arXiv subjects

Farzad Didehvar

Publications and source records attributed to Farzad Didehvar.

At least 19 recordsLinked to original sources

arXiv2025

Finding the Best Route During the Pandemic Disease

This article presents a mathematical model for identifying the safest travel routes during a pandemic by minimizing disease contraction risks, such as COVID-19. We formulate this as the LEAST INFECTION PROBABILITY PATH (LIPP) problem, which optimizes routes between two nodes in a transportation network based on minimal disease transmission probability. Our model evaluates risk factors including environmental density, likelihood of encountering carriers, and exposure duration across multiple transportation modes (walking, subway, BRT, buses, and cars). The probabilistic framework incorporates additional variables such as ventilation quality, activity levels, and interpersonal distances to estimate transmission risks. Applied to Tehran's transportation network using routing applications (Neshan and Balad), our model demonstrates that combined pedestrian-subway-BRT routes exhibit significantly lower infection risks compared to car or bus routes, as illustrated in our case study of peak-hour travel between Sadeghiyeh Square and Amirkabir University. We develop a practical routing algorithm suitable for integration with existing navigation software to provide pandemic-aware path recommendations. Potential future extensions include incorporating additional variables like waiting times and line changes, as well as adapting the model for other infectious diseases. This research offers a valuable tool for urban travelers seeking to minimize infection risks during pandemic conditions.

physics.soc-ph↗

arXiv2024

Vocal Melody Construction for Persian Lyrics Using LSTM Recurrent Neural Networks

The present paper investigated automatic melody construction for Persian lyrics as an input. It was assumed that there is a phonological correlation between the lyric syllables and the melody in a song. A seq2seq neural network was developed to investigate this assumption, trained on parallel syllable and note sequences in Persian songs to suggest a pleasant melody for a new sequence of syllables. More than 100 pieces of Persian music were collected and converted from the printed version to the digital format due to the lack of a dataset on Persian digital music. Finally, 14 new lyrics were given to the model as input, and the suggested melodies were performed and recorded by music experts to evaluate the trained model. The evaluation was conducted using an audio questionnaire, which more than 170 persons answered. According to the answers about the pleasantness of melody, the system outputs scored an average of 3.005 from 5, while the human-made melodies for the same lyrics obtained an average score of 4.078.

cs.SD↗

arXiv2024

Finding the Best Route During the Pandemic Disease

In this article, we try to find the best routes during the pandemic so that the probability of contracting the disease is the lowest. According to the results of this article, we can design software to find the best route.

cs.SI↗

arXiv2024

A Fixed-Parameter Study on Propositional Dynamic Logic

Since its establishment, propositional dynamic logic (PDL) has been a subject of intensive academic research and frequent use in the industry. We have studied the complexity of some PDL problems and in this paper, we show results for some special cases of PL and PDL.

cs.LO↗

arXiv2023

Turing Machines Equipped with CTC in Physical Universes

We study the paradoxical aspects of closed time-like curves and their impact on the theory of computation. After introducing the $\text{TM}_\text{CTC}$, a classical Turing machine benefiting CTCs for backward time travel, Aaronson et al. proved that $\text{P} = \text{PSPACE}$ and the $Δ_2$ sets, such as the halting problem, are computable within this computational model. Our critical view is the physical consistency of this model, which leads to proposing the strong axiom, explaining that every particle rounding on a CTC will be destroyed before returning to its starting time, and the weak axiom, describing the same notion, particularly for Turing machines. We claim that in a universe containing CTCs, the two axioms must be true; otherwise, there will be an infinite number of any particle rounding on a CTC in the universe. An immediate result of the weak axiom is the incapability of Turing machines to convey information for a full round on a CTC, leading to the proposed $\text{TM}_\text{CTC}$ programs for the aforementioned corollaries failing to function. We suggest our solution for this problem as the data transferring hypothesis, which applies another $\text{TM}_\text{CTC}$ as a means for storing data. A prerequisite for it is the existence of the concept of Turing machines throughout time, which makes it appear infeasible in our universe. Then, we discuss possible physical conditions that can be held for a universe containing CTCs and conclude that if returning to an approximately equivalent universe by a CTC was conceivable, the above corollaries would be valid.

