Execution Duration Research Articles

Investigating the jumping to conclusion bias in bipolar disorder

ABSTRACTIntroduction: Hemsley and Garety described the “jumping to conclusions bias” in which patients with delusions may reach unreasonable results with insufficient information. In this study patients with bipolar disorder and healthy volunteers were compared in terms of jumping to conclusions bias using the beads in the jar task.Methods: 37 patients with DSM-5 diagnosis of bipolar disorder and 30 healthy controls were tested with the Beads Task (BT), Tower of London Test (ToL) and Barrat Impulsiveness Scale (BIS).Results: In the BT, the mean score of DtD (draws to decision) and JTC (jumping to conclusions) scores were not statistically different between the two groups. In the ToL test, the duration of the total execution and the total time were significantly longer in the bipolar group than the control group. BIS scores were significantly higher in the bipolar group. YMRS (Young Mania Rating Scale) scores were not correlated with BT.Conclusions: This study is the first clinical study to assess the jumping to conclusions bias in patients with bipolar disorder. No JTC bias was detected in bipolar disorder. Further studies may assess JTC in larger samples to determine the effects of clinical state changes, psychotic symptoms, medication and impulsivity.

A reverse-engineering methodology for medical enhancement processes

Abstract This study was initiated for the benefit of the Tunisian Ministry of Health and the Informatics Centre of the Ministry of Health (CIMSP). The scope of our study is restricted to two university hospitals: HUC Habib Thameur considered as pilot institution and the University Hospital Charles Nicolle. We have identified the hospitalized patient pathway with additional acts” process as a typical process for conducting this study. The objective of this paper is to propose a quality assurance approach for automating and managing hospital business processes. This is to show how to build a framework for an existing process in order to evaluate it and analyse it. In particular, we are looking into identifying the process’s operational limits, its malfunctioning and shortcoming, its degree of ICT integration and finally we are interested in evaluating the process’s quality when deployed on different health care sites. It is in this sense that we propose, in this work, to put in place an approach for managing hospital business processes. This approach contributes first to ensuring reliable monitoring of the processes by obtaining an overview of each one. Second, it helps to precisely measure the minimum and maximum duration of execution of the process. Third, we also aim to identify the formal and informal actors involved and validate their commitment and expertise with relation to the implementation of the process. We chose to use Business Process Modelling and Notation (BPMN) [13] and UML for our business processes modelling. Both technologies are recognized in the industrial world and are recommended by a wide audience for formal definition, documentation and understanding of the hospital business process. Finally, the proposed approach can also be exploited for the development of new processes as extension or enhancement to the existing ones. The resulting models will be used as a framework for actors centred process management and evaluation.

Comparative analgesic efficacy of ultrasound-guided nerve blocks induced by three anesthetics with different duration of action in the treatment of resistant neuropathic pain in the lower extremities

