**Commenced**in January 2007

**Frequency:**Monthly

**Edition:**International

**Paper Count:**3596

# Search results for: ambiguity problem

##### 3596 Exploring the Ambiguity Resolution in Spacecraft Attitude Determination Using GNSS Phase Measurement

**Authors:**
Lv Meibo,
Naqvi Najam Abbas,
Li YanJun

**Abstract:**

Attitude Determination (AD) of a spacecraft using the phase measurements of the Global Navigation Satellite System (GNSS) is an active area of research. Various attitude determination algorithms have been developed in yester years for spacecrafts using different sensors but the last two decades have witnessed a phenomenal increase in research related with GPS receivers as a stand-alone sensor for determining the attitude of satellite using the phase measurements of the signals from GNSS. The GNSS-based Attitude determination algorithms have been experimented in many real missions. The problem of AD algorithms using GNSS phase measurements has two important parts; the ambiguity resolution and the determining of attitude. Ambiguity resolution is the widely addressed topic in literature for implementing the AD algorithm using GNSS phase measurements for achieving the accuracy of millimeter level. This paper broadly overviews the different techniques for resolving the integer ambiguities encountered in AD using GNSS phase measurements.

**Keywords:**
Attitude Determination,
Ambiguity Resolution,
GNSS,
LAMBDA Method,
Satellite.

##### 3595 Unambiguous Signal Acquisition Based On Recombination of Sub-Correlations of BOC Signals

**Authors:**
Hongdeuk Kim,
Youngpo Lee,
Seokho Yoon

**Abstract:**

Due to side-peaks of autocorrelation function, the binary offset carrier (BOC) signal acquisition suffers from an ambiguity when one of the side-peaks is acquired. In this paper, we first analyze that the BOC autocorrelation is made up of the sum of subcorrelations, and then, remove the side-peaks causing the ambiguity by recombining the sub-correlations. The proposed scheme is shown to remove the side-peaks completely. From numerical results, it is confirmed that the proposed scheme outperforms the conventional schemes in terms of the receiver operating characteristic and mean acquisition time.

**Keywords:**
Binary offset carrier (BOC),
acquisition,
ambiguity problem,
side-peak.

##### 3594 Influence of Ambiguity Cluster on Quality Improvement in Image Compression

**Authors:**
Safaa Al-Ali,
Ahmad Shahin,
Fadi Chakik

**Abstract:**

**Keywords:**
Ambiguity Cluster,
Anisotropic Diffusion,
Fuzzy
Clustering,
Image Compression.

##### 3593 An Approach to Solving a Permutation Problem of Frequency Domain Independent Component Analysis for Blind Source Separation of Speech Signals

**Authors:**
Masaru Fujieda,
Takahiro Murakami,
Yoshihisa Ishida

**Abstract:**

**Keywords:**
Blind source separation,
Independent componentanalysis,
Frequency domain,
Permutation ambiguity.

##### 3592 Resolving Dependency Ambiguity of Subordinate Clauses using Support Vector Machines

**Authors:**
Sang-Soo Kim,
Seong-Bae Park,
Sang-Jo Lee

**Abstract:**

**Keywords:**
Dependency analysis,
subordinate clauses,
binaryclassification,
support vector machines.

##### 3591 A Side-Peak Cancellation Scheme for CBOC Code Acquisition

**Authors:**
Youngpo Lee,
Seokho Yoon

**Abstract:**

**Keywords:**
CBOC,
side-peak,
ambiguity problem,
synchronization

##### 3590 When Explanations “Cause“ Error: A Look at Representations and Compressions

**Authors:**
Michael Lissack

**Abstract:**

**Keywords:**
Coherence,
Emergence,
Reduction,
Model

##### 3589 Iterative Methods for An Inverse Problem

**Authors:**
Minghui Wang,
Shanrui Hu

**Abstract:**

An inverse problem of doubly center matrices is discussed. By translating the constrained problem into unconstrained problem, two iterative methods are proposed. A numerical example illustrate our algorithms.

**Keywords:**
doubly center matrix,
electric network theory,
iterative methods,
least-square problem.

##### 3588 Deep Learning Based 6D Pose Estimation for Bin-Picking Using 3D Point Clouds

**Authors:**
Hesheng Wang,
Haoyu Wang,
Chungang Zhuang

**Abstract:**

Estimating the 6D pose of objects is a core step for robot bin-picking tasks. The problem is that various objects are usually randomly stacked with heavy occlusion in real applications. In this work, we propose a method to regress 6D poses by predicting three points for each object in the 3D point cloud through deep learning. To solve the ambiguity of symmetric pose, we propose a labeling method to help the network converge better. Based on the predicted pose, an iterative method is employed for pose optimization. In real-world experiments, our method outperforms the classical approach in both precision and recall.

