Proposed Decision Algorithm Research Articles

Game-Based Vehicle Strategy Equalization Algorithm for Unsignalized Intersections

To address the coordination issue of connected autonomous vehicles (CAVs) at unsignalized intersections, this paper proposes a game-theory-based distributed strategy equalization algorithm. To begin, the vehicles present in the scene are conceptualized as participants in a game theory. The decision-payoff function takes into account three critical performance indicators: driving safety, driving comfort, and driving efficiency. Then, virtual logic lines connect the front and rear extremities of vehicles with odd and even numbers at the intersection to create a virtual logic ring. By dividing the virtual logic ring into numerous overlapping game groups, CAVs can engage in negotiation and interaction within their respective game groups. This enables the revision of action strategies and facilitates interaction between the overlapping game groups. A further application of the genetic algorithm (GA) is the search for the optimal set of strategies in constrained multi-objective optimization problems. The proposed decision algorithm is ultimately assessed and certified through a collaborative simulation utilizing Python and SUMO. In comparison to the first-come, first-served algorithm and the cooperative driving model based on cooperative games, the average passing delay is decreased by 40.7% and 6.17%, respectively, resulting in an overall improvement in the traffic system’s passing efficiency.

Decision-making in surgical study designs: a proposed decision algorithm to aid in the selection of an appropriate research study design for a given surgical intervention: the PERFECT tool.

Cite this article: Bone Joint Res 2023;12(9):598–600.

Early Switch From Intravenous to Oral Antibiotics in Skin and Soft Tissue Infections: An Algorithm-Based Prospective Multicenter Pilot Trial.

BackgroundIn hospitalized patients with skin and soft tissue infections (SSTIs), intravenous (IV) empiric antibiotic treatment is initiated. The best time point for switching from IV to oral treatment is unknown. We used an algorithm-based decision tree for the switch from IV to oral antibiotics within 48 hours and aimed to investigate the treatment outcome of this concept.MethodsIn a nonrandomized trial, we prospectively enrolled 128 patients hospitalized with SSTI from July 2019 to May 2021 at 3 institutions. Clinical and biochemical response data during the first week and at follow-up after 30 days were analyzed. Patients fulfilling criteria for the switch from IV to oral antibiotics were assigned to the intervention group. The primary outcome was a composite definition consisting of the proportion of patients with clinical failure or death of any cause.ResultsNinety-seven (75.8%) patients were assigned to the intervention group. All of them showed signs of clinical improvement (ie, absence of fever or reduction of pain) within 48 hours of IV treatment, irrespective of erythema finding or biochemical response. The median total antibiotic treatment duration was 11 (interquartile range [IQR], 9–13) days in the invention group and 15 (IQR, 11–24) days in the nonintervention group (P < .001). The median duration of hospitalization was 5 (IQR, 4–6) days in the intervention group and 8 (IQR, 6–12) days in the nonintervention group (P < .001). There were 5 (5.2%) failures in the intervention group and 1 (3.2%) in the nonintervention group after a median follow-up of 37 days.ConclusionsIn this pilot trial, the proposed decision algorithm for early switch from IV to oral antibiotics for SSTI treatment was successful in 95% of cases. Clinical Trials Registration. ISRCTN15245496

Human-like driving decision at unsignalized intersections based on game theory

Unsignalized intersection driving is challenging for automated vehicles. For safe and efficient performances, the diverse and dynamic behaviors of interacting vehicles should be considered. Based on a game-theoretic framework, a human-like payoff design methodology is proposed for the automated decision at unsignalized intersections. Prospect Theory is introduced to map the objective collision risk to the subjective driver payoffs, and the driving style can be quantified as a tradeoff between safety and speed. To account for the dynamics of interaction, a probabilistic model is further introduced to describe the acceleration tendency of drivers. Simulation results show that the proposed decision algorithm can describe the dynamic process of two-vehicle interaction in limit cases. Statistics of uniformly-sampled cases simulation indicate that the success rate of safe interaction reaches 98%, while the speed efficiency can also be guaranteed. The proposed approach is further applied and validated in four-vehicle interaction scenarios at a four-arm intersection.

