Implementation of Rule Based Algorithm for Sandhi-Vicheda Of Compound Hindi Words

Sandhi means to join two or more words to coin new word. Sandhi literally means `putting together' or combining (of sounds), It denotes all combinatory sound-changes effected (spontaneously) for ease of pronunciation. Sandhi-vicheda describes [5] the process by which one letter (whether single or cojoined) is broken to form two words. Part of the broken letter remains as the last letter of the first word and part of the letter forms the first letter of the next letter. Sandhi-Vicheda is an easy and interesting way that can give entirely new dimension that add new way to traditional approach to Hindi Teaching. In this paper using the Rule based algorithm we have reported an accuracy of 60-80% depending upon the number of rules to be implemented

Evaluation of Hindi to Punjabi Machine Translation System

Machine Translation in India is relatively young. The earliest efforts date from the late 80s and early 90s. The success of every system is judged from its evaluation experimental results. Number of machine translation systems has been started for development but to the best of author knowledge, no high quality system has been completed which can be used in real applications. Recently, Punjabi University, Patiala, India has developed Punjabi to Hindi Machine translation system with high accuracy of about 92%. Both the systems i.e. system under question and developed system are between same closely related languages. Thus, this paper presents the evaluation results of Hindi to Punjabi machine translation system. It makes sense to use same evaluation criteria as that of Punjabi to Hindi Punjabi Machine Translation System. After evaluation, the accuracy of the system is found to be about 95%

Terrorism and Role of Media

Terrorism is the systematic use of terror, violent or destructive acts committed by groups in order to intimidate a population or government into granting their demands. All the developed, developing nations have confronted the horrors of Terrorism. It is one of him devastating threats for the whole world. Due to the advent of Terrorism in humane life, we have been confined to in destruction. To live the life of a common man becomes unendurable. Further the role of media and science is very much evident in Terrorism. Terror means disastrous fear. It becomes highly destructive and leading us towards the Holocaust. This paper proposes to examine the role of media in Terrorism. Really, it is the need of the hour that we should have to awaken our society. Technology has enabled Terrorism and Terrorism to create havoc in the world. But at the same time there are so many solutions which can be found & implemented by the technologies. Therefore, here in such circumstances, we have to take an oath to fight against Terrorism and establish ourselves well equipped and enforced. It will also not come to happen without the optimum utilization of technology. The paper illustrates definition, types, history of Terrorism and history of Terrorists group too in brief. It also gives an outline of Terrorism by ideology, involvement of state etc. A successful attempt has also been made to rule out the basic cause of terrorism and role of media in terrorism. As Terrorism appears to be one of the burning issues in present state of world However, this paper is going evaluate the role of media in the Terrorism

Application of Diversity Techniques for Multi User IDMA Communication System

In wireless communication, fading problem is mitigated with help of diversity techniques. This paper presents Maximal Ratio Combining (MRC) diversity approach to uproot the fading problem in interleave-division multiple-access (IDMA) scheme. The approach explains receiver diversity as well as transmits diversity analysis as 1:2 and 2:1 antenna system in fading environment, no. of antennas can be increased to improve diversity order. Random interleaver as well tree based interleaver has been taken for study. Significant improvements in performance of IDMA communication is observed with application of diversity techniques. Keywords: Random Interleaver, Tree Based Interleaver, MRC diversity, IDM

Rate enhancing role of molybdenum chloride in molten KCl for methane activation

Molten salts have been recently used as catalysts for methane pyrolysis to generate hydrogen and carbon. It was found that molten alkali chlorides, which are poor catalysts, become rather active upon the addition of a small amount of FeCl3. Calculations have shown that this takes place through an unusual mechanism. Due to fluctuations in the position of the ions, the charge on the iron fluctuates between Fe3+ and Fe2+. The electron required for forming Fe2+ is donated by several chlorine ions, and this causes them to be active in breaking the carbon hydrogen bond in methane. It was suggested that this mechanism is general: it takes place whenever the dopant is such that a lower charge state is possible. We test this hypothesis here by examining KCl doped with MoCl5, MoCl4, or MoCl3. We find that MoCl5 and MoCl4 activate KCl by the mechanism described above. MoCl3 does not because Mo3+ is not converted by fluctuations to Mo2+. We also show that the gas-phase dissociation energy of molybdenum chloride can be used as a descriptor to assess its ability to activate methane. Because it is easy to remove one Cl from MoCl5 or MoCl4, they are effective dopants for methane activation. The energy required for the dissociation of MoCl3 is very high, and doping with MoCl3 does not improve catalytic activity

Focal Left Atrial Tachycardia in a Patient with Left Ventricular Noncompaction

Left ventricular noncompaction (LVNC) is a rare disease caused by intrauterine failure of the myocardium to compact. The major clinical manifestations of LVNC include heart failure, ventricular tachyarrhythmia, thromboembolic event, and sudden deaths. Atrial arrhythmia usually seen is atrial fibrillation. We report a rare case of focal left atrial tachycardia in an 18-year-old patient who presented for evaluation of persistent tachycardia. Transthoracic echocardiogram showed severe systolic dysfunction and evidence of noncompaction of the left ventricle. A detailed review of ECG revealed the possibility of ectopic atrial tachycardia, most likely originating from the left side. Electrophysiology study showed sustained atrial tachycardia originating on the ridge anterior to the left sided pulmonary veins. A successful radiofrequency catheter ablation was performed at this site without any complications

EXTRACTING PROVERBS IN MACHINE TRANSLATION FROM HINDI TO PUNJABI USING RELATIONAL DATA APPROACH

1 , Vishal.pup @gmail.com 2 Proverb is a group of two or more words which cannot be directly translated into another language word by word. These groups of words have a special behaviour. Machine Translation faces a lot of complex problems from its origination. Extracting proverbs is also one of the complex problems in Machine Translation. Finding proverbs during translating a sentence from Hindi to Punjabi, through existing solutions, takes a lot of time. We have designed a simple relational data approach to find and handle proverbs. This approach handles proverbs efficiently

Applying Convolutional-GRU for Term Deposit Likelihood Prediction

Banks are normally offered two kinds of deposit accounts. It consists of deposits like current/saving account and term deposits like fixed or recurring deposits.For enhancing the maximized profit from bank as well as customer perspective, term deposit can accelerate uplifting of finance fields. This paper focuses on likelihood of term deposit subscription taken by the customers. Bank campaign efforts and customer detail analysis caninfluence term deposit subscription chances. An automated system is approached in this paper that works towards prediction of term deposit investment possibilities in advance. This paper proposes deep learning based hybrid model that stacks Convolutional layers and Recurrent Neural Network (RNN) layers as predictive model. For RNN, Gated Recurrent Unit (GRU) is employed. The proposed predictive model is later compared with other benchmark classifiers such as k-Nearest Neighbor (k-NN), Decision tree classifier (DT), and Multi-layer perceptron classifier (MLP). Experimental study concludesthat proposed model attainsan accuracy of 89.59% and MSE of 0.1041 which outperform wellother baseline models