Syntactic Based Machine Translation from English to Malayalam

Due to the emergence of multiple language support on the Internet, machine translation (MT) technologies are indispensable to the communication between speakers using different languages. Recent research works have started to explore tree-based machine translation systems with syntactical and morphological information. This work aims the development of Syntactic Based Machine Translation from English to Malayalam by adding different case information during translation. The system identifies general rules for various sentence patterns in English. These rules are generated using the Parts Of Speech (POS) tag information of the texts. Word Reordering based on the Syntax Tree is used to improve the translation quality of the system. The system used Bilingual English –Malayalam dictionary for translation.

Handling OOV Words in Phrase-Based Statistical Machine Translation for Malayalam

Statistical Machine Translation (SMT) is one of the potential applications in the field of Natural Language Processing. The translation process in SMT is carried out by acquiring translation rules automatically from the parallel corpora. However, for many language pairs (e.g. Malayalam- English), they are available only in very limited quantities. Therefore, for these language pairs a huge portion of phrases encountered at run-time will be unknown. This paper focuses on methods for handling such out-of-vocabulary (OOV) words in Malayalam that cannot be translated to English using conventional phrase-based statistical machine translation systems. The OOV words in the source sentence are pre-processed to obtain the root word and its suffix. Different inflected forms of the OOV root are generated and a match is looked up for the word variants in the phrase translation table of the translation model. A Vocabulary filter is used to choose the best among the translations of these word variants by finding the unigram count. A match for the OOV suffix is also looked up in the phrase entries and the target translations are filtered out. Structuring of the filtered phrases is done and SMT translation model is extended by adding OOV with its new phrase translations. By the results of the manual evaluation done it is observed that amount of OOV words in the input has been reduced considerably

Offline Handwritten Malayalam Character Recognition Based on Chain Code Histogram

Optical Character Recognition plays an important role in Digital Image Processing and Pattern Recognition. Even though ambient study had been performed on foreign languages like Chinese and Japanese, effort on Indian script is still immature. OCR in Malayalam language is more complex as it is enriched with largest number of characters among all Indian languages. The challenge of recognition of characters is even high in handwritten domain, due to the varying writing style of each individual. In this paper we propose a system for recognition of offline handwritten Malayalam vowels. The proposed method uses Chain code and Image Centroid for the purpose of extracting features and a two layer feed forward network with scaled conjugate gradient for classification

A Secure Email System Based on Identity Based Encryption

Now a days, email has become the most widely communication way in daily life. The main reason for using email is probably because of the convenience and speed in which it can be transmitted irrespective of geographical distances. To improve security and efficiency of email system, most of the email system adopt PKI and IBE encryption schemes. However, both PKI and IBE encryption schemes have their own shortcomings and consequently bring security issues to email systems. This paper proposes a new secure email system based on IBE which combines finger print authentication and proxy service for encryption and decryption

Matrix based Key Generation to Enhance Key Avalanche in Advanced Encryption Standard

In symmetric block ciphers, substitution and diffusion operations are performed in multiple rounds using sub-keys generated from a key generation procedure called key schedule. The key schedule plays a very important role in deciding the security of block ciphers. In this paper we propose a complex key generation procedure, based on matrix manipulations, which could be introduced in symmetric ciphers. The proposed key generation procedure offers two advantages. First, the procedure is simple to implement and has complexity in determining the sub-keys through crypt analysis. Secondly, the procedure produces a strong avalanche effect making many bits in the output block of a cipher to undergo changes with one bit change in the secret key. As a case study, matrix based key generation procedure has been introduced in Advanced Encryption Standard (AES) by replacing the existing key schedule of AES. The key avalanche and differential key propagation produced in AES have been observed. The paper describes the matrix based key generation procedure and the enhanced key avalanche and differential key propagation produced in AES. It has been shown that, the key avalanche effect and differential key propagation characteristics of AES have improved by replacing the AES key schedule with the Matrix based key generation procedure

Investigations on Metamaterial Based Spiral Inductors for Compact Microwave Devices

Division of Electronics Engineering

Conceptual information systems discussed through an IT-security tool

Conceptual Information Systems are based on a formalization of the concept of "concept" as it is discussed in traditional philosophical logic. This formalization supports a human-centered approach to the development of Information Systems. We discuss this approach by means of an implemented Conceptual Information System for supporting IT security management in companies and organizations.