cs.CC↗

arXiv2022

Iranian Modal Music (Dastgah) detection using deep neural networks

Music classification and genre detection are topics in music information retrieval (MIR) that many articles have been published regarding their utilities in the modern world. However, this contribution is insufficient in non-western music, such as Iranian modal music. In this work, we have implemented several deep neural networks to recognize Iranian modal music in seven highly correlated categories. The best model, BiLGNet, which achieved 92 percent overall accuracy, uses an architecture inspired by autoencoders, including bidirectional LSTM and GRU layers. We trained the models using the Nava dataset, which includes 1786 records and up to 55 hours of music played solo by Kamanche, Tar, Setar, Reed, and Santoor (Dulcimer). We considered Multiple features such as MFCC, Chroma CENS, and Mel spectrogram as input. The results indicate that MFCC carries more valuable information for detecting Iranian modal music (Dastgah) than other sound representations. Moreover, the architecture inspired by autoencoders is robust in distinguishing highly correlated data like Dastgahs. It also shows that because of the precise order in Iranian Dastgah Music, Bidirectional Recurrent networks are more efficient than any other networks that have been implemented in this study.

cs.SD↗

arXiv2022

Graph Comparison Based on Adjacency Function Matrix

In this paper, we present a new metric distance for comparing two large graphs to find similarities and differences between them based on one of the most important graph structural properties, which is Node Adjacency Information, for all vertices in the graph. Then, we defined a new function and some parameters to find the distance of two large graphs using different neighbors of vertices. There are some methods which they focused on the other features of graphs to obtain the distance between them, but some of them are Node Correspondence which means their node set have the same size. However, in this paper, we introduce a new method which can find the distance between two large graphs with different size of node set.

cs.DM↗

arXiv2021

An upper bound for min-max angle of polygons

Let $S$ be a set of $n$ points in the plane, $\wp(S)$ be the set of all simple polygons crossing $S$, $γ_P$ be the maximum angle of polygon $P \in \wp(S)$ and $θ=min_{P\in\wp(S)} γ_P$. In this paper, we prove that $θ\leq 2π-\frac{2π}{r.m}$ where $m$ and $r$ are the number of edges and inner points of the convex hull of $S$, respectively. We also propose an algorithm to construct a polygon with the said upper bound on its angles. Constructing a simple polygon with angular constraint on a given set of points in the plane can be used for path planning in robotics. Moreover, we improve our upper bound on $θ$ and prove that this is tight for $r=1$.

cs.CG↗

arXiv2020

Approximation Algorithms for the Load Balanced Capacitated Vehicle Routing Problem

We study the load balanced capacitated vehicle routing problem (LBCVRP): the problem is to design a collection of tours for a fixed fleet of vehicles with capacity Q to distribute a supply from a single depot between a number of predefined clients, in a way that the total traveling cost is a minimum, and the vehicle loads are balanced. The unbalanced loads cause the decrease of distribution quality especially in business environments and exibility in the logistics activities. The problem being NP-hard, we propose two approximation algorithms. When the demands are equal, we present a (1-1/Q)p+3/2approximation algorithm that finds balanced loads. Here, p is the approximation ratio for the known metric traveling salesman problem (TSP). This result leads to a 2.5-1/Q approximation ratio for the tree metrics since an optimal solution can be found for the TSP on a tree. We present an improved 2 approximation algorithm. When the demands are unequal, we focus on obtaining approximate solutions since finding balanced loads is NP-complete. We propose an algorithm that provides a 4 approximation for the balance of the loads. We assume a second approach to get around the difficulties of the feasibility. In this approach, we redefine and convert the problem into a multi-objective problem. The algorithm we propose has a 4 factor of approximation.

