String Search

Hardware forensic analysis involves the process of analyzing digital evidence derived from digital sources. The analysis is done to facilitate and prove either the device is used to commit crime, whether it contains evidence of a crime or is the target of a crime. Gambling machines serve as the main source by which illegal games are conducted. This paper presents a method for retrieving information from a seized gaming machine, along with an analysis of the interpreted information to prove that the gaming machine was used illegally. The proposed procedures for the gambling machine forensic process will be important for forensic investigators (e.g., the police or private investigators), as they will assist these individuals in the digital forensic evidence analysis necessary to produce evidence relevant to illegal gambling.

This paper introduces an advanced Arabic handwriting recognition technique using lexicon reduction. The lexicon reduction technique stands on extracting the Arabic character shape descriptors. The technique implementation consists of two major stages. The first stage presents a method for extracting the shape descriptor of each character. The second stage suggests Aho-Corasik string searching algorithm for Arabic character recognition. Various stages have been evaluated on the IFN/ENIT database. The results demonstrate the efficiency of the suggested technique.

This paper introduces an advanced Arabic handwriting recognition technique using lexicon reduction. The lexicon reduction technique stands on extracting the Arabic character shape descriptors. The technique implementation consists of two major stages. The first stage presents a method for extracting the shape descriptor of each character. The second stage suggests Aho-Corasik string searching algorithm for Arabic character recognition. Various stages have been evaluated on the IFN/ENIT database. The results demonstrate the efficiency of the suggested technique.

In the introductory paper, [Physics Letters A 373 (2009) 911-918], about noise-based logic, we showed how simple superpositions of single logic basis vectors can be achieved in a single wire. The superposition components were the N orthogonal logic basis vectors. Supposing that the different logic values have "on/off" states only, the resultant discrete superposition state represents a single number with N bit accuracy in a single wire, where N is the number of orthogonal logic vectors in the base. In the present paper, we show that the logic hyperspace (product) vectors defined in the introductory paper can be generalized to provide the discrete superposition of 2 N orthogonal system states. This is equivalent to a multi-valued logic system with 2 2 N logic values per wire. This is a similar situation to quantum informatics with N qubits, and hence we introduce the notion of noise-bit. This system has major differences compared to quantum informatics. The noise-based logic system is deterministic and each superposition element is instantly accessible with the high digital accuracy, via a real hardware parallelism, without decoherence and error correction, and without the requirement of repeating the logic operation many times to extract the probabilistic information. Moreover, the states in noise-based logic do not have to be normalized, and non-unitary operations can also be used. As an example, we introduce a string search algorithm which is O(M) times faster than Grover's quantum algorithm (where M is the number of string entries), while it has the same hardware complexity class as the quantum algorithm.

Hardware forensic analysis involves the process of analyzing digital evidence derived from digital sources. The analysis is done to facilitate and prove either the device is used to commit crime, whether it contains evidence of a crime or is the target of a crime. Gambling machines serve as the main source by which illegal games are conducted. This paper presents a method for retrieving information from a seized gaming machine, along with an analysis of the interpreted information to prove that the gaming machine was used illegally. The proposed procedures for the gambling machine forensic process will be important for forensic investigators (e.g., the police or private investigators), as they will assist these individuals in the digital forensic evidence analysis necessary to produce evidence relevant to illegal gambling.

This paper presents a systematic technique for expressing a string search algorithm as a regular iterative expression to explore all possible processor arrays for deep packet classification. The computation domain of the algorithm is obtained and three affine scheduling functions are presented. The technique allows some of the algorithm variables to be pipelined while others are broadcast over system-wide buses. Nine possible processor array structures are obtained and analyzed in terms of speed, area, power, and I/O timing requirements. Time complexities are derived analytically and through extensive numerical simulations. The proposed designs exhibit optimum speed and area complexities. The processor arrays are compared with previously derived processor arrays for the string matching problem.

Evolutionary studies usually assume that the genetic mutations are independent of each other. However, that does not imply that the observed mutations are independent of each other because it is possible that when a nucleotide is mutated, then it may be biologically beneficial if an adjacent nucleotide mutates too. With a number of decoded genes currently available in various genome libraries and online databases, it is now possible to have a large-scale computer-based study to test whether the independence assumption holds for pairs of adjacent amino acids. Hence the independence question also arises for pairs of adjacent amino acids within proteins. The independence question can be tested by considering the evolution of proteins within a closely related sets of proteins, which are called protein families. In this thesis, we test the independence hypothesis for three protein families from the PFAM library, which is a publicly available online database that records a growing number of protein families. For each protein family, we construct a hypothetical common ancestor, or consensus sequence. We compare the hypothetical common ancestor of a protein family with each of the descendant protein sequences in the family to test where the mutations occurred during evolution. The comparison yields actual probabilities for each pair of amino acids changing into another pair of amino acids. By comparing the actual probabilities with the theoretical probabilities under the independence assumption, we identify anomalies that indicate that the independence assumption does not hold for many pairs of amino acids.

