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The advancement in on demand Multimedia Streaming Applications (MAS) enables faster video transmission as per the user request in various fields. This system suffers from poor speed, flexibility and efficiency in accessing and presenting the multimedia contents from the archive. It mostly undergoes delay, packet loss and congestion during data delivery. Hence, the requirement of manual annotation is required for access and retrieval but it suffers from poor retrieval accuracy over large databases. The need of automatic annotation in MAS takes the lead for increased retrieval accuracy on most similar image retrieval systems based on various low-level features. Thus, it eliminates the gap between the high-level semantics and low-level feature representation. The approach on automated annotation of images is considered dependent on the accuracy of a model while detecting edges, color, texture, shape and spatial information. In this paper, we develop an automated annotation model that retrieves visually similar images from online multimedia streams with optimal feature extraction. The automated annotation model is designed with a Multi-modal Active Learning (MAL) that uses Convolutional Recurrent Neural Network (CRNN) for automatic annotation of labels based on visually similar contents or features like edges, color, texture, shape and spatial information. Further, a Deep Reinforcement Learning (DRL) algorithm is used that increases the performance of the retrieval engine based on validating the visually extracted features. The simulation of MAL-CNN is conducted over large online streaming databases and it is then validated by DRL on an online real-time streaming. The performance is validated in terms of its retrieval accuracy, sensitivity, specificity, f-measure, geometric mean and mean absolute percentage error (MAPE). The results confirm the accuracy of the proposed MAL-DRL model against conventional machine learning, reinforcement learning and deep learning automatic annotation models. [ABSTRACT FROM AUTHOR]

Biomedical Event Extraction (BEE) is a demanding and prominent technology that attracts the researchers and scientists in the field of natural language processing (NLP). The conventional method relies mostly on external NLP packages and manual designed features, where the features engineering is complex and large. In addition, the conventional methods on BEE uses a pipeline process that splits a task into many sub-tasks, however, the relationship between these sub-tasks is not defined. In this paper, such limitations are avoided using the combination technique that relies on Capsule Network (CapsNet) to perform a task. The CapsNet is used for the extraction of feature representation from the input corpora and then the combination technique reconstructs the events from RNN output. This method extracts the tasks from a BEE over several annotated corpora that extract the events from the molecular level in case of multi-level events. The proposed model is compared with state-of-the-art models over various text corpora datasets. The results show an improved rate of accuracy of CapsNet classification over cancer biomedical events than the existing methods. [ABSTRACT FROM AUTHOR]

OFDM is a ubiquitous modulation scheme used to achieve high data rate during transmission and reception in broadband internet of things application. But the envelope aberration of OFDM signal leads to high peak-to-average power ratio (PAPR) which finally results in overall transmitter inefficiency. This article proposes a neural network (NN) based gradient clipping approach at the transmitter and a linear regression model at the receiver to minimize the PAPR in OFDM systems with reasonable computational complexity. The simulation result shows that when compared to the original OFDM signal, the proposed Neural network-based Regression assisted PAPR Reduction achieves PAPR reduction by 82.9% and 84.1% for 64QAM-OFDM and 16QAM OFDM signal respectively without compromising on the bit error rate (BER) performance. [ABSTRACT FROM AUTHOR]

Full adder circuit is a ubiquitous building block in VLSI systems and application specific integrated circuits. This article presents an area and power delay product (PDP) efficient CMOS based 1 bit full adder which is suitable to perform arithmetic operations. The simulation results obtained for parameter analysis using Cadence tool shows that the proposed adder preserves more than 20.7% power over the conventional CMOS adder. The PDP is reduced by almost 26.8–55.5% and performs 9.8–46.1% faster operation than the existing adders. The proposed design is investigated in terms of variations in supply voltage, load capacitance, process corner and temperature. To evaluate the performance of LR-HFA in real time environment, we embedded it in a 4, 8, 16 bit carry propagation adder. The proposed adder displays improved PDP performance when compared with standard adder circuits. [ABSTRACT FROM AUTHOR]