Local food security and principle of organic farming (from farm to fork) in context of food culture in Indonesia: Minangkabau's case study

The basic idea behind improving local food security consists of two paths; first, accessibility (price, stock) and second, availability (quantity and biodiversity); both are perquisites to the provision of nutrients and a continuous food supply with locally available resources. The objectives of this thesis are to investigate if indigenous knowledge still plays an important role in traditional farming in the Minangkabau`s culture, thus supporting local food security. If the indigenous knowledge still plays a role in food culture in the Minangkabau`s culture which is linked to the matrilineal role and leads to a sound nutrition. Further, it should be tested if marantau influences traditional farming and food culture in Minangkabau`s, and if the local government plays a role in changing of traditional farming systems and food culture. Furthermore this thesis wants to prove if education and gender are playing a role in changing traditional farming system and food culture, and if the mass media affects traditional farming systems and food culture for the Minangkabau. The study was completed at four locations in West Sumatera; Nagari Ulakan (NU) (coastal area), Nagari Aia Batumbuak (NAB) (hilly area), Nagari Padang Laweh Malalo (NPLM) (lake area), Nagari Pandai Sikek (NPS) (hilly area). The rainfall ranged from 1400- 4800 mm annually with fertile soils. Data was collected by using PRA (Participatory Rural Appraisal) to investigate indigenous knowledge (IK) and its interactions, which is also combining with in depth-interview, life history, a survey using semi-structured-questionnaire, pictures, mapping, and expert interview. The data was collected from June - September 2009 and June 2010. The materials are; map of area, list of names, questionnaires, voices recorder, note book, and digital camera. The sampling method was snowball sampling which resulted in the qualitative and quantitative data taken. For qualitative data, ethnography and life history was used. For quantitative, a statistical survey with a semi-structured questionnaire was used. 50 respondents per each site participated voluntarily. Data was analyzed by performing MAXQDA 10, and F4 audio analysis software (created and developed by Philip-University Marburg). The data is clustered based on causality. The results show that; the role of IK on TFS (traditional farming system) shown on NPLM which has higher food crop biodiversity in comparison to the other three places even though it has relatively similar temperature and rainfall. This high food crop biodiversity is due to the awareness of local people who realized that they lived in unfavourable climate and topography; therefore they are more prepared for any changes that may occur. Carbohydrate intake is 100 % through rice even though they are growing different staple crops. Whereas most of the people said in the interviews that not eating rice is like not really eating for them. In addition to that, mothers still play an important role in kitchen activities. But when the agriculture income is low, mothers have to decide whether to change the meals or to feel insecure about their food supply. Marantau yields positive impact through the remittances it provides to invest on the farm. On the other hand, it results in fewer workers for agriculture, and therefore a negative impact on the transfer of IK. The investigation showed that the local government has a PTS (Padi Tanam Sabatang) programme which still does not guarantee that the farmers are getting sufficient revenue from their land. The low agricultural income leads to situation of potential food insecurity. It is evident that education is equal among men and women, but in some cases women tend to leave school earlier because of arranged marriages or the distances of school from their homes. Men predominantly work in agriculture and fishing, while women work in the kitchen. In NAB, even though women work on farmland they earn less then men. Weaving (NPS) and kitchen activity is recognized as women’s work, which also supports the household income. Mass media is not yielding any changes in TFS and food culture in these days. The traditional farming system has changed because of intensive agricultural extension which has introduced new methods of agriculture for the last three decades (since the 1980’s). There is no evidence that they want to change any of their food habits because of the mass media despite the lapau activity which allows them to get more food choices, instead preparing traditional meal at home. The recommendations of this thesis are: 1) The empowerment of farmers. It is regarding the self sufficient supply of manure, cooperative seed, and sustainable farm management. Farmers should know – where are they in their state of knowledge – so they can use their local wisdom and still collaborate with new sources of knowledge. Farmers should learn the prognosis of supply and demand next prior to harvest. There is a need for farm management guidelines; that can be adopted from both their local wisdom and modern knowledge. 2) Increase of non-agricultural income Increasing the non-agricultural income is strongly recommended. The remittances can be invested on non-agricultural jobs. 3) The empowerment of the mother. The mother plays an important role in farm to fork activities; the mother can be an initiator and promoter of cultivating spices in the backyard. Improvement of nutritional knowledge through information and informal public education can be done through arisan ibu-ibu and lapau activity. The challenges to apply these recommendations are: 1) The gap between institutions and organizations of local governments. There is more than one institution involved in food security policy. 2) Training and facilities for field extension agriculture (FEA) is needed because the rapid change of interaction between local government and farmer’s dependent on this agency.

