The emphasis of Master Production Scheduling (MPS) or tactic planning is on time and spatial disintegration of the cumulative planning targets and forecasts, along with the provision and forecast of the required resources. This procedure eventually becomes considerably difficult and slow as the number of resources, products and periods considered increases. A number of studies have been carried out to understand these impediments and formulate algorithms to optimise the production planning problem, or more specifically the master production scheduling (MPS) problem. These algorithms include an Evolutionary Algorithm called Genetic Algorithm, a Swarm Intelligence methodology called Gravitational Search Algorithm (GSA), Bat Algorithm (BAT), Teaching Learning Based Algorithm and Harmony Search Algorithm (GA, TLBO and HS). This segment of the research constitutes of two parts the first emphasises on the outcome of the five simulation algorithms and then identifies the best, while the second part is about comparing the best with the search algorithm work in 2009, the applicability of BAT Algorithm and Gravitational Search Algorithm (GSABAT) to planning problems, the technique used for calculating master production scheduling, and the very important results and recommendations for future studies
Genistein (GEN) is one of the predominant dietary isoflavones found in legumes such as soybeans. Genistein has been recommended as an osteoporosis treatment for postmenopausal women and elderly men, with the intention of reducing cardiovascular disease and hormone-dependent malignancies. Therefore, two sensitive and simple methods for quantifying it in the supplements preparation were developed.The first method (A) comprised employing the surfactant Triton X-114 to extract the result of the diazotization reaction with 4-Aminoacetophenone(4AMA) utilizing a cloud point extraction technique. The product was extracted using micelles of a non-ionic surfactant (TritonX-114) and then spectrophotometrically detected at a specified wa
... Show More'Steganography is the science of hiding information in the cover media', a force in the context of information sec, IJSR, Call for Papers, Online Journal
This paper presents a method to classify colored textural images of skin tissues. Since medical images havehighly heterogeneity, the development of reliable skin-cancer detection process is difficult, and a mono fractaldimension is not sufficient to classify images of this nature. A multifractal-based feature vectors are suggested hereas an alternative and more effective tool. At the same time multiple color channels are used to get more descriptivefeatures.Two multifractal based set of features are suggested here. The first set measures the local roughness property, whilethe second set measure the local contrast property.A combination of all the extracted features from the three colormodels gives a highest classification accuracy with 99.4
... Show MoreThe basic solution to overcome difficult issues related to huge size of digital images is to recruited image compression techniques to reduce images size for efficient storage and fast transmission. In this paper, a new scheme of pixel base technique is proposed for grayscale image compression that implicitly utilize hybrid techniques of spatial modelling base technique of minimum residual along with transformed technique of Discrete Wavelet Transform (DWT) that also impels mixed between lossless and lossy techniques to ensure highly performance in terms of compression ratio and quality. The proposed technique has been applied on a set of standard test images and the results obtained are significantly encourage compared with Joint P
... Show MoreImportance of Arabic language stemming algorithm is not less than that of other languages stemming in Information Retrieval (IR) field. Lots of algorithms for finding the Arabic root are available and they are mainly categorized under two approaches which are light (stem)-based approach and root-based approach. The latter approach is somehow better than the first approach. A new root-based stemmer is proposed and its performance is compared with Khoja stemmer which is the most efficient root-based stemmers. The accuracy ratio of the proposed stemmer is (99.7) with a difference (1.9) with Khoja stemmer.
Clustering algorithms have recently gained attention in the related literature since
they can help current intrusion detection systems in several aspects. This paper
proposes genetic algorithm (GA) based clustering, serving to distinguish patterns
incoming from network traffic packets into normal and attack. Two GA based
clustering models for solving intrusion detection problem are introduced. The first
model coined as handles numeric features of the network packet, whereas
the second one coined as concerns all features of the network packet.
Moreover, a new mutation operator directed for binary and symbolic features is
proposed. The basic concept of proposed mutation operator depends on the most
frequent value
The agent-based modeling is currently utilized extensively to analyze complex systems. It supported such growth, because it was able to convey distinct levels of interaction in a complex detailed environment. Meanwhile, agent-based models incline to be progressively complex. Thus, powerful modeling and simulation techniques are needed to address this rise in complexity. In recent years, a number of platforms for developing agent-based models have been developed. Actually, in most of the agents, often discrete representation of the environment, and one level of interaction are presented, where two or three are regarded hardly in various agent-based models. The key issue is that modellers work in these areas is not assisted by simulation plat
... Show MoreAdvances in digital technology and the World Wide Web has led to the increase of digital documents that are used for various purposes such as publishing and digital library. This phenomenon raises awareness for the requirement of effective techniques that can help during the search and retrieval of text. One of the most needed tasks is clustering, which categorizes documents automatically into meaningful groups. Clustering is an important task in data mining and machine learning. The accuracy of clustering depends tightly on the selection of the text representation method. Traditional methods of text representation model documents as bags of words using term-frequency index document frequency (TFIDF). This method ignores the relationship an
... Show MoreFuzzy Based Clustering for Grayscale Image Steganalysis