Terminal Problem Research Articles

Local discovery in Bayesian networks by information-connecting

<p>Local discovery plays an important role in Bayesian networks (BNs), mainly addressing PC (parents and children) discovery and MB (Markov boundary) discovery. In this paper, we considered the problem of large local discovery. First, we focused on an assumption about conditional independence (CI) tests: We explained why it was unreasonable to assume all CI tests were reliable in large local discovery, studied how the power and reliability of CI tests changed with the data size and the number of degrees of freedom, and then modified the assumption about CI tests in a more reasonable way. Second, we concentrated on improving local discovery algorithms: We posed the problem of premature termination of the forward search, analyze why it arose frequently in large local discovery when implementing the existing local discovery algorithms, put forward an idea of preventing the premature termination of forward search called information connection (IC), and used IC to build a novel algorithm called ICPC; the theoretical basis of ICPC was detailedly presented. In addition, a more steady incremental algorithm as the subroutine of ICPC was proposed. Third, the way of breaking ties among equal associations was considered and optimized. Finally, we conducted a benchmarking study by means of six synthetic BNs from various domains. The experimental results revealed the applicability and superiority of ICPC in solving the problem of premature termination of the forward search that arose frequently in large local discovery.</p>

On the nonlocal hybrid $ ({\mathsf{k}}, {\rm{\mathsf{φ}}}) $-Hilfer inverse problem with delay and anticipation

<p>This paper focused on establishing results regarding the existence of solutions for a class of nonlocal terminal value problems involving hybrid implicit nonlinear fractional differential equations with the $ ({\mathsf{k}}, {\rm{\mathsf{φ}}}) $-Hilfer fractional derivative, which includes both finite delay and anticipation arguments. Our analysis was based on the Banach fixed point technique, and the Schauder and Krasnoselskii fixed point theorems. Moreover, illustrative examples were considered to support our new results.</p>

New regularization and error estimate on terminal value problem for elliptic equations

New regularization and error estimate on terminal value problem for elliptic equations

On terminal value problem for fractional superdiffusive of Sobolev equation type

On terminal value problem for fractional superdiffusive of Sobolev equation type

REPRESENTATION IN BANKRUPTCY PROCEEDINGS (ON MATERIALS OF COURT PRACTICE)

The article deals with the issues arising when notaries certify powers of attorney in bankruptcy proceedings on behalf of financial managers and citizens in respect of whom bankruptcy proceedings have been introduced. The attention of law enforcers to the limitations provided by the current legislation in the certification of these powers of attorney is emphasized. The problem of termination of validity of the power of attorney at introduction of bankruptcy procedure in respect of the citizen is highlighted.

A Simulated Annealing Algorithm for Quay Crane Scheduling and Assignment Problem Under Uncertain Conditions

In this paper, a mixed integer programming (MIP) mathematical model was formulated for the quay crane scheduling and assignment problem (QCSAP) in container terminals with the aim of minimizing the total cost of activities. With the assumption that due to the uncertain nature of the ship’s activities and operations, we have considered most of the parameters of the problem to be indeterminate in order to bring the optimal solution closer to the real world. In this paper, the uncertain nature of the parameters was investigated by using uncertainty theory and in the form of indeterminate quantities. These uncertainties might be subject to the conditions, such as the failure of cranes, container terminal transportation means, congestion in the dockyard, adverse weather conditions, etc. Further, considering the large dimensions of such real problems and the complexity of solving them in terms of processing time, the simulated annealing (SA) meta-heuristic optimization algorithm was utilized to solve the above model. The proposed algorithm has been coded by MATLAB software and its efficiency was put on test by comparing its results for a low-dimensional problem with the accurate solution from GAMS software is compared in terms of computational times for small sizes. The proposed algorithm exhibited promising potentials for quick approximation of usable solutions to high-dimensional QCSAPs. The calculations show that, nondeterministic model with the help of the above proposed algorithm can be one of the basic factors in increasing the productivity of container terminals and the main purpose and advantage of this research is compared to the basic model presented by Tavakkoli-Moghaddam et al. in 2009 which has been analyzed and investigated with definitive data and optimized with the help of genetic algorithm. In addition, some restrictions were added to the basic model in order to make the above crane assignment scheduling problem more practical.