Enterprise Modelling Approach based on Maturity and Business Scope perspectives

This paper introduces a framework that supports users to implement enterprise modelling within collaborative companies. These enterprise models are the basis for a holistic interoperability measurement and management methodology which will be presented in the second part of the paper. The discipline of enterprise modelling aims at capturing all dimensions of an enterprise in a simplified model. Thus enterprise models are the appropriate basis for managing collaborative enterprise as they reduce the complexity of interoperability problems. Therefore, a first objective of this paper is to present an approach that enables companies to get the most effect out of enterprise modelling in a collaborative environment based on the maturity of their organisation relative to modelling. Within this first step, the user will get recommendations e.g. for the correct modelling language as well as the right level of detail.

Improving food and nutritional security of small and marginal coconut growers through diversification of crops and enterprises

This paper presents the impact of integrating interventions like nutrition gardening, livestock rearing, product diversification and allied income generation activities in small and marginal coconut homesteads along with nutrition education in improving the food and nutritional security as well as the income of the family members. The activities were carried out through registered Community Based Organizations (CBOs) in three locations in Kerala, India during 2005-2008. Data was collected before and after the project periods through interviews using a pre-tested questionnaire containing statements indicating the adequacy, quality and diversity of food materials. Fifty respondents each were randomly selected from the three communities, thereby resulting in a total sample size of 150. The data was analysed using SPSS by adopting statistical tools like frequency, average, percentage analysis, t – test and regression. Participatory planning and implementation of diverse interventions notably intercropping and off-farm activities along with nutrition education brought out significant improvements in the food and nutritional security, in terms of frequency and quantity of consumption as well as diet diversity. At the end of the project, 96%of the members became completely food secure and 72% nutritionally secure. The overall consumption of fruits, vegetables and milk by both children and adults and egg by children recorded increase over the project period. Consumption of fish was more than the Recommended Dietary Intake (RDI) level during pre and post project periods. Project interventions like nutrition gardening could bring in surplus consumption of vegetables (35%) and fruits (10%) than RDI. In spite of the increased consumption of green leafy vegetables and milk and milk products over the project period, the levels of consumption were still below the RDI levels. CBO-wise analysis of the consumption patterns revealed the need for location-specific interventions matching to the needs and preferences of the communities.

Climate-Adaptive Community Water Management for Food Security: Experiences from the UNDP Community Water Initiative

Facing the double menace of climate change threats and water crisis, poor communities have now encountered ever more severe challenges in ensuring agricultural productivity and food security. Communities hence have to manage these challenges by adopting a comprehensive approach that not only enhances water resource management, but also adapts agricultural activities to climate variability. Implemented by the Global Environment Facility’s Small Grants Programme, the Community Water Initiative (CWI) has adopted a distinctive approach to support demand-driven, innovative, low cost and community-based water resource management for food security. Experiences from CWI showed that a comprehensive, locally adapted approach that integrates water resources management, poverty reduction, climate adaptation and community empowerment provides a good model for sustainable development in poor rural areas.

Adaptive Real-time Anomaly-based Intrusion Detection using Data Mining and Machine Learning Techniques