Cloud computing environments enable real time applications on virtualized resources that can be provisioned dynamically. It is one of the efficient platform service which permits to enable the various applications based on cloud infrastructure. Nowadays workflow systems become an easy and efficient task for the development of scientific applications. Efficient workflow scheduling algorithms are employed to improve the resource utilization by enhancing the cloud computing performance and to meet the users' requirements. Many scheduling algorithms have been proposed but they are not optimal to incorporate benefits of cloud computing. In this paper a new framework are introduced as whale optimizer algorithm (WOA) which mimics the social behaviour of humpback whales and aims to maximize the work completion for meeting QoS constraints such as deadline and budget. This proposed method outperforms well when compared with other techniques and measured in terms of makespan, deadline and it is applicable for real time applications. [ABSTRACT FROM AUTHOR]

Software testing has its main goal as designing new test case sets in a manner in which it is able to depict its maximum faults. As soon as these test cases have been designed, Oracle software provides a method in which the software has to behave for a particular test case given. Prioritization of such test cases with the execution of their components specifying inputs, their operation and their outcome will determine as to whether the application and their properties are working in the right manner. The prioritization methods are as follows: initial ordering, random ordering and finally reverse ordering that were based on fault detection abilities. For developing software applications, a test suite that was less commonly known as the suite for checking the validity of software was employed. The test suite contained a detailed set of instructions and goals for each test case collection based on the system and its configuration used during testing. Automating the generation of a test case and test oracle was researched in an extensive manner. From among the automated test oracle, the artificial neural network (ANN) was used extensively but with a high cost of computation. This work proposed a weight optimized ANN using stochastic diffusion search to find the optimal weights with a unique fitness function such that computational time is reduced and misclassification rate reduced. [ABSTRACT FROM AUTHOR]

The web service is proved to be one of significant milestone in the evolution of distributed computing. Applications interoperate with programs providing simple services to deliver sophisticated value-added services. Web service proves to be a loosely coupled way of achieving complex operations with less ownership of the resources in a standard way. Variety of platforms and frameworks communicate with the aim of transferring the business intelligence, domain specific functionalities and so on. The communication between the server providing the service and the client revolves around two main web technologies such as World Wide Web, and Hyper Text Transfer Protocol. As specified earlier web service invocation is achieved due to collaboration of multiple entities on the web. The quality of service factors such as performance, reliability, security, response time, availability etc., are very important to enable this web service invocation. Among which security proves to be a challenging factor due to vulnerabilities in the web that is imposed on the usage of numerous methods, tools and technologies. In the same pace, numerous standards and mechanisms has been introduced to handle the security threats. It is found to be difficult to arrive at a complete solution or standard to address the security issues of web services. As an initiative to provide a broader perspective on security of web services the review presented could provide glimpses of security vulnerabilities and solutions available. [ABSTRACT FROM AUTHOR]

As is well-known Cloud is an Environment for sharing resources based on Anything as a Service (XaaS) pattern that includes software, platform, infrastructure, storage, etc. on demand. For allocating resources and managing it efficiently, the load has to be balanced on the cloud paradigm. Moreover, the reliable resource allocation with load balancing has become the significant resource focus in the current scenario. In the heterogeneous cloud environment, dispersion and uncertainty of cloud resources faces issues on the process of allocation that are not effectively handled and accessed by the existing approaches. With that concern, for providing proficient resource scheduling with apposite load balancing, an efficient load-balancing model based on modified particle swarm optimization with membrane computing has been proposed. Based on that, suitable resources are allocated for different jobs in accordance with the factors like completion time, scalability, makespan, utilization of resources, reliability, availability, etc. Moreover, in this paper, effective resource scheduling has been achieved with the modified particle swarm optimization that combined with membrane computing local and glob optimization of inter-membranes for providing an optimal solution. Spatial segmentation has also been performed for enhancing the membrane-based optimization. [ABSTRACT FROM AUTHOR]

