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1.1              Background of the Study

Semen, also known as seminal fluid, is an organic fluid that may contain spermatozoa. It is secreted by the gonads (sexual glands) and other sexual organs of male or hermaphroditic animals and can fertilize female ova. In humans, seminal fluid contains several components besides spermatozoa: proteolytic and other enzymes as well as fructose are elements of seminal fluid which promote the survival of spermatozoa, and provide a medium through which they can move or "swim". Semen is produced and originates from the seminal vesicle, which is located in the pelvis. The process that results in the discharge of semen is called ejaculation (Balk & Bubley, 2003).

Semen is also a form of genetic material. In animals, semen has been collected for cryoconservation. Cryoconservation of animal genetic resources is a practice that calls for the collection of genetic material in efforts for conservation of a particular breed.
Depending on the species, spermatozoa can fertilize ova externally or internally. In external fertilization, the spermatozoa fertilize the ova directly, outside of the female's sexual organs. Female fish, for example, spawn ova into their aquatic environment, where they are fertilized by the semen of the male fish (Balk & Bubley, 2003).

In Human, during the process of ejaculation, sperm passes through the ejaculatory ducts and mixes with fluids from the seminal vesicles, the prostate, and the bulbourethral glands to form the semen. The seminal vesicles produce a yellowish viscous fluid rich in fructose and other substances that makes up about 70% of human semen. The prostatic secretion, influenced by dihydrotestosterone, is a whitish (sometimes clear), thin fluid containing proteolytic enzymes, citric acid, acid phosphatase and lipids. The bulbourethral glands secrete a clear secretion into the lumen of the urethra to lubricate it (Balk & Bubley, 2003).

Sertoli cells, which nurture and support developing spermatocytes, secrete a fluid into seminiferous tubules that helps transport sperm to the genital ducts. The ductuli efferentes possess cuboidal cells with microvilli and lysosomal granules that modify the ductal fluid by reabsorbing some fluid. Once the semen enters the ductus epididymis the principle cells, which contain pinocytotic vessels indicating fluid reabsorption, secrete glycerophosphocholine which most likely inhibits premature capacitation. The accessory genital ducts, the seminal vesicle, prostate glands, and the bulbourethral glands, produce most of the seminal fluid (Bernstein, 2011).

Seminal plasma of humans contains a complex range of organic and inorganic constituents. The seminal plasma provides a nutritive and protective medium for the spermatozoa during their journey through the female reproductive tract. The normal environment of the vagina is a hostile one for sperm cells, as it is very acidic (from the native microflora producing lactic acid), viscous, and patrolled by immune cells. The components in the seminal plasma attempt to compensate for this hostile environment. Basic amines such as putrescine, spermine, spermidine and cadaverine are responsible for the smell and flavor of semen. These alkaline bases counteract and buffer the acidic environment of the vaginal canal, and protect DNA inside the sperm from acidic denaturation (Richthoff, Rylander, Hagmar,  Malm & Giwercman, 2002).

Semen is typically translucent with white, grey or even yellowish tint. Blood in the semen can cause a pink or reddish colour, known as hematospermia, and may indicate a medical problem which should be evaluated by a doctor if the symptom persists (Bernstein, 2011).

After ejaculation, the latter part of the ejaculated semen coagulates immediately, forming globules, while the earlier part of the ejaculate typically does not. After a period typically ranging from 15 – 30 minutes, prostate-specific antigen present in the semen causes the decoagulation of the seminal coagulum. It is postulated that the initial clotting helps keep the semen in the vagina, while liquefaction frees the sperm to make their journey to the ova (Bernstein, 2011).

In machine learning and statistics, classification is the problem of identifying to which of a set of categories (sub-populations) a new observation belongs, on the basis of a training set of data containing observations (or instances) whose category membership is known. An example would be assigning a given email into "spam" or "non-spam" classes or assigning a diagnosis to a given patient as described by observed characteristics of the patient (gender, blood pressure, presence or absence of certain symptoms, and so on.). Classification is an example of pattern recognition (Alpaydin, 2010).

An adaptive neuro-fuzzy inference system or adaptive network-based fuzzy inference system (ANFIS) is a kind of artificial neural network that is based on Takagi–Sugeno fuzzy inference system. The technique was developed in the early 1990s. Since it integrates both neural networks and fuzzy logic principles, it has potential to capture the benefits of both in a single framework. Its inference system corresponds to a set of fuzzy IF–THEN rules that have learning capability to approximate nonlinear functions. Hence, ANFIS is considered to be a universal estimator (Abraham, 2005).

ANFIS uses a hybrid learning algorithm to tune the parameters of a Sugeno-type fuzzy inference system (FIS). The algorithm uses a combination of the least-squares and back-propagation gradient descent methods to model a training data set. ANFIS also validates models using a checking data set to test for overfitting of the training data (Abraham, 2005).

In layman terms, ANFIS combines the learning capability of Neural Networks with the capability of Fuzzy Logic to model uncertainty in expressiveness that is model the uncertain scenarios using Fuzzy Logic and make Neural Network learn that model (Abraham, 2005).

1.2       Statement of the Problem

High costs of medical equipment and insufficient number of medical specialists have immensely contributed to the increment in the cost of medical tests (Examinations) including semen examination in most developing countries which Nigeria is not left out (Weschler, 2002).

Around 10% to 15 % of couples who want to start a family face problems with their fertility (Lovett, 2007). This may be due to a problem with the male partner or the female partner, or a combination of the two (Lovett, 2007).

To solve the above problem relating to male, there is need to develop a system that can classify semen into Normal or Altered based on social life of individual male.

1.3       Aim and Objectives

The aim of the Research is to classify Semen using Adaptive Neural Fuzzy Inference System (ANFIS).

The Objectives are to:

  1. Collect data.
  2. Pre-process data collected.
  3. Train the system using ANFIS with the pre-processed data.
  4. To measure the performance accuracy of the system.

1.4       Scope and Limitation of the Study

This scope of this research is to classify semen based on the fertility of the semen that is fertile or infertile. The classification will be done by looking at the social life of person like number of hours spent seating, alcohol drinking, smoking and so on.

This proposed system will be limited to the classification of fertility of the semen that is the quality, quantity is not taken into consideration in this study.

1.5       Significance of the Study

This study will be useful to medical practitioners and Medical Institute in the following ways:

        i.            To be able to predict man semen early in a case where the patient need immediate attention.

      ii.            It can be used to classify semen been tested may be fertile or infertile.

1.6       Definition of Terms

        i.            ANFIS: ANFIS combines the learning capability of Neural Networks with the capability of Fuzzy Logic to model uncertainty in expressiveness i.e. model the uncertain scenarios using Fuzzy Logic and make Neural Network learn that model.

      ii.            Fertile: Fertile in human means ability of reproducing or ability of developing past the egg stage.

    iii.            Fuzzy Logic: a form of reasoning, derived from fuzzy set theory, whereby a truth value need not be exactly zero (false) or one (true), but rather can be zero, one or any value in between. 

    iv.            Neural Network: a real or virtual computer system designed to emulate the human brain in its ability to learn and to assess imprecise data.

      v.            Semen: a slimy, milky fluid produced in male reproductive organs that contain the reproductive cells.

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