ANGELAH: A Framework for Assisting Elders At Home

The ever growing percentage of elderly people within modern societies poses welfare systems under relevant stress. In fact, partial and progressive loss of motor, sensorial, and/or cognitive skills renders elders unable to live autonomously, eventually leading to their hospitalization. This results in both relevant emotional and economic costs. Ubiquitous computing technologies can offer interesting opportunities for in-house safety and autonomy. However, existing systems partially address in-house safety requirements and typically focus on only elder monitoring and emergency detection. The paper presents ANGELAH, a middleware-level solution integrating both ”elder monitoring and emergency detection” solutions and networking solutions. ANGELAH has two main features: i) it enables efficient integration between a variety of sensors and actuators deployed at home for emergency detection and ii) provides a solid framework for creating and managing rescue teams composed of individuals willing to promptly assist elders in case of emergency situations. A prototype of ANGELAH, designed for a case study for helping elders with vision impairments, is developed and interesting results are obtained from both computer simulations and a real-network testbed

Region-based Skin Color Detection.

Skin color provides a powerful cue for complex computer vision applications. Although skin color detection has been an active research area for decades, the mainstream technology is based on the individual pixels. This paper presents a new region-based technique for skin color detection which outperforms the current state-of-the-art pixel-based skin color detection method on the popular Compaq dataset (Jones and Rehg, 2002). Color and spatial distance based clustering technique is used to extract the regions from the images, also known as superpixels. In the first step, our technique uses the state-of-the-art non-parametric pixel-based skin color classifier (Jones and Rehg, 2002) which we call the basic skin color classifier. The pixel-based skin color evidence is then aggregated to classify the superpixels. Finally, the Conditional Random Field (CRF) is applied to further improve the results. As CRF operates over superpixels, the computational overhead is minimal. Our technique achieves 91.17% true positive rate with 13.12% false negative rate on the Compaq dataset tested over approximately 14,000 web images

Detecting indicators of cognitive impairment via Graph Convolutional Networks

While the life expectancy is on the rise all over the world, more people face health related problems such as cognitive decline. Dementia is a name used to describe progressive brain syndromes affecting memory, thinking, behaviour and emotion. People suffering from dementia may lose their abilities to perform daily life activities and they become on their caregivers. Hence, detecting the indicators of cognitive decline and warning the caregivers and medical doctors for further diagnosis would be helpful. In this study, we tackle the problem of activity recognition and abnormal behaviour detection in the context of dementia by observing daily life patterns of elderly people. Since there is no real-world data available, firstly a method is presented to simulate abnormal behaviour that can be observed in daily activity patterns of dementia sufferers. Secondly, Graph Convolutional Networks (GCNs) are exploited to recognise activities based on their granular-level sensor activations. Thirdly, abnormal behaviour related to dementia is detected using activity recognition confidence probabilities. Lastly, GCNs are compared against the state-of-the-art methods. The results obtained indicate that GCNs are able to recognise activities and flag abnormal behaviour related to dementia

Effect of Pores on Mechanical Behavior. Application to the Composite Material

The effects of microscopic pores, during the historical deformation on the behavior of ductile material are experimentally and numerically investigated. The material used in this study is constituted from the glass beads which are incorporated in the polyester resin. During moulding of these constituents, the pores remain in the material because of the resin viscosity. The experimental technique used for the characterization of the effect of pores is the tensile test. The constitutive equations of poroelastoplasticity are developed according to the micromechanical consideration. The material model developed by Gurson is extended to this composite material. The numerical results are obtained and compared with the experimental ones.Выполнены экспериментальное исследование и численное моделирование влияния микроскопических пор на поведение вязкого материала при деформировании с учетом истории нагружения. Объектом исследования служил композитный материал на основе полиэстер- ной резины с включениями из бисера. В процессе формовки указанных компонентов в материале образуются поры из-за вязкости резины. Для оценки эффекта пор использовали экспериментальную технологию испытаний на растяжение. В рамках микромеханического подхода получены основные уравнения пороупругопластичности. Проведено обобщение модели материала Гурсона на исследуемый композитный материал. Результаты расчетов сопоставлены с экспериментальными данными.Виконано експериментальні дослідження і числове моделювання впливу мікроскопічних пор на поведінку в ’язкого матеріалу при деформуванні з урахуванням історії навантаження. Об’єктом дослідження служив композитний матеріал на основі поліестерної гуми з вкрапленнями з бісеру. У процесі формовки указаних компонентів у матеріалі з ’являються пори внаслідок в ’язкості гуми. Для оцінки ефекту пор використовували експериментальну технологію випробувань на розтяг. У рамках мікромеханічного підходу отримано основні рівняння поропружнопластичності. Проведено узагальнення моделі матеріалу Гурсона на композитний матеріал, що досліджується. Розрахункові результати зіставляються з експериментальними

A Low-Profile four-port MIMO Antenna for 5G-n79 Band with high diversity performance

This paper presents a simple design of a compact 4-port multiple-input multiple-output (MIMO) microstrip antenna using polarization diversity technique. The proposed structure consists of four monopole elements operating in the fifth generation n79 band (4800–5000 MHz). To achieve good performance with a more compact design, the four identical elements are arranged orthogonally to each other. The proposed antenna is fabricated using a Rogers RT6010 substrate with a compact size of 28 × 28mm2.  The measured results of the manufactured antenna in terms of S-parameters and radiation pattern are in good agreement at the operating frequency band. Moreover, the diversity performance of the proposed MIMO antenna is evaluated through the envelope correlation coefficient (ECC), the diversity gain (DG), the total active reflection coefficient (TARC) and the channel capacity loss (CCL)

