In recent years, many classification models have been developed and applied to increase their accuracy. The concept of distance between two samples or two variables is a fundamental concept in multivariate analysis. This paper proposed a tool that used different similarity distance approaches with ranking method based on Mean Average Precision (MAP). In this study, several similarity distance methods were used, such as Euclidean, Manhattan, Chebyshev, Sorenson and Cosine. The most suitable distance measure was based on the smallest value of distance between the samples. However, the real solution showed that the results were not accurate as and thus, MAP was considered the best approach to overcome current limitations.
The side sensitive group runs (SSGR) chart is better than both the Shewhart and synthetic charts in detecting small and moderate process mean shifts. In practical circumstances, the process parameters are seldom known, so it is necessary to estimate them from in-control Phase-I samples. Research has discovered that a large number of in-control Phase-I samples are needed for the SSGR chart with estimated process parameters to behave similarly to a chart with known process parameters. The common metric to evaluate the performance of the control chart is average run length (ARL). An assumption for the computation of the ARL is that the shift size is assumed to be known. In reality however, the practitioners may not know the following shift size in advance. In light of this, the expected average run length (EARL) will be considered to measure the performance of the SSGR chart. Moreover, the standard deviation of the ARL (SDARL) will be studied, which is used to quantify the between-practitioner variability in the SSGR chart with estimated process parameters. This paper proposes the optimal design of the estimated process parameters SSGR chart based on the EARL criterion. The application of the optimal SSGR chart with estimated process parameters is demonstrated with actual data taken from a manufacturing company.
Many receiver-based Preamble Sampling Medium Access Control (PS-MAC) protocols have been proposed to provide better performance for variable traffic in a wireless sensor network (WSN). However, most of these protocols cannot prevent the occurrence of incorrect traffic convergence that causes the receiver node to wake-up more frequently than the transmitter node. In this research, a new protocol is proposed to prevent the problem mentioned above. The proposed mechanism has four components, and they are Initial control frame message, traffic estimation function, control frame message, and adaptive function. The initial control frame message is used to initiate the message transmission by the receiver node. The traffic estimation function is proposed to reduce the wake-up frequency of the receiver node by using the proposed traffic status register (TSR), idle listening times (ILTn, ILTk), and "number of wake-up without receiving beacon message" (NWwbm). The control frame message aims to supply the essential information to the receiver node to get the next wake-up-interval (WUI) time for the transmitter node using the proposed adaptive function. The proposed adaptive function is used by the receiver node to calculate the next WUI time of each of the transmitter nodes. Several simulations are conducted based on the benchmark protocols. The outcome of the simulation indicates that the proposed mechanism can prevent the incorrect traffic convergence problem that causes frequent wake-up of the receiver node compared to the transmitter node. Moreover, the simulation results also indicate that the proposed mechanism could reduce energy consumption, produce minor latency, improve the throughput, and produce higher packet delivery ratio compared to other related works.
The timing of ABG procedure in a cleft patient is crucial to provide room and bony
support for the eruption of canine. However, there seems to be a delay in execution of this
procedure in certain centres. Material and Methods: Sample consists of records of cleft patients
treated from 2000-2016. The date and age for commencement of active orthodontic treatment,
date referred for ABG and date ABG done were retrieved. The centres that conducted these
surgeries identified. (Copied from article).
Waiting is a common phenomenon in the doctor's waiting room. The purpose of this audit is to assess patient waiting time and doctor consultation time in a primary healthcare clinic and to formulate strategies for improvement. This audit was conducted at a primary care clinic for 4 weeks using the universal sampling method. All patients who attended the clinic during this period was included in the study except for those who required more time to be seen such as those who were critically ill, aggressive or those who came for repeat medication or procedures only without needing to see the doctor. The time of arrival was captured using the queue management system (QMS) and then the patient was given a timing chit which had to be manually filled by the staff at every station. The waiting time for registration, pre-consultation, consultation, appointment, payment and pharmacy were recorded as well as consultation time. The data were entered into the statistical software SPSS version 17 for analysis. version 17. Results showed that more than half of the patients were registered within 15 minutes (53%) and the average total waiting time from registration to seeing a doctor was 41 minutes. Ninety-nine percentage of patients waited less than 30 minutes to get their medication. The average consultation time was 18.21 minutes. The problems identified in this audit were addressed and strategies formulated to improve the waiting and consultation time were carried out including increasing the number of staff at the registration counter, enforcing the staggered appointment system for follow-up patients and improving the queuing system for walk-in patients.