Chicken leg pieces (60 g each). with optimized quantity of additives were fried in hydrogenated vegetable oil at 180°C for 8 min. The fried product was packed in paper-foil-polyethylene pouches (PFP) and stored under ambient (20 ± 5°C, 65–80% RH), refrigerator (5°C, 80% RH) and deep freezer (−18°C, 85–90% RH) conditions. The changes in microbial profile, oxidative and hydrolytic rancidity and sensory quality were evaluated periodically. It was found that the product was microbiologically (standard plate count (SPC) < 3 log cfu/g) safe and sensorily acceptable (overall acceptability >7) up to 4 days under ambient conditions. Hydrolytic and oxidative rancidity values during four days storage at room temperature were less than 0.16 % oleic acid and 3.5 mg malonaldehyde/kg, respectively. The products stored under refrigerated and deep freezer exhibited a shelf stability of 10 and 18 weeks, respectively. SPC was 1.3 log cfu/g while rancidity parameters were free fatty acid < 0.43% oleic acid and thiobarbituric acid reactive substances were <6.13 mg malonaldehyde/kg. Sensorily the product exhibited an overall acceptability score of >7 on a 9-point Hedonic scale during refrigerated and frozen storage. [ABSTRACT FROM AUTHOR]

The advent of miniature surface-mount components coupled with increasing lead counts poses tremendous challenges during the assembly of printed circuit boards (PCBs). This is especially true in an electronics manufacturing service (EMS) industry, where the focus has been to increase throughput and first-pass yields at minimum expenditure. Hence, robust inspection systems are required to achieve the objectives of inspecting all the solder joints on a PCB assembly without affecting throughput and of accurately and repeatedly detecting solder-joint-related defects. Conventional inspection technologies are limited in their capability to inspect and detect solder-joint-related defects. However, these limitations have been addressed to a considerable extent by automated 3D laminography x-ray inspection systems. This research effort ascertained the effectiveness of an automated 3D laminography x-ray inspection system from a statistical and assembly perspective. The results of this investigation were analyzed and continuous improvement measures were initiated and employed to improve the performance of the automated 3D laminography x-ray inspection system and, subsequently, of the surface-mount technology (SMT) line. [ABSTRACT FROM AUTHOR]

The exponential growth of the electronics packaging industry has fueled the availability of a variety of area array packages. The reliability of these packages, as characterized by their capacity to withstand the IPC- (formerly Institute of Interconnecting and Packaging Electronic Circuits) prescribed swings in temperature, differentiates one from the other. With design cycles shrinking and competition surging, the capability to make instant package selection decisions by leveraging prior empirical data could pose as a potential alternative for exhaustive experimentation. By employing expert systems techniques, this research developed suitable models that accurately depict field conditions in order to assist in delineating trends in package reliability data. The fatigue behavior of the solder joints subjected to accelerated thermal cycling is often used as an indicator of the reliability of electronic packages in field conditions. Design for reliability (DFR) could be pursued if the thermal fatigue behavior can be predicted in the design phase of a product. The finite element method (FEM) and accelerated testing such as air-to-air thermal cycling (AATC) have been used extensively to study second-level package reliability. Factors like incorrect assumptions or unknown material properties involved in the development of the FEM models are the cause of deviations between actual and predicted values The mathematical complexity and the time needed for model development further aggravate the situation. The focal point of this research was to develop a generic method that could be used to predict the second-level solder joint reliability of area array packages from the analysis of empirical data. While package characteristics play an important role in identifying the similarities between various subsets of packages, the role of assembly parameters is crucial in terms of their impact on reliability. Weights, in terms of the parameters’ impact on reliability, are computed by examining each individual experiment. Based upon identified trends and the separation of qualitative and quantitative impact of the contributing parameters, regression models may be developed to capture the second-level reliability behavior of the package. These models make it possible to predict reliability and potentially save time and resources for an end-user. [ABSTRACT FROM AUTHOR]

This research addressed the feasibility of using a substrate preheat temperature which is higher than the manufacturer’s recommendation in order to reduce the cycle time of the encapsulation process while still ensuring package reliability. temperature are discussed and evaluated. A statistical model was generated to help determine the optimal substrate preheat temperature for given chip dimensions, standoff height, surface texture, etc. Using the substrate preheat temperature determined by the model, the flow time of the encapsulant could be reduced by more than a factor of two while still ensuring a 6s quality level. [ABSTRACT FROM AUTHOR]

