There is, I think, something ethereal about i —the square root of minus one. I remember first hearing about it at school. It seemed an odd beast at that time—an intruder hovering on the edge of reality.

Usually familiarity dulls this sense of the bizarre, but in the case of i it was the reverse: over the years the sense of its surreal nature intensified. It seemed that it was impossible to write mathematics that described the real world in …

I and i

Data Mining Practical Machine Learning Tools and Techniques

Soil Chemical Analysis

This Review summarizes the simultaneous transmission of several independent spatial channels of light along optical fibres to expand the data-carrying capacity of optical communications. Recent results achieved in both multicore and multimode optical fibres are documented.

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Space-division multiplexing in optical fibres

Traditional engineering instruction is deductive, beginning with theories and progressing to the applications of those theories Alternative teaching approaches are more inductive Topics are introduced by presenting specific observations, case studies or problems, and theories are taught or the students are helped to discover them only after the need to know them has been established This study reviews several of the most commonly used inductive teaching methods, including inquiry learning, problem-based learning, project-based learning, case-based teaching, discovery learning, and just-in-time teaching The paper defines each method, highlights commonalities and specific differences, and reviews research on the effectiveness of the methods While the strength of the evidence varies from one method to another, inductive methods are consistently found to be at least equal to, and in general more effective than, traditional deductive methods for achieving a broad range of learning outcomes

Inductive Teaching and Learning Methods: Definitions, Comparisons, and Research Bases

AbstractAlzheimer’s Disease (AD) is a dynamic condition that affects cognitive capabilities and functioning. It is a challenging disease to detect, particularly in its early stages. Early diagnosis of AD is the key for its treatment and slowing of its progress. This paper argues and clearly shows the benefits of using cognitive tests for efficient and early AD detection. In this study, a novel approach for the early detection of AD is proposed. We refer to it as Neighborhood Component Analysis and Correlation-based Filtration (NCA-F) and is based on selecting and identifying significant cognitive features. Cognitive features are used to train four Machine Learning (ML) classifiers, including Support Vector Machine (SVM), Naïve Bayes (NB), ANN, and AdaBoost Ensemble (AdB). Our analysis shows that the proposed approach can achieve an 88% classification accuracy. In addition, the performance of various ML classifiers with varying combinations of features has been studied. The proposed feature selection approach that implements AdB is seen to provide the best performance by various metrics.KeywordsAlzheimer’s DiseaseFeature selectionMachine LearningANNSVMNBAdaBoost Ensemble 

Early Detection of the Alzheimer’s Disease: A Novel Cognitive Feature Selection Approach Using Machine Learning

The present invention relates to a preparation comprising at least one capsule material and at least one bioactive natural substance, wherein the bioactive natural substance can be controllably released from the preparation, wherein the capsule material comprises at least one glyceride with a melting point of at least 35°C and additionally, at least one polymer with polyester units, which polymer has a melting point of at least 30°C and a viscosity in the range of 50 mPa*s to 250 Pa*s, measured by rotation viscometry at 110°C. Moreover, the present invention relates to methods for the production and preferred uses of the preparation according to the invention.

