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Algorithms Grouped by Learning Style
There are different ways an algorithm can model a problem based on its interaction with the experience or environment or whatever we want to call the input data.
It is popular in machine learning and artificial intelligence textbooks to first consider the learning styles that an algorithm can adopt.
There are only a few main learning styles or learning models that an algorithm can have and we’ll go through them here with a few examples of algorithms and problem types that they suit.
This taxonomy or way of organizing machine learning algorithms is useful because it forces you to think about the roles of the input data and the model preparation process and select one that is the most appropriate for your problem in order to get the best result.
Let’s take a look at three different learning styles in machine learning algorithms:
1. Supervised Learning
Input data is called training data and has a known label or result such as spam/not-spam or a stock price at a time.
A model is prepared through a training process in which it is required to make predictions and is corrected when those predictions are wrong. The training process continues until the model achieves a desired level of accuracy on the training data.
Example problems are classification and regression.
Example algorithms include Logistic Regression and the Back Propagation Neural Network.
2. Unsupervised Learning
Input data is not labeled and does not have a known result.
A model is prepared by deducing structures present in the input data. This may be to extract general rules. It may be through a mathematical process to systematically reduce redundancy, or it may be to organize data by similarity.
Example problems are clustering, dimensionality reduction and association rule learning.
Example algorithms include: the Apriori algorithm and k-Means.
3. Semi-Supervised Learning
Input data is a mixture of labeled and unlabelled examples.
There is a desired prediction problem but the model must learn the structures to organize the data as well as make predictions.
Example problems are classification and regression.
Example algorithms are extensions to other flexible methods that make assumptions about how to model the unlabeled data.
Overview
When crunching data to model business decisions, you are most typically using supervised and unsupervised learning methods.
A hot topic at the moment is semi-supervised learning methods in areas such as image classification where there are large datasets with very few labeled examples.
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Algorithms Grouped By Similarity
Algorithms are often grouped by similarity in terms of their function (how they work). For example, tree-based methods, and neural network inspired methods.
I think this is the most useful way to group algorithms and it is the approach we will use here.
This is a useful grouping method, but it is not perfect. There are still algorithms that could just as easily fit into multiple categories like Learning Vector Quantization that is both a neural network inspired method and an instance-based method. There are also categories that have the same name that describe the problem and the class of algorithm such as Regression and Clustering.
We could handle these cases by listing algorithms twice or by selecting the group that subjectively is the “best” fit. I like this latter approach of not duplicating algorithms to keep things simple.
In this section, I list many of the popular machine learning algorithms grouped the way I think is the most intuitive. The list is not exhaustive in either the groups or the algorithms, but I think it is representative and will be useful to you to get an idea of the lay of the land.
Please Note: There is a strong bias towards algorithms used for classification and regression, the two most prevalent supervised machine learning problems you will encounter.
If you know of an algorithm or a group of algorithms not listed, put it in the comments and share it with us. Let’s dive in.
Regression Algorithms
Regression is concerned with modeling the relationship between variables that is iteratively refined using a measure of error in the predictions made by the model.
Regression methods are a workhorse of statistics and have been co-opted into statistical machine learning. This may be confusing because we can use regression to refer to the class of problem and the class of algorithm. Really, regression is a process.
The most popular regression algorithms are:
Ordinary Least Squares Regression (OLSR)
Linear Regression
Logistic Regression
Stepwise Regression
Multivariate Adaptive Regression Splines (MARS)
Locally Estimated Scatterplot Smoothing (LOESS)
Instance-based Algorithms
Instance-based learning model is a decision problem with instances or examples of training data that are deemed important or required to the model.
Such methods typically build up a database of example data and compare new data to the database using a similarity measure in order to find the best match and make a prediction. For this reason, instance-based methods are also called winner-take-all methods and memory-based learning. Focus is put on the representation of the stored instances and similarity measures used between instances.
The most popular instance-based algorithms are:
k-Nearest Neighbor (kNN)
Learning Vector Quantization (LVQ)
Self-Organizing Map (SOM)
Locally Weighted Learning (LWL)