Bioinformatics Tools and Databases to Assess the Pathogenicity of Mitochondrial DNA Variants in the Field of Next Generation Sequencing

The development of next generation sequencing (NGS) has greatly enhanced the diagnosis of mitochondrial disorders, with a systematic analysis of the whole mitochondrial DNA (mtDNA) sequence and better detection sensitivity. However, the exponential growth of sequencing data renders complex the interpretation of the identified variants, thereby posing new challenges for the molecular diagnosis of mitochondrial diseases. Indeed, mtDNA sequencing by NGS requires specific bioinformatics tools and the adaptation of those developed for nuclear DNA, for the detection and quantification of mtDNA variants from sequence alignment to the calling steps, in order to manage the specific features of the mitochondrial genome including heteroplasmy, i.e., coexistence of mutant and wildtype mtDNA copies. The prioritization of mtDNA variants remains difficult, relying on a limited number of specific resources: population and clinical databases, and tools providing a prediction of the variant pathogenicity. An evaluation of the most prominent bioinformatics tools showed that their ability to predict the pathogenicity was highly variable indicating that special efforts should be directed at developing new bioinformatics tools dedicated to the mitochondrial genome. In addition, massive parallel sequencing raised several issues related to the interpretation of very low mtDNA mutational loads, discovery of variants of unknown significance, and mutations unrelated to patient phenotype or the co-occurrence of mtDNA variants. This review provides an overview of the current strategies and bioinformatics tools for accurate annotation, prioritization and reporting of mtDNA variations from NGS data, in order to carry out accurate genetic counseling in individuals with primary mitochondrial diseases

Clinical and Genetic Risk Factors for Adverse Metabolic Outcomes in North American Testicular Cancer Survivors

Background: Testicular cancer survivors (TCS) are at significantly increased risk for cardiovascular disease (CVD), with metabolic syndrome (MetS) an established risk factor. No study has addressed clinical and genetic MetS risk factors in North American TCS. Patients and Methods: TCS were aged <55 years at diagnosis and received first-line chemotherapy. Patients underwent physical examination, and had lipid panels, testosterone, and soluble cell adhesion molecule-1 (sICAM-1) evaluated. A single nucleotide polymorphism in rs523349 (5-α-reductase gene, SRD5A2), recently implicated in MetS risk, was genotyped. Using standard criteria, MetS was defined as ≥3 of the following: hypertension, abdominal obesity, hypertriglyceridemia, decreased high-density lipoprotein (HDL) cholesterol level, and diabetes. Matched controls were derived from the National Health and Nutrition Examination Survey. Results: We evaluated 486 TCS (median age, 38.1 years). TCS had a higher prevalence of hypertension versus controls (43.2% vs 30.7%; P<.001) but were less likely to have decreased HDL levels (23.7% vs 34.8%; P<.001) or abdominal obesity (28.2% vs 40.1%; P<.001). Overall MetS frequency was similar in TCS and controls (21.0% vs 22.4%; P=.59), did not differ by treatment (P=.20), and was not related to rs523349 (P=.61). For other CVD risk factors, TCS were significantly more likely to have elevated low-density lipoprotein (LDL) cholesterol levels (17.7% vs 9.3%; P<.001), total cholesterol levels (26.3% vs 11.1%; P<.001), and body mass index ≥25 kg/m2 (75.1% vs 69.1%; P=.04). On multivariate analysis, age at evaluation (P<.001), testosterone level ≤3.0 ng/mL (odds ratio [OR], 2.06; P=.005), and elevated sICAM-1 level (ORhighest vs lowest quartile, 3.58; P=.001) were significantly associated with MetS. Conclusions and Recommendations: Metabolic abnormalities in TCS are characterized by hypertension and increased LDL and total cholesterol levels but lower rates of decreased HDL levels and abdominal obesity, signifying possible shifts in fat distribution and fat metabolism. These changes are accompanied by hypogonadism and inflammation. TCS have a high prevalence of CVD risk factors that may not be entirely captured by standard MetS criteria. Cancer treatment–associated MetS requires further characterization

DETERMINATION OF THERMAL AND PHYSICAL PROPERTIES OF PALMYRA WOOD (BORASSUS AETHIOPUM MART.) FROM MALFANA IN CHAD

ABSTRACT Palmyra or Borassus aethiopum Mart is a timber that is used in th

Status and Recent Results of the Acoustic Neutrino Detection Test System AMADEUS

The AMADEUS system is an integral part of the ANTARES neutrino telescope in the Mediterranean Sea. The project aims at the investigation of techniques for acoustic neutrino detection in the deep sea. Installed at a depth of more than 2000m, the acoustic sensors of AMADEUS are based on piezo-ceramics elements for the broad-band recording of signals with frequencies ranging up to 125kHz. AMADEUS was completed in May 2008 and comprises six "acoustic clusters", each one holding six acoustic sensors that are arranged at distances of roughly 1m from each other. The clusters are installed with inter-spacings ranging from 15m to 340m. Acoustic data are continuously acquired and processed at a computer cluster where online filter algorithms are applied to select a high-purity sample of neutrino-like signals. 1.6 TB of data were recorded in 2008 and 3.2 TB in 2009. In order to assess the background of neutrino-like signals in the deep sea, the characteristics of ambient noise and transient signals have been investigated. In this article, the AMADEUS system will be described and recent results will be presented.Comment: 7 pages, 8 figures. Proceedings of ARENA 2010, the 4th International Workshop on Acoustic and Radio EeV Neutrino Detection Activitie