**Keywords:**
Pose estimation,
deep learning,
point cloud,
bin-picking,
3D computer vision.

##### 3587 Analysis of Classifications of Unsolicited Bulk Emails

**Authors:**
Jatinderkumar R. Saini,
Apurva A. Desai

**Abstract:**

**Keywords:**
E-mail,
Scams,
Spam Email,
Unsolicited Bulk Email(UBE)

##### 3586 Evolutionary Search Techniques to Solve Set Covering Problems

**Authors:**
Darwin Gouwanda,
S. G. Ponnambalam

**Abstract:**

**Keywords:**
Set covering problem,
genetic algorithm,
ant colony
optimization,
LINGO.

##### 3585 Contextual SenSe Model: Word Sense Disambiguation Using Sense and Sense Value of Context Surrounding the Target

**Authors:**
Vishal Raj,
Noorhan Abbas

**Abstract:**

Ambiguity in NLP (Natural Language Processing) refers to the ability of a word, phrase, sentence, or text to have multiple meanings. This results in various kinds of ambiguities such as lexical, syntactic, semantic, anaphoric and referential. This study is focused mainly on solving the issue of Lexical ambiguity. Word Sense Disambiguation (WSD) is an NLP technique that aims to resolve lexical ambiguity by determining the correct meaning of a word within a given context. Most WSD solutions rely on words for training and testing, but we have used lemma and Part of Speech (POS) tokens of words for training and testing. Lemma adds generality and POS adds properties of word into token. We have designed a method to create an affinity matrix to calculate the affinity between any pair of lemma_POS (a token where lemma and POS of word are joined by underscore) of given training set. Additionally, we have devised an algorithm to create the sense clusters of tokens using affinity matrix under hierarchy of POS of lemma. Furthermore, three different mechanisms to predict the sense of target word using the affinity/similarity value are devised. Each contextual token contributes to the sense of target word with some value and whichever sense gets higher value becomes the sense of target word. So, contextual tokens play a key role in creating sense clusters and predicting the sense of target word, hence, the model is named Contextual SenSe Model (CSM). CSM exhibits a noteworthy simplicity and explication lucidity in contrast to contemporary deep learning models characterized by intricacy, time-intensive processes, and challenging explication. CSM is trained on SemCor training data and evaluated on SemEval test dataset. The results indicate that despite the naivety of the method, it achieves promising results when compared to the Most Frequent Sense (MFS) model.

**Keywords:**
Word Sense Disambiguation,
WSD,
Contextual SenSe Model,
Most Frequent Sense,
part of speech,
POS,
Natural Language Processing,
NLP,
OOV,
out of vocabulary,
ELMo,
Embeddings from Language Model,
BERT,
Bidirectional Encoder Representations from Transformers,
Word2Vec,
lemma_POS,
Algorithm.

##### 3584 Bi-linear Complementarity Problem

**Authors:**
Chao Wang,
Ting-Zhu Huang Chen Jia

**Abstract:**

In this paper, we propose a new linear complementarity problem named as bi-linear complementarity problem (BLCP) and the method for solving BLCP. In addition, the algorithm for error estimation of BLCP is also given. Numerical experiments show that the algorithm is efficient.

**Keywords:**
Bi-linear complementarity problem,
Linear complementarity
problem,
Extended linear complementarity problem,
Error
estimation,
P-matrix,
M-matrix.

##### 3583 A Method for Solving a Bi-Objective Transportation Problem under Fuzzy Environment

**Authors:**
Sukhveer Singh,
Sandeep Singh

**Abstract:**

A bi-objective fuzzy transportation problem with the objectives to minimize the total fuzzy cost and fuzzy time of transportation without according priorities to them is considered. To the best of our knowledge, there is no method in the literature to find efficient solutions of the bi-objective transportation problem under uncertainty. In this paper, a bi-objective transportation problem in an uncertain environment has been formulated. An algorithm has been proposed to find efficient solutions of the bi-objective transportation problem under uncertainty. The proposed algorithm avoids the degeneracy and gives the optimal solution faster than other existing algorithms for the given uncertain transportation problem.