Regularization Algorithms
An extension made to another method (typically regression methods) that penalizes models based on their complexity, favoring simpler models that are also better at generalizing.
I have listed regularization algorithms separately here because they are popular, powerful and generally simple modifications made to other methods.
The most popular regularization algorithms are:
Ridge Regression
Least Absolute Shrinkage and Selection Operator (LASSO)
Elastic Net
Least-Angle Regression (LARS)
Decision Tree Algorithms
Decision tree methods construct a model of decisions made based on actual values of attributes in the data.
Decisions fork in tree structures until a prediction decision is made for a given record. Decision trees are trained on data for classification and regression problems. Decision trees are often fast and accurate and a big favorite in machine learning.
The most popular decision tree algorithms are:
Classification and Regression Tree (CART)
Iterative Dichotomiser 3 (ID3)
C4.5 and C5.0 (different versions of a powerful approach)
Chi-squared Automatic Interaction Detection (CHAID)
Decision Stump
M5
Conditional Decision Trees
Bayesian Algorithms
Bayesian methods are those that explicitly apply Bayes’ Theorem for problems such as classification and regression.
The most popular Bayesian algorithms are:
Naive Bayes
Gaussian Naive Bayes
Multinomial Naive Bayes
Averaged One-Dependence Estimators (AODE)
Bayesian Belief Network (BBN)
Bayesian Network (BN)
Clustering Algorithms
Clustering, like regression, describes the class of problem and the class of methods.
Clustering methods are typically organized by the modeling approaches such as centroid-based and hierarchal. All methods are concerned with using the inherent structures in the data to best organize the data into groups of maximum commonality.
The most popular clustering algorithms are:
k-Means
k-Medians
Expectation Maximisation (EM)
Hierarchical Clustering
Association Rule Learning Algorithms
Association rule learning methods extract rules that best explain observed relationships between variables in data.
These rules can discover important and commercially useful associations in large multidimensional datasets that can be exploited by an organization.
The most popular association rule learning algorithms are:
Apriori algorithm
Eclat algorithm
Artificial Neural Network Algorithms
Artificial Neural Networks are models that are inspired by the structure and/or function of biological neural networks.
They are a class of pattern matching that are commonly used for regression and classification problems but are really an enormous subfield comprised of hundreds of algorithms and variations for all manner of problem types.
Note that I have separated out Deep Learning from neural networks because of the massive growth and popularity in the field. Here we are concerned with the more classical methods.
The most popular artificial neural network algorithms are:
Perceptron
Back-Propagation
Hopfield Network
Radial Basis Function Network (RBFN)
Deep Learning Algorithms
Deep Learning methods are a modern update to Artificial Neural Networks that exploit abundant cheap computation.
They are concerned with building much larger and more complex neural networks and, as commented on above, many methods are concerned with semi-supervised learning problems where large datasets contain very little labeled data.
The most popular deep learning algorithms are:
Deep Boltzmann Machine (DBM)
Deep Belief Networks (DBN)
Convolutional Neural Network (CNN)
Stacked Auto-Encoders
Dimensionality Reduction Algorithms
Like clustering methods, dimensionality reduction seek and exploit the inherent structure in the data, but in this case in an unsupervised manner or order to summarize or describe data using less information.
This can be useful to visualize dimensional data or to simplify data which can then be used in a supervised learning method. Many of these methods can be adapted for use in classification and regression.
Principal Component Analysis (PCA)
Principal Component Regression (PCR)
Partial Least Squares Regression (PLSR)
Sammon Mapping
Multidimensional Scaling (MDS)
Projection Pursuit
Linear Discriminant Analysis (LDA)
Mixture Discriminant Analysis (MDA)
Quadratic Discriminant Analysis (QDA)
Flexible Discriminant Analysis (FDA)
Ensemble Algorithms
Ensemble methods are models composed of multiple weaker models that are independently trained and whose predictions are combined in some way to make the overall prediction.
Much effort is put into what types of weak learners to combine and the ways in which to combine them. This is a very powerful class of techniques and as such is very popular.
Boosting
Bootstrapped Aggregation (Bagging)
AdaBoost
Stacked Generalization (blending)
Gradient Boosting Machines (GBM)
Gradient Boosted Regression Trees (GBRT)
Random Forest
Other Algorithms
Many algorithms were not covered.
For example, what group would Support Vector Machines go into? Its own?
I did not cover algorithms from specialty tasks in the process of machine learning, such as:
Feature selection algorithms
Algorithm accuracy evaluation
Performance measures
I also did not cover algorithms from specialty subfields of machine learning, such as:
Computational intelligence (evolutionary algorithms, etc.)
Computer Vision (CV)
Natural Language Processing (NLP)
Recommender Systems
Reinforcement Learning
Graphical Models
And more…
These may feature in future posts.

