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Search Results: 1 - 10 of 734 matches for " Tamanna Siddiqui "
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Forecasting the Tehran Stock Market by Artificial Neural Network
Reza Aghababaeyan,Tamanna Siddiqui,Najeeb Ahmad Khan
International Journal of Advanced Computer Sciences and Applications , 2011,
Abstract: One of the most important problems in modern finance is finding efficient ways to summarize and visualize the stock market data to give individuals or institutions useful information about the market behavior for investment decisions. The enormous amount of valuable data generated by the stock market has attracted researchers to explore this problem domain using different methodologies. Potential significant benefits of solving these problems motivated extensive research for years. In this paper, computational data mining methodology was used to predict seven major stock market indexes. Two learning algorithms including Linear Regression and Neural Network Standard feed-forward back prop (FFB) were tested and compared. The models were trained from four years of historical data from March 2007 to February 2011 in order to predict the major stock prices indexes in the Iran (Tehran Stock Exchange). The performance of these prediction models was evaluated using two widely used statistical metrics. We can show that using Neural Network Standard feed-forward back prop (FFB) algorithm resulted in better prediction accuracy. In addition, traditional knowledge shows that a longer training period with more training data could help to build a more accurate prediction model. However, as the stock market in Iran has been highly fluctuating in the past two years, this paper shows that data collected from a closer and shorter period could help to reduce the prediction error for such highly speculated fast changing environment.
Discovery of Scalable Association Rules from Large Set of Multidimensional Quantitative Datasets
Tamanna Siddiqui,M Afshar Aalam,Sapna Jain
Journal of Advances in Information Technology , 2012, DOI: 10.4304/jait.3.1.69-76
Abstract: In proposed approach, we introduce the problem of mining association rules in large relational tables containing both quantitative and categorical attributes. We have proposed an algorithm for Discovery of Scalable Association Rules from large set of multidimensional quantitative datasets using k-means clustering method based on the range of the attributes in the rules and Equi-depth partitioning using scale k-means for obtaining better association rules with high support and confidence. The discretization process is used to create intervals of values for every one of the attributes in order to generate the association rules. The result of the proposed algorithm discover association rules with high confidence and support in representing relevant patterns between project attributes using the scalable k-means .The experimental studies of proposed algorithm have been done and obtain results are quite encouraging.
Guillain-Barre Syndrome Presenting as a Complication of Enteric Fever
Sheelu S. Siddiqui, Zikrullah Tamanna, Khalid Rashid, Anoop Gopinath
JK Science : Journal of Medical Education & Research , 2006,
Abstract: Not available
Knowledge-driven Intuitionistic Fuzzy Decision Support for finding out the causes of Obesity
Asma R Shora,M Afshar Alam,Tamanna Siddiqui
International Journal on Computer Science and Engineering , 2012,
Abstract: In this paper, we propose an Intuitionistic Fuzzy decision support system for determining the causes of a more or less common disorder – obesity. Obesity can be simply lifestyle related i.e. excessive food energy intake and a lack of physical activity related or it may be caused due to hormonal,pathological or genetic factors. Whenever a patient is examined, our goal is to find out the cause of obesity so that appropriate treatment can be prescribed to the patient. All this involves a particular amount of uncertainty and imprecision. We take the help of an intuitionistic fuzzy diagnostic system that works at two levels. At the first level, we try to filter out the set of patients, who don’t exhibit the signs and symptoms of hormonal, pathological or genetic disorders i.e. reduced set of patients (suffering from SIMPLE OBESITY). At the second level, we diagnose the rest of the obese patients for Metabolic or Cushing’s syndrome (only two disorders have been taken for the sake of convenience). The values used in the databases are both crisp and intuitionistic fuzzy in nature. The latter ones may be directly recorded or may get their values quantized from linguistic expressions such as MILD, MODERATE, LOW.
Efficiency Metrics
Tamanna Siddiqui,Munior Ahmad Wani,Najeeb Ahmad Khan
BVICAM's International Journal of Information Technology , 2011,
Abstract: Software measurement is a challenging but essential component of a healthy and highly capable software engineering culture. It is an integral part of the state-of the- practice in software engineering. More and more customers are specifying software and/or quality metrics reporting as part of their contractual requirements. Software Engineering has always been a matter of concern for every individual involved in software development starting from analysis phase to delivery phase or even at the maintenance time. There have been novel approaches for developing program complexity metrics. In this regard we have proposed the Efficiency Metrics, which can calculate the efficiency of a programmer and can also calculate the exact time taken by the development team to complete the software development under various complexities. Over and above we have also developed a relation between time and efficiency.