POSC314 Indirect Treatment Comparison: A Proposed Decision Algorithm to Define the Best Approach

POSC314 Indirect Treatment Comparison: A Proposed Decision Algorithm to Define the Best Approach

Decision making for highway complex scenario by improved safety field with learning process

To improve the agility and efficiency of the highway decision-making system and overcome the local optimal dilemma of the existing safety field, this paper builds an improved safety field to reflect the advantage of the reachable states and the learning process is further employed to make the decision long-term optimal. Firstly, the improved safety field is prepared by the kinematic model-based prediction of surrounding vehicles and the boundary is determined elaborately to ensure real-time performance. Then, the field is constructed by three individual fields. One is the kinematic field, which is built based the safe-distance model to measure the colliding risk of both moving or no-moving objects accurately. Another is the road field that reflects the lane-marker constraint. The last is the efficiency field, which is introduced creatively to improve efficiency. Furthermore, the learning algorithm is adopted to learn the long-term optimal state-action sequence in the safety field. Finally, the simulations are conducted in Prescan platform to validate the feasibility of the improved safety field in complex scenarios. The results show that the proposed decision algorithm can always drive autonomous vehicle to the state with a long-term optimal payoff and can improve the overall performance compared to the existing pure safety field and the interaction-aware method.

Providing Predictable Quality of Service in a Cloud-Based Web System

Cloud-computing web systems and services revolutionized the web. Nowadays, they are the most important part of the Internet. Cloud-computing systems provide the opportunity for businesses to undergo digital transformation in order to improve efficiency and reduce costs. The sudden shutdown of schools and offices during the pandemic of Covid 19 significantly increased the demand for cloud solutions. Load balancing and sharing mechanisms are implemented in order to reduce the costs and increase the quality of web service. The usage of those methods with adaptive intelligent algorithms can deliver the highest and a predictable quality of service. In this article, a new HTTP request-distribution method in a two-layer architecture of a cluster-based web system is presented. This method allows for the provision of efficient processing and predictable quality by servicing requests in adopted time constraints. The proposed decision algorithms utilize fuzzy-neural models allowing service times to be estimated. This article provides a description of this new solution. It also contains the results of experiments in which the proposed method is compared with other intelligent approaches such as Fuzzy-Neural Request Distribution, and distribution methods often used in production systems.

Aeromedical disposition dilemma: Renal calculi

Renal colic is a condition which causes acute pain of variable intensity. At times, this makes the sufferer visibly powerless and prevents him from performing any skilled task satisfactorily. The most common cause of the symptom is related to a calculus, which is moving inside the ureter inducing ureteral spasm. A military aircrew is declared unfit to fly in case he/she is detected to have renal calculi. At present, with the newer and advanced investigation techniques, the detection of even small renal calculi is possible. This has led to an increase in clinical data. Since the clinical outcome of renal calculi is unpredictable, aeromedical disposition becomes a challenging task for such cases. The paper brings a review of existing disposition guidelines for cases of renal calculi both in the military and civil aviation in different parts of the globe. An attempt is also made to present an approach toward aeromedical certification and surveillance in the form of a proposed decision algorithm to be used by the flight surgeon.

S1055 Decreased Time to Diagnostic Paracentesis in the Hospitalized Internal Medicine Patient