The decision was taken by the joint session of Nigeria Labour congress, and public service joint negotiating council as they raised from a meeting held yesterday where the union resolved to resume the earlier suspended indefinitely strike. source ; Blue print newspaper on friday, September 22, 2017 page 7.

bus,keke and bike

over 27 persons was killed

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Deputy edition news edition head,sport desk etc go and buy blueprint newspaper on 19,July 2017 page 8 for information.

FAST FACTS
Van hits pedestrians on London Bridge
Reports of multiple stabbing attacks at
Borough Market. Shots fired.
Third incident in Vauxhall unconnected
More than one fatality, multiple injuries
Armed British police locked down London
Bridge late on Saturday after a vehicle
slammed into pedestrians and
stabbing attacks were reported nearby in
what appeared to be a coordinated attack.
London's Metropolitan Police declared the
events at London Bridge and Borough
Market as "terrorist incidents".
"Witnesses say a white van rammed
into pedestrians hitting several people
before coming to a halt," said AlJazeera's
Yao Chin, reporting from
London.
"Another witness said three men got
out with long blades and randomly
started stabbing people along Borough High
Street. Other witnesses have also
mentioned seeing knife victims."
The BBC reported that more than one
person had been killed. The London
Ambulance Service said it had taken at
least 20 people to six hospitals across the
city, and had treated a number of people at
the scene for less serious injuries.
Police said in a statement that officers
"responded to reports of a vehicle
incollision with pedestrians on London
Bridge" and then "to reports of stabbings in
Borough Market," a busy area of
restaurants and bars at the south end of the
bridge.
"Armed officers responded and shots have
been fired," the statement said. Police ruled
a third incident - a stabbing in London's
Vauxhall area initially thought to be linked
to the other two scenes - to be unrelated.
Britain's Sun newspaper said as many as
seven people were feared killed and
that two attackers were shot dead by police
near London Bridge - but there was no
immediate confirmation from police. Some
media reports said police were seeking
another attacker. Police told pedestrians
leaving the scene near the bridge to raise
their hands over their heads as they exited
the area [Reuters]
One of the men suspected of being
involved in the attack was shown in a
photograph lying on the ground with
canisters strapped to his body after he was
shot by the police.
The possible attacker was shown on
the ground outside the Wheatsheaf
pub in Borough Market near London
Bridge.
Another man was seen lying on the
ground a short distance away in the
photograph.
"There is a huge police presence,
emergency services are all over the
place," said Al Jazeera's Oliver Varney from
the scene.
Metropolitan police Tweeted a photo
telling Londoners to "run, hide, tell".
http://confluencenewsbit..co.ke/2017/06/london-bridge-fatalities-after-car-and.html?m=1

The Joint Action Committee (JAC) of trade
unions of tertiary institutions owned by Kogi
State government has assured government
of her readiness to suspend her 4-month
old strike action as soon as their reviewed
demands are met.
This position was contained in a
communique issued at the close of the 12th
General meeting of JAC, yesterday.
According to JAC, the trade unions has
graciously contracted its thirty-one (31)
collective demands to five (5) irreducible
demands. This action is geared towards
suspension of the ongoing strike.
The demands are;
“The Visitor to our schools (Governor)
should approve and implement the
screening reports of the Governor Councils
in its entirety, because, Members of our
Governing Councils are people of integrity
who have carved niches for themselves in
their endeavours. Therefore, only their
screening list is acceptable to JAC and any
other list from anywhere shall be rejected.
“Salaries of our Members who are cleared,
uncleared and omitted should be paid
without further delays.
Government should elucidate its actions on
the peculiar needs of each Tertiary
institutions submitted by the Governing
Councils.
“Government should urgently honour the
Joint Resolution reached by the
representatives of the Government and JAC
on 24th March, 2017 which include reversal
of the new tax rates and refund of January,
2017 excess tax to tertiary institutions.
“Government should give definite date for
the refund of excess tax to Kogi State
University, Anyigba and Kogi State College
of Education, Ankpa.
JAC extends its appreciation to the
Governing Council members of tertiary
institutions owned by Kogi State for their
genuine efforts to resolve the ongoing
industrial strike.
The body frowned at the directive of
government to heads of tertiary institutions
to re-open schools on the 5th June, 2017.
“JAC empathizes with our students who
have been at home for this long. They
should be reminded that, JAC’s struggle is
to save the soul of our educational system.
And we hope that, at the end of this painful
industrial strike, tertiary institutions owned
by Kogi state will be better positioned to
turn out qualified graduates.
“There are evil machinations from some
quarters to incite students against our
members on resumption, let it be clear to
those behind this plot that, “whatever
comes around, goes around”.
“JAC is disappointed with Government’s
decision to prematurely retire our non-
teaching members; this is an outright
violation of the extant Law of 65 years
retirement age for staff of tertiary
institutions.
“The fate of those employed in 2015/2016
is still unknown, despite convincing reasons
put forward by Heads of institutions;
employments in tertiary institutions is
based on needs.
“The recent lists released on 31st May,
2017 and 1st June, 2017 is a complete
setback to any ongoing dialogue. Our
Members who had been on the ‘cleared’ list
since the onset of the protracted staff
screening exercise are now being move to
the ‘uncleared’ list. This unwholesome act is
another move by the “Czars” in this
government to destroy the gains made from
the screening exercise”, the communique
reads.
However, JAC maintained that it cannot be
intimidated and coerced to resume work on
the 5th June, 2017. The body advised Kogi
government to do the needful and bring this
impasse to an end. http://kogireports.com/kogi-we-are-ready-to-suspend-strike-as-soon-as-demands-are-met-lecturers/?utm_source=WhatsApp&utm_medium=IM&utm_campaign=share

