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Ahmed Radwan

Bio: Ahmed Radwan is an academic researcher from Hamad Medical Corporation. The author has contributed to research in topics: Link-state routing protocol & Salinity. The author has an hindex of 12, co-authored 36 publications receiving 444 citations. Previous affiliations of Ahmed Radwan include National Institute of Oceanography, India & National Institute of Oceanography and Fisheries, Egypt.

Papers
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Journal ArticleDOI
TL;DR: In this article, the effect of three factors, biosorbent dose BD (0.1 and 0.5 g/L), pH (2 and 7) and initial Cd2+ concentration X (10 and 100 mg/L) at two levels “low” and “high” was investigated at room temperature (25 ± 4 °C), contact time (2 h) and agitation rate (5 Hz).
Abstract: The biosorption efficiency of Cd2+ using rice straw was investigated at room temperature (25 ± 4 °C), contact time (2 h) and agitation rate (5 Hz). Experiments studied the effect of three factors, biosorbent dose BD (0.1 and 0.5 g/L), pH (2 and 7) and initial Cd2+ concentration X (10 and 100 mg/L) at two levels “low” and “high”. Results showed that, a variation in X from high to low revealed 31 % increase in the Cd2+ biosorption. However, a discrepancy in pH and BD from low to high achieved 28.60 and 23.61 % increase in the removal of Cd2+, respectively. From 23 factorial design, the effects of BD, pH and X achieved p value equals to 0.2248, 0.1881 and 0.1742, respectively, indicating that the influences are in the order X > pH > BD. Similarly, an adaptive neuro-fuzzy inference system indicated that X is the most influential with training and checking errors of 10.87 and 17.94, respectively. This trend was followed by “pH” with training error (15.80) and checking error (17.39), after that BD with training error (16.09) and checking error (16.29). A feed-forward back-propagation neural network with a configuration 3-6-1 achieved correlation (R) of 0.99 (training), 0.82 (validation) and 0.97 (testing). Thus, the proposed network is capable of predicting Cd2+ biosorption with high accuracy, while the most significant variable was X.

77 citations

Journal Article
TL;DR: A new fitness function for approximate information retrieval which is very fast and very flexible, than cosine similarity fitness function is presented.
Abstract: This study investigates the use of genetic algorithms in information retrieval. The method is shown to be applicable to three well-known documents collections, where more relevant documents are presented to users in the genetic modification. In this paper we present a new fitness function for approximate information retrieval which is very fast and very flexible, than cosine similarity fitness function. Keywords—Cosine similarity, Fitness function, Genetic Algorithm, Information Retrieval, Query learning.

66 citations

Journal ArticleDOI
TL;DR: In this paper, a study was carried out to determine the water quality of the beaches at Matrouh, south-eastern Mediterranean Sea, Egypt, by studying environmental variables as well as phytoplankton abundance and community structure.

53 citations

Journal ArticleDOI
TL;DR: Dead leaves of a common ornamental plant, Dracaena draca, was used as a biosorbent for the removal of Cadmium (Cd2+) from aqueous solutions using a full 23 factorial experimental design and showed that the most significant effect for Cd2+ biosorption was ascribed to (X).
Abstract: In this research, dead leaves of a common ornamental plant, Dracaena draca known also as dragon tree was used as a biosorbent for the removal of Cadmium (Cd2+) from aqueous solutions using a full 23 factorial experimental design. Three factors were investigated at two different levels, metal ion concentration (X = 10 and 100 ppm), hydrogen ion concentration (Ph = 2 and 7) and biomass dose (BD = 0.1 and 0.5g). Experiments were carried out in duplicates with 50 ml of Cd2+ solutions at room temperature.When comparing observed values (experimental) with calculated values (model), they were set closely together that allowed suggesting a normal distribution where (R2 = 0.9938). A characterization of the biosorbent was done by pHzpc and SEM-EDAX.Results also showed that the most significant effect for Cd2+ biosorption was ascribed to (X). The interaction effects of (pH BD) and (X pH) were found to have significant influence on Cd2+ removal efficiency. The highest Cd2+ removal percentage attained by 79.60...

51 citations

Journal ArticleDOI
TL;DR: The distributions of various types of prevalence estimates of NPS use are described and the impact of different population groups and study-related and tempo-geographical variables on characteristics of these distributions over the period of 2010 to 2016 is explored.
Abstract: Novel psychoactive substances (NPS) are new narcotic or psychotropic drugs that are not controlled by the United Nations drug convention that may pose a serious public health threat due to their wide availability for purchase on the internet and in so called “head shops.” Yet, the extent of their global use remains largely unknown. The aim of this study is to conduct a systematic review of the prevalence of NPS use in non-clinical populations. This is a systematic review of observational studies. Embase, MEDLINE, PubMed, Cumulative Index to Nursing and Allied Health (CINAHL), Cochrane Library, Lilacs, Scopus, Global Health, PsychINFO, Web of Science, and the World Health Organization (WHO) regional databases will be searched for eligible prevalence studies published between 2010 and 2016. Data from cross-sectional studies that report the prevalence of NPS use (one or more types) in participants (of any age) from censuses or probabilistic or convenience samples will be included. Data will be extracted from eligible publications, using a data extraction tool developed for this study. Visual and statistical approaches will be adopted instead of traditional meta-analytic approaches. This review will describe the distributions of various types of prevalence estimates of NPS use and explore the impact of different population groups and study-related and tempo-geographical variables on characteristics of these distributions over the period of 2010 to 2016. PROSPERO CRD42016037020