Background/Aim. The neuropathic pain (NP) treatment is a big medical and socioeconomical problem. The new sorts of the NP treatment was developed and are applied in case of a medical treatment failure. The aim of this work was to investigate the efficacy of the ultrasound-assisted treatment of the resistant and chronic peripheral neuropathic pain with the local anesthetic nerve blocks. Due to the inefficacy of conventional treatment, three local anesthetics (shortacting, medium-term and long-acting) were administered in a series of the same minimal dose on a daily basis. Complications, side effects, the execution time of procedure and the onset time of local anesthetic were also investigated. Methods. In this prospective, randomized and doubleblinded study, 108 patients (of which 53 were diagnosed with diabetes and 55 with radiculopathy) with the resistant and chronic peripheral neuropathic pain in the lower extremities were treated with a series of ultra-sound assisted peripheral nerve blocks. The conventional treatment was exhausted. The presence of this neuropathic pain was confirmed by, at least, one of the three scales ? the Leeds Assesment of Neuropathic Simptoms and Signs (LANSS) scale, the Dolour Neuropathic 4 questions (DN4) scale and the pain DETECT(PD-Q) scale. Other therapies were not applied. The nerve blocks were administered on a daily basis until the relief of pain (visual analogue scale ? VAS < 30), and after that, two additional nerve blocks were given. The three local anesthetics of the different duration of therapeutic effect were given at the same minimal dose: the schortacting (1% procaine-chloride solution), medium-term (1% lidocaine-chloride solution) and long-acting (0.25% levobupivacaine-chloride solution) local anesthetics were used. The therapeutic efficacy was measured with the percentage reduction in the pain intensity on the VAS scale before and after the therapy and one month after the treatment: > 50% ? excellent results; 31?49% ? good results; < 30% the therapy did not work. The side effects, complications, the execution duration of procedure, the onset time of numbness, the number of corrections of the needle direction were recorded as well. Results. For all three groups: nerve blocks took 5.4 ? 1.48 minutes to do (withouth difference among the groups), the onset of numbness occured, on average, within 3.75 ? 2.62 minutes (withouth differences among the groups), and the need for corrections of needle direction was minimal (1.03 ? 0.17 corrections). All the patients experienced a loss of pain sensation (VAS < 30); when a long-acting anesthetic was used, the number of required nerve blocks was significant (p < 0.001) smallest (4.33 ? 0.63 blocks), than in other two groups, and the percentage pain reduction was highest (73.13%) (p < 0.001). The pain relief lasted one month after the therapy without the application of any other therapy. Neither complications nor side effects were observed. Conclusion. The procedure dercibed is a safe, efficient and easy-to-perform and does not lead to any complications and side effects. The pain relief is achieved most effectively and rapidly with the longacting local anesthetics, and maintained even for one month without the introduction of any additional therapy.

Resource Allocation and Task Offloading for Heterogeneous Real-Time Tasks With Uncertain Duration Time in a Fog Queueing System

Fog computing has become the primary infrastructure on the Internet for improving the quality of service. We consider a fog queueing system with limited infrastructure resources to accommodate real-time tasks with heterogeneities in task types and execution deadlines. Owing to the uncertain execution duration, such a fog system should jointly consider fog resource allocation and a task offloading to satisfy the deadline requirements. To consider the task heterogeneity, a parallel virtual queue model is applied to buffer each type of task in a separate queue. Subsequently, we use a framework, including three parallel algorithms, namely, offloading, buffering, and resource allocation, to improve resource allocation balance, throughput, and task completion ratio. The task offloading is decided according to the task urgencies in terms of the laxity times, which accounts for the deadline, estimated execution time, and transmission delay to the cloud. The buffering process rearranges the arriving tasks based on their laxity time and the estimated task execution time at the fog tier. The resource allocation uses an adaptive queue weight based on the Lyapunov drift to avoid task starvation that may lead to a long queueing delay for tasks with long execution time. The simulation results indicate that our proposed policies can avoid task starvation and yields a tradeoff between high throughput and a high task completion ratio.

Strength Training Session Induces Important Changes on Physiological, Immunological, and Inflammatory Biomarkers

