Abstract :  CIMO is a combinatorial system which computes optimal multimodal itineraries consisting in itineraries which are sorted, multimodal and trans-territorial. In this work we propose the formalism of ad hoc multimodal itinerary problematic, the multi-constraints based dynamic programming algorithm approach, and a realistic evaluation of the solution proposed which address new aggregation of operational transportation territories. The solution is based on a dynamic programming algorithm ”cut”, ”price” and ”share”. This solution is multi-objectives and multi-constraints. Progressive versions of this algorithm are proposed following a methodological approach that enables evaluation of efficiency and complexity’s gain. Test benchmarks are run to validate the contributions, until the overall system shows its capacity to propose multimodal itineraries for real metropolis area. Other parameters are defined as the speed up and the relative gain. This work also provides a set of evaluations of CIMO’s versions: from a real illustration based on two extractions transport networks with small overlap (bus) and connected transversely by two other modes (train and cars), to a simulation of territorial areas comprising the territories served by 3-modes transport services (bus, car and train) of AOTS prefectures and sub-prefectures (2 x 800 stations, 2 x 20 lines, journey time-tabling’s ranging from 6 am to 20 pm, lines of trains and buses serving longitudinally these 2 networks). This study shows that an optimal itinerary can be calculated with an exact, dynamic programming algorithm ”cut” and ”price” and ”share” which generates 3-modes itinerary over two connected transportation networks, deserving 300,000 inhabitants.

Abstract :  Due to rise of quantum computers which leads to faster computation, there is an increasing interest in the field of physical layer security. This paper presents an idea involving some physical layer technique to drastically change the intactness of symmetric key encryption protocols, viz. DES, AES. Our invention combines physical layer security with cryptographic protocols to some extent, resulting into stronger cipher. Current work shows how we can achieve greater security in symmetric key encryption protocols. This paper gives a new way to look at wireless security. With the given analysis and the plots we can surely predict how much promising the field of Physical Layer Security is. Besides, if we use it properly, we can even stand strong against the rise of faster computation. The solution provided for the limitations of symmetric key encryption can easily implemented practically, since, due to the purpose of quality improvement of service, service providers already use the channel characteristics detection mechanism at the transmitter node.

Abstract :  Keystroke dynamics is gaining popularity and researchers are striving to improve existing techniques or to explore aspects that have not been given much attention. In this paper, a new means of authentication for keystroke dynamics has been provided, by using a password with different distances between the keys. The classifier used in this paper is neural network. The mean square error has been used to compute the performance of the classifier. After the analysis and evaluations of the results, it was deduced that distance of keys on a keyboard affect the reliability of the password. The mean square error of the most space digraph was in the range of 15.5×10-3 to 107.6 ×10-3 and the least distant digraph has a mean square error range of 8.5×10-8 to 3.7×10-9. In this way, it is observed that the smaller the distance between the keys of the password used, the easier is the keystroke pattern compromise compared to larger distance between keys. Hence, it can be concluded by the larger is the distance between the keys, the more the security increases.

Abstract :  This paper presents an improved algorithm to extract the fuzzy logic rules from measurement data, to be used in turn in a Fuzzy Logic Expert System FLES. Fuzzy logic rule extraction from measurement data is a complex task, this algorithm simplifies this task to a considerable degree. In a conventional algorithm, each input variable has its own set of input membership functions. In the algorithm we have developed, all input variables are normalized to the same minmax- ranges and have the same input membership functions IMFs. This means you just have only one set of membershipfunctions for all of the input variables, simplifying IMF definitions. Further simplification in this single IMF-definition is achieved by choosing suitable min-max values so that MFvertex values are round numbers for given number of IMFs. We have applied the same normalization technique to simplify the membership function definitions for the output variables. To illustrate the functionality and accuracy of the algorithm three case studies are used: one, measurement of battery state of charge SOC using FLES-based impedance-interrogation method; two, classical balance of inverted pendulum IP problem; and third, KB generated by some other study for the same IP-problem is compared with that generated by our algorithm. For implementing the three case studies, we developed three C++ programs for rule-extraction; and three other C++ programs for corresponding FLES-predictors. The FLES-predictor estimates outputs for a given set of inputs. If the extracted rule-set is correct, for a given measured input the estimated value must match with the corresponding measured value. The number of measurement pairs used in the case studies one, two, and three were: 100, 70 and 70. In case studies one and two the rms-error between the measured outputs and fuzzy-predicted outputs was within 3.3. In case study three, for a given input while KBs were slightly different, the rms-error between the output values predicted by our FLES-predictor the Motorola generated KB were near the same with less than 2.1 percent.