INTRODUCTION: Early diagnostic paracentesis decreases mortality, length of stay, readmission rates and cost of hospitalization. We sought to decrease the time to initial diagnostic paracentesis to below 24 hours at our institution over three months. METHODS: We reviewed data from medicine admissions at our hospital between September 2018 and September 2019. Any patient admitted with ascites was included. Interventions included education for internal medicine residents and faculty, a knowledge and barrier survey, a diagnostic paracentesis checklist and kit for efficiency, and education for emergency department providers with a proposed decision algorithm. Our intervention implementation date was December 1st, 2019. We collected post-intervention data from December 2019 through February 2020. RESULTS: Our pre-intervention average time to paracentesis was 37.8 hours. Spontaneous bacterial peritonitis (SBP) was diagnosed in 16.6% of pre-intervention cases. The post-intervention average time from December to February was 21.6, 32.4 and 17.3 hours for each respective month with a total average of 24.3 hours for the three-month period. There was a total of 79 paracenteses completed and 9 cases of SBP (11.4%). Pre-intervention, the emergency department (ED) completed 20.4% of the paracenteses with a 9.2 hour average which improved to 34.2% at 7.3 hours post-intervention. The primary medicine team improved from 33.6 hour to 27.1 hour with completion of 26.6% of the cases. The medicine procedure team improved from 47.8 hour to 38.5 hour with completion of 10.1% of the cases. Interventional radiology improved from 51.6 hour to 36.8 hour with 29.1% of the cases. CONCLUSION: We were close to achieving our targeted goal of time to diagnostic paracentesis for the hospitalized internal medicine patients by decreasing the time to diagnostic paracentesis from 37.8 to 24.3 hours. This effectively decreased the time by 13.5 hours for patients on average. Each specialty involved improved on their average time with our interventions. The ED performed more paracenteses in the post-intervention period, taking some burden off of the internal medicine physicians. We project that because the patients we collected data on were admitted to the hospital, this effectively decreased their length of stay by at least half a day which is considered a positive return on investment for the hospital. Further investigation is required to determine the other benefits of improving the time to paracentesis in our institution.Image 1.: Weekly average time to diagnotic paracentesis from pre-intervention time through post-intervention time.Image 2.: Number of paracenteses completed by department in post-intervention data.

Is nonanatomic rectal resection a valid therapeutic option for rectal gastrointestinal stromal tumors? A proposed decision algorithm.

The best surgical approach to rectal gastrointestinal stromal tumors (GISTs) is still debated, and both nonanatomic rectal resection (NARR) and anatomic rectal resection (ARR) are applied. The aim of this study was to evaluate the feasibility and oncological outcomes of NARR and ARR for rectal GISTs (R-GISTs). Through a large French multicentre retrospective study, 35 patients were treated for R-GIST between 2001 and 2013. Patients who underwent NARR and ARR were compared. There were 23 (65.7%) patients in group ARR and 12 (34.3%) in group NARR. Significantly more patients in the group with ARR had a neoadjuvant treatment (86%) with tyrosine kinase inhibitor (TKI) (imatinib) compared to those with NARR (25%) (p < .01). The median preoperative tumor size was significantly different between the groups without and with neoadjuvant TKI: 30 ± 23 mm versus 64 ± 44.4 mm, respectively (p < .001). Overall postoperative morbidity was 20% (n = 7) (26% for ARR vs. 8% for NARR; p = .4). After a median follow-up of 60.2 (3.2-164.3) months, the 5-year disease-free survival rates were 79.5% (confidence interval [CI] 95%: 54-100) for the NARR group and 68% (CI 95%: 46.4-89.7) for the ARR group (p = .697), respectively. The use of NARR for small R-GIST's does not seem to impair the oncological prognosis.

A Topological Approach to Secure Message Dissemination in Vehicular Networks

Secure message dissemination is an important issue in vehicular networks, especially considering the vulnerability of vehicle-to-vehicle message dissemination to malicious attacks. Traditional security mechanisms, largely based on message encryption and key management, can only guarantee secure message exchanges between a known source and destination pairs. In vehicular networks, however, every vehicle may learn its surrounding environment and contributes as a source, while in the meantime, acting as a destination or a relay of information from other vehicles, and message exchanges often occur between “stranger” vehicles. This makes secure message dissemination against malicious tampering much more intricate. For secure message dissemination in vehicular networks against insider attackers, who may tamper the content of the disseminated messages, ensuring the consistency and integrity of the transmitted messages becomes a major concern which the traditional message encryption and key management-based approaches fall short to provide. However, it is challenging for a vehicle to distinguish which message is true when the messages received from multiple nearby vehicles are conflicting. In this paper, by incorporating the underlying network topology information, we propose an optimal decision algorithm that is able to maximize the chance of making a correct decision on the message content, assuming the prior knowledge of the percentage of malicious vehicles in the network. Furthermore, a novel heuristic decision algorithm is proposed that can make decisions without the aforementioned knowledge of the percentage of malicious vehicles. The simulations are conducted to compare the security performance achieved by our proposed decision algorithms with that achieved by the existing ones that do not consider or only partially consider the topological information to verify the effectiveness of the algorithms. Our results show that by incorporating the network topology information, the security performance can be much improved. This paper sheds light on the optimum algorithm design for secure message dissemination.

