Sparse detector sensor: Profiling experiments for broad-scale classification

This paper presents a simple prototype sparse detector imaging sensor built using sixteen off-the-shelf, retro-reflective, infrared-sensing elements placed at five-inch intervals in a vertical configuration. Profiling experiments for broad-scale classification of objects, such as humans, humans wearing large backpacks, and humans wearing small backpacks were conducted from data acquired from the sensor. Empirical analysis on models developed using fusion of various classifiers based on a diversity measure shows over ninety percent (90.07%) accuracy (using 10-fold cross validation) in categorizing sensed data into specific classes of interest, such as, humans wearing a large backpack. The results demonstrate that shadow images of sufficient resolution can be captured by the sensor such that broad-scale classification of objects is feasible. The sensor appears to be a low-cost alternative to traditional, high-resolution imaging sensors, and, after industrial packaging, it may be a good candidate for deployment in vast geographic regions in which low-cost, unattended ground sensors with highly accurate classification algorithms are needed

An Internet of Things approach for managing smart services provided by wearable devices.

The Internet of Things (IoT) is growing at a fast pace with new devices getting connected all the time. A new emerging group of these devices are the wearable devices, and Wireless Sensor Networks are a good way to integrate them in the IoT concept and bring new experiences to the daily life activities. In this paper we present an everyday life application involving a WSN as the base of a novel context-awareness sports scenario where physiological parameters are measured and sent to the WSN by wearable devices. Applications with several hardware components introduce the problem of heterogeneity in the network. In order to integrate different hardware platforms and to introduce a service-oriented semantic middleware solution into a single application, we propose the use of an Enterprise Service Bus (ESB) as a bridge for guaranteeing interoperability and integration of the different environments, thus introducing a semantic added value needed in the world of IoT-based systems. This approach places all the data acquired (e.g., via Internet data access) at application developers disposal, opening the system to new user applications. The user can then access the data through a wide variety of devices (smartphones, tablets, computers) and Operating Systems (Android, iOS, Windows, Linux, etc.)

An Initial Exploration of Engineering Student Perceptions of COVID’s Impact on Connectedness, Learning, and STEM Identity

This paper studied the development of STEM identity for freshman students in Engineering. An Urban Research University received a 5-year S-STEM award in fall 2018. So far, two cohorts of scholars have received the scholarship as well as academic support, mentoring support, and customized advising from faculty and upper level peers. The objective of this project is to help underrepresented and talented students in engineering to pursue an undergraduate degree. A Multi-Layered Mentoring(MLM) Program was established, and several interviews were conducted with scholarship recipients. The qualitative and qualitative analysis of the student success shows an improvement in GPA of students in the program as compared to the rest of the school. The students not only received financial help through the program based on their unmet needs, they are were placed in an engineering learning community (ELC). The participants in ELC and MLM programs agreed to participate in research studies to assess their success. This NSF funded program also helped freshman students be involved in a hands-on Design Innovations class where they learned design process and human centered design. The students were surveyed on a regular basis to identify their needs and were approached by faculty advisor as well as their mentors to trouble shoot their concerns and help them with both social and academic aspects of their concerns. The first cohort joined the program in AY 2019-2020, as freshmen. This cohort had experienced a full semester of in-person engagement before the COVID-19 hit in the middle of the second semester of their freshman year. We have researched the impact of the pandemic on their academic progress, sense of belonging, and STEM identity. The second cohort joined the program in AY 2020-2021. They have not had the chance to experience the campus life and their perspective of college life is very different than the first cohort. The STEM identity was one of the success indicators for freshman students who entered the university in one of the most difficult and un-usual circumstances under the COVID-19 pandemic

Knowledge and health care resource allocation: CME/CPD course guidelines-based efficacy.