The focus of this work was to develop a robust assembly process for low and high input/output (I/O) ball grid arrays (BGAs). The test vehicles considered had a wide variety of components including full and perimeter array BGAs, and ultrafine pitch peripheral leaded devices. Experimental design techniques were applied in order to identify, screen, and control the parameters that affect the stencil printing process. The factors that affect the process were screened using Taguchi-based methodology. These significant factors and their interactions were then further analysed using full factorial designs. The volume and the quality of the solder paste deposits were considered as the response variables. Response surface plots were developed to provide process windows for paste deposition. Process capability studies were performed to evaluate the capability of the solder paste deposition process. Boards were assembled using optimal settings obtained from the experiments. No process-induced defects were found, and 100% yield was obtained. [ABSTRACT FROM AUTHOR]

The fresh water field crab Oziotelphusa senex senex was adapted to artificial sea water. The changes in its feeding behaviour on adaptation to salinity were recorded. Adaptation to higher salinity reduced the daily voluntary food intake and increased the scope for work and level of excitability. Under experimental conditions fresh water field crabs, regardless of their nutritional state, showed preference to marine fish muscle as food and sea water adapted crabs prefer fresh water fish muscle. The food consumption was reduced to a third in the sea water adapted crabs and the oxygen consumption was reduced by about half. Since minimal respiratory metabolism was available in the salinity adapted crabs, it was suggested that such animals have a lower calorific demand associated with low appetite. It was discussed that the behaviour of crabs exposed to higher salinity was not a non-genetic adaptation. Probably, the modifications of gustatory cues occur due to salinity stress. [ABSTRACT FROM AUTHOR]

The food preferences of the South-Asian commensal rat, Bandicota indica were studied to evolve a suitable bait for control. Amongst cereals clear preference towards rice in its whole/divided form was evident. Amongst additives 7\2-10% groundnut oil enhanced bait intake significantly while 2% salt and sugar did not influence the rat's diet choice. The results indicate whole/broken rice mixed with 7\2-10% groundnut oil as the most attractive bait for poisoning B. indica. [ABSTRACT FROM AUTHOR]

The study was aimed at detecting the development of bait shyness towards zinc phosphide and vacor in Mus platythrix and its persistence. Both the rodenticides induced poison aversion after single ingestion of sub lethal quantities, while bait shyness towards zinc phosphide lasted 170 days, vacor produced poison shyness persisted upto 120 days. Based on these results it may be concluded that poisoning M. platythrix with zinc phosphide and vacor should be done for a single day only and residual population be killed by other means. Secondly control of M. platythrix by zinc phosphide poisoning should not be repeated till 170 days and that of vacor till 120 days. [ABSTRACT FROM AUTHOR]

Both zinc phosphide and vacor induced almost similar changes in the haematology of Bandicota bengalensis and Tatera indica. Lymphocytes decline and an increase was seen in the counts of red blood cells (RBC) and neutrophils, bleeding and clotting times. Per cent weight loss was more in zinc phosphide poisoned B. bengalensis. The variations exhibited by the two species and sexes indicate gerbils, particularly females as most resistant and female lesser bandicoots to be the most susceptible to the poisons tested. [ABSTRACT FROM AUTHOR]

Occurrence of Physaloptera Rud. 1819 (Syn. Chlamydonema sp.) and Subulura Molin 1860 (Syn. Allodapa sp.) in the slender Loris, Loris tardigradus, was not known thus far and this paper reports the occurrence of these two parasites. There was a 35·7% occurrence of Physaloptera masoodi in the stomach and a 100% occurrence of Subulura indica in the large intestine and the vermiform appendix of 14 animals studied. While Physaloptera masoodi developed in the stomach, the Subulura indica did in the appendix. Data on the size and the dimensions of these parasites are tabulated and nematode parasites in the loris and their pathogenicity to the host are discussed. [ABSTRACT FROM AUTHOR]

