall risks. In doing so, we can open a new window to human health and safety prevention.

Sindrom profesionalnog sagorijevanja,kao psihološki sindrom, uveden jeu psihološku literaturu i klasifikacijskepreglede sedamdesetih godina prošlogstoljeća i od tada su izvršena brojnaistraživanja prisustva simptoma ovogsindroma u raznim pomažućim profesijama.Ovo empirijsko istraživanje bavise profesionalnim sagorijevanjem u nastavničkojprofesiji, a obuhvata mjerenjeizraženosti tri skupine simptoma:emocionalne iscrpljenosti (EE), depersonalizacije(DP) i osjećaja profesionalnekompetentnosti (PA). Istraživanje jeobavljeno na uzorku od 353 nastavnikaosnovnih i srednjih škola standardiziranimUpitnikom profesionalnog sago-rijevanja (MBI). Testiranje značajnostirazlika između aritmetičkih sredina ukupnogrezultata na svakoj od tri subskalevršena je s obzirom na spol, školskuspremu, vrstu posla, vrstu škole i godineradnog iskustva ispitanika, kao kriterijskevarijable. Ni po jednom od ovih kriterijanisu se pokazale značajnim razlikearitmetičkih sredina na skali PA, dokse statistički značajnom pokazala razlikana dimenziji EE jedino s obzirom navrstu nastave i godine radnog iskustva.Na dimenziji depersonalizacije (DP) pokazalase statistički značajnom razlikaaritmetičkih sredina po svakom od kriterijaosim s obzirom na radno iskustvoispitanika.

Severe hypoglycemia leverages complication in diabetes patients: e.g., it increases death rate by a six-fold. Therefore, early detection and prediction of hypoglycemic events are of utmost importance. This publication presents a prototype of a wearable hand-tremor system that detects the onset of hypoglycemic events. The results show the prototype is capable of simulating anticipated frequency and amplitude of the tremor relevant for hypoglycemic events. The initial functional performance-tests demonstrate a maximum error of 4.75% in the detecting the tremor frequency.

ABSTRACT The main purpose of the substations grounding systems is to ensure integrity of substations equipment and safety of personnel in and outside of substation at the maximum fault currents. To meet safety requirements, grounding system should have a low as possible resistance. In order to achieve low resistance, grounding systems are designed in a way to achieve as large as possible contact surface between the grounding system conductors and the surrounding soil. On the other hand, cost – efficiency of the proposed solution must be taken into account. Therefore, to meet the technical criteria on the one hand and economic criteria on the other hand, grounding systems are composed from large number of horizontal, vertical and inclined galvanic connected unisolated conductors that in most practical cases form complex geometries. Additionally, soil in which grounding systems are placed is almost always composed of a number of layers with different electric conductivity. In this paper, numerical model based on the indirect boundary element method is presented for calculation of grounding system parameters placed into the vertically layered soil.

In this paper, a new multi-criteria problem solving method—the Full Consistency Method (FUCOM)—is proposed. The model implies the definition of two groups of constraints that need to satisfy the optimal values of weight coefficients. The first group of constraints is the condition that the relations of the weight coefficients of criteria should be equal to the comparative priorities of the criteria. The second group of constraints is defined on the basis of the conditions of mathematical transitivity. After defining the constraints and solving the model, in addition to optimal weight values, a deviation from full consistency (DFC) is obtained. The degree of DFC is the deviation value of the obtained weight coefficients from the estimated comparative priorities of the criteria. In addition, DFC is also the reliability confirmation of the obtained weights of criteria. In order to illustrate the proposed model and evaluate its performance, FUCOM was tested on several numerical examples from the literature. The model validation was performed by comparing it with the other subjective models (the Best Worst Method (BWM) and Analytic Hierarchy Process (AHP)), based on the pairwise comparisons of the criteria and the validation of the results by using DFC. The results show that FUCOM provides better results than the BWM and AHP methods, when the relation between consistency and the required number of the comparisons of the criteria are taken into consideration. The main advantages of FUCOM in relation to the existing multi-criteria decision-making (MCDM) methods are as follows: (1) a significantly smaller number of pairwise comparisons (only n − 1), (2) a consistent pairwise comparison of criteria, and (3) the calculation of the reliable values of criteria weight coefficients, which contribute to rational judgment.