37 citations


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Journal Article
TL;DR: This book by a teacher of statistics (as well as a consultant for "experimenters") is a comprehensive study of the philosophical background for the statistical design of experiment.
Abstract: THE DESIGN AND ANALYSIS OF EXPERIMENTS. By Oscar Kempthorne. New York, John Wiley and Sons, Inc., 1952. 631 pp. $8.50. This book by a teacher of statistics (as well as a consultant for \"experimenters\") is a comprehensive study of the philosophical background for the statistical design of experiment. It is necessary to have some facility with algebraic notation and manipulation to be able to use the volume intelligently. The problems are presented from the theoretical point of view, without such practical examples as would be helpful for those not acquainted with mathematics. The mathematical justification for the techniques is given. As a somewhat advanced treatment of the design and analysis of experiments, this volume will be interesting and helpful for many who approach statistics theoretically as well as practically. With emphasis on the \"why,\" and with description given broadly, the author relates the subject matter to the general theory of statistics and to the general problem of experimental inference. MARGARET J. ROBERTSON

13,333 citations

Journal ArticleDOI
TL;DR: Machine learning addresses many of the same research questions as the fields of statistics, data mining, and psychology, but with differences of emphasis.
Abstract: Machine Learning is the study of methods for programming computers to learn. Computers are applied to a wide range of tasks, and for most of these it is relatively easy for programmers to design and implement the necessary software. However, there are many tasks for which this is difficult or impossible. These can be divided into four general categories. First, there are problems for which there exist no human experts. For example, in modern automated manufacturing facilities, there is a need to predict machine failures before they occur by analyzing sensor readings. Because the machines are new, there are no human experts who can be interviewed by a programmer to provide the knowledge necessary to build a computer system. A machine learning system can study recorded data and subsequent machine failures and learn prediction rules. Second, there are problems where human experts exist, but where they are unable to explain their expertise. This is the case in many perceptual tasks, such as speech recognition, hand-writing recognition, and natural language understanding. Virtually all humans exhibit expert-level abilities on these tasks, but none of them can describe the detailed steps that they follow as they perform them. Fortunately, humans can provide machines with examples of the inputs and correct outputs for these tasks, so machine learning algorithms can learn to map the inputs to the outputs. Third, there are problems where phenomena are changing rapidly. In finance, for example, people would like to predict the future behavior of the stock market, of consumer purchases, or of exchange rates. These behaviors change frequently, so that even if a programmer could construct a good predictive computer program, it would need to be rewritten frequently. A learning program can relieve the programmer of this burden by constantly modifying and tuning a set of learned prediction rules. Fourth, there are applications that need to be customized for each computer user separately. Consider, for example, a program to filter unwanted electronic mail messages. Different users will need different filters. It is unreasonable to expect each user to program his or her own rules, and it is infeasible to provide every user with a software engineer to keep the rules up-to-date. A machine learning system can learn which mail messages the user rejects and maintain the filtering rules automatically. Machine learning addresses many of the same research questions as the fields of statistics, data mining, and psychology, but with differences of emphasis. Statistics focuses on understanding the phenomena that have generated the data, often with the goal of testing different hypotheses about those phenomena. Data mining seeks to find patterns in the data that are understandable by people. Psychological studies of human learning aspire to understand the mechanisms underlying the various learning behaviors exhibited by people (concept learning, skill acquisition, strategy change, etc.).

13,246 citations

04 Mar 2014
TL;DR: In this article, a systematic review investigates the effectiveness of online services in facilitating mental health help-seeking in young people and concludes that online services can be useful for many young people.
Abstract: This systematic review investigates the effectiveness of online services in facilitating mental health help-seeking in young people.

208 citations

Journal ArticleDOI
TL;DR: The researcher explored the problems embedded in this process, attempted to find solutions such as the way of choosing mutation probability and fitness function, and chose Cranfield English Corpus test collection on mathematics, and concluded that the authors might have several improvements when using adaptive genetic algorithms.
Abstract: Genetic algorithms are usually used in information retrieval systems (IRs) to enhance the information retrieval process, and to increase the efficiency of the optimal information retrieval in order to meet the users' needs and help them find what they want exactly among the growing numbers of available information. The improvement of adaptive genetic algorithms helps to retrieve the information needed by the user accurately, reduces the retrieved relevant files and excludes irrelevant files. In this study, the researcher explored the problems embedded in this process, attempted to find solutions such as the way of choosing mutation probability and fitness function, and chose Cranfield English Corpus test collection on mathematics. Such collection was conducted by Cyrial Cleverdon and used at the University of Cranfield in 1960 containing 1400 documents, and 225 queries for simulation purposes. The researcher also used cosine similarity and jaccards to compute similarity between the query and documents, and used two proposed adaptive fitness function, mutation operators as well as adaptive crossover. The process aimed at evaluating the effectiveness of results according to the measures of precision and recall. Finally, the study concluded that we might have several improvements when using adaptive genetic algorithms. �

191 citations

Journal ArticleDOI
01 Aug 2020
TL;DR: In this paper, the composition of rice straw and husks, the various processes involved in the production of valuable products, and a range of uses to which they can be put.
Abstract: As a staple food for much of the world, rice production is widespread. However, it also results in the generation of large quantities of non-food biomass, primarily in the form of straw and husks. Although they have been little utilized and much rice straw is still simply burned, these lignocellulosic materials potentially have considerable values. This review considers the composition of rice straw and husks, the various processes involved in the production of valuable products, and a range of uses to which they can be put. These include agricultural amendments, energy production, environmental adsorbents, construction materials, and various speciality products.

171 citations