Component placement is a critical and time consuming task in the assembly of surface mount printed circuit boards (PCBs). The past decade has witnessed the need for high speed, accurate, and repeatable placement procedures in the PCB assembly domain. At the same time, manufacturing engineers are faced with demands to reduce flow-time and increase throughput rates in order to increase productivity. A consequence of these trends has been the need to identify acceptable (possibly optimal) placement sequences during surface mount PCB assembly. The focus of this research was the identification of 'near optimal' solutions for the placement sequence identification problem while considering machine and process constraints in a manufacturing environment. Expert (or knowledge-based) systems were used as the solution method for this problem. PROLOG, a popular language for artificial intelligence applications, was used in this research. The prototype knowledge-based system developed in this research identifies solutions in (almost) real-time. [ABSTRACT FROM AUTHOR]

The widespread use of automation in the printed circuit board (PCB) assembly domain has been dictated by the increasing density of components on PCBs coupled with the continual decrease in component lead pitch, greater product mix, smaller volumes, quality considerations, and the increased cost of labour. However, these advances in technology have also resulted in automated systems that are complex, and solving problems related to these systems requires the efficient use of extensive specialised knowledge. Expert (or knowledge-based) systems have become a widely accepted problem solving methodology for the surface mount PCB assembly domain. Nevertheless, problems in the PCB assembly domains are frequently unstructured, ill-defined, and difficult to communicate. Artificial neural networks provide a novel approach and an advanced technology to deal with the weaknesses and problems associated with expert systems. The surface mount component (SMC) placement process plays a vital and influential part in determining the throughput time of a PCB assembly line. It is important to identify an efficient component placement sequence while considering constraints such as feeder location and tooling and nozzle optimisation. This research studied the use of artificial neural networks as a complement to expert systems in PCB assembly. A prototype decision support system that combined the use of artificial neural networks and expert system techniques to identify a near optimal solution for the surface mount placement sequence problem was designed, implemented, and validated. Artificial intelligence based technologies such as expert systems and artificial neural networks were used in a mutually supportive manner to solve a complex problem within the surface mount PCB assembly domain. [ABSTRACT FROM AUTHOR]

Reflow soldering of solder paste is a critical process in the surface mount assembly of printed circuit boards (PCBs). Infrared (IR) radiation and/or forced convection are often used in an oven to heat the PCB assembly and the deposited solder paste to cause the solder to reflow and subsequently form the interconnection between the component terminations and the attachment pads. Control of the reflow soldering process requires the understanding and regulation of several complex variables. Understanding the interrelationships among process control parameters is important in achieving a low defect rate and high yields in reflow soldering. When a variety of components are soldered onto a printed circuit board (PCB) simultaneously in an IR/convection oven through reflow soldering, the process control variables that need to be considered include the characteristics of solder paste used, the size, type, and quantity of components placed on the PCB, the substrate used, the mass and the thermal area of the workpiece, and the conveyor speed. A prerequisite for the achievement of high process yields in the reflow soldering process is the identification of the optimal temperature profile and the range between which the profile is acceptable for the specific assembly. This information is subsequently used by the process engineer to arrive at the relevant temperature of power (wattage) settings for the oven. The in-depth process knowledge required to study the process variables and deduce thermal profiles is not commonly available. Consequently, the objective of this research was to use an expert system approach to help a manufacturing engineer with thermal profile identification in surface mount PCB assembly. The system developed considers the major process control parameters and the interrelationships among them to deduce the optimal temperature profile and a range in which the profile is considered 'acceptable'. The profile identification expert system was developed using PROLOG on a personal computer. Results are displayed using a combination of graphical and textual output. The system was designed to function in a stand-alone capacity. The profile identification expert system's architecture integrates an inference mechanism with the knowledge (facts and rules) provided by the domain expert. It allows the user to update or delete the facts and rules stored in the knowledge base. Consequently, it provides an avenue to enhance the capacity of the system to incorporate domain specific changes. [ABSTRACT FROM AUTHOR]

