Active noise control on high frequency narrow band dental drill noise: Preliminary results

Dental drills produce a characteristic noise that is uncomfortable for patients and is also known to be harmful to dentists under prolonged exposure. It is therefore desirable to protect the patient and dentist whilst allowing two-way communication. A solution is to use a combination of the three main noise cancellation methods, namely, Passive Noise Control, Adaptive Filtering and Active Noise Control. Dental drill noise occurs at very high frequency ranges in relation to conventional ANC, typically 2kHz to 6kHz and it has a narrow band characteristic due to the direct relation of the noise to the rotational speed of the bearing. This paper presents a design of an experimental rig where first applications of ANC on dental drill noise are executed using the standard filtered reference Least Mean Square (FXLMS) algorithm. The secondary path is kept as simple as possible, due to the high frequency range of interest, and hence is chosen as the space between headphone loudspeaker and error microphone placed in the ear (input of the headphone loudspeaker and the output of the error microphone). A standard headphone loudspeaker is used for the control source and the microphone inside of an “Ear and Cheek Simulator Type 43AG” is used as the error microphone. The secondary path transfer function is obtained and preliminary results of the application of ANC are discussed

Dental drill noise reduction using a combination of active noise control, passive noise control and adaptive filtering

Dental drills produce a characteristic high frequency, narrow band noise that is uncomfortable for patients and is also known to be harmful to dentists under prolonged exposure. It is therefore desirable to protect the patient and dentist whilst allowing two-way communication. A solution is to use a combination of the three main noise control methods, namely, Passive Noise Control (PNC), Adaptive Filtering (AF) and Active Noise Control (ANC). This paper discusses the application of the three methods to reduce dental drill noise while allowing two-way communication. Experimental setup for measuring the noise reduction by PNC is explained and results from different headphones and headphone types are presented. The implementation and results of an AF system using the Least Mean Square (LMS) algorithm are shown. ANC requires a modification of the LMS algorithm due to the introduction of the electro-acoustical cancellation path transfer function to compensate for the delays introduced by the control system. Therefore a cancellation path transfer function modeling method based on the filtered reference LMS (FXLMS) algorithm is presented along with preliminary results of the implementation

Active noise control for high frequencies

There are many applications that can benefit from Active Noise Control (ANC) such as in aircraft cabins and air conditioning ducts, i.e. in situations where technology interferes with human hearing in a harmful way or disrupts communication. Headsets with analogue ANC circuits have been used in the armed forces for attenuating frequencies below 1 kHz, which when combined with passive filtering offers protection across the whole frequency range of human hearing. A dental surgery is also a noisy environment; in which dental drill noise is commonly off-putting for many patients and is believed to harm the dentist’s hearing over a long period of time. However, dealing with dental drill noise is a different proposition from the applications mentioned above as the frequency range of the peak amplitudes goes from approximately 1.5 kHz to 12 kHz, whereas conventional ANC applications consider a maximum of 1.5 kHz. This paper will review the application of ANC at low frequencies and justify an approach for dealing with dental noise using digital technologies at higher frequencies. The limits of current ANC technologies will be highlighted and the means of improving performance for this dental application will be explored. In particular, technicalities of implementing filtering algorithms on a Digital Signal Processor will be addressed

Real-time adaptive filtering of dental drill noise using a digital signal processor

The application of noise reduction methods requires the integration of acoustics engineering and digital signal processing, which is well served by a mechatronic approach as described in this paper. The Normalised Least Mean Square (NLMS) algorithm is implemented on the Texas Instruments TMS320C6713 DSK Digital Signal Processor (DSP) as an adaptive digital filter for dental drill noise. Blocks within the Matlab/Simulink Signal Processing Blockset and the Embedded Target for TI C6000 DSP family are used. A working model of the algorithm is then transferred to the Code Composer Studio (CCS), where the desired code can be linked and transferred to the target DSP. The experimental rig comprises a noise reference microphone, a microphone for the desired signal, the DSK and loudspeakers. Different load situations of the dental drill are considered as the noise characteristics change when the drill load changes. The result is that annoying drill noise peaks, which occur in a frequency range from 1.5 kHz to 10 kHz, are filtered out adaptively by the DSP. Additionally a schematic design for its implementation in a dentist’s surgery will also be presented

A maturity model for care pathways

Over the last recent decades, increasing the quality of healthcare services while reducing costs has been among the top concerns in the healthcare landscape. Several healthcare institutions have initiated improvement programs and invested considerably in process orientation and management. Care pathways are receiving increasing attention from clinicians, healthcare managers, and academics, as a way to standardize healthcare processes to improve the safety, quality, and efficiency of healthcare services. Despite considerable literature on the definition of care pathways, to date there is no agreement on their key process characteristics and the way they traverse from an immature to a mature state. Such a model would guide healthcare institutions to assess pathways’ level of maturity and generate a roadmap for improving towards higher levels. In this paper, we propose a maturity model for care pathways that is constructed taking a generic business process maturity model as a basis. The model was refined through a Delphi study with nine domain experts to address healthcare domain specific concerns. To evaluate its validity, we applied it in assessing the maturity of a particular care pathway taking place in 11 healthcare institutions. The results indicate the usefulness of the proposed model in assessing pathway’s maturity and its potential to provide guidance for its improvement