Termination of triangular polynomial loops

AbstractWe consider the problem of proving termination for triangular weakly non-linear loops (twn-loops) over some ring $$\mathcal {S}$$ S like $$\mathbb {Z}$$ Z , $$\mathbb {Q}$$ Q , or $$\mathbb {R}$$ R . The guard of such a loop is an arbitrary quantifier-free Boolean formula over (possibly non-linear) polynomial inequations, and the body is a single assignment of the form $$\begin{bmatrix} x_1\\ \ldots \\ x_d \end{bmatrix} \leftarrow \begin{bmatrix} c_1 \cdot x_1 + p_1\\ \ldots \\ c_d \cdot x_d + p_d \end{bmatrix}$$ x 1 … x d ← c 1 · x 1 + p 1 … c d · x d + p d where each $$x_i$$ x i is a variable, $$c_i \in \mathcal {S}$$ c i ∈ S , and each $$p_i$$ p i is a (possibly non-linear) polynomial over $$\mathcal {S}$$ S and the variables $$x_{i+1},\ldots ,x_{d}$$ x i + 1 , … , x d . We show that the question of termination can be reduced to the existential fragment of the first-order theory of $$\mathcal {S}$$ S . For loops over $$\mathbb {R}$$ R , our reduction implies decidability of termination. For loops over $$\mathbb {Z}$$ Z and $$\mathbb {Q}$$ Q , it proves semi-decidability of non-termination.Furthermore, we present a transformation to convert certain non-twn-loops into twn-form. Then the original loop terminates iff the transformed loop terminates over a specific subset of $$\mathbb {R}$$ R , which can also be checked via our reduction. Moreover, we formalize a technique to linearize (the updates of) twn-loops in our setting and analyze its complexity. Based on these results, we prove complexity bounds for the termination problem of twn-loops as well as tight bounds for two important classes of loops which can always be transformed into twn-loops.Finally, we show that there is an important class of linear loops. where our decision procedure results in an efficient procedure for termination analysis, i.e., where the parameterized complexity of deciding termination is polynomial.

Flexible storage yard management in container terminals under uncertainty

As the port bottleneck shifts from the shore side to the yard side, yard management is crucial to the operation efficiency of the container port. This paper studies the yard management problem in container terminals under the flexible storage strategy which does not fix the size of the storage templates in the yard. The problem considers the uncertainty of container demand and the flexibility of the block and jointly optimizes the storage space allocation, yard crane deployment, and container allocation problems. A two-stage stochastic optimization model under uncertainty is established to minimize the port operation cost. Two heuristic algorithms, a column generation-based heuristic algorithm and a tabu search algorithm, are proposed to solve the model. Numerical experiments validate the effectiveness of the proposed algorithms. Furthermore, some management implications for port operators are proposed according to the results of sensitivity analysis experiments.

Fixed terminal time fractional optimal control problem for discrete time singular system

Fixed terminal time fractional optimal control problem for discrete time singular system

Proposed Mutual Exclusion MAC Protocol for MANET to Overcome Hidden and Exposed Terminal Problem

Mobile Adhoc Network (MANET) is a kind of wireless transmission network could able to form the communication network without need of any basic infrastructure with all the communication nodes can able to move freely ad communication could be done b forwarding the received packet from one node to another nodes in order to reach until the desired destination node found. One of the major challenges in MANET is nodes can move freely from one region to another region where the possibilities route failure and collision among the node. Especially the of Hidden and exposed node problem is the major challenges in the MANET which could not able to define the permanent solution to resolve the issue. This research article focus on hidden and Exposed terminal problem in MAC layer and proposed the new protocol called the Mutual Exclusion MAC protocol (ME- MAC) which support to solve the Hidden and Exposed Terminal issue in MAC layer.

MANET Hidden and Exposed Terminal - Challenges and Survey

Mobile Adhoc Network (MANET)is a self organized wireless Network which was created to communicate among the nodes without support of the any Infrastructure. While transmission of the packets between the nodes, many challenges the every nodes faces. One of the Major challenges is Hidden and Exposed nodes issues in the MANET. This causes the packet drop or packet failure while the transmitting the packets. Also which reflects in degrades the throughput of the MANET and performance of the MANET nodes when the heavy traffic ,retransmission of the dropped packets delayed the communication. This article discussed about hidden and Exposed terminal problem and challenges in MANET and also dissimilar survey in MANET.

A New Approach to Shooting Methods for Terminal Value Problems of Fractional Differential Equations

For terminal value problems of fractional differential equations of order alpha in (0,1) that use Caputo derivatives, shooting methods are a well developed and investigated approach. Based on recently established analytic properties of such problems, we develop a new technique to select the required initial values that solves such shooting problems quickly and accurately. Numerical experiments indicate that this new proportional secting technique converges very quickly and accurately to the solution. Run time measurements indicate a speedup factor of between 4 and 10 when compared to the standard bisection method.