Strength exercise is a strategy applied in sports and physical training processes. It may induce skeletal muscle hypertrophy. The hypertrophy is dependent on the eccentric muscle actions and on the inflammatory response. Here, we evaluate the physiological, immunological, and inflammatory responses induced by a session of strength training with a focus on predominance of the eccentric muscle actions. Twenty volunteers were separated into two groups: the untrained group (UTG) and the trained group (TG). Both groups hold 4 sets of leg press, knee extensor, and leg curl at 65% of personal one-repetition maximum (1RM), 90 s of recovery, and 2″conc/3″eccen of duration of execution in each repetition. Blood samples were collected immediately before and after, 2 hours after, and 24 h after the end of the exercise session. The single session of strength training elevated the heart rate (HR), rating of perceived exertion (RPE), visual analog scale (VAS), and lactate blood level in UTG and TG. Creatine kinase (CK) levels were higher at 2 and 24 h after the end of the exercise in UTG and, in TG, only at 24 h. The number of white blood cells (WBC) and neutrophils increased in UTG and TG, post and 2 h after exercise. Lymphocytes increased postexercise but reduced 2 h after exercise in both groups, while the number of monocytes increased only immediately after the exercise session in UTG and TG. The strength training session elevated the levels of apelin and fatty acid-binding proteins-3 (FABP3) in both groups and brain-derived neurotrophic factor (BDNF) in TG. The single exercise session was capable of inducing elevated HR, RPE, lactate level, and CK levels. This protocol changed the count/total number of circulating immune cells in both groups (UTG and TG) and also increased the level of plasmatic apelin, BDNF, and FLTS1 only in TG and FABP3 myokines in both groups.

The hybrid neural model to strengthen the e-nose restricted in real complex conditions

The assessment sensors’ signals, noised in real complex condition, is a serious problem, which restrains the performance of the neural model application laboratory in its real application. Indeed, the Self-Organizing Maps (SOM) and neural multilayer perceptron (MLP) are fused to reinforce the olfactory devices power for optimum pollutants identification. As soon as the SOM is developed, with the whole key parameters, carefully selected (as Epanichnikov kernel function), to automatic elimination of uninformative signals, the few useful signals are MLP trained to optimally determine the model to improve the results performance. Fast precise identification, short execution duration, small local data, having strong signals selected, are all required to attenuate the sensors several criticalities emerged from the lowest content (1ppm) of interfering mixed gases at relative humidity presence. Moreover, the practical application of this hybrid tool on 1ppm concentration has another advantage to ensure the air quality, either in critical condition control or in safety.

Analysis of Delays and Extension of Execution Duration of a Road Project

Abstract The implementation of road infrastructure projects often results in delays due to objective causes, with repercussions on the final execution deadline and with value implications. The use of critical path method for planning and the executin windows, will result in better time process management and optimization delays.

An evaluation of the state of time synchronization on leadership class supercomputers

SummaryWe present a detailed examination of time agreement characteristics for nodes within extreme‐scale parallel computers. Using a software tool we introduce in this paper, we quantify attributes of clock skew among nodes in three representative high‐performance computers sited at three national laboratories. Our measurements detail the statistical properties of time agreement among nodes and how time agreement drifts over typical application execution durations. We discuss the implications of our measurements, why the current state of the field is inadequate, and propose strategies to address observed shortcomings.

Performance Evaluation of Passive Haptic Feedback for Tactile HMI Design in CAVEs.

This article presents a comparison of different haptic systems, which are designed to simulate flat Human Machine Interfaces (HMIs) like touchscreens in virtual environments (VEs) such as CAVEs, and their respective performance. We compare a tangible passive transparent slate to a classic tablet and a sensory substitution system. These systems were tested during a controlled experiment. The performance and impressions from 20 subjects were collected to understand more about the modalities in the given context. The results show that the preferences of the subjects are strongly related to the use-cases and needs. In terms of performance, passive haptics proved to be significantly useful, acting as a space reference and a real-time continuous calibration system, allowing subjects to have lower execution durations and relative errors. Sensory substitution induced perception drifts during the experiment, causing significant performance disparities, demonstrating the low robustness of perception when spatial cues are insufficiently available. Our findings offer a better understanding on the nature of perception drifts and the need of strong multisensory spatial markers for such use-cases in CAVEs. The importance of a relevant haptic modality specifically designed to match a precise use-case is also emphasized.