Die zunehmende Vernetzung der Informations- und Kommunikationssysteme führt zu einer weiteren Erhöhung der Komplexität und damit auch zu einer weiteren Zunahme von Sicherheitslücken. Klassische Schutzmechanismen wie Firewall-Systeme und Anti-Malware-Lösungen bieten schon lange keinen Schutz mehr vor Eindringversuchen in IT-Infrastrukturen. Als ein sehr wirkungsvolles Instrument zum Schutz gegenüber Cyber-Attacken haben sich hierbei die Intrusion Detection Systeme (IDS) etabliert. Solche Systeme sammeln und analysieren Informationen von Netzwerkkomponenten und Rechnern, um ungewöhnliches Verhalten und Sicherheitsverletzungen automatisiert festzustellen. Während signatur-basierte Ansätze nur bereits bekannte Angriffsmuster detektieren können, sind anomalie-basierte IDS auch in der Lage, neue bisher unbekannte Angriffe (Zero-Day-Attacks) frühzeitig zu erkennen. Das Kernproblem von Intrusion Detection Systeme besteht jedoch in der optimalen Verarbeitung der gewaltigen Netzdaten und der Entwicklung eines in Echtzeit arbeitenden adaptiven Erkennungsmodells. Um diese Herausforderungen lösen zu können, stellt diese Dissertation ein Framework bereit, das aus zwei Hauptteilen besteht. Der erste Teil, OptiFilter genannt, verwendet ein dynamisches "Queuing Concept", um die zahlreich anfallenden Netzdaten weiter zu verarbeiten, baut fortlaufend Netzverbindungen auf, und exportiert strukturierte Input-Daten für das IDS. Den zweiten Teil stellt ein adaptiver Klassifikator dar, der ein Klassifikator-Modell basierend auf "Enhanced Growing Hierarchical Self Organizing Map" (EGHSOM), ein Modell für Netzwerk Normalzustand (NNB) und ein "Update Model" umfasst. In dem OptiFilter werden Tcpdump und SNMP traps benutzt, um die Netzwerkpakete und Hostereignisse fortlaufend zu aggregieren. Diese aggregierten Netzwerkpackete und Hostereignisse werden weiter analysiert und in Verbindungsvektoren umgewandelt. Zur Verbesserung der Erkennungsrate des adaptiven Klassifikators wird das künstliche neuronale Netz GHSOM intensiv untersucht und wesentlich weiterentwickelt. In dieser Dissertation werden unterschiedliche Ansätze vorgeschlagen und diskutiert. So wird eine classification-confidence margin threshold definiert, um die unbekannten bösartigen Verbindungen aufzudecken, die Stabilität der Wachstumstopologie durch neuartige Ansätze für die Initialisierung der Gewichtvektoren und durch die Stärkung der Winner Neuronen erhöht, und ein selbst-adaptives Verfahren eingeführt, um das Modell ständig aktualisieren zu können. Darüber hinaus besteht die Hauptaufgabe des NNB-Modells in der weiteren Untersuchung der erkannten unbekannten Verbindungen von der EGHSOM und der Überprüfung, ob sie normal sind. Jedoch, ändern sich die Netzverkehrsdaten wegen des Concept drif Phänomens ständig, was in Echtzeit zur Erzeugung nicht stationärer Netzdaten führt. Dieses Phänomen wird von dem Update-Modell besser kontrolliert. Das EGHSOM-Modell kann die neuen Anomalien effektiv erkennen und das NNB-Model passt die Änderungen in Netzdaten optimal an. Bei den experimentellen Untersuchungen hat das Framework erfolgversprechende Ergebnisse gezeigt. Im ersten Experiment wurde das Framework in Offline-Betriebsmodus evaluiert. Der OptiFilter wurde mit offline-, synthetischen- und realistischen Daten ausgewertet. Der adaptive Klassifikator wurde mit dem 10-Fold Cross Validation Verfahren evaluiert, um dessen Genauigkeit abzuschätzen. Im zweiten Experiment wurde das Framework auf einer 1 bis 10 GB Netzwerkstrecke installiert und im Online-Betriebsmodus in Echtzeit ausgewertet. Der OptiFilter hat erfolgreich die gewaltige Menge von Netzdaten in die strukturierten Verbindungsvektoren umgewandelt und der adaptive Klassifikator hat sie präzise klassifiziert. Die Vergleichsstudie zwischen dem entwickelten Framework und anderen bekannten IDS-Ansätzen zeigt, dass der vorgeschlagene IDSFramework alle anderen Ansätze übertrifft. Dies lässt sich auf folgende Kernpunkte zurückführen: Bearbeitung der gesammelten Netzdaten, Erreichung der besten Performanz (wie die Gesamtgenauigkeit), Detektieren unbekannter Verbindungen und Entwicklung des in Echtzeit arbeitenden Erkennungsmodells von Eindringversuchen.