**Keywords:**
Transportation problem,
efficient solution,
ranking function,
fuzzy transportation problem.

##### 3582 Bee Colony Optimization Applied to the Bin Packing Problem

**Authors:**
Kenza Aida Amara,
Bachir Djebbar

**Abstract:**

**Keywords:**
Bee colony optimization,
bin packing,
heuristic algorithm,
pretreatment.

##### 3581 Modeling Language for Machine Learning

**Authors:**
Tsuyoshi Okita,
Tatsuya Niwa

**Abstract:**

**Keywords:**
Formal language,
statistical inference problem,
reduction.

##### 3580 Transformation of Course Timetablinng Problem to RCPSP

**Authors:**
M. Ahmad,
M. Gourgand,
C. Caux

**Abstract:**

**Keywords:**
Course Timetabling,
Integer programming,
Combinatorial optimizations

##### 3579 How to Build and Evaluate a Solution Method: An Illustration for the Vehicle Routing Problem

**Authors:**
Nicolas Zufferey

**Abstract:**

The vehicle routing problem (VRP) is a famous combinatorial optimization problem. Because of its well-known difficulty, metaheuristics are the most appropriate methods to tackle large and realistic instances. The goal of this paper is to highlight the key ideas for designing VRP metaheuristics according to the following criteria: efficiency, speed, robustness, and ability to take advantage of the problem structure. Such elements can obviously be used to build solution methods for other combinatorial optimization problems, at least in the deterministic field.

**Keywords:**
Vehicle routing problem,
Metaheuristics,
Combinatorial optimization.

##### 3578 Seat Assignment Problem Optimization

**Authors:**
Mohammed Salem Alzahrani

**Abstract:**

**Keywords:**
Assignment Problem,
Hungarian Method,
Least Cost
Method,
Northwest Corner Method,
Seat Assignment Method
(SAM),
A Real Word Assignment Problem.

##### 3577 The Multi-scenario Knapsack Problem: An Adaptive Search Algorithm

**Authors:**
Mhand Hifi,
Hedi Mhalla,
Mustapha Michaphy

**Abstract:**

In this paper, we study the multi-scenario knapsack problem, a variant of the well-known NP-Hard single knapsack problem. We investigate the use of an adaptive algorithm for solving heuristically the problem. The used method combines two complementary phases: a size reduction phase and a dynamic 2- opt procedure one. First, the reduction phase applies a polynomial reduction strategy; that is used for reducing the size problem. Second, the adaptive search procedure is applied in order to attain a feasible solution Finally, the performances of two versions of the proposed algorithm are evaluated on a set of randomly generated instances.

**Keywords:**
combinatorial optimization,
max-min optimization,
knapsack,
heuristics,
problem reduction

##### 3576 A Deterministic Polynomial-time Algorithm for the Clique Problem and the Equality of P and NP Complexity Classes

**Authors:**
Zohreh O. Akbari

**Abstract:**

**Keywords:**
Clique problem,
Deterministic Polynomial-time
Algorithm,
Equality of P and NP Complexity Classes.

##### 3575 Optimization by Ant Colony Hybryde for the Bin-Packing Problem

**Authors:**
Ben Mohamed Ahemed Mohamed,
Yassine Adnan

**Abstract:**

The problem of bin-packing in two dimensions (2BP) consists in placing a given set of rectangular items in a minimum number of rectangular and identical containers, called bins. This article treats the case of objects with a free orientation of 90Ôùª. We propose an approach of resolution combining optimization by colony of ants (ACO) and the heuristic method IMA to resolve this NP-Hard problem.

**Keywords:**
Ant colony algorithm,
bin-packing problem,
heuristics methods.

##### 3574 Optimal Facility Layout Problem Solution Using Genetic Algorithm

**Authors:**
Maricar G. Misola,
Bryan B. Navarro

**Abstract:**

Facility Layout Problem (FLP) is one of the essential problems of several types of manufacturing and service sector. It is an optimization problem on which the main objective is to obtain the efficient locations, arrangement and order of the facilities. In the literature, there are numerous facility layout problem research presented and have used meta-heuristic approaches to achieve optimal facility layout design. This paper presented genetic algorithm to solve facility layout problem; to minimize total cost function. The performance of the proposed approach was verified and compared using problems in the literature.