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check daily trust Newspaper on February 15, 2017

Federal Government Scholarship
Awards (2016/2017) for eligible
Nigerians studying in all Public
Tertiary institutions in the country.visit http://education.gov.ng/index.php/78-featured/156-federal-scholar-board.

… Expects 1.7m candidates to apply – Registrar, Prof. Oloyede The Registrar, Joint Admission and Matriculation Board (JAMB), Prof. Ishaq Oloyede, Tuesday hinted that the body would soon commence the sale of the application form for the 2017 Unified Tertiary Matriculation Examination(UTME). . Oloyede said an estimated 1.7 million candidates are expected register and sit for the Computer Based Test (CBT) across the country, adding that they are also increasing the capacity of the CBT centres to maximise their effectiveness to examine more candidates within a given date. The Chief Executive Officer of JAMB made this known at the Green Legacy, Olusegun Obasanjo Presidential Library (OOPL), Abeokuta, the Ogun State capital, while fielding questions from journalists shortly after a meeting of the JAMB officials and other stakeholders regarding the new Information Technology being introduced into the system to make it less stressful to candidates. According to him, the body is working with the possibility of conducting a “mock examination” not only to test its preparedness with the new technology, but also to examine some people that are desirous of knowing their competence with the JAMB examination. He noted that stakeholders meeting was predicated on the need for people to make inputs into the new ICT facilities and critique it before putting them into use. Oloyede said Nigeria is ripe for an ICT – driven examinations, disclosing that the innovation would definitely unsettle some people, who hitherto were short-changing JAMB through “fraud” and in some cases, duplication of PIN. “What we are doing appears to be suitable to majority of our stakeholders. It is a surprise to us that we are apprehensive of what we wanted to do that maybe we are going to create problem. We are more confident to go along with the sale of the form for 2017 UTME examination. “I believed that Nigeria is ripe for this. Nigeria is more advanced than some of these countries. At least, we have three or four countries that are observing our examination and they want to go the way of the conduct of the examination. “We are expecting 1.7 million candidates and we want to make sure we satisfy these candidates within a week or there about. That is why we are increasing the capacity of the Computer Based Test centres to be able to examine more candidates within a given date “If we are talking about 1.5 million candidates, it means that in a given day about 60,000 or 70,000 candidates will take the examination. “We have invited stakeholders to critique the process because we don’t want to go in the wrong direction. We are creating some ICT facilities and we want our stakeholders, prospective candidates, respected scholars, institutions, civil societies to come together and critique what we are doing, so that we can be sure, before we go too far in a wrong direction. “This is with a view of harvesting good ideas that could improve what we are doing. We thought we are coming here to get dismantled, all we have put together, but what we are having are cheers that we can do it this way, or amend it that way. “I must be frank with you, I cannot promise hitch free examination because we are testing certain things. We are changing certain things. We want to question the status quo and of course, we expect a fight back by interest that will be trampled upon. “We are going to be as sincere as possible in the direction we are going. We are going to be as flexible as humanly possible. We are not promising hitch free examination. “We envisaged that there will be hitches here and there, but they will not be insurmountable. Rather than promising the nation hitch free examination, we will be promising a direction we will all be pleased with. “Initially there might be hiccups and of course one would not have been appointed if it is routine. I believe that I have been given a very difficult job and that is why I’m promising that it will be all smooth,” Oloyede said.

from 8:00pm till now firework is on going in lokoja at mount pati

he is the through son of is father, clean he up and tell he story of My own life

To view admission list, select the Programme, Course of Study and Mode of Study of your application,This list contains Batch I and II Full AdmissionList, kindly check for your name among the list. To go: http:// confluencenewsbit..co.ke/2017/01/kogi- state-polytechnic-20162017.html?m=1