cs.DS↗

arXiv2019

Approximation of subsets of natural numbers by c.e. sets

The approximation of natural numbers subsets has always been one of the fundamental issues in computability theory. Computable approximation, $Δ_2$-approximation, as well as introducing the generically computable sets have been some efforts for this purpose. In this paper, a type of approximation for natural numbers subsets by computably enumerable sets will be examined. For an infinite and non-c.e set, $W_i$ will be an $A$.maximal (maximal inside $A$) if $W_i \subseteq A$, is infinite and $\forall j (W_i \subseteq W_j \subseteq A) \to Δ(W_i, W_j )< \infty$, where $Δ$ is the symmetric difference of the two sets. In this study, the natural numbers subsets will be examined from the maximal subset contents point of view, and we will categorize them on this basis. We will study c.regular sets that are non-c.e. and include a maximal set inside themselves, and c.irregular sets that are non-c.e. and non-immune sets which do not include maximal sets. Finally, we study the graph of relationship between c.e. subsets of c.irregular sets.

cs.LO↗

arXiv2015

A Semantic Situation without Syntax (Non- axiomatizibility of Theories)

Here, by introducing a version of Unexpected hanging paradox first we try to open a new way and a new explanation for paradoxes, similar to liar paradox. Also, we will show that we have a semantic situation which no syntactical logical system could support it. Finally, we propose a claim in the subject of axiomatizibility. Based on this claim, having an axiomatic system for Computability Theory is not possible. In fact, the same argument shows that many other theories are non-axiomatizable. (Dare to say: General Theories of Physics and Mathematics).

math.LO↗

arXiv2014

Alpha-Concave Hull, a Generalization of Convex Hull

Bounding hull, such as convex hull, concave hull, alpha shapes etc. has vast applications in different areas especially in computational geometry. Alpha shape and concave hull are generalizations of convex hull. Unlike the convex hull, they construct non-convex enclosure on a set of points. In this paper, we introduce another generalization of convex hull, named alpha-concave hull, and compare this concept with convex hull and alpha shape. We show that the alpha-concave hull is also a generalization of an NP-complete problem named min-area TSP. We prove that computing the alpha-concave hull is NP-hard on a set of points.

cs.CG↗

arXiv2013

Clustering validity based on the most similarity

One basic requirement of many studies is the necessity of classifying data. Clustering is a proposed method for summarizing networks. Clustering methods can be divided into two categories named model-based approaches and algorithmic approaches. Since the most of clustering methods depend on their input parameters, it is important to evaluate the result of a clustering algorithm with its different input parameters, to choose the most appropriate one. There are several clustering validity techniques based on inner density and outer density of clusters that represent different metrics to choose the most appropriate clustering independent of the input parameters. According to dependency of previous methods on the input parameters, one challenge in facing with large systems, is to complete data incrementally that effects on the final choice of the most appropriate clustering. Those methods define the existence of high intensity in a cluster, and low intensity among different clusters as the measure of choosing the optimal clustering. This measure has a tremendous problem, not availing all data at the first stage. In this paper, we introduce an efficient measure in which maximum number of repetitions for various initial values occurs.

cs.LG↗

arXiv2012

A Semantic Without Syntax 1

Here, by introducing a version of "Unexpected hanging paradox" we try to open a new way and a new explanation for paradoxes, similar to liar paradox. Also, we will show that we have a semantic situation which no syntactical logical system could support that. In the end, we propose a claim as a question. Based on this claim, having an axiomatic system for computability theory is not possible. In fact we will show that the method applied here could yields us as a generalized result, some Theories like Physic is not axiomatizable.

cs.OH↗

arXiv2012

How much could we cover a set by c.e sets?