Improved sequential insertion heuristics for berth allocation problems

AbstractBerth allocation decisions affect all subsequent decisions in port terminals. Thus assigning berthing positions and berthing times to vessels—known as the berth allocation problem (BAP)—is one of the most important problems in port terminals. Because this is an NP‐hard problem, most of the solution methods proposed for solving it are heuristics. Although very different, some heuristics applied to the continuous BAP share a common step usually performed several times: the insertion of vessels from an insertion sequence in the time‐space diagram that represents a BAP solution. This process is frequently done by using minimum cost sequential insertion heuristics such as bottom‐left‐based heuristics. Although fast and simple, these heuristics may not lead to high‐quality solutions. In this paper, we propose improved sequential insertion heuristics that generally outperform the traditional ones and keep their simplicity and speed. The proposed heuristics are tested on a large set of instances of BAPs with different optimization objectives, and the obtained results show that they can lead to solutions up to 70% better than those obtained by traditional sequential insertion heuristics.

CONTROL OF BUNDLE OF TRAJECTORIES OF A LINEAR DISCRETE SYSTEM WITH FINITE SETS OF INITIAL AND FINAL STATES

The article proposes an analysis of the problem of control of trajectory bundle of a linear discrete system. The problem of trajectory bundle control arises in applications characterized by the deterministic uncertainty of the initial conditions of the system, control of a group of objects of a similar nature, etc. To such problems belongs, in particular, the control problem for a beam of charged particles. In the statement of the problem studied in the paper, the control function is scalar, the set of initial states and the set of final states contain a finite number of elements. At the same time, the system is completely controlled. The problem is to find a control that transfers the system from a set of initial conditions to a set of final states. The problem is to find a control that transfers the system from a set of initial conditions to a set of final states. In the article, the problem of controlling a bundle of trajectories is reduced to the problem of terminal control of a linear discrete system of higher dimension. At the same time, the resulting system has a block structure. This approach is new. Applying the formula that establishes the dependence between the initial and final states of a discrete system, the problem of terminal control is reduced to the problem of finding a solution to a system of linear algebraic equations. Using the structure of the matrix of the system, as well as the form of the general solution of the system of linear algebraic equations, we obtain a general solution of the terminal control problem. Applying the properties of the pseudoinverse matrix, we prove the theorem on conditions of the solution existence and establish the function, which gives the general solution of the trajectory bundle control problem. This result has an algorithmic orientation.

Adaptive Channel Detection for Full-Duplex IAB Systems on Unlicensed Bands

The integration of integrated access and backhaul (IAB) and full-duplex communications on unlicensed bands can improve the spectrum efficiency and mitigate the spectrum resource shortage. To guarantee fair coexistence on unlicensed spectrum, the listen-before-talk mechanism needs to be executed at the IAB nodes, where the clear channel assessment (CCA) is applied before transmission. However, the residual self-interference (RSI) brought by the full-duplex communication may degrade the CCA detection performance tremendously. Therefore, in this paper we propose an adaptive channel detection scheme for the full-duplex IAB network to minimize the impact of RSI on the CCA detection, which can enhance the spectrum efficiency. In particular, the closed-form expressions of false alarm probability and detection probability are derived. Accordingly, the energy detection (ED) threshold applied in CCA is adjusted adaptively to improve the system throughput. Then, a novel timing sequence with respect to the self-interference cancellation and CCA detection is proposed. The corresponding optimal initial threshold is also derived to realize the adaptive ED threshold. Furthermore, an enhanced request to send/clear to send mechanism is proposed to solve the hidden terminal problem. Simulation results demonstrate that the proposed schemes can effectively reduce the impact of RSI on the CCA detection accuracy and significantly improve the system throughput.

Machine learning for predicting the outcome of terminal ballistics events

Machine learning (ML) is well suited for the prediction of high-complexity, high-dimensional problems such as those encountered in terminal ballistics. We evaluate the performance of four popular ML-based regression models, extreme gradient boosting (XGBoost), artificial neural network (ANN), support vector regression (SVR), and Gaussian process regression (GP), on two common terminal ballistics’ problems: (a) predicting the V50 ballistic limit of monolithic metallic armour impacted by small and medium calibre projectiles and fragments, and (b) predicting the depth to which a projectile will penetrate a target of semi-infinite thickness. To achieve this we utilise two datasets, each consisting of approximately 1000 samples, collated from public release sources. We demonstrate that all four model types provide similarly excellent agreement when interpolating within the training data and diverge when extrapolating outside this range. Although extrapolation is not advisable for ML-based regression models, for applications such as lethality/survivability analysis, such capability is required. To circumvent this, we implement expert knowledge and physics-based models via enforced monotonicity, as a Gaussian prior mean, and through a modified loss function. The physics-informed models demonstrate improved performance over both classical physics-based models and the basic ML regression models, providing an ability to accurately fit experimental data when it is available and then revert to the physics-based model when not. The resulting models demonstrate high levels of predictive accuracy over a very wide range of projectile types, target materials and thicknesses, and impact conditions significantly more diverse than that achievable from any existing analytical approach. Compared with numerical analysis tools such as finite element solvers the ML models run orders of magnitude faster. We provide some general guidelines throughout for the development, application, and reporting of ML models in terminal ballistics problems.