The string-matching problem is defined as a given large text string and a pattern string to find all its occurrences in the given text. A modification of one of the recent and fast string-matching algorithms is presented here. The modification was tested with English text. The results suggest a reduction in the average number of comparisons performed up to 36% comparing to the original Double-Skip Algorithm (DSA).

➢ Limbajul Prolog (PROgrammation en LOGique) a fost elaborat la Universitatea din Marsilia în jurul anului 1970, ca instrument pentru programarea şi rezolvarea problemelor ce implicau reprezentări simbolice de obiecte şi relaţii dintre acestea.

One of the fundamental problems of computer science is ordering a list of items. There are a lot of solutions for this problem, known as sorting algorithms. Some sorting algorithms are simple and intuitive, such as the bubble sort, but others, like quick sort, are extremely complicated but produce lightening-fast results.

Se cercetează resursele soft reutilizabile ca mijloace de micşorare a timpului  de elaborare şi ca mijloace de sporire a calităţii aplicaţiilor. Se propune o descriere a modelelor de aplicare a diferitor tipuri de resurse reutilizabile şi un set de recomandări metodologice orientate spre utilizarea cu succes a acestor resurse.

A cluster analysis task has to identify the grouping trends of data, to decide on the sound clusters as well as to validate somehow the resulted structure. The identification of the grouping tendency existing in a data collection assumes the selection of a framework stated in terms of a mathematical model allowing to express the similarity degree between couples of particular objects, quasi-metrics expressing the similarity between an object an a cluster and between clusters, respectively. In supervised classification, we are provided with a collection of preclassified patterns, and the problem is to label a newly encountered pattern. Typically, the given training patterns are used to learn the descriptions of classes which in turn are used to label a new pattern. The final section of the paper presents a new methodology for supervised learning based on PCA. The classes are represented in the measurement/feature space by a continuous repartitions

________________________________________________________________________________ Structuri de date şi algoritmi _______________________________________________________________________________ propoziţii nestandard. Aşa cum se va arăta mai târziu, propoziţiile nestandard sunt texte care descriu părţi ale algoritmului încă incomplet elaborate, nefinisate, asupra cărora urmează să se revină. Ele se recunosc prin faptul că încep întotdeauna cu semnul '@' şi se termină cu punctul obişnuit (caracterul '.').

________________________________________________________________________________ Structuri de date şi algoritmi _______________________________________________________________________________ propoziţii nestandard. Aşa cum se va arăta mai târziu, propoziţiile nestandard sunt texte care descriu părţi ale algoritmului încă incomplet elaborate, nefinisate, asupra cărora urmează să se revină. Ele se recunosc prin faptul că încep întotdeauna cu semnul '@' şi se termină cu punctul obişnuit (caracterul '.').

Metoda Divide et Impera este utilizată în sortarea rapidă. Ideea algoritmului: 1. Se alege o valoare pivot. Se ia valoarea elementului din mijloc ca valoare pivot, dar poate fi oricare altă valoare, care este în intervalul valorilor sortate, chiar dacă nu este prezentă în tablou. 2. Partiţionare. Se rearanjează elementele în aşa fel încât, toate elementele care sunt mai mari decât pivotul merg în partea dreaptă a tabloului. Valorile egale cu pivotul pot sta în orice parte a tabloului. În plus, tabloul poate fi împărţit în părţi care nu au aceeaşi dimensiune (nu sunt egale). 3. Se sortează amândouă părţile.se aplică recursiv algoritmul de sortare rapidă în partea stângă şi în partea dreaptă.

Un algoritm genetic reprezintă o transpunere in programare a unor principii biologice. Structura unui astfel de algoritm este descrisă prin următorii paşi: Pasul 1. generează populaţia iniţială Pasul 2. generează urmaşii (off-sping) Pasul 3. aplică mutaţii genetice Pasul 4. selectează o parte a populaţiei care părăseşte sistemul Pasul 5. repetă pasii 2, 3, 4, până la satisfacerea unui criteriu de optimalitate (sau de un anumit număr de ori)