The Role of Epistemic Monitoring in Language Comprehension

In der psycholinguistischen Forschung ist die Annahme weitverbreitet, dass die Bewertung von Informationen hinsichtlich ihres Wahrheitsgehaltes oder ihrer Plausibilität (epistemische Validierung; Richter, Schroeder & Wöhrmann, 2009) ein strategischer, optionaler und dem Verstehen nachgeschalteter Prozess ist (z.B. Gilbert, 1991; Gilbert, Krull & Malone, 1990; Gilbert, Tafarodi & Malone, 1993; Herbert & Kübler, 2011). Eine zunehmende Anzahl an Studien stellt dieses Zwei-Stufen-Modell von Verstehen und Validieren jedoch direkt oder indirekt in Frage. Insbesondere Befunde zu Stroop-artigen Stimulus-Antwort-Kompatibilitätseffekten, die auftreten, wenn positive und negative Antworten orthogonal zum aufgaben-irrelevanten Wahrheitsgehalt von Sätzen abgegeben werden müssen (z.B. eine positive Antwort nach dem Lesen eines falschen Satzes oder eine negative Antwort nach dem Lesen eines wahren Satzes; epistemischer Stroop-Effekt, Richter et al., 2009), sprechen dafür, dass Leser/innen schon beim Verstehen eine nicht-strategische Überprüfung der Validität von Informationen vornehmen. Ausgehend von diesen Befunden war das Ziel dieser Dissertation eine weiterführende Überprüfung der Annahme, dass Verstehen einen nicht-strategischen, routinisierten, wissensbasierten Validierungsprozesses (epistemisches Monitoring; Richter et al., 2009) beinhaltet. Zu diesem Zweck wurden drei empirische Studien mit unterschiedlichen Schwerpunkten durchgeführt. Studie 1 diente der Untersuchung der Fragestellung, ob sich Belege für epistemisches Monitoring auch bei Informationen finden lassen, die nicht eindeutig wahr oder falsch, sondern lediglich mehr oder weniger plausibel sind. Mithilfe des epistemischen Stroop-Paradigmas von Richter et al. (2009) konnte ein Kompatibilitätseffekt von aufgaben-irrelevanter Plausibilität auf die Latenzen positiver und negativer Antworten in zwei unterschiedlichen experimentellen Aufgaben nachgewiesen werden, welcher dafür spricht, dass epistemisches Monitoring auch graduelle Unterschiede in der Übereinstimmung von Informationen mit dem Weltwissen berücksichtigt. Darüber hinaus belegen die Ergebnisse, dass der epistemische Stroop-Effekt tatsächlich auf Plausibilität und nicht etwa auf der unterschiedlichen Vorhersagbarkeit von plausiblen und unplausiblen Informationen beruht. Das Ziel von Studie 2 war die Prüfung der Hypothese, dass epistemisches Monitoring keinen evaluativen Mindset erfordert. Im Gegensatz zu den Befunden anderer Autoren (Wiswede, Koranyi, Müller, Langner, & Rothermund, 2013) zeigte sich in dieser Studie ein Kompatibilitätseffekt des aufgaben-irrelevanten Wahrheitsgehaltes auf die Antwortlatenzen in einer vollständig nicht-evaluativen Aufgabe. Die Ergebnisse legen nahe, dass epistemisches Monitoring nicht von einem evaluativen Mindset, möglicherweise aber von der Tiefe der Verarbeitung abhängig ist. Studie 3 beleuchtete das Verhältnis von Verstehen und Validieren anhand einer Untersuchung der Online-Effekte von Plausibilität und Vorhersagbarkeit auf Augenbewegungen beim Lesen kurzer Texte. Zusätzlich wurde die potentielle Modulierung dieser Effeke durch epistemische Marker, die die Sicherheit von Informationen anzeigen (z.B. sicherlich oder vielleicht), untersucht. Entsprechend der Annahme eines schnellen und nicht-strategischen epistemischen Monitoring-Prozesses zeigten sich interaktive Effekte von Plausibilität und dem Vorhandensein epistemischer Marker auf Indikatoren früher Verstehensprozesse. Dies spricht dafür, dass die kommunizierte Sicherheit von Informationen durch den Monitoring-Prozess berücksichtigt wird. Insgesamt sprechen die Befunde gegen eine Konzeptualisierung von Verstehen und Validieren als nicht-überlappenden Stufen der Informationsverarbeitung. Vielmehr scheint eine Bewertung des Wahrheitsgehalts oder der Plausibilität basierend auf dem Weltwissen – zumindest in gewissem Ausmaß – eine obligatorische und nicht-strategische Komponente des Sprachverstehens zu sein. Die Bedeutung der Befunde für aktuelle Modelle des Sprachverstehens und Empfehlungen für die weiterführende Forschung zum Vehältnis von Verstehen und Validieren werden aufgezeigt.

Principle-Based Parsing

During the past few years, there has been much discussion of a shift from rule-based systems to principle-based systems for natural language processing. This paper outlines the major computational advantages of principle-based parsing, its differences from the usual rule-based approach, and surveys several existing principle-based parsing systems used for handling languages as diverse as Warlpiri, English, and Spanish, as well as language translation.

UNITRAN: A Principle-Based Approach to Machine Translation

Machine translation has been a particularly difficult problem in the area of Natural Language Processing for over two decades. Early approaches to translation failed since interaction effects of complex phenomena in part made translation appear to be unmanageable. Later approaches to the problem have succeeded (although only bilingually), but are based on many language-specific rules of a context-free nature. This report presents an alternative approach to natural language translation that relies on principle-based descriptions of grammar rather than rule-oriented descriptions. The model that has been constructed is based on abstract principles as developed by Chomsky (1981) and several other researchers working within the "Government and Binding" (GB) framework. Thus, the grammar is viewed as a modular system of principles rather than a large set of ad hoc language-specific rules.