Discrete Time Inventory Models with/without Positive Service Time

In everyday life different flows of customers to avail some service facility or other at some service station are experienced. In some of these situations, congestion of items arriving for service, because an item cannot be serviced Immediately on arrival, is unavoidable. A queuing system can be described as customers arriving for service, waiting for service if it is not immediate, and if having waited for service, leaving the system after being served. Examples Include shoppers waiting in front of checkout stands in a supermarket, Programs waiting to be processed by a digital computer, ships in the harbor Waiting to be unloaded, persons waiting at railway booking office etc. A queuing system is specified completely by the following characteristics: input or arrival pattern, service pattern, number of service channels, System capacity, queue discipline and number of service stages. The ultimate objective of solving queuing models is to determine the characteristics that measure the performance of the system

Immobilization of nitrifying bacterial consortia on wood particles for bioaugmenting nitrification in shrimp culture systems

Shrimp grow out systems under zero water exchange mode demand constant remediation of total ammonia nitrogen (TAN) andNO2 −–Nto protect the crop. To address this issue, aninexpensive and user-friendly technology using immobilized nitrifying bacterial consortia (NBC) as bioaugmentors has been developed and proposed for adoption in shrimp culture systems. Indigenous NBC stored at 4 °C were activated at room temperature (28 °C) and cultured in a 2 L bench top fermentor. The consortia, after enumeration by epifluorescence microscopy,were immobilized on delignifiedwood particles of a soft wood tree Ailantus altissima (300–1500 μm) having a surface area of 1.87m2 g−1. Selection of wood particle as substratumwas based on adsorption of NBC on to the particles, biofilm formation, and their subsequent nitrification potential. The immobilization could be achievedwithin 72 h with an initial cell density of 1×105 cells mL−1. On experimenting with the lowest dosage of 0.2 g (wet weight) immobilized NBC in 20 L seawater, a TAN removal rate of 2.4 mg L−1 within three days was observed. An NBC immobilization device could be developed for on site generation of the bioaugmentor preparation as per requirement. The product of immobilization never exhibited lag phase when transferred to fresh medium. The extent of nitrification in a simulated systemwas two times the rate observed in the control systems suggesting the efficacy in real life situations. The products of nitrification in all experiments were undetectable due to denitrifying potency, whichmade the NBC an ideal option for biological nitrogen removal. The immobilized NBC thus generated has been named TANOX (Total Ammonia Nitrogen Oxidizer)

Development of nitrifying bacterial consortia for immobilizing in nitrifying bioreactors designed for penaeid and non-penaeid larval rearing systems in the tropics

Two ammonia oxidizing (AMOPCU-1 and AMONPCU-1) and two nitrite oxidizing (NIOPCU-1 and NIONPCU-1) consortia for activating nitrifying bioreactors and thereby establishing nitrification in penaeid and non-penaeid hatchery systems were developed by enrichment. For further amplification of the consortia a simple medium having seawater (either salinity 30 ‰ or 15 ‰) as base, supplemented with NH4+-N/NO2--N and PO4- and pH adjusted to 8 was identified. During the amplification in a fermentor the consortia exhibited excessive wall growth and diminished their yield coefficient posing difficulty in harvesting the cells completely. The consortia consisted of both Gram negative and Gram-positive bacterial cells embedded in a mucilaginous matrix of glycocalyx - like material presumably composed of polysaccharides. The consortia besides being useful in activating nitrifying bioreactors developed for shrimp/prawn hatchery systems can also be used as bioaugmentors in the bioremediation of ammonia and nitrite toxicity in aquaculture systems.

Antimicrobial activity of chitosan against vibrios from freshwater prawn Macrobrachium rosenbergii larval rearing systems

Chitosan is a biocompatible and biodegradable natural polymer with established antimicrobial properties against specific microorganisms. The present study demonstrates its antibacterial activity against 48 isolates of Vibrio species from prawn larval rearing systems. The antibacterial activity had a positive correlation with the concentration of chitosan. This work opens up avenues for using chitosan as a prophylactic biopolymer for protecting prawn larvae from vibriosis.

Research Directions in Cyber Physical Systems

Cyber Physical systems (CPS) connect the physical world with cyber world. The events happening in the real world is enormous and most of it go unnoticed and information is lost. CPS enables to embed tiny smart devices to capture the data and send it to Internet for further processing. The entire set-up call for lots of challenges and open new research problems. This talk is a journey through the landscape of research problems in this emerging area.