**Keywords:**
Facility Layout Problem,
Genetic Algorithm,
Material Handling Cost,
Meta-heuristic Approach.

##### 3573 Solving the Teacher Assignment-Course Scheduling Problem by a Hybrid Algorithm

**Authors:**
Aldy Gunawan,
Kien Ming Ng,
Kim Leng Poh

**Abstract:**

This paper presents a hybrid algorithm for solving a timetabling problem, which is commonly encountered in many universities. The problem combines both teacher assignment and course scheduling problems simultaneously, and is presented as a mathematical programming model. However, this problem becomes intractable and it is unlikely that a proven optimal solution can be obtained by an integer programming approach, especially for large problem instances. A hybrid algorithm that combines an integer programming approach, a greedy heuristic and a modified simulated annealing algorithm collaboratively is proposed to solve the problem. Several randomly generated data sets of sizes comparable to that of an institution in Indonesia are solved using the proposed algorithm. Computational results indicate that the algorithm can overcome difficulties of large problem sizes encountered in previous related works.

**Keywords:**
Timetabling problem,
mathematical programming
model,
hybrid algorithm,
simulated annealing.

##### 3572 Stochastic Programming Model for Power Generation

**Authors:**
Takayuki Shiina

**Abstract:**

**Keywords:**
electric power capacity expansion problem,
integerprogramming,
L-shaped method,
stochastic programming

##### 3571 On Optimum Stratification

**Authors:**
M. G. M. Khan,
V. D. Prasad,
D. K. Rao

**Abstract:**

In this manuscript, we discuss the problem of determining the optimum stratification of a study (or main) variable based on the auxiliary variable that follows a uniform distribution. If the stratification of survey variable is made using the auxiliary variable it may lead to substantial gains in precision of the estimates. This problem is formulated as a Nonlinear Programming Problem (NLPP), which turn out to multistage decision problem and is solved using dynamic programming technique.

**Keywords:**
Auxiliary variable,
Dynamic programming technique,
Nonlinear programming problem,
Optimum stratification,
Uniform distribution.

##### 3570 Enhanced Traveling Salesman Problem Solving by Genetic Algorithm Technique (TSPGA)

**Authors:**
Buthainah Fahran Al-Dulaimi,
Hamza A. Ali

**Abstract:**

The well known NP-complete problem of the Traveling Salesman Problem (TSP) is coded in genetic form. A software system is proposed to determine the optimum route for a Traveling Salesman Problem using Genetic Algorithm technique. The system starts from a matrix of the calculated Euclidean distances between the cities to be visited by the traveling salesman and a randomly chosen city order as the initial population. Then new generations are then created repeatedly until the proper path is reached upon reaching a stopping criterion. This search is guided by a solution evaluation function.

**Keywords:**
Genetic algorithms,
traveling salesman problem solving,
optimization.

##### 3569 Two-Stage Approach for Solving the Multi-Objective Optimization Problem on Combinatorial Configurations

**Authors:**
Liudmyla Koliechkina,
Olena Dvirna

**Abstract:**

**Keywords:**
Discrete set,
linear combinatorial optimization,
multi-objective optimization,
multipermutation,
Pareto solutions,
partial permutation set,
permutation,
structural graph.

##### 3568 P-ACO Approach to Assignment Problem in FMSs

**Authors:**
I. Mahdavi,
A. Jazayeri,
M. Jahromi,
R. Jafari,
H. Iranmanesh

**Abstract:**

One of the most important problems in production planning of flexible manufacturing system (FMS) is machine tool selection and operation allocation problem that directly influences the production costs and times .In this paper minimizing machining cost, set-up cost and material handling cost as a multi-objective problem in flexible manufacturing systems environment are considered. We present a 0-1 integer linear programming model for the multiobjective machine tool selection and operation allocation problem and due to the large scale nature of the problem, solving the problem to obtain optimal solution in a reasonable time is infeasible, Paretoant colony optimization (P-ACO) approach for solving the multiobjective problem in reasonable time is developed. Experimental results indicate effectiveness of the proposed algorithm for solving the problem.

**Keywords:**
Flexible manufacturing system,
Production planning,
Machine tool selection,
Operation allocation,
Multiobjective optimization,
Metaheuristic.

##### 3567 A Comparison of Exact and Heuristic Approaches to Capital Budgeting

**Authors:**
Jindřiška Šedová,
Miloš Šeda

**Abstract:**

**Keywords:**
Capital budgeting,
knapsack problem,
GAMS,
heuristic method,
genetic algorithm.