The volume and complexity of printed circuit boards (PCBs) that use surface mount technology has increased tremendously over the past decade. The intricacy of the design and manufacturing functions associated with this domain is continuously increasing. Several researchers have documented the significance of the design functions on product life cycle costs. In the surface mount PCB assembly area, the integration of the design and manufacturing activity is hampered by the lack of sufficient, in-depth manufacturing knowledge among the PCB designers. Also, the heuristic nature of manufacturing knowledge coupled with the frequent advances in the state-of-the-art has resulted in the lack of widespread in-depth process knowledge. This research focused on the design and development of a knowledge-based methodology which can be used to assist the design engineer in the surface mount PCB assembly domain. The rules relate primarily to the solderability, cleanability and reflow aspects of the design. An object oriented programming (OOP) methodology is used. The OOP framework allows for structured and modular development and implementation of the knowledge-based design advisor. It allows for the easy maintenance and update of the software along with the integration of knowledge bases and databases. The system has been partitioned into three major components - the user interface, the update mechanism along with the inference engine, and the database management utility. An important feature of this research has been the focus on updateability of the design advisor with respect to data and knowledge (rules). The logic or the rules within the system have been developed in an updateable format. The calculations required during the firing of the rules are performed by dynamic linked libraries (dlls). The design advisor has been developed in the Windows operating system using the C++ language. The database manipulation functions are handled by CodeBase 5.0 libraries. [ABSTRACT FROM AUTHOR]

Process planning is a critical function in any manufacturing domain. This is especially true in the electronics manufacturing area where substantial heuristic and experiential knowledge is commonly used during process plan development. While research in computer-aided process planning (CAPP) has tended to concentrate in the machining realm, few CAPP systems have been developed for electronics manufacturing applications and more specifically for the printed circuit board (PCB) assembly domain. Besides, the CAPP systems that have been developed for this area have dealt with either insertion mount or surface mount PCB assembly processes only. Tape automated bonding (TAB), though a relatively new technology, is gaining importance in electronics assembly owing to its inherent advantages. The advent of fine pitch technology together with the ever increasing need for more inputs/outputs and greater pin counts in integrated circuit applications has enhanced the use of TAB technology in electronics manufacturing. This trend has been further augmented by the increasing need for compactness in consumer electronics. This research designed and developed a prototype CAPP system for the PCB assembly domain. The system developed generates a process plan for PCBs populated with surface mount and/or TAB components. An artificial-intelligence based expert system approach has been used in the design and development of the CAPP system. Outputs generated by the system are presented along with ideas for future research. [ABSTRACT FROM AUTHOR]

This paper describes a real-time computer-aided process planning (CAPP) system for printed circuit board (PCB) assembly using surface mount technology. The prototype, dynamic, realtime CAPP system described uses a blackboard to integrate multiple knowledge sources (knowledge bases) in implementing the process planning procedure. The CAPP system is implemented using the expert system environment (ESE) and structured query language (SQL). The system uses two subsystems (knowledge bases). They are a planning subsystem which performs the static process planning task and a dynamic information processing subsystem which considers the real-time changes on the shop floor and routes the PCB assembly flow. The integrated system developed generates process plans that can be implemented in real time. The use of the blackboard concept for CAPP architecture is unique and well suited for this task. [ABSTRACT FROM AUTHOR]

The interrelationships that exist in the manufacturing processes associated with the surface mount manufacture of printed circuit boards (PCBs) are complex and varied. Proper understanding of the relationships between the variables in a surface mount technology (SMT) process are critical for achieving effective process control and high yields. One aspect of the complex relationship is the selection and dispensing of adhesives for the wave soldering of surface mount components on a PCB. The quantitative and repeatable dispensing of adhesive dots is critical to providing adequate process control for attaching components including chip resistors, capacitors, and small outline type transistors to the wave solder side of a PCB. Variables that need to be considered include facility temperature, humidity, size and types of components used on the PCB, adhesive properties, type of dispenser used, curing requirements, and the soldering time and temperature, A knowledge-based approach which considers these relationships is described. Developed in PROLOG, this stand alone adhesive selection advisor is capable of guiding the user in the selection of the proper adhesive and providing dispenser related information. The factors considered include facility temperature, material property requirements, productivity measures including yield, and the process used to dispense the adhesive. The system also functions as a database for adhesive related properties and as an on-line installation and maintenance manual for the adhesive dispenser. Twenty-one different commerically available adhesives and two types of dispensers (air over and positive displacement) have been considered in this research. [ABSTRACT FROM AUTHOR]