Learning analysis by reduction from positive data

Analysis by reduction is a linguistically motivated method for checking correctness of a sentence. It can be modelled by restarting automata. In this paper we propose a method for learning restarting automata which are strictly locally testable (SLT-R-automata). The method is based on the concept of identification in the limit from positive examples only. Also we characterize the class of languages accepted by SLT-R-automata with respect to the Chomsky hierarchy.

Designing in the real world is complex anyway - so what?

Designing is a heterogeneous, fuzzily defined, floating field of various activities and chunks of ideas and knowledge. Available theories about the foundations of designing as presented in "the basic PARADOX" (Jonas and Meyer-Veden 2004) have evoked the impression of Babylonian confusion. We located the reasons for this "mess" in the "non-fit", which is the problematic relation of theories and subject field. There seems to be a comparable interface problem in theory-building as in designing itself. "Complexity" sounds promising, but turns out to be a problematic and not really helpful concept. I will argue for a more precise application of systemic and evolutionary concepts instead, which - in my view - are able to model the underlying generative structures and processes that produce the visible phenomenon of complexity. It does not make sense to introduce a new fashionable meta-concept and to hope for a panacea before having clarified the more basic and still equally problematic older meta-concepts. This paper will take one step away from "theories of what" towards practice and doing and try to have a closer look at existing process models or "theories of how" to design instead. Doing this from a systemic perspective leads to an evolutionary view of the process, which finally allows to specify more clearly the "knowledge gaps" inherent in the design process. This aspect has to be taken into account as constitutive of any attempt at theory-building in design, which can be characterized as a "practice of not-knowing". I conclude, that comprehensive "unified" theories, or methods, or process models run aground on the identified knowledge gaps, which allow neither reliable models of the present, nor reliable projections into the future. Consolation may be found in performing a shift from the effort of adaptation towards strategies of exaptation, which means the development of stocks of alternatives for coping with unpredictable situations in the future.

CD-Systems of Restarting Automata

Die vorliegende Arbeit behandelt Restartautomaten und Erweiterungen von Restartautomaten. Restartautomaten sind ein Werkzeug zum Erkennen formaler Sprachen. Sie sind motiviert durch die linguistische Methode der Analyse durch Reduktion und wurden 1995 von Jancar, Mráz, Plátek und Vogel eingeführt. Restartautomaten bestehen aus einer endlichen Kontrolle, einem Lese/Schreibfenster fester Größe und einem flexiblen Band. Anfänglich enthält dieses sowohl die Eingabe als auch Bandbegrenzungssymbole. Die Berechnung eines Restartautomaten läuft in so genannten Zyklen ab. Diese beginnen am linken Rand im Startzustand, in ihnen wird eine lokale Ersetzung auf dem Band durchgeführt und sie enden mit einem Neustart, bei dem das Lese/Schreibfenster wieder an den linken Rand bewegt wird und der Startzustand wieder eingenommen wird. Die vorliegende Arbeit beschäftigt sich hauptsächlich mit zwei Erweiterungen der Restartautomaten: CD-Systeme von Restartautomaten und nichtvergessende Restartautomaten. Nichtvergessende Restartautomaten können einen Zyklus in einem beliebigen Zustand beenden und CD-Systeme von Restartautomaten bestehen aus einer Menge von Restartautomaten, die zusammen die Eingabe verarbeiten. Dabei wird ihre Zusammenarbeit durch einen Operationsmodus, ähnlich wie bei CD-Grammatik Systemen, geregelt. Für beide Erweiterungen zeigt sich, dass die deterministischen Modelle mächtiger sind als deterministische Standardrestartautomaten. Es wird gezeigt, dass CD-Systeme von Restartautomaten in vielen Fällen durch nichtvergessende Restartautomaten simuliert werden können und andererseits lassen sich auch nichtvergessende Restartautomaten durch CD-Systeme von Restartautomaten simulieren. Des Weiteren werden Restartautomaten und nichtvergessende Restartautomaten untersucht, die nichtdeterministisch sind, aber keine Fehler machen. Es zeigt sich, dass diese Automaten durch deterministische (nichtvergessende) Restartautomaten simuliert werden können, wenn sie direkt nach der Ersetzung einen neuen Zyklus beginnen, oder ihr Fenster nach links und rechts bewegen können. Außerdem gilt, dass alle (nichtvergessenden) Restartautomaten, die zwar Fehler machen dürfen, diese aber nach endlich vielen Zyklen erkennen, durch (nichtvergessende) Restartautomaten simuliert werden können, die keine Fehler machen. Ein weiteres wichtiges Resultat besagt, dass die deterministischen monotonen nichtvergessenden Restartautomaten mit Hilfssymbolen, die direkt nach dem Ersetzungsschritt den Zyklus beenden, genau die deterministischen kontextfreien Sprachen erkennen, wohingegen die deterministischen monotonen nichtvergessenden Restartautomaten mit Hilfssymbolen ohne diese Einschränkung echt mehr, nämlich die links-rechts regulären Sprachen, erkennen. Damit werden zum ersten Mal Restartautomaten mit Hilfssymbolen, die direkt nach dem Ersetzungsschritt ihren Zyklus beenden, von Restartautomaten desselben Typs ohne diese Einschränkung getrennt. Besonders erwähnenswert ist hierbei, dass beide Automatentypen wohlbekannte Sprachklassen beschreiben.

