Convergence results for continuous-time dynamics arising in ant colony optimization

This paper studies the asymptotic behavior of several continuous-time dynamical systems which are analogs of ant colony optimization algorithms that solve shortest path problems. Local asymptotic stability of the equilibrium corresponding to the shortest path is shown under mild assumptions. A complete study is given for a recently proposed model called EigenAnt: global asymptotic stability is shown, and the speed of convergence is calculated explicitly and shown to be proportional to the difference between the reciprocals of the second shortest and the shortest paths.Comment: A short version of this paper was published in the preprints of the 19th World Congress of the International Federation of Automatic Control, Cape Town, South Africa, 24-29 August 201

Speech Delivered

Hon'ble Chief Minister, Prof. Altekar, Distinguished Guests and Friends, I do not feel very apologetic in joining the battery of non-technical speakers in the morning session, because everyone here will appreciate that the steel industry is so basic that it does not even allow non-technical people to remain innocent or non-technical for very long and that is why we are also participating in that International Symposia. My task this morning is on behalf of the steel industry of India, to extend a hearty welcome to our distinguished visitors and the steel technologists from abroad and from within the country as well as to thank the Organisers of the Symposium which promises to be probably the most significant Symposium of the year

Reviews

Rohinton MISTRY, A fine balanc

A cooperative conjugate gradient method for linear systems permitting multithread implementation of low complexity

This paper proposes a generalization of the conjugate gradient (CG) method used to solve the equation $Ax=b$ for a symmetric positive definite matrix $A$ of large size $n$. The generalization consists of permitting the scalar control parameters (= stepsizes in gradient and conjugate gradient directions) to be replaced by matrices, so that multiple descent and conjugate directions are updated simultaneously. Implementation involves the use of multiple agents or threads and is referred to as cooperative CG (cCG), in which the cooperation between agents resides in the fact that the calculation of each entry of the control parameter matrix now involves information that comes from the other agents. For a sufficiently large dimension $n$, the use of an optimal number of cores gives the result that the multithread implementation has worst case complexity $O(n^{2+1/3})$ in exact arithmetic. Numerical experiments, that illustrate the interest of theoretical results, are carried out on a multicore computer.Comment: Expanded version of manuscript submitted to the IEEE-CDC 2012 (Conference on Decision and Control

Bringing English into the 21st century: A view from India

English in India has had an extended and elite colonial history. It was the dominant language of governance in the 19th and 20th centuries till India became independent and a new set of language policies came into being. This paper traces the narrative of English on the Indian subcontinent from its genesis as a foreign and imperial tongue to its acceptance and ‘democratization’ as one amongst the many languages of India. It is emphasized that English in India has always existed in a vibrant multilingual environment and that the emergence of Indian English as a ‘world’ variety owes much to this fact. A detailed analysis of the lexicon, grammar and pragmatics of the English spoken today in urban India especially by India’s youth who comprise over 65% of India’s population is undertaken in the paper with a view to demonstrating that radical and striking shifts in attitudes toward English in India have occurred over the last few decades of economic liberalization and technological growth. Yet, the timeline created in this paper also shows that many of the paradoxes and dilemmas that attended English from its inception in India have not quite been banished. Rather, they have taken on new, acutely self-reflexive and challenging forms that will require a radical reassessment in the 21st century

Bio-cryptography using Zernike Moments and Key Generation by Cubic Splines

Cryptography is the process of protecting sensitive information and making it unreadable to unwanted parties. Since all algorithms that perform this task depend on the process of finding a suitable key, the key generation is considered the soul of powerful encryption. The traditionally generated keys are long and random, hence are difficult to memorize, and we need a database to store the keys. To alleviate this limitation, we use bio-cryptography that is combined of biometrics and cryptography. Using Bio-Cryptography generated keys provides the necessary security through powerful encryption and decryption of data. This paper uses cubic spline to generate a cryptographic key through extracting the features from fingerprint. The approach is based on extracting the features generated by using Zernike Moment on a biometric, and then sending these features to a Cubic-Spline Interpolator to generate the keys. A key encryption will be generated for every person through extracting the features from his / her biometric (fingerprint) and then applying these features on the cubic spline interpolator to obtain some points. These interpolated points will be used as keys to encrypt the information by using a suitable encryption algorithm.  The benefit presented by this approach is to ensure a high level of security to protect the information through generating secure keys ready to be used for unsecured channel. In this paper, we used fingerprints from Biometric Recognition Group - ATVS to examine the performance of this approach. Keywords: Biometrics, Key Generation, Zernike Moment, Cubic Spline, Cryptography, RSA, Fingerprint

Most Recent Malicious Software Datasets and Machine Learning Detection Techniques: A Review

مقدمة: في سياق الأمن السيبراني ، أصبح من الضروري مراقبة الأنظمة وتحليل البيانات للحفاظ على أمن البيانات وسلامتها. في الآونة الأخيرة ، أصبح من المهم إنشاء نظام لتحليل البيانات وتصنيفها ، بهدف منع أي برامج ضارة مثل البرامج الضارة. طرق العمل: تم استخدام أحدث مجموعة بيانات للبرامج الضارة وتقنيات التعلم الآلي الحديثة للكشف عن البرامج الضارة ، بناءً على اختيار الميزات الديناميكية. الاستنتاجات: أدت الزيادة المستمرة في عدد وأنواع الهجمات إلى توسع هائل في متغيرات عينات البرامج الضارة. لذلك ، يجب تصنيف البرامج الضارة إلى مجموعات وفقًا لسلوكها وتأثيرها وخصائصها. بالنظر إلى حقيقة أن البحث والتدريب عنصران أساسيان للأمن السيبراني ، فإن تغيير الطبيعة باستمرار يشكل تحديًا كبيرًا. تهدف هذه الدراسة بشكل أساسي إلى توضيح أحدث مجموعة بيانات للبرامج الضارة وتقنيات التعلم الآلي الحديثة للكشف عن البرامج الضارة ، بناءً على اختيار الميزات الديناميكيةBackground: Within the context of cyber security, it has become crucial to monitor systems and analyze data to maintain data security and integrity. Recently, it has become important to create a system for analyzing and classifying data, to prevent any malicious programs such as malware. Materials and Methods: The latest malware dataset and the latest machine-learning techniques were used to detect malware, based on dynamic feature identification. Results: The results showed that the FFNN algorithm was the best algorithm for the sorel20M dataset based on the research work discussed in this paper.  Conclusion: The continuous increase in the number and types of attacks has led to a huge expansion in the variants of malware samples. Therefore, malware needs to be categorized into groups according to their behavior, influence, and characteristics. Given the fact that research and training are essential elements of cyber security, its constantly changing nature poses a great challenge. This study mainly aims to demonstrate the most recent malware dataset and modern machine-learning techniques of malware detection, based on dynamic feature selection