The Role of Process Improvement in Attaining Strategic Goals and Providing Financial Value

Customers are demanding increasing value for the money they spend on high technology products. Moreover, competition in the high tech industry is increasing -nationally as well as internationally. As a result, satisfying the customer and providing increased customer value are becoming primary objectives for high technology executives and managers.Many firms that once considered themselves hardware companies are now finding that they are developing a significant amount of software. This software is becoming increasingly sophisticated and costly. Moreover, software projects are increasingly on the critical path . Software developers can put in more effort and work harder. However, it isthe process used to develop the software which coordinates developer efforts and tools. This process can make or break the ability of the firm to deliver. From a strategic standpoint for many high tech firms, improving the software development processes is becoming critically important. However, it is difficult to determine which processes to improve. Studies have shown that firms are finding it difficult to quantitatively justify the resources required to successfully improve their software development processes [5]. Still, many firms are involved in software process improvement efforts.This paper provides summarized results from several companies who have been involved in process improvement activities to show the potential which can be achieved. We then discuss a framework for viewing process changes along strategic lines -with the goal of improving customer value. Once a set of potential process changes has been identified, these changes need to be evaluated. We discuss an approach which can be used to evaluate and tradeoff among proposed alternatives. This approach predicts the performance of process alternatives quantitatively in terms of development cost, product quality, and project schedule. In addition, financial measures such as return on investment (ROI) and net present value (NPV) can be obtaine

Housing problems in a changing society. Regulation and training needs in Italy

The paper focuses on the social, economic and environmental trends of recent years in Italy, highlighting the issue of housing emergency, both in quantitative and qualitative terms. What emerges are several shortages in housing especially in the suburbs of large cities, emphasizing the relevance of this issue in terms of health consequences and its priority for the definition of local policies. The authors underline that the availability of accessible and healthy housing is a human right, and a multisectoral responsibility, achievable only if a contribution is made by all relevant sectors including housing, environmental, social welfare, urban planning, building management and public health. The authors conclude by stressing the strategic role of training and illustrating a proposal addressed to all stakeholders, aiming to provide health evidences in terms of impact of housing hazards on health and to describe good building practices, helpful in order to obtain safe and healthy homes

Hygienic and sanitary standards of housing in Europe: a comparative analysis of nine countries

In recent years, growing interest was devoted to housing conditions from both scientific community and public health, so they are now considered among the main environmental and social health determinants of health of the population. Aim of the study is to analyze and compare the current regulations regarding housing sanitary requirements in different Countries of the EU (Sweden, United Kingdom, Denmark, the Netherlands, France, Germany, Portugal, Spain) with the contents of the Italian Health Ministerial Decree 5th July 1975. From the websites of the official channels of the various countries the regulations have been downloaded. For the comparison, only the aspects of BCs concerning the scale of the building were examined; the comparison concerned all the requirements of the Health Ministerial Decree of 5.07.1975 and some other parameters (e.g. indoor chemical pollution, ionizing radiation, non-ionizing radiation) not provided for in the Ministerial Decree, treated in the other standards regulations, and relevant for the indoor well-being of the occupants. The authors observe a wide variability in the contents and in the formulation of the hygienic-sanitary requirements among the different Building Codes, above all as regards the dimensional data and some fundamental themes (e.g. heating systems, mechanical ventilation) whose treatment is often not it is updated with respect to the technological-scientific innovation consolidated over the past few years. A diverse approach among European Countries is also observed: from a market-oriented logic (e.g. UK), to a prescriptive one (Italy), to a functionality-oriented (the Netherlands). The comparative analysis we carried out made it possible to identify convergences and divergences in the standards analysed for the different European countries. As far as the Italian legislation on the usability of residential premises, finally, considering the health, social, environmental and economic trends, many standards contained in the MD 5th July 1975 should be reviewed and updated

Set-based state estimation and fault diagnosis of linear discrete-time descriptor systems using constrained zonotopes

This paper presents new methods for set-valued state estimation and active fault diagnosis of linear descriptor systems. The algorithms are based on constrained zonotopes, a generalization of zonotopes capable of describing strongly asymmetric convex sets, while retaining the computational advantages of zonotopes. Additionally, unlike other set representations like intervals, zonotopes, ellipsoids, paralletopes, among others, linear static constraints on the state variables, typical of descriptor systems, can be directly incorporated in the mathematical description of constrained zonotopes. Therefore, the proposed methods lead to more accurate results in state estimation in comparison to existing methods based on the previous sets without requiring rank assumptions on the structure of the descriptor system and with a fair trade-off between accuracy and efficiency. These advantages are highlighted in two numerical examples.Comment: This paper was accepted and presented in the 1st IFAC Virtual World Congress, 202

An Adaptive Cognitive Sensor Node for ECG Monitoring in the Internet of Medical Things