"How much c.e. sets could cover a given set?" in this paper we are going to answer this question. Also, in this approach some old concepts come into a new arrangement. The major goal of this article is to introduce an appropriate definition for this purpose. Introduction In Computability Theory (Recursion Theory) in the first step we wish to recognize the sets which could be enumerated by Turing machines (equivalently, algorithms) and in the next step we will compare these sets by some reasonable order (Like Turing degree). Also sometimes with some extra information (Oracles) a class of non c.e. sets show the same behavior as c.e. sets (Post hierarchy and related theorems). Here we try another approach: "Let A be an arbitrary set and we wish to recognize how much this set might be covered by a c.e. set?" Although in some sense this approach could be seen in some definitions of Recursion Theory, but at the best of our knowledge it didn't considered as an approach yet, even though it is able to shed a light on some subjects of Computability of sets. Defining this approach is not quite straightforward and there are some obstacles to define them. To overcome these difficulties we modify the definitions. We have an alternative problem here when we consider recursive sets and not c.e. sets. In this case, the problem would be: "Let A be an arbitrary set and we wish to know that how much this set might be covered by a recursive Set?" Here, we try the first definition and the first problem.

cs.FL↗

arXiv2012

Modification of the Elite Ant System in Order to Avoid Local Optimum Points in the Traveling Salesman Problem

This article presents a new algorithm which is a modified version of the elite ant system (EAS) algorithm. The new version utilizes an effective criterion for escaping from the local optimum points. In contrast to the classical EAC algorithms, the proposed algorithm uses only a global updating, which will increase pheromone on the edges of the best (i.e. the shortest) route and will at the same time decrease the amount of pheromone on the edges of the worst (i.e. the longest) route. In order to assess the efficiency of the new algorithm, some standard traveling salesman problems (TSPs) were studied and their results were compared with classical EAC and other well-known meta-heuristic algorithms. The results indicate that the proposed algorithm has been able to improve the efficiency of the algorithms in all instances and it is competitive with other algorithms.

cs.AI↗

arXiv2011

Co-ordering and Type 2 co-ordering

In [arXiv:1006.4939] the enumeration order reducibility is defined on natural numbers. For a c.e. set A, [A] denoted the class of all subsets of natural numbers which are co-order with A. In definition 5 we redefine co-ordering for rational numbers. One of the main questions there, was: "For a specific c.e. set A, consider set of all enumerations of it which is generated by some Turing machine {TM_A} what are the associated order types in [A]?" Here, we propose the same question for rational numbers, and we try to investigate the varieties of c.e. sets on Q. The theories here are hold for R_c and we could repeat the same theories in this domain, in a parallel way.

cs.LO↗

arXiv2011

A Novel Template-Based Learning Model

This article presents a model which is capable of learning and abstracting new concepts based on comparing observations and finding the resemblance between the observations. In the model, the new observations are compared with the templates which have been derived from the previous experiences. In the first stage, the objects are first represented through a geometric description which is used for finding the object boundaries and a descriptor which is inspired by the human visual system and then they are fed into the model. Next, the new observations are identified through comparing them with the previously-learned templates and are used for producing new templates. The comparisons are made based on measures like Euclidean or correlation distance. The new template is created by applying onion-pealing algorithm. The algorithm consecutively uses convex hulls which are made by the points representing the objects. If the new observation is remarkably similar to one of the observed categories, it is no longer utilized in creating a new template. The existing templates are used to provide a description of the new observation. This description is provided in the templates space. Each template represents a dimension of the feature space. The degree of the resemblance each template bears to each object indicates the value associated with the object in that dimension of the templates space. In this way, the description of the new observation becomes more accurate and detailed as the time passes and the experiences increase. We have used this model for learning and recognizing the new polygons in the polygon space. Representing the polygons was made possible through employing a geometric method and a method inspired by human visual system. Various implementations of the model have been compared. The evaluation results of the model prove its efficiency in learning and deriving new templates.

cs.LG↗