Detecting life signatures with RNA sequence similarity measures

The RNA World is currently the most plausible hypothesis for explaining the origins of life on Earth. The supporting body of evidence is growing and it comes from multiple areas, including astrobiology, chemistry, biology, mathematics, and, in particular, from computer simulations. Such methods frequently assume the existence of a hypothetical species on Earth, around three billion years ago, with a base sequence probably dissimilar from any in known genomes. However, it is often hard to verify whether or not a hypothetical sequence has the characteristics of biological sequences, and is thus likely to be functional. The primary objective of the presented research was to verify the possibility of building a computational ‘life probe’ for determining whether a given genetic sequence is biological, and assessing the sensitivity of such probes to the signatures of life present in known biological sequences. We have proposed decision algorithms based on the normalized compression distance (NCD) and Levenshtein distance (LD). We have validated the proposed method in the context of the RNA World hypothesis using short genetic sequences shorter than the error threshold value (i.e., 100 nucleotides). We have demonstrated that both measures can be successfully used to construct life probes that are significantly better than a random decision procedure, while varying from each other when it comes to detailed characteristics. We also observed that fragments of sequences related to replication have better discriminatory power than sequences having other molecular functions. In a broader context, this shows that the signatures of life in short RNA samples can be effectively detected using relatively simple means.

Research on intelligent collision avoidance decision-making of unmanned ship in unknown environments

To solve the problem of intelligent collision avoidance by unmanned ships in unknown environments, a deep reinforcement learning obstacle avoidance decision-making (DRLOAD) algorithm is proposed. The problems encountered in unmanned ships’ intelligent avoidance decisions are analyzed, and the design criteria for a proposed decision algorithm are put forward. Based on the Markov decision process, an intelligent collision avoidance model is established for unmanned ships. The optimal strategy for an intelligent decision system is determined through the value function which maximizes the return for the mapping of the in unmanned ship’s state to behavior. A reward function is specifically designed for obstacle avoidance, approaching a target and safety. Finally, simulation experiments are carried out in multi-state obstacle environments, demonstrate the effectiveness of the proposed DRLOAD algorithm.

Doppler Echocardiography for the Estimation of LV Filling Pressure in Patients With Mitral Annular Calcification

ObjectivesThis study sought to identify Doppler parameters useful for the assessment of left ventricular filling pressure (LVFP) in patients with mitral annular calcification (MAC) and to develop and validate a decision algorithm for assessing LVFP in such patients. BackgroundPredicting LVFP in the presence of MAC is problematic. MethodsProspectively, 50 patients with MAC (mean 72 ± 11 years of age) underwent a complete Doppler echocardiographic study and right or left heart catheterization. Standard and nonstandard parameters of ventricular filling and relaxation were correlated with LVFP. Classification and regression tree analysis was used to develop a decision tree for prediction of LVFP. Validation was performed prospectively using an additional cohort with MAC and invasive hemodynamics (n = 21). ResultsIn the initial study group, 26 patients had mild MAC, and 24 had moderate or severe MAC. Mean LVFP was 17.0 ± 8.1 mm Hg (range 4 to 50 mm Hg). Of the variables tested, the best predictor of LVFP was the ratio of early-to-late diastolic filling velocity (mitral E/A) (r = 0.66; p < 0.001). This finding was observed in subjects with mild as well as moderate-to-severe MAC. Importantly, the ratio of early diastolic filling velocity-to-mitral annulus velocity (E/e′) demonstrated weak correlation (r = 0.42; p = 0.003). A clinical algorithm using mitral E/A and isovolumic relaxation time (IVRT) was associated with good specificity (100%) and positive predictive value (100%), and moderate sensitivity (81%) and negative predictive value (67%) for high LVFP. Validation of the clinical algorithm in a separate prospective cohort yielded a diagnostic accuracy of 94%. ConclusionsThe E/e′ ratio should not be used to estimate LVFP in subjects with significant MAC. However, mitral E/A ratio and IVRT are useful predictors of LVFP in this patient population. The proposed decision algorithm combining these Doppler parameters is accurate in estimating LVFP in patients with MAC.