The Internet of Medical Things (IoMT) paradigm is becoming mainstream in multiple clinical trials and healthcare procedures. Cardiovascular diseases monitoring, usually involving electrocardiogram (ECG) traces analysis, is one of the most promising and high-impact applications. Nevertheless, to fully exploit the potential of IoMT in this domain, some steps forward are needed. First, the edge-computing paradigm must be added to the picture. A certain level of near-sensor processing has to be enabled, to improve the scalability, portability, reliability and responsiveness of the IoMT nodes. Second, novel, increasingly accurate data analysis algorithms, such as those based on artificial intelligence and Deep Learning, must be exploited. To reach these objectives, designers, and programmers of IoMT nodes, have to face challenging optimization tasks, in order to execute fairly complex computing tasks on low-power wearable and portable processing systems, with tight power and battery lifetime budgets. In this work, we explore the implementation of a cognitive data analysis algorithm, based on a convolutional neural network trained to classify ECG waveforms, on a resource-constrained microcontroller-based computing platform. To minimize power consumption, we add an adaptivity layer that dynamically manages the hardware and software configuration of the device to adapt it at runtime to the required operating mode. Our experimental results show that adapting the node setup to the workload at runtime can save up to 50% power consumption. Our optimized and quantized neural network reaches an accuracy value higher than 97% for arrhythmia disorders detection on MIT-BIH Arrhythmia dataset

In vivo estimation of the shoulder joint center of rotation using magneto-inertial sensors: MRI-based accuracy and repeatability assessment

Background: The human gleno-humeral joint is normally represented as a spherical hinge and its center of rotation is used to construct humerus anatomical axes and as reduction point for the computation of the internal joint moments. The position of the gleno-humeral joint center (GHJC) can be estimated by recording ad hoc shoulder joint movement following a functional approach. In the last years, extensive research has been conducted to improve GHJC estimate as obtained from positioning systems such as stereo-photogrammetry or electromagnetic tracking. Conversely, despite the growing interest for wearable technologies in the field of human movement analysis, no studies investigated the problem of GHJC estimation using miniaturized magneto-inertial measurement units (MIMUs). The aim of this study was to evaluate both accuracy and precision of the GHJC estimation as obtained using a MIMU-based methodology and a functional approach. Methods: Five different functional methods were implemented and comparatively assessed under different experimental conditions (two types of shoulder motions: cross and star type motion; two joint velocities: ωmax = 90°/s, 180°/s; two ranges of motion: Θ = 45°, 90°). Validation was conducted on five healthy subjects and true GHJC locations were obtained using magnetic resonance imaging. Results: The best performing methods (NAP and SAC) showed an accuracy in the estimate of the GHJC between 20.6 and 21.9 mm and repeatability values between 9.4 and 10.4 mm. Methods performance did not show significant differences for the type of arm motion analyzed or a reduction of the arm angular velocity (180°/s and 90°/s). In addition, a reduction of the joint range of motion (90° and 45°) did not seem to influence significantly the GHJC position estimate except in a few subject-method combinations. Conclusions: MIMU-based functional methods can be used to estimate the GHJC position in vivo with errors of the same order of magnitude than those obtained using traditionally stereo-photogrammetric techniques. The methodology proposed seemed to be robust under different experimental conditions. The present paper was awarded as "SIAMOC Best Methodological Paper 2016"

Runtime adaptive iomt node on multi-core processor platform

The Internet of Medical Things (IoMT) paradigm is becoming mainstream in multiple clinical trials and healthcare procedures. Thanks to innovative technologies, latest-generation communication networks, and state-of-the-art portable devices, IoTM opens up new scenarios for data collection and continuous patient monitoring. Two very important aspects should be considered to make the most of this paradigm. For the first aspect, moving the processing task from the cloud to the edge leads to several advantages, such as responsiveness, portability, scalability, and reliability of the sensor node. For the second aspect, in order to increase the accuracy of the system, state-of-the-art cognitive algorithms based on artificial intelligence and deep learning must be integrated. Sensory nodes often need to be battery powered and need to remain active for a long time without a different power source. Therefore, one of the challenges to be addressed during the design and development of IoMT devices concerns energy optimization. Our work proposes an implementation of cognitive data analysis based on deep learning techniques on resource-constrained computing platform. To handle power efficiency, we introduced a component called Adaptive runtime Manager (ADAM). This component takes care of reconfiguring the hardware and software of the device dynamically during the execution, in order to better adapt it to the workload and the required operating mode. To test the high computational load on a multi-core system, the Orlando prototype board by STMicroelectronics, cognitive analysis of Electrocardiogram (ECG) traces have been adopted, considering single-channel and six-channel simultaneous cases. Experimental results show that by managing the sensory node configuration at runtime, energy savings of at least 15% can be achieved

Automated microwave device characterization set-up based on a technology-independent generalized Bias System

In this paper an automated laboratory set-up for the characterization of micro- and millimeter-wave electron devices under DC, small- and large-signal operation is described, which is based on a generalized, technology-independent bias system. The biasing parameters adopted, which are a linear combination between currents and voltages at the device ports, allow for a complete characterization of the desired empirical data (e.g. multi-frequency S-matrix) throughout all the regions in which the quiescent operation of the device can be conventionally divided, without any need for the switch between different biasing strategies. The look-up tables of experimental data obtained, which are carried out homogeneously with respect to the same couple of bias parameters, independently of the quiescent regions investigated, are particularly suitable for the characterization of empirical non-linear dynamic models for the electron device