BACKGROUND: Most health care systems consider continuing medical education a potential tool to improve quality of care and reduce disease management costs. Its efficacy in general practitioners needs to be further explored. OBJECTIVE: This study assesses the effectiveness of a one-year continuing medical education/continuing professional development course for general practitioners, regarding the improvement in knowledge of ARIA and GINA guidelines and compliance with them in asthma management. METHODS: Sixty general practitioners, covering 68,146 inhabitants, were randomly allocated to continuing medical education/continuing professional development (five residential events +four short distance-learning refresher courses over one year) or no training. Participants completed a questionnaire after each continuing medical education event; key questions were repeated at least twice. The Local Health Unit prescription database was used to verify prescription habits (diagnostic investigations and pharmacological therapy) and hospitalizations over one year before and after training. RESULTS: Fourteen general practitioners (46.7%) reached the cut-off of 50% attendance of the training courses. Knowledge improved significantly after training (p < 0.001, correct answers to key questions +13%). Training resulted in pharmaceutical cost containment (trained general practitioners +0.5% vs. controls +18.8%) and greater attention to diagnosis and monitoring (increase in spirometry +63.4%, p < 0.01). CONCLUSION: This study revealed an encouraging impact of educational events on improvement in general practitioner knowledge of guidelines and daily practice behavioral changes. Long-term studies of large populations are required to assess the effectiveness of education on the behavior of physicians in asthma management, and to establish the best format for educational events

Defining a volume of threshold value with Prolog

Three-dimensional finite element torso models are widely used to simulate defibrillation field quantities such as the voltage, potential, gradient, and current density. These quantities are computed at spatial nodes that comprise the torso model. These spatial nodes typically number between 105 and 106 in magnitude making visualization and comprehension of torso defibrillation model output difficult. Thus, the objective of this study is to display a subset of the geometric model of the torso where the nodal information associated with the geometry of the model meets a specified threshold value (e.g. minimum gradient). The study is implemented with a SWI Prolog interpreter that is used to aid in the correlation between the coordinate, structural, and nodal databases of the torso model. Prolog is used to develop new methods for sorting, collecting, and optimizing data from defibrillation simulations in a human torso model based on declarative queries

Robust classification of objects using a sparse detector sensor

This paper emphasizes techniques for broad-scale classification of objects sensed by a prototype unattended ground sparse detector sensor. A wide range of machine learning techniques were applied to create models of three broad classes of objects, such as humans, humans wearing large backpacks, and non-humans using data obtained from the sparse detector sensor in a laboratory environment. Fusion of models was performed based on a measure of diversity among classifiers to improve the robustness and also the accuracy of the models. Empirical analysis on 230 sample datasets shows up to a 91.74% accuracy (10-fold cross validation) in classifying three broad classes of objects of interest and shows very promising scores on other various performance indices

Floquet resonances close to the adiabatic limit and the effect of dissipation

We study the approach to the adiabatic limit in periodically driven systems. Specifically focusing on a spin-1/2 in a magnetic field we find that, when the parameters of the Hamiltonian lead to a quasi-degeneracy in the Floquet spectrum, the evolution is not adiabatic even if the frequency of the field is much smaller than the spectral gap of the Hamiltonian. We argue that this is a general phenomenon of periodically driven systems. Although an explanation based on a perturbation theory in cannot be given, because of the singularity of the zero frequency limit, we are able to describe this phenomenon by means of a mapping to an extended Hilbert space, in terms of resonances of an effective two-band Wannier-Stark ladder. Remarkably, the phenomenon survives in presence of dissipation towards an environment and can be therefore easily experimentally observed

Thermalization in a periodically driven fully connected quantum Ising ferromagnet

By means of a Floquet analysis, we study the quantum dynamics of a fully connected Lipkin-Ising ferromagnet in a periodically driven transverse field showing that thermalization in the steady state is intimately connected to properties of the N\u2192 1e classical Hamiltonian dynamics. When the dynamics is ergodic, the Floquet spectrum obeys a Wigner-Dyson statistics and the system satisfies the eigenstate thermalization hypothesis (ETH): Independently of the initial state, local observables relax to the T= 1e thermal value, and Floquet states are delocalized in the Hilbert space. On the contrary, if the classical dynamics is regular no thermalization occurs. We further discuss the relationship between ergodicity and dynamical phase transitions, and the relevance of our results to other fully-connected periodically driven models (like the Bose-Hubbard), and possibilities of experimental realization in the case of two coupled BEC