Optimized decision algorithm for Information Centric Networks

Information Centric Networks (ICN) enable network, server context and user context-awareness, to achieve an enhanced architecture for the delivery of the multimedia content. The information comes from different sources and serves as input for the decision algorithms for choosing the pertinent configuration such as the best server or the suitable delivery path. Therefore, the relevance of the input information and the efficiency of the decision algorithms are both crucial for the system performance. This paper proposes exploiting the multi-criteria optimization algorithms in the context of the ICN. Based on the approach of the reference level decision, an optimized algorithm is proposed, which considers the impact of different network and server parameters, and dynamically adapts the decision to the current state of the system. The additional contribution of the paper is comprehensive video content consumption simulation model, which represents large scale network. This model was designed to compare effectiveness of decision algorithms proposed for ICN. The presented simulation results prove effectiveness of proposed decision algorithm and suggest its deployment on the future media networks.

AN INTELLIGENT VERTICAL HANDOVER DECISION ALGORITHM FOR WIRELESS HETEROGENEOUS NETWORKS

The Next Generation Wireless Networks (NGWN) should be compatible with other communication technologies to offer the best connectivity to the mobile terminal which can access any IP based servi ces at any time from any network without the knowledge of its user. It requires an intelligent vertical hando ver decision making algorithm to migrate between technologies that enable seamless mobility, always best connection and minimal terminal power consumption. Currently existing decision engines are simple, proprietary and its handover is only based on the r eceived signal strength which has been proven unintelligent. The proposed decision algorithm gain s intelligence by combining fuzzy logic system to handle imprecise data, multiple attribute decision making to handle multiple attributes for decision m aking and context aware strategies to reduce unnecessary handover. The proposed intelligent decision algorit hm detects new network which offers best connectivity than current network and does authentication and mobile IP registration before making the handover; thereby reducing the packet loss to ensure high qua lity of service. This algorithm is capable of forwarding data packets to appropriate attachment point to maximize battery lifetime and also to maintain load balancing. The performance analysis shows that the proposed algorithm efficiently uses the network res ources by switching between 3G and Wi-Fi under the different RF environmental conditions to offer best connectivity with minimal service cost to the user s. It is observed that average handover delay for the experi ment is 30-40ms and the integration of cellular net work with WLAN using the proposed intelligent decision algorithm reduces the call dropping rate (<0.006) an d call blocking probability (<0.00607) as well as unn ecessary handover in heterogeneous networks.

A mathematical model for a T cell fate decision algorithm during immune response

We formulate and analyze an algorithm of cell fate decision that describes the way in which division vs. apoptosis choices are made by individual T cells during an infection. Such model involves a minimal number of known biochemical mechanisms: it basically relies on the interplay between cell division and cell death inhibitors on one hand, and membrane receptors on the other. In spite of its simplicity, the proposed decision algorithm is able to account for some significant facts in immune response. At the individual level, the existence of T cells that continue to replicate in the absence of antigen and the possible occurrence of T cell apoptosis in the presence of antigen are predicted by the model. Moreover, the latter is shown to yield an emergent collective behavior, the observed delay in clonal contraction with respect to the end of antigen stimulation, which is shown to arise just from individual T cell decisions made according to the proposed mechanism.

Traumatic sciatic paralysis after inferior gluteal artery rupture. Case report and proposed decision algorithm