A Novel UML Based Approach for Early Detection of Change Prone Classes

This article describes how predicting change-prone classes is essential for effective development of software. Evaluating changes from one release of software to the next can enhance software quality. This article proposes an efficient novel-based approach for predicting changes early in the object-oriented software. Earlier researchers have calculated change prone classes using static characteristics such as source line of code e.g. added, deleted and modified. This research work proposes to use dynamic metrics such as execution duration, run time information, regularity, class dependency and popularity for predicting change prone classes. Execution duration and run time information are evaluated directly from the software. Class dependency is obtained from UML2.0 class and sequence diagrams. Regularity and popularity is acquired from frequent item set mining algorithms and an ABC algorithm. For classifying the class as change-prone or non-change-prone class an Interactive Dichotomizer version 3 (ID3) algorithm is used. Further validation of the results is done using two open source software, OpenClinic and OpenHospital.

Contribution of the supplementary motor area and the cerebellum to the anticipatory postural adjustments and execution phases of human gait initiation

Several brain structures including the brainstem, the cerebellum and the frontal cortico-basal ganglia network, with the primary and premotor areas have been shown to participate in the functional organization of gait initiation and postural control in humans, but their respective roles remain poorly understood. The aim of this study was to better understand the role of the supplementary motor area (SMA) and posterior cerebellum in the gait initiation process. Gait initiation parameters were recorded in 22 controls both before and after continuous theta burst transcranial stimulation (cTBS) of the SMA and cerebellum, and were compared to sham stimulation, using a randomized double-blind design study. The two phases of gait initiation process were analyzed: anticipatory postural adjustments (APAs) and execution, with recordings of soleus and tibialis anterior muscles. Functional inhibition of the SMA led to a shortened APA phase duration with advanced and increased muscle activity; during execution, it also advanced muscle co-activation and decreased the duration of stance soleus activity. Cerebellar functional inhibition did not influence the APA phase duration and amplitude but increased muscle co-activation, it decreased execution duration and showed a trend to increase velocity, with increased swing soleus muscle duration and activity. The results suggest that the SMA contributes to both the timing and amplitude of the APAs with no influence on step execution and the posterior cerebellum in the coupling between the APAs and execution phases and leg muscle activity pattern during gait initiation.

Method for creating a work management plan of a construction company

ABSTRACTThis article indicates the place and the role of a work management plan in the creation of an annual production programme of a construction company. It contains the list of documents and the procedure for their formalization, as well as the list of initial documents, including both perspective and operational data. It reveals the algorithm for developing a consolidated annual work plan that links all the facilities to be built based on the balance between the labour intensity of the main activity with the highest unit weight in terms of volume and duration of execution, and the capacity of the construction company. It describes the conditions for minimizing losses in the value of personnel when performing other activities. It also considers the options and the ways for making decisions in different assessments of consolidated annual work plan of a construction company, as well as the methods for linkage and combined execution of activities sharing the same work area.

Bidding Strategy and Cash Flow Forecasting in Private Construction Companies in Iraq

The sector of Private Construction Companies is one of the most important sectors in construction market in IRAQ. This sector played an important role in the last ten years in the Iraqi construction field. The idea of this research came from the hardly competitive bidding among these many private companies, and because of the lack of knowledge by many of these companies about the bidding strategy theories. This research is a trial to create a balanced condition of the bidding price for the contractor. The average bidding strategy method depends on historical data for the bidders and it is a relationship between the added percentage of profit and the winning probability. An important factor is inserted in this research, which is the maximum fiscal deficit that is facing the contractor during construction period of any project; this deficit is the difference between the received discounted payments and the cost of finished works for any period during construction. The contractor apply the bidding strategy method to lower his profit margin to the lowest certain extent to rise the opportunity to win the contract. Nevertheless, he forget that the lowest profit margin leads to highest cash deficit during construction. A survey was done for a contract construction company in the private sector in Iraq, where the competition is more clearly than the governmental sector, by collecting data for (5) competitive companies in (16) projects. By using the average bid method, to determine the added (12%) of profit the winning probability was (9%), and from the analysis of the cash flow forecasting curve the maximum fiscal deficit will be IQD (8,972,000) at the second month of the project execution duration. By applying the resultant equation and to lower the deficit through rising profit by (0.1%) the winning opportunity will be decrease by (0.6%). In this research, a relationship is drawn between the profit margin and the maximum deficit for project, and finally a relationship is drawn between the deficit and the winning opportunity of the contract. Both of these two relationships are linear, and the important results are that any contract should apply both average bid method and cash deficit method at the same time, according to the economic condition to its firm.

