Rancang Bangun Aplikasi Monitoring dan Evaluasi Pekerjaan Proyek pada Bidang Penataan Ruang di Dinas PU. Cipta Karya Sumenep

Dinas PU. Cipta Karya dan Tata Ruang Kabupaten Sumenep as executive agencies wheel development. Bidang penataan ruang became a top priority along with the occurrence of resistance in the city of sumenep, among others, the construction of a drainage channel, local roads and sidewalks. Problems encountered can not do monitoring with respect to time, cost, and project work progress in the field. So in the initial evaluation and identification work difficult, it often causes a delay in the implementation of the project work. To overcome the obstacles faced by bidang penataan ruang, can be done by means of building the application of monitoring and evaluation of the project in bidang penataan ruang di dinas PU. Cipta Karya Sumenep. Monitoring included the time, cost, and work progress. If there is a mismatch of the project, the system will give an alert/notification to immediately followed up. The results of monitoring will be evaluated by the system for each stretch out. So if there is a discovery that could harm the project can be identified since the beginning. At this stage of implementation, the application indicates conformity with the expectation of 100% and worth to be used. Based on test data planning and realization, obtained results information monitoring and evaluation of each project is presented in the form of the curve S

Beyond financial proxies in Cohesion Policy inputs' monitoring: A system dynamics approach

European Union's Cohesion Policy aims to foster development and reduce disparities among regions by redistributing more than one-third of the European budget. Given the policy's importance and complexity, an elaborated monitoring and evaluation system has been established. While attention has been dedicated to evaluating policy impact, the monitoring of inputs (i.e., allocated financial resources) has been limited to the control of financial dimensions (i.e., funds' absorption rate). As the implementation process entails a sequence of steps, this research explores whether financial proxies alone are adequate to monitor the policy inputs. To test this hypothesis, a system dynamics model is built. Simulations highlight that the absorption rate captures shocks that might occur during the inputs' expenditure with significant delay. To that end, we elaborate three novel operative monitoring indicators (i.e., funds' demand, funds' offer, procedural efficiency), which may overcome the financial indicators' mono-dimensionality and time lags' limitations

A Review of Selected Applications of GNSS CORS and Related Experiences at the University of Palermo (Italy)

Services from the Continuously Operating Reference Stations (CORS) of the Global Navigation Satellite System (GNSS) provide data and insights to a range of research areas such as physical sciences, engineering, earth and planetary sciences, computer science, and environmental science. Even though these fields are varied, they are all linked through the GNSS operational application. GNSS CORS have historically been deployed for three-dimensional positioning but also for the establishment of local and global reference systems and the measurement of ionospheric and tropospheric errors. In addition to these studies, CORS is uncovering new, emerging scientific applications. These include real-time monitoring of land subsidence via network real-time kinematics (NRTK) or precise point positioning (PPP), structural health monitoring (SHM), earthquake and volcanology monitoring, GNSS reflectometry (GNSS-R) for mapping soil moisture content, precision farming with affordable receivers, and zenith total delay to aid hydrology and meteorology. The flexibility of CORS infrastructure and services has paved the way for new research areas. The aim of this study is to present a curated selection of scientific papers on prevalent topics such as network monitoring, reference frames, and structure monitoring (like dams), along with an evaluation of CORS performance. Concurrently, it reports on the scientific endeavours undertaken by the Geomatics Research Group at the University of Palermo in the realm of GNSS CORS over the past 15 years

Neural network based partial tomography for in-vehicle network monitoring

In-vehicle network monitoring is one of the important elements in vehicular network management and security. Most of the existing network monitoring approaches rely on measuring every part of the network. Such approaches overburden the network by transmitting active probes. In this work, we propose a new in-vehicle network monitoring approach that benefits from network tomography and the advances in deep learning to infer the network delay performance. Specifically, the available measurements can be used to estimate the performance of the remaining network where direct measurements cannot be applied. Performance evaluation has been conducted using in-vehicle network simulation with different TSN (Time-Sensitive Network) traffics and the proposed monitoring approach shows the delay estimation accuracy of up to 99%