; but, in exceptional circumstances, itcan be secondary to a traumatic arterial injury.We present the first case of traumatic sciatic paralysissecondary to compartment syndrome of the buttock caused byinferior gluteal artery rupture. We are proposing a decisionalgorithm designed to optimise the medical and surgical careprovided and limit sequelae.2. Case reportMr X was a 25-year-old male, athletic and with no previoushistory. Hewasinvolvedina snow-boardingaccidentand suffereda blunt force impact to the left buttock. He rapidly experiencedswelling andburningpainradiatingalongthebackofhisleftlowerextremity. At initial clinical examination, 2 h after the trauma, nohaemodynamic abnormalitywasobserved,buttherewasapainfulswelling in the left buttock with fluctuating paraesthesia in theterritory of the common fibular nerve, without associated motorsymptoms. Pelvic X-rays showed no fracture. The angiogramrevealed a haematoma in the buttock muscles (Fig. 1) withoutactive bleeding. In view of the fluctuating nature of theneurological symptoms and the absence of motor effects, thepatient was hospitalised for analgesic treatment and hourlyneurological monitoring.Fifteen hoursafterthetrauma,thepatient’sconditionworsenedrapidly, with increased hypoaesthesia and the onset of motordeficit ofthecommonfibularnerve.Undergeneralanaestheticandwith the patient in prone position, we carried out a fasciotomythrough a direct posterior, longitudinal incision and evacuated acompressive haematoma (approximately 1.5 l). Intra-operatively,the sciatic nerve was found to be contused and bleeding and therewas active arterial bleeding from the greater sciatic notch. As thebleedingcouldnotbecontrolled,itwaspackedwithahaemostaticmesh until an arteriogram could be performed. This showedbleeding from one branch of the inferior gluteal artery (Fig. 2);selective embolisation was performed, with success. Due to thedelay (2 h) between the initial surgery and embolisation, thereremained a haematoma in the buttock compressing the sciaticnerve and potentially compromising neurological recovery. It wasdecided that further surgery should be performed, through thesame incision, and this allowed the evacuation of a residual 1-lhaematoma. The transfusion of 7 units of packed red blood cellsand 2 units of fresh frozen plasma was necessary during the first24 h. The postoperative course was uneventful, with completedisappearance of motor symptoms but persistence of moderateparaesthesia in the territory of the common fibular nerve.

Dynamic Cluster Reconfiguration for Energy Conservation in Computation Intensive Service

This paper considers the problem of dynamic cluster reconfiguration for computation intensive services. In order to provide a quality-of-service in terms of overload probability, we formulate the problem of energy consumption as a constrained optimization problem, i.e., minimizing the number of active servers to reduce the energy consumption while keeping the overload probability below a desired threshold. An overload probability estimation model is derived by applying large deviation principle, and an online measurement based algorithm is developed to decide the number of servers to power on/off, which makes decision based on current workload without any prior knowledge of the workload statistics. Moreover, the proposed dynamic cluster reconfiguration algorithm iteratively adjusts the number of the active servers, instead of directly determining the number of active servers that is hard to guarantee optimality for the nonstationary workloads. Since the distribution of the workloads among the servers has an impact on potential active servers to turn off, a server scheduling strategy is proposed to collaborate with the proposed decision algorithm to achieve better energy conservation. In order to provide an integrated solution, we present an event model-based implementation to demonstrate the practical application of the proposed approach. Finally, we evaluate the performance of the scheme by using real workloads. The experimental results show the adaptability of the proposed approach to the variations in the workload and robustness of quality-of-service for nonstationary workloads.

Multi-criteria decision algorithms for efficient content delivery in content networks

Today’s Internet is prominently used for content distribution. Various platforms such as content delivery networks (CDNs) have become an integral part of the digital content ecosystem. Most recently, the information-centric networking (ICN) paradigm proposes the adoption of native content naming for secure and efficient content delivery. This further enhances the flexibility of content access where a content request can be served by any source within the Internet. In this paper, we propose and evaluate a multi-criteria decision algorithm for efficient content delivery applicable for content networks in general (among others, CDN and ICN). Our algorithm computes the best available source and path for serving content requests taking into account information about content transfer requirements, location of the consumer, location of available content servers, content server load and content delivery paths between content servers and consumer. The proposed algorithm exploits two closely related processes. The first level discovers multiple content delivery paths and gathers their respective transfer characteristics. This discovery process is based on long-term network measurements and performed offline. The second process is invoked for each content request to find the best combined content server and delivery path. The cooperation between both levels allows our algorithm to increase the number of satisfied content requests thanks to efficient utilisation of network and server resources. The proposed decision algorithm was evaluated by simulation using Internet scale network model. The results confirm the effectiveness gain of content network architectures that introduce network awareness. Moreover, the simulation process allows for a comparison between different routing algorithms and, especially, between single and multipath routing algorithms.