The aim of this study was to examine whether perceptual variables can provide informational constraints for the goalkeepers to intercept the ball successfully in 1v1 dyads. Video images of 42 actions (1v1 in direct shots) were selected randomly from different matches and divided into conceded goals (n = 20) and saved actions (n = 22) to investigate interceptive actions of 20 goalkeepers in the English Premier League in season 2013-2014. Time to Contact (TTC) of the closing distance gap between shooter and goalkeeper was obtained by digitising actions in the 18-yard penalty box. Statistical analyses revealed that, in sequences of play resulting in an intercepted shot at goal, goalkeepers closed down outfield players in the X axis, whereas when a goal was conceded, there was a significantly delayed movement by goalkeepers toward the shooters in this plane. The results of canonical correlations showed that a decreasing distance between a shooter and goalkeeper, and accompanied reduction in relative interpersonal velocity followed a temporal pattern. Findings of this study showed how perception of key informational constraints on dyadic system relations, such as TTC, interpersonal distance and relative velocity, constrain elite goalkeepers' interceptive actions, playing an important role in successful performance.
Matched MeSH terms: Reaction Time; Time Perception/physiology*
Centrifugation of blood samples to produce platelet-poor plasma is one of the important steps for coagulation testing. Reduction of the time required for specimen processing without affecting quality of results should be ideal for tests which require immediate results. Centrifugation of platelet-poor plasma (3580 rpm) for 15 minutes performed for routine coagulation tests would prolong the turn-around time for an urgent test (30 minutes). This study was done to determine the effect of reducing centrifugation time for routine coagulation tests in order to meet the turn-around time (TAT) for urgent tests. Seventy-nine blood samples sent for routine coagulation tests, were assayed for prothrombin time (PT), activated partial thromboplastin time (APTT), fibrinogen level and platelet counts, using two different centrifugation speed for plasma preparation: centrifugation at 3580 rpm for 15 minutes and rapid centrifugation at 4000 rpm for five minutes. Paired sample t-test showed that there was a significant
difference in the platelet count between the two groups (p=0.001). However, there was no significant difference in the normal APTT (p=0.16), abnormal APTT (p=0.80), abnormal PT (p=0.43) and the results of fibrinogen levels (p=0.36). In conclusion, rapid centrifugation at 4000 rpm for five minutes does not modify results of routine coagulation tests (PT, APTT and fibrinogen). It would be beneficial in providing rapid results for urgent coagulation tests.
Matched MeSH terms: Partial Thromboplastin Time; Prothrombin Time
Identifying the abnormally high-risk regions in a spatiotemporal space that contains an unexpected disease count is helpful to conduct surveillance and implement control strategies. The EigenSpot algorithm has been recently proposed for detecting space-time disease clusters of arbitrary shapes with no restriction on the distribution and quality of the data, and has shown some promising advantages over the state-of-the-art methods. However, the main problem with the EigenSpot method is that it cannot be adapted to detect more than one spatiotemporal hotspot. This is an important limitation, since, in reality, we may have multiple hotspots, sometimes at the same level of importance. We propose an extension of the EigenSpot algorithm, called Multi-EigenSpot that is able to handle multiple hotspots by iteratively removing previously detected hotspots and re-running the algorithm until no more hotspots are found. In addition, a visualization tool (heatmap) has been linked to the proposed algorithm to visualize multiple clusters with different colors. We evaluated the proposed method using the monthly data on measles cases in Khyber-Pakhtunkhwa, Pakistan (Jan 2016- Dec 2016), and the efficiency was compared with the state-of-the-art methods: EigenSpot and Space-time scan statistic (SaTScan). The results showed the effectiveness of the proposed method for detecting multiple clusters in a spatiotemporal space.