Error Detection and Correction over Two-Dimensional and Two-Diagonal Model and Five-Dimensional Model
:Danial Aflakian,Dr.Tamanna Siddiqui,Najeeb Ahmad Khan,,Davoud Aflakian
International Journal of Advanced Computer Sciences and Applications , 2011,
Abstract: In this research paper we discover two different schemes of error detection and correction which are based on parity-check code for optimal error detection and correction utilizing check bits without degrading the data rate too much. The scheme of the first method is obtained by arranging data in rows, to form a square, and then parity bits are added. The second scheme builds upon the first, by forming a square cube and the parity scheme is extended to this shape.
PROSPECTIVE TEACHERS' SENSE OF RESPONSIBILITY TOWARDS ENVIRONMENT
TAMANNA KAUSHAL
Indian Streams Research Journal , 2013,
Abstract: Teachers play a prominent role in national and social reconstruction and in transmission of wisdom, knowledge and experiences of one generation, to another generation. This study was carried out to identify the prospective teachers' Sense of responsibility towards environment at bachelor of education level in National Capital Region (NCR). The sample comprised of 100 prospective teachers (males & females) of B. Ed colleges. Data was collected from prospective teachers, through an Environmental Responsibility Assessment Inventory (ERAI). The results of the study revealed that State Board and CBSE Board prospective teachers are equally aware of environmental issues and overall responsibilities. English and Hindi Medium prospective teachers also bear equal environmental responsibilities.
Numerical Investigation of Phase and Group Propagation of Time-Domain Signals in a Novel Band-Reject Metamaterial Ring Hybrid  [PDF]
Omar Siddiqui
Journal of Computer and Communications (JCC) , 2015, DOI: 10.4236/jcc.2015.36002
Abstract: Phase and group propagation in metamaterial-based microwave components has always been intellectually challenging for students and engineers new to the area of periodic structures and metamaterials. This paper aims in tackling this important topic by studying the wave propagation in a metamaterial-based microwave device. Hence, the contribution of this paper is twofold. First, design of a novel metamaterial ring hybrid (or rate-race) is presented which has a large rejection band so that the second and third harmonics are effectively suppressed. Second, the electromagnetic phase and the group propagation in the ring hybrid are investigated by numerically exciting the input ports with band-limited Gaussian pulses and then finding their responses at various locations in the device.
Perillyl Alcohol Protects against Fe-NTA-Induced Nephrotoxicity and Early Tumor Promotional Events in Rat Experimental Model
Tamanna Jahangir,Sarwat Sultana
Evidence-Based Complementary and Alternative Medicine , 2007, DOI: 10.1093/ecam/nel104
Abstract: Plants have been widely used as protective agents against a wide variety of processes and compounds that damage tissues via free radical mechanisms. Perillyl alcohol (PA) is a naturally occurring monoterpene found in the essential oils of numerous species of plants including mints, cherries and celery seeds. This monocyclic monoterpene has shown antioxidant and therapeutic activity in various studies against various xenobiotics. In this study, we have analyzed the effects of PA against single intraperitoneal dose of ferric nitrilotriacetate (Fe-NTA) (9 mg iron per kg body weight)-induced nephrotoxicity and early tumor promotional events. The pretreatment of Fe-NTA-treated rats with 0.5% per kg body weight dose and 1% per kg body weight dose of PA for seven consecutive days significantly reversed the Fe-NTA-induced malondialdehyde formation, xanthine oxidase activity (P < 0.001), ornithine decarboxylase activity (P < 0.001) and 3[H]thymidine incorporation in renal DNA (P < 0.001) with simultaneous significant depletion in serum toxicity markers blood urea nitrogen and creatinine (P < 0.001). Significant restoration at both the doses was recorded in depleted renal glutathione content, and its dependent enzymes with prophylactic treatment of PA. Present results suggest that PA potentially attenuates against Fe-NTA-induced oxidative damage and tumor promotional events that preclude its development as a future drug to avert the free radical-induced toxicity.
Analysis of the Protein Phosphotome of Entamoeba histolytica Reveals an Intricate Phosphorylation Network
Tamanna Anwar, Samudrala Gourinath
PLOS ONE , 2013, DOI: 10.1371/journal.pone.0078714
Abstract: Phosphorylation is the most common mechanism for the propagation of intracellular signals. Protein phosphatases and protein kinases play a dynamic antagonistic role in protein phosphorylation. Protein phosphatases make up a significant fraction of eukaryotic proteome. In this article, we report the identification and analysis of protein phosphatases in the intracellular parasite Entamoeba histolytica. Based on an in silico analysis, we classified 250 non-redundant protein phosphatases in E. histolytica. The phosphotome of E. histolytica is 3.1% of its proteome and 1.3 times of the human phosphotome. In this extensive study, we identified 42 new putative phosphatases (39 hypothetical proteins and 3 pseudophosphatases). The presence of pseudophosphatases may have an important role in virulence of E. histolytica. A comprehensive phosphotome analysis of E. histolytica shows spectacular low similarity to human phosphatases, making them potent candidates for drug target.
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