Standardized Sampling Plan for the Thrips Frankliniella schultzei (Thysanoptera: Thripidae) on Watermelon Crops.

Sampling plans are essential components of integrated pest management programs. The thrips Frankliniella schultzei (Trybom) (Thysanoptera: Thripidae) is an important pest of watermelon crops. Despite the importance of sampling plans and of F. schultzei as a pest of watermelon crops, no research has been previously conducted on this subject for this crop. The objective of this work was to create a standardized sampling plan for F. schultzei in watermelon crops. Over two consecutive years, weekly samplings were performed in commercial watermelon crops. The aim of these assessments was to select the best sampling unit and the best sampling technique for F. schultzei assessment and to determine the number of samples necessary for a standardized sampling plan for this pest. In watermelon crops in the vegetative, flowering, and fruiting stages, the ideal location for sampling F. schultzei was the most apical leaf of the branches. The best sampling technique was a direct count of F. schultzei individuals. The F. schultzei sampling plan involved the evaluation of 69 samples per plot. The execution duration of this sampling plan in 1- to 15-ha plots was <1 h and was inexpensive (<US$ 2 per sampling). This has not been reported for watermelon before.

Using contextualized activity-level duration to discover irregular process instances in business operations

Effective time management is one of the most crucial characteristics of a successful business. For most businesses, time management is an area that has much scope for further improvement. Irregularities in the execution duration of business processes impede corporate agility and can incur severe consequences, such as project failures and financial losses. Efficient managers must constantly identify potential irregularities in process durations to anticipate and avoid process glitches. This paper proposed a k-nearest neighbor method for systematically detecting irregular process instances in a business using a comprehensive set of activity-level durations, namely execution, transmission, queue, and procrastination durations. Moreover, because agents, customers, and other variables influence the progress of processes, contextual information was presented using fuzzy values. The values and corresponding membership functions were used to adjust the durations of each activity. This proposed method was applied to the system logs of a medium-sized logistics company to identify irregularities. Experts confirmed that 81% of the identified irregular instances were abnormal.

Hierarchical task network-based emergency task planning with incomplete information, concurrency and uncertain duration

This paper focuses on the emergency task planning problem with the following characteristics: incomplete initial environment information, concurrent execution and uncertain execution durations. To address this problem, the conditional temporal hierarchical task network (HTN) planning with uncertain durations should be investigated. However, the research work on conditional HTN planning mainly concentrates on the planning domain without temporal features and pays no attention to the handling of concurrency and uncertain durations. This motivates us to propose a planning paradigm based on the conditional HTN planning. The planning paradigm incorporates a temporal reasoning technique suitable for conditional HTN planning to achieve concurrency and a temporal management approach to confirm the satisfiability of temporal constraints efficiently. For temporal reasoning, rules for generating temporal constraints are designed to avoid three types of flaws due to interactions between durative actions; a mechanism for detecting invalid temporal constraints is also presented. Regarding temporal management, Conditional Simple Temporal Network with Uncertainty (CSTNU) is utilized to represent the temporal constraints involving uncontrollable intervals and observations, and an approach for eliminating redundant temporal constraints is proposed to reduce the temporal constraint to be represented in a CSTNU to promote efficiency. Finally, an experimental study of an earthquake rescue domain demonstrates the viability of the proposed planning paradigms.