Modelling electrical conductivity of groundwater using an adaptive neuro-fuzzy inference system

Electrical conductivity is an important indicator for water quality assessment. Since the composition of mineral salts affects the electrical conductivity of groundwater, it is important to understand the relationships between mineral salt composition and electrical conductivity. In this present paper, we develop an adaptive neuro-fuzzy inference system (ANFIS) model for groundwater electrical conductivity based on the concentration of positively charged ions in water. It is shown that the ANFIS model outperforms more traditional methods of modelling electrical conductivity based on the total solids dissolved in the water, even though ANFIS uses less information. Additionally, the fuzzy rules in the ANFIS model provide a categorization of ground water samples in a manner that is consistent with the current understanding of geophysical processes

An open platform for personal health record apps with platform-level privacy protection

One of the main barriers to the adoption of Personal Health Records (PHR) systems is their closed nature. It has been argued in the literature that this barrier can be overcome by introducing an open market of substitutable PHR apps. The requirements introduced by such an open market on the underlying platform have also been derived. In this paper, we argue that MyPHRMachines, a cloud-based PHR platform recently developed by the authors, satisfies these requirements better than its alternatives. The MyPHRMachines platform leverages Virtual Machines as flexible and secure execution sandboxes for health apps. MyPHRMachines does not prevent pushing hospital- or patient-generated data to one of its instances, nor does it prevent patients from sharing data with their trusted caregivers. External software developers have minimal barriers to contribute innovative apps to the platform, since apps are only required to avoid pushing patient data outside a MyPHRMachines cloud. We demonstrate the potential of MyPHRMachines by presenting two externally contributed apps. Both apps provide functionality going beyond the state-of-the-art in their application domain, while they did not require any specific MyPHRMachines platform extension

Genetic Algorithms in Supply Chain Scheduling of Ready-Mixed Concrete

The coordination of just-in-time production and transportation in a network of partially independent facilities to guarantee timely delivery to distributed customers is one of the most challenging aspects of supply chain management. From the theoretical perspective, the timely production/distribution can be viewed as a hybrid combination of planning, scheduling and routing problem, each notoriously affected by nearly prohibitive combinatorial complexity. From a practical viewpoint, the problem calls for a trade-off between risks and profits. This paper focuses on the ready-made concrete delivery: in addition to the mentioned complexity, strict time-constraints forbid both earliness and lateness of the supply. After developing a detailed model of the considered problem, we propose a novel meta-heuristic approach based on a hybrid genetic algorithm combined with constructive heuristics. A detailed case study derived from industrial data is used to illustrate the potential of the proposed approach

The European Union, borders and conflict transformation: the case of Cyprus

Much of the existing literature on the European Union (EU), conflict transformation and border dynamics has been premised on the assumption that the nature of the border determines EU intervention and the consequences that flow from this in terms of EU impact. The article aims to transcend this literature through assessing how domestic interpretations influence EU border transformation in conflict situations, taking Cyprus as a case study. Moreover, the objective is to fuse the literature on EU bordering impact and perceptions of the EU’s normative projection in conflict resolution. Pursuing this line of inquiry is an attempt to depart from the notion of borders being constructed solely by unidirectional EU logics of engagement or bordering practices to a conceptualization of the border as co-constituted space, where the interpretations of the EU’s normative projections by conflict parties, and the strategies that they pursue, can determine the relative openness of the EU border

Detection by tissue printing hybridization of Pome fruit viroids in the mediterranean basin

Available data on the incidence and biodiversity of pome fruit viroids in the Mediterranean basin are limited. Before starting a research survey to fill this gap, a tissue-printing hydridization (TPH) method to detect Apple scar skin viroid (ASSVd), Pear blister canker viroid (PBCVd) and Apple dimple fruit viroid (ADFVd) has been developed and validated. Afterward, TPH was used in large-scale indexing of pome fruit viroids in Bosnia and Herzegovina, Malta, Lebanon and Turkey. A total of about 1,000 trees was randomly collected and tested. Positive results obtained by TPH were confirmed by at least one additional detection method (RT-PCR and/or Northern-blot hybridization) and viroids were finally identified by sequencing full-length cDNA clones. PBCVd was detected in 13%, 12.4% and 5.4% of the tested pear trees in Bosnia and Herzegovina, Malta and Turkey, respectively, showing a wider diffusion of this viroid than expected. In contrast, ASSVd was never detected and ADFVd was only found in symptomatic trees (cv. Starking Delicious) in Lebanon, confirming a restricted presence of these viroids in the Mediterranean basin. Altogether, these data support the use of TPH as an easy and valuable tool for exploring pome fruit viroid spread. Keywords: Viroid disease, viroid spread, pome fruit trees, detection methods, molecular hybridizatio