Applicability of Emergence Engineering to Distributed Systems Scenarios

Genetic Programming can be effectively used to create emergent behavior for a group of autonomous agents. In the process we call Offline Emergence Engineering, the behavior is at first bred in a Genetic Programming environment and then deployed to the agents in the real environment. In this article we shortly describe our approach, introduce an extended behavioral rule syntax, and discuss the impact of the expressiveness of the behavioral description to the generation success, using two scenarios in comparison: the election problem and the distributed critical section problem. We evaluate the results, formulating criteria for the applicability of our approach.

On Globally Deterministic CD-Systems of Stateless R-Automata with Window Size One

It is known that cooperating distributed systems (CD-systems) of stateless deterministic restarting automata with window size 1 accept a class of semi-linear languages that properly includes all rational trace languages. Although the component automata of such a CD-system are all deterministic, in general the CD-system itself is not, as in each of its computations, the initial component and the successor components are still chosen nondeterministically. Here we study CD-systems of stateless deterministic restarting automata with window size 1 that are themselves completely deterministic. In fact, we consider two such types of CD-systems, the strictly deterministic systems and the globally deterministic systems.

Agri-environmental evaluation of traditional and alternative corn production systems in Chiapas, Mexico

This study evaluates the effects of environmental variables on traditional and alternative agroecosystems in three Ejidos (communal lands) in the Chiapas rainforest in Mexico. The tests occurred within two seasonal agricultural cycles. In spring-summer, experiments were performed with the traditional slash, fell and burn (S-F-B) system, no-burn systems and rotating systems with Mucuna deeringiana Bort., and in the autumn-winter agricultural cycle, three no-burn systems were compared to evaluate the effect of alternative sowing with corn (no-burn and topological modification of sowing). The results show a high floristic diversity in the study area (S_S = 4 - 23%), with no significant differences among the systems evaluated. In the first cycle, the analysis of the agronomical variables of the corn indicated better properties in the fallowing systems, with an average yield of 1950 kg ha^‑1, but there was variation related to the number of years left fallow. In the second cycle, the yields were positive for the alternative technology (average yield 3100 kg ha^‑1). The traditional S-F-B systems had reduced pests and increased organic matter and soil phosphorous content. These results are the consequence of fallow periods and adaptation to the environment; thus, this practice in the Chiapas rainforest constitutes an ethnocultural reality, which is unlikely to change in the near future if the agrosystems are managed based on historical principles.

Effects of transformation processes in 'jubraka' agroforestry systems of the Nuba Mountains, Sudan, on nutrient fluxes