Preparation for the Controlled Release of Bioactive Natural Substances

Abstrak. Travelling Salesman Problem (TSP) adalah permasalahan dimana seorang salesman harus mengunjungi semua kota yang mana tiap kota hanya dikunjungi sekali, dan harus kembali ke kota asal. Masalah utama yang dihadapi sebuah TSP adalah bagaimana mencari rute terpendek dari perjalanan seorang salesman dengan biaya minimum. Penelitian ini bertujuan untuk mengetahui penyelesaian masalah TSP dengan menggunakan algoritma Hill Climbing baik Simple Hill Climbing (SHC) maupun Steepest-Ascent Hill Climbing (SAHC). Berdasarkan hasil kajian teori yang dilakukan, dapat disimpulkan bahwa algoritma Hill Climbing dapat digunakan untuk menyelesaikan TSP. Algoritma Hill Climbing dalam menyelesaikan masalah TSP yaitu: menentukan initial state, melakukan pengujian panjang lintasan, melakukan kombinasi penukaran dua kota, dan kemudian melakukan pengujian terhadap nilai heuristiknya. Penyelesaian masalah TSP dengan menggunakan algoritma Hill Climbing masing-masing mempunyai karakteristik yang berbeda-beda. Dalam menyelesaikan masalah TSP, SHC memilih keadaan yang lebih baik tanpa melakukan pengujian dikombinasi pertukaran kota pada iterasi yang sama. Sedangkan SAHC membandingkan keadaan yang lebih baik sebelum memilih keadaan tersebut sebagai new state . Selanjutnya untuk membantu proses komputasi pada saat menyelesaikan TSP, dibuat sebuah program dengan model algoritma Hill Climbing menggunakan MATLAB. Program yang terbentuk memberikan solusi berupa rute perjalanan yang disajikan dalam bentuk diagram. Kata kunci: Algoritma, Hill Climbing, Travelling Salesman Problem Abstract. ( Completion of Traveling Salesman Problem (TSP) Using the Hill Climbing and MATLAB Algorithms ) Traveling Salesman Problem (TSP) is a problem where a salesman must visit all cities where each city is visited only once, and he/she must return to the hometown. The main problem facing a TSP is how to find the shortest route of a sales trip with minimum cost. This study aims to determine the solution of TSP problems using Hill Climbing algorithm both Simple Hill Climbing (SHC) and Steepest-Ascent Hill Climbing (SAHC). Based on the result of the theoretical study, it can be concluded that Hill Climbing algorithm can be used to solve TSP. Hill Climbing algorithm in solving TSP problem is: determining initial state, conducting track length test, performing combination of two city exchanges, and then testing the heuristic value. TSP problem solving using Hill Climbing algorithm each have different characteristics. In solving the TSP problem, SHC chooses a better state, without performing tests in combination of city exchanges on the same iteration. While SAHC compares the situation better before choosing the state as a new state. Furthermore, to assist the computing process when completing the TSP then made a program model Hill Climbing algorithm using MATLAB language. The program is formed to provide solutions in the form of travel routes presented in the form of diagrams. Keywords i: Algorithm , Hill Climbing, Travelling Salesman Problem

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Penyelesaian Travelling Salesman Problem (TSP) Menggunakan Algoritma Hill Climbing dan MATLAB

Hematopoietic stem cell in bone marrow committed to produce erythrocyte- the red blood cells. Once mature these cells continuously egress out into general circulation to perform their normal function in the body. Bone marrow generally separated from peripheral blood via sinusoid membrane that has small pores in its endothelial layer. RBCs egress out through specific sites (pores) from endothelial layer. During maturation process RBCs lose its nucleus and became discoid shape. That imparts the greater deformability into them so they could easily squeeze out through marrow aperture. The egress of RBCs further accelerated as a result of humoral factors (releasing factors) i.e. stress, cytokines, chemokines, erythropoietin and proteolytic enzymes like GTPases.

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An Overview of Mechanism of Egress of RBC from Bone Marrow

Cover Picture: Green and Sustainable Chemical Synthesis Using Flow Microreactors / Continuous Synthesis of tert-Butyl Peroxypivalate using a Single-Channel Microreactor Equipped with Orifices as Emulsification Units / Heterogeneous Catalytic Hydrogenation Reactions in Continuous-Flow Reactors (ChemSusChem 3/2011)

Muhammad Irfan

Papers

Early Detection of the Alzheimer’s Disease: A Novel Cognitive Feature Selection Approach Using Machine Learning

Preparation for the Controlled Release of Bioactive Natural Substances

Penyelesaian Travelling Salesman Problem (TSP) Menggunakan Algoritma Hill Climbing dan MATLAB

An Overview of Mechanism of Egress of RBC from Bone Marrow