Cooperative Time-Frequency Localization for Wideband Spectrum Sensing With A Lightweight Detector

With the ability to solve the hidden terminal problem, cooperative spectrum sensing (CSS) in cognitive radio networks has attracted much attention. However, existing CSS mainly focuses on detecting the spectrum usage status of primary users (PUs) in time dimension under the premise of known center frequency and bandwidth of PU, which is limited in practical scenarios. For the emerging time-frequency localization based two-dimensional wideband spectrum sensing (SS), how to incorporate cooperation into secondary users (SUs) to enhance sensing performance is still a challenging problem. In this letter, considering the limited storage and computation capacity of SUs, we first propose a lightweight detector for time-frequency localization. Then, through analyzing the characteristics of the sensed spectrogram, we propose a non-maximum suppression based fusion algorithm. Finally, simulation results validate the advantages of the proposed lightweight detector compared with existing detectors, and show the recognition performance of CSS is superior to that of the individual SUs.

THE POWER OF AIRPORT BRANDING IN SHAPING TOURIST DESTINATION IMAGE: PASSENGER COMMITMENT PERSPECTIVE

To providing an empirical investigation into how affective, continuance, and normative commitment could build airport branding. A quantitative content analysis was conducted by analyzing 400 passengers' reviews of Cairo International Airport from the following platforms (Skytrax, Tripadvisor, traveller, and flight report). Affective and continuance commitment are likely to build a strong brand rather than normative commitment. Passengers’ negative experiences with airports make them feel less emotionally attached, resulting in lower levels of affective and continuance commitments. Terminal problems can decrease affective and continuance commitment among passengers. The study identified factors that affect all three types of commitments (affective, continuance, and normative) at international airports, providing significant theoretical contributions and managerial implications.

On Lexicographic Proof Rules for Probabilistic Termination

We consider the almost-sure (a.s.) termination problem for probabilistic programs, which are a stochastic extension of classical imperative programs. Lexicographic ranking functions provide a sound and practical approach for termination of non-probabilistic programs, and their extension to probabilistic programs is achieved via lexicographic ranking supermartingales (LexRSMs). However, LexRSMs introduced in the previous work have a limitation that impedes their automation: all of their components have to be non-negative in all reachable states. This might result in a LexRSM not existing even for simple terminating programs. Our contributions are twofold. First, we introduce a generalization of LexRSMs that allows for some components to be negative. This standard feature of non-probabilistic termination proofs was hitherto not known to be sound in the probabilistic setting, as the soundness proof requires a careful analysis of the underlying stochastic process. Second, we present polynomial-time algorithms using our generalized LexRSMs for proving a.s. termination in broad classes of linear-arithmetic programs.

Cooperative Multiband Spectrum Sensing Using Radio Environment Maps and Neural Networks.

Cogitive radio networks (CRNs) require high capacity and accuracy to detect the presence of licensed or primary users (PUs) in the sensed spectrum. In addition, they must correctly locate the spectral opportunities (holes) in order to be available to nonlicensed or secondary users (SUs). In this research, a centralized network of cognitive radios for monitoring a multiband spectrum in real time is proposed and implemented in a real wireless communication environment through generic communication devices such as software-defined radios (SDRs). Locally, each SU uses a monitoring technique based on sample entropy to determine spectrum occupancy. The determined features (power, bandwidth, and central frequency) of detected PUs are uploaded to a database. The uploaded data are then processed by a central entity. The objective of this work was to determine the number of PUs, their carrier frequency, bandwidth, and the spectral gaps in the sensed spectrum in a specific area through the construction of radioelectric environment maps (REMs). To this end, we compared the results of classical digital signal processing methods and neural networks performed by the central entity. Results show that both proposed cognitive networks (one working with a central entity using typical signal processing and one performing with neural networks) accurately locate PUs and give information to SUs to transmit, avoiding the hidden terminal problem. However, the best-performing cognitive radio network was the one working with neural networks to accurately detect PUs on both carrier frequency and bandwidth.