Intensification processes in homegardens of the Nuba Mountains, Sudan, raise concerns about strongly positive carbon (C) and nutrient balances which are expected to lead to substantial element losses from these agroecosystems, in particular via soil gaseous emissions. Therefore, this thesis aimed at the quantification of C, nitrogen (N), phosphorus (P) and potassium (K) input and output fluxes with a special focus on soil gaseous losses, and the calculation of respective element balances. A further focus in this thesis was rainfall, a valuable resource for rain-fed agriculture in the Nuba Mountains. To minimize negative consequences of the high variability of rainfall, risk reducing mechanisms were developed by rain-fed farmers that may lose their efficacy in the course of climate change effects predicted for East Africa. Therefore, the second objective of this study was to examine possible changes in rainfall amounts during the last 60 years and to provide reliable risk and probability statements of rainfall-induced events of agricultural importance to rain-fed farmers in the Nuba Mountains. Soil gaseous emissions of C (in form of CO2) and N (in form of NH3 and N2O) of two traditional and two intensified homegardens were determined with a portable dynamic closed chamber system. For C gaseous emission rates reached their peak at the onset of the rainy season (2,325 g CO2-C ha-1 h-1 in an intensified garden type) and for N during the rainy season (16 g NH3-N ha-1 h-1 and 11.3 g N2O-N ha-1 h-1, in a traditional garden type). Data indicated cumulative annual emissions of 5,893 kg CO2-C ha-1, 37 kg NH3-N ha-1, and 16 kg N2O-N ha-1. For the assessment of the long-term productivity of the two types of homegardens and the identification of pathways of substantial element losses, a C and nutrient budget approach was used. In three traditional and three intensified homegardens observation plots were selected. The following variables were quantified on each plot between June and December in 2010: soil amendments, irrigation, biomass removal, symbiotic N2 fixation, C fixation by photosynthesis, atmospheric wet and dry deposition, leaching and soil gaseous emissions. Annual balances for C and nutrients amounted to -21 kg C ha-1, -70 kg N ha-1, 9 kg P ha-1 and -117 kg K ha-1 in intensified homegardens and to -1,722 kg C ha-1, -167 kg N ha-1, -9 kg P ha-1 and -74 kg K ha-1 in traditional homegardens. For the analysis of rainfall data, the INSTAT+ software allowed to aggregate long-term daily rainfall records from the Kadugli and Rashad weather stations into daily, monthly and annual intervals and to calculate rainfall-induced events of agricultural importance. Subsequently, these calculated values and events were checked for possible monotonic trends by Mann-Kendall tests. Over the period from 1970 to 2009, annual rainfall did not change significantly for either station. However, during this period an increase of low rainfall events coinciding with a decline in the number of medium daily rainfall events was observed in Rashad. Furthermore, the availability of daily rainfall data enabled frequency and conditional probability calculations that showed either no statistically significant changes or trends resulting only in minor changes of probabilities.

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.

Optimising contributions of goat farming to household economic success and food security in three production systems in Ethiopia

The study aims to analyse factors affecting contributions of goat farming to household economic success and food security in three goat production systems of Ethiopia. A study was conducted in three districts of Ethiopia representing arid agro-pastoral (AAP), semi-arid agro-pastoral (SAAP) and highland mixed crop-livestock (HMCL) systems involving 180 goat keeping households. Gross margin (GM) and net benefit (NB1 and NB2) were used as indicators of economic success of goat keeping. NB1 includes in-kind benefits of goats (consumption and manure), while NB2 additionally constitutes intangible benefits (insurance and finance). Household dietary diversity score (HDDS) was used as a proxy indicator of food security. GM was significantly affected by an off-take rate and flock size interaction (P<0.001). The increment of GM due to increased off-take rate was more prominent for farmers with bigger flocks. Interaction between flock size and production system significantly (P<0.001) affected both NB1 and NB2. The increment of NB1 and NB2 by keeping larger flocks was higher in AAP system, due to higher in-kind and intangible benefits of goats in this system. Effect of goat flock size as a predictor of household dietary diversity was not significant (P>0.05). Nevertheless, a significant positive correlation (P<0.05) was observed between GM from goats and HDDS in AAP system, indicating the indirect role of goat production for food security. The study indicated that extent of utilising tangible and intangible benefits of goats varied among production systems and these differences should be given adequate attention in designing genetic improvement programs.

Surface Reflectance Recognition and Real-World Illumination Statistics

Humans distinguish materials such as metal, plastic, and paper effortlessly at a glance. Traditional computer vision systems cannot solve this problem at all. Recognizing surface reflectance properties from a single photograph is difficult because the observed image depends heavily on the amount of light incident from every direction. A mirrored sphere, for example, produces a different image in every environment. To make matters worse, two surfaces with different reflectance properties could produce identical images. The mirrored sphere simply reflects its surroundings, so in the right artificial setting, it could mimic the appearance of a matte ping-pong ball. Yet, humans possess an intuitive sense of what materials typically "look like" in the real world. This thesis develops computational algorithms with a similar ability to recognize reflectance properties from photographs under unknown, real-world illumination conditions. Real-world illumination is complex, with light typically incident on a surface from every direction. We find, however, that real-world illumination patterns are not arbitrary. They exhibit highly predictable spatial structure, which we describe largely in the wavelet domain. Although they differ in several respects from the typical photographs, illumination patterns share much of the regularity described in the natural image statistics literature. These properties of real-world illumination lead to predictable image statistics for a surface with given reflectance properties. We construct a system that classifies a surface according to its reflectance from a single photograph under unknown illuminination. Our algorithm learns relationships between surface reflectance and certain statistics computed from the observed image. Like the human visual system, we solve the otherwise underconstrained inverse problem of reflectance estimation by taking advantage of the statistical regularity of illumination. For surfaces with homogeneous reflectance properties and known geometry, our system rivals human performance.