This paper presents a performance analysis of two open-source, laser scanner-based Simultaneous Localization and Mapping (SLAM) techniques (i.e., Gmapping and Hector SLAM) using a Microsoft Kinect to replace the laser sensor. Furthermore, the paper proposes a new system integration approach whereby a Linux virtual machine is used to run the open source SLAM algorithms. The experiments were conducted in two different environments; a small room with no features and a typical office corridor with desks and chairs. Using the data logged from real-time experiments, each SLAM technique was simulated and tested with different parameter settings. The results show that the system is able to achieve real time SLAM operation. The system implementation offers a simple and reliable way to compare the performance of Windows-based SLAM algorithm with the algorithms typically implemented in a Robot Operating System (ROS). The results also indicate that certain modifications to the default laser scanner-based parameters are able to improve the map accuracy. However, the limited field of view and range of Kinect's depth sensor often causes the map to be inaccurate, especially in featureless areas, therefore the Kinect sensor is not a direct replacement for a laser scanner, but rather offers a feasible alternative for 2D SLAM tasks.
'Causal' direction is of great importance when dealing with complex systems. Often big volumes of data in the form of time series are available and it is important to develop methods that can inform about possible causal connections between the different observables. Here we investigate the ability of the Transfer Entropy measure to identify causal relations embedded in emergent coherent correlations. We do this by firstly applying Transfer Entropy to an amended Ising model. In addition we use a simple Random Transition model to test the reliability of Transfer Entropy as a measure of 'causal' direction in the presence of stochastic fluctuations. In particular we systematically study the effect of the finite size of data sets.
Newtonian and special-relativistic predictions, based on the same model parameters and initial conditions for the trajectory of a low-speed scattering system are compared. When the scattering is chaotic, the two predictions for the trajectory can rapidly diverge completely, not only quantitatively but also qualitatively, due to an exponentially growing separation taking place in the scattering region. In contrast, when the scattering is nonchaotic, the breakdown of agreement between predictions takes a very long time, since the difference between the predictions grows only linearly. More importantly, in the case of low-speed chaotic scattering, the rapid loss of agreement between the Newtonian and special-relativistic trajectory predictions implies that special-relativistic mechanics must be used, instead of the standard practice of using Newtonian mechanics, to correctly describe the scattering dynamics.
Bujang Valley is a well-known historical complex found in the north-west of peninsular Malaysia; more than 50 ancient monuments and hundreds of artefacts have been discovered throughout the area. The discovery of these suggests Bujang Valley to have been an important South East Asian trading centre over the period from the 10th to 14th centuries. Present work concerns thermoluminescence (TL) dating analysis of shards collected from a historic monument located at Pengkalan Bujang in Bujang Valley. All the shards were prepared using the fine grain technique and the additive dose method was applied in determining the paleodose of each shard. The annual dose rate was obtained by measuring the concentration of naturally occurring radionuclides (U, Th and K) in the samples and their surroundings. The TL ages of the shards were found to range between 330±21 years and 920±69 years, indicative of the last firing of the bricks and tiles from which the shards originated, some dating back to the period during which the historical complex remained active.
Fast and computationally less complex feature extraction for moving object detection using aerial images from unmanned aerial vehicles (UAVs) remains as an elusive goal in the field of computer vision research. The types of features used in current studies concerning moving object detection are typically chosen based on improving detection rate rather than on providing fast and computationally less complex feature extraction methods. Because moving object detection using aerial images from UAVs involves motion as seen from a certain altitude, effective and fast feature extraction is a vital issue for optimum detection performance. This research proposes a two-layer bucket approach based on a new feature extraction algorithm referred to as the moment-based feature extraction algorithm (MFEA). Because a moment represents the coherent intensity of pixels and motion estimation is a motion pixel intensity measurement, this research used this relation to develop the proposed algorithm. The experimental results reveal the successful performance of the proposed MFEA algorithm and the proposed methodology.
Schizophrenia is a common and devastating illness. Patients with schizophrenia may develop many disabilities both due to the disease process as well as due to side effects of the medication used. There are many advances in the treatment of schizophrenia, which can effectively reduce many of these disabilities. Treatment of schizophrenia is a primary health care responsibility and thus all health care personnel need to equip themselves with the latest knowledge on management issues. This article outlines the current management issues in schizophrenia.