Computational Approaches for Remote Monitoring of Symptoms and Activities

We now have a unique phenomenon where significant computational power, storage, connectivity, and built-in sensors are carried by many people willingly as part of their life style; two billion people now use smart phones. Unique and innovative solutions using smart phones are motivated by rising health care cost in both the developed and developing worlds. In this work, development of a methodology for building a remote symptom monitoring system for rural people in developing countries has been explored. Design, development, deployment, and evaluation of e-ESAS is described. The system’s performance was studied by analyzing feedback from users. A smart phone based prototype activity detection system that can detect basic human activities for monitoring by remote observers was developed and explored in this study. The majority voting fusion technique, along with decision tree learners were used to classify eight activities in a multi-sensor framework. This multimodal approach was examined in details and evaluated for both single and multi-subject cases. Time-delay embedding with expectation-maximization for Gaussian Mixture Model was explored as a way of developing activity detection system using reduced number of sensors, leading to a lower computational cost algorithm. The systems and algorithms developed in this work focus on means for remote monitoring using smart phones. The smart phone based remote symptom monitoring system called e-ESAS serves as a working tool to monitor essential symptoms of patients with breast cancer by doctors. The activity detection system allows a remote observer to monitor basic human activities. For the activity detection system, the majority voting fusion technique in multi-sensor architecture is evaluated for eight activities in both single and multiple subjects cases. Time-delay embedding with expectation-maximization algorithm for Gaussian Mixture Model was studied using data from multiple single sensor cases

THE CLINICAL AND FORENSIC ROLE OF CITOLOGY IN PTA AND PT1 BLADDER CANCER MONITORING. CASE STUDY REVISION FOR THE PERIOD 2008 – 2017.

Introduction: The Authors describe the results of a retrospective study that analyzes importance of a proper bladder cancer monitoring, comparing the use of the different methods available, both in terms of diagnostic delay and in terms of legal medical repercussions. Materials and methods: Using the database of the Pathological Anatomy Department of the Modena Polyclinic, we have isolated a series of 238 patients with histological diagnosis of bladder urothelial carcinoma in pTa and pT1 stages with an observational minimum time interval after first diagnosis of at least 5 years. The observational statistical analysis of the data stored was made through a statistical software (SPSS report 11.00 USA). Results: The results of the present study show how cytological screening, performed constantly with urine tests during early-stage monitoring of bladder tumors, can be a valid tool for the timely diagnosis of tumor stage evolution. Indeed positivity of the cytological examination can direct to a rapid diagnostic and therapeutic re-planning. Conclusion: It would be desirable to standardize the best screening strategies about bladder cancer. With a correct standardization, a valid reference could be obtained both from a clinical point of view, and for a correct legal medical evaluation in term of diagnostic delay and, consequently, reduction in the chance of survival

Computational Approaches for Remote Monitoring of Symptoms and Activities

We now have a unique phenomenon where significant computational power, storage, connectivity, and built-in sensors are carried by many people willingly as part of their life style; two billion people now use smart phones. Unique and innovative solutions using smart phones are motivated by rising health care cost in both the developed and developing worlds. In this work, development of a methodology for building a remote symptom monitoring system for rural people in developing countries has been explored. Design, development, deployment, and evaluation of e-ESAS is described. The system’s performance was studied by analyzing feedback from users. A smart phone based prototype activity detection system that can detect basic human activities for monitoring by remote observers was developed and explored in this study. The majority voting fusion technique, along with decision tree learners were used to classify eight activities in a multi-sensor framework. This multimodal approach was examined in details and evaluated for both single and multi-subject cases. Time-delay embedding with expectation-maximization for Gaussian Mixture Model was explored as a way of developing activity detection system using reduced number of sensors, leading to a lower computational cost algorithm. The systems and algorithms developed in this work focus on means for remote monitoring using smart phones. The smart phone based remote symptom monitoring system called e-ESAS serves as a working tool to monitor essential symptoms of patients with breast cancer by doctors. The activity detection system allows a remote observer to monitor basic human activities. For the activity detection system, the majority voting fusion technique in multi-sensor architecture is evaluated for eight activities in both single and multiple subjects cases. Time-delay embedding with expectation-maximization algorithm for Gaussian Mixture Model was studied using data from multiple single sensor cases