A speculative approach to spatial‐temporal efficiency with multi‐objective optimization in a heterogeneous cloud environment

AbstractA heterogeneous cloud system, for example, a Hadoop 2.6.0 platform, provides distributed but cohesive services with rich features on large‐scale management, reliability, and error tolerance. As big data processing is concerned, newly built cloud clusters meet the challenges of performance optimization focusing on faster task execution and more efficient usage of computing resources. Presently proposed approaches concentrate on temporal improvement, that is, shortening MapReduce time, but seldom focus on storage occupation; however, unbalanced cloud storage strategies could exhaust those nodes with heavy MapReduce cycles and further challenge the security and stability of the entire cluster. In this paper, an adaptive method is presented aiming at spatial–temporal efficiency in a heterogeneous cloud environment. A prediction model based on an optimized Kernel‐based Extreme Learning Machine algorithm is proposed for faster forecast of job execution duration and space occupation, which consequently facilitates the process of task scheduling through a multi‐objective algorithm called time and space optimized NSGA‐II (TS‐NSGA‐II). Experiment results have shown that compared with the original load‐balancing scheme, our approach can save approximate 47–55 s averagely on each task execution. Simultaneously, 1.254‰ of differences on hard disk occupation were made among all scheduled reducers, which achieves 26.6% improvement over the original scheme. Copyright © 2016 John Wiley &amp; Sons, Ltd.

Detecting obfuscated malware using reduced opcode set and optimised runtime trace

The research presented, investigates the optimal set of operational codes (opcodes) that create a robust indicator of malicious software (malware) and also determines a program’s execution duration for accurate classification of benign and malicious software. The features extracted from the dataset are opcode density histograms, extracted during the program execution. The classifier used is a support vector machine and is configured to select those features to produce the optimal classification of malware over different program run lengths. The findings demonstrate that malware can be detected using dynamic analysis with relatively few opcodes.

Influence of Radiation and Convective Types of Heat Exchange on the Necessary Duration of Temperature Measurement by Thermocouples

Results of research of influence of radiation heat exchange on duration of execution of measurement high темератур are given by thermocouples, influence of the free convection on results of temperature measurement is also considered by the thermocouples set in protective sleeves with a gap. Researches showed that radiation heat exchange leads to lowering of duration of heating of the thermocouple to 30% whereas the free convection in a protective sleeve practically doesn’t exert impact on process of heating up of the sensor.

Scalable wake-up of multi-channel single-hop radio networks

We consider single-hop radio networks with multiple channels as a model of wireless networks. There are n stations connected to b radio channels that do not provide collision detection. A station uses all the channels concurrently and independently. Some k stations may become active spontaneously at arbitrary times. The goal is to wake up the network, which occurs when all the stations hear a successful transmission on some channel. Duration of a waking-up execution is measured starting from the first spontaneous activation. We present a deterministic algorithm that wakes up a network in O(klog1/b⁡klog⁡n) time, where k is unknown. We give a deterministic scalable algorithm for the special case when b>dlog⁡log⁡n, for some constant d>1, which wakes up a network in O(kblog⁡nlog⁡(blog⁡n)) time, with k unknown. This algorithm misses time optimality by at most a factor of O(log⁡n(log⁡b+log⁡log⁡n)), because any deterministic algorithm requires Ω(kblog⁡nk) time. We give a randomized algorithm that wakes up a network within O(k1/bln⁡1ϵ) rounds with a probability that is at least 1−ϵ, for any 0<ϵ<1, where k is known. We also consider a model of jamming, in which each channel in any round may be jammed to prevent a successful transmission, which happens with some known parameter probability p, independently across all channels and rounds. For this model, we give two deterministic algorithms for unknown k: one wakes up a network in time O(log−1⁡(1p)klog⁡nlog1/b⁡k), and the other in time O(log−1⁡(1p)kblog⁡nlog⁡(blog⁡n)) when the inequality b>log⁡(128blog⁡n) holds, both with probabilities that are at least 1−1/poly(n).