Early math skills are a good predictor of later academic success. Finding what factors influence math performance might help educators create better and more efficient math programs. The goal of the present study was to assess the relationship of math achievement and verbal fluency, selective attention, visual-motor integration and inhibitory control. An additional goal was to assess the effect of gender and grade on math achievement. The sample for this study comprised 210 children from grades 1 to 3 (107 boys, 103 girls). Children were individually administered a math test and tests of various predictor measures. The significant predictors of math achievement were verbal fluency, selective attention, visual-motor integration, and inhibitory control. The proposed model explained around 70% of the variance in the math scores. There were no gender differences in the math scores. Given the fact that all the predictors used in this study are very susceptible to inclusion in instruction, their incorporation in an early age curriculum might significantly improve math skills at a later age.

Introduction: Diabetes mellitus type 2 has become a global health-care problem of modern society due to a pronounced increase of prevalence to pandemic proportions and vascular complications. At present, glycated hemoglobin (HbA1c) is widely accepted as a measure of glycemic control in established diabetes. The aim of this study was to analyze the lipid profile in serum of patients with diabetes mellitus type 2, and its relationship with HbA1c levels. Methods: The observational cross-sectional study included 60 diabetic patients, 30 men, and 30 women, age 32–94 years. Patients were assigned into two groups based on HbA1c values; Group 1: HbA1c ≤ 7% (good glycemic control) and Group 2: HbA1c > 7% (poor glycemic control). We analyzed the concentration of glucose, HbA1c, and lipid profile including total cholesterol levels, triglycerides (TAG), low-density lipoproteins (LDL), and high-density lipoproteins (HDL). Results: Significantly lower values of glucose concentration, TAG and the ratio TAG/HDLc were obtained in the group of patients with good glycemic control. (p < 0.0005) Patients with good glycemic control had lower values of Castelli 1 and Castelli 2 index, and atherogenic index of plasma, compared to patients with poor glycemic control, but this difference was not significant. (p > 0.005) Our study revealed a significant positive correlation between HbA1c and triglyceride level (r = 0.375; p = 0.003) and HbA1c and ratio triglyceride/HDLc (r = 0.335; p = 0.009). Conclusion: HbA1c can also be used as a predictor of dyslipidemia in type 2 diabetics in addition to as a glycemic control parameter.

Product Line Engineering is an approach to reuse assets of complex systems by taking advantage of commonalities between product families. Reuse within complex systems usually means reuse of artifacts from different engineering domains such as mechanical, electronics and software engineering. Model-based systems engineering is becoming a standard for systems engineering and collaboration within different domains. This paper presents an exploratory case study on initial efforts of adopting Product Line Engineering practices within the model-based systems engineering process at Volvo Construction Equipment (Volvo CE), Sweden. We have used SysML to create overloaded models of the engine systems at Volvo CE. The variability within the engine systems was captured by using the Orthogonal Variability Modeling language. The case study has shown us that overloaded SysML models tend to become complex even on small scale systems, which in turn makes scalability of the approach a major challenge. For successful reuse and to, possibly, tackle scalability, it is necessary to have a database of reusable assets from which product variants can be derived.

We study the problem of maximizing privacy of quantized sensor measurements by adding random variables. In particular, we consider the setting where information about the state of a process is obtained using noisy sensor measurements. This information is quantized and sent to a remote station through an unsecured communication network. It is desired to keep the state of the process private; however, because the network is not secure, adversaries might have access to sensor information, which could be used to estimate the process state. To avoid an accurate state estimation, we add random numbers to the quantized sensor measurements and send the sum to the remote station instead. The distribution of these random variables is designed to minimize the mutual information between the sum and the quantized sensor measurements for a desired level of distortion - how different the sum and the quantized sensor measurements are allowed to be. Simulations are presented to illustrate our results.