Computer-aided process planning (CAPP) systems need to consider the uncertain nature of the shop-floor prior to the identification of job routes and processing sequences. This paper describes the design and development of a prototype, real-time dynamic CAPP (RDCAPP) system for a multimachining-centre flexible manufacturing system (FMS). Concepts relevant to this research include CAPP, profile input using group technology (GT), artificial-intelligence-based expert systems, and FMSs. RDCAPP considers facility characteristics, machine capacity and the current shop-floor conditions prior to developing a process plan Input to the system is through a GT code and additional auxiliary interactive inputs. RDCAPP uses uncertainty management techniques to keep track of and adapt to changes in shop-floor status. The paper discusses the architecture of RDCAPP in detail. The system was tested rigorously and its outputs validated. Ideas for future research are presented. [ABSTRACT FROM AUTHOR]

Petri-nets (PNs) can model concurrent and synchronous activities in a manufacturing system at various levels of abstraction. They have been used for modelling manufacturing systems, knowledge representation on the shop floor, process-planning applications, decisionsupport tasks, etc. PNs are being used in a growing variety of application areas. This paper focuses on PN applications in manufacturing. A comprehensive review of research is provided. The paper also describes the design and application of PNs in the modelling of a manufacturing cell, the representation of the working of the cell at various levels of abstraction, and the inferences that can be drawn through PN use. Ideas for future research are presented. [ABSTRACT FROM AUTHOR]

This paper deals with the role, advantages, problems and solution techniques for the implementation of dynamic Computer Aided Process Planning (CAPP) systems in a Felxible Manufacturing system (FMS). A large variety of part features for both rotational and prismatic parts are considered. A custom group technology coding technique is designed and implemented to describe part profile to system software concisely and comprehensively. The part profile code is assimilated by the system interactively. A prototype CAPP system was designed for a pseudo FMS containing multiple machining centres. The system described develops process plans that consider both alternative routes and methods to manufacture a part. Heuristic knowledge was implemented to choose between alternatives with flowtime minimization as the objective function. The system was tested and its outputs validated with respect to both prismatic and rotational parts. [ABSTRACT FROM AUTHOR]

The 4-hydroxy coumarins have been reacted with o-benzoquinone, in acetone in the absence of the oxidant potassium ferricyanide. The products were found to be 3-aryl-4-hydroxy coumarins which were cyclised to the corresponding 11,12-dihydroxy coumestans. The structure of 11,12-dihydroxy coumestan has been confirmed by an unambiguous synthesis. The structures of other compounds were confirmed on the basis of their analytical, chemical and spectral data. [ABSTRACT FROM AUTHOR]

Changes in the exeretory patterns of the fresh-water field crab Paratelphusa hydrodromous were studied in relation to salinity adaptation. Fifty percent sea-water medium was found to be the threshold of a change from ammonotelism to ureotelism in the crabs. Adaptation for 11 days in the 100% (=34‰ S) sea water brought about this change. Sea-water-adapted crabs excreted more urea, uric acid, and trimethylamine than controls, irrespective of starvation. Starvation reduced the quantitative excretion. Blood aspartic and glutamic acid levels increased on adaptation to sea water, in contrast to the levels of asparagine and glutamine. The activities of asparaginase and glutaminase in the tissues decreased on salinity adaptation. The reduction in amidase activity in 100% sea-water-adapted crabs is discussed with reference to acid-base homeostasis in the crabs. [ABSTRACT FROM AUTHOR]

Denervation of genitofemoralis in the bonnet monkey for 60 days resulted in a significant increase in neutral salt-soluble, alkali-soluble and insoluble collagens as well as glycoproteins. The hydroxyproline content of the salt-soluble and insoluble collagens in the muscle increased on denervation. These changes are discussed to imply the impairment of the action of specific structural genes. [ABSTRACT FROM AUTHOR]