To view admission list, select the Programme,
Course of Study and Mode of Study of your
application,This list contains Batch I and II Full AdmissionList, kindly check for your name among the list.
To go: http://confluencenewsbit..co.ke/2017/01/kogi-state-polytechnic-20162017.html?m=1

Yahya Jammeh, president of The Gambia, surprised his critics by accepting defeat after
22 years in power- though he now says he will
contest the result. Known for walking around with his trademark prayer beads and a
stick, he was reputed to be one of the world's most eccentric and ruthless leaders.Born
in May 1965, he came to power in 1994 as a 29-year-old army lieutenant in a country
portrayed in tourist brochures as an idyllic holiday destination. He became a portly
president who portrays himself as a devout Muslim with miraculous powers, such as the
power to cure people of Aids and infertility. He also believes that homosexuality
threatens human existence.
Mr Jammeh divorced his first wife Tuti Faal and subsequently married two other women,
though his official website refers only to Zineb Yahya Jammeh , who holds the title of
First Lady.
According to The Gambia's privately owned Point newspaper, he married his second wife,
Alima Sallah, in 2010, but Mr Jammeh's office issued an instruction that she should not
be referred to as First Lady - in contrast to South Africa where all four wives of
President Jacob Zuma hold the title.
"She is not to be addressed as the First Lady because, according to protocol, there can
only be one First Lady and, in this case, that is Madam Zineb Yahya Jammeh," the
newspaper quoted the presidency as saying. Mr Jammeh won four multiparty elections
before he was finally defeated. After his 2011 victory, in a sign that his credibility
among African leaders had plummeted, the regional body, the Economic Community of
West
African States (Ecowas), refused to endorse his victory, saying voters and the opposition
had been "cowed by repression and intimidation". His decision to withdraw from the
Commonwealth in 2013, which had been pushing for reforms in the tiny West African
state, was a further sign of Mr Jammeh's growing isolation. 'Rule for a billion years' In
an interview in 2011 with the BBC's Focus on Africa radio programme, Mr Jammeh said
he did not fear a fate similar to Libya's killed leader Muammar Gaddafi or Egypt's
ousted President Hosni Mubarak. "My fate is in the hands of almighty Allah," he told the
BBC. "I will deliver to the Gambian people and if I have to rule this country for one billion
years, I will, if Allah says so." Mr Jammeh said he was not bothered by the criticism of
human rights groups. "I will not bow down before anybody, except the almighty Allah
and if they don't like that they can go to hell," he said.
'Executions'
Mr Jammeh is known for expressing bizarre views. In 2007, he claimed that he could
cure Aids with a herbal concoction - a view condemned by health experts. Later, he also
claimed that he could cure infertility among women.
Mr Jammeh is also known for his virulent opposition to gay rights, having once
threatened to behead gay people.
In a 2014 address to the UN General Assembly, Mr Jammeh lamented that Western
governments were pushing for homosexuality to be legalised.
"Homosexuality in all its forms and
manifestations which, though very evil, anti- human as well as anti-Allah, is being
promoted as a human right by some powers," he said.
The Gambian government's treatment of journalists and opposition parties has also
caused huge concern among human rights groups.
Mr Jammeh's government has been under intense pressure to solve the murder of the
editor of The Point newspaper, Deyda Hydara. Gunned down i n 2004, he has become a symbol of the campaign for press freedom in The Gambia. The international media group
Reporters Without Borders (RSF) said there was "absolute intolerance of any form of
criticism" in The Gambia, with death threats, surveillance and
arbitrary night-time arrests of journalists "who do not sing the government's praises".
In the BBC interview, Mr Jammeh denied his security agents had killed Mr Hydara. "Other
people have also died in this country. So
why is Deyda Hydara so special?" he said. http://confluencenewsbit..in/2017/01/full-profile-gambia-yahya-jammeh.html?m=1

Prof. Aliyu Usman Mani was born in Katsina
town on Thursday 11 April, 1957. He attended
Kayalwa Primary School, Katsina (1964-1970),
then he proceed to Government college Kaduna
(1971-1975) from there he went to School of
Basic Studies (SBS) ABU Zaria (1975-1976).
After passing he got admission into the faculty
of veterinary medicine ABU, zaria and
graduated with the award of Doctor of
Veterinary Medicine DVM in 1981. He did his
NYSC with school of Agriculture in Asaba,
Bendel state.
He worked briefly with Niger Basin Development
Authority in Ilorin Kwara state before
proceeding to University of Maiduguri as an
Assistant Lecturer Department of Veterinary
Medicine in October, 1982. Later he attended
the center for Tropical Veterinary studies
Edinburgh UK (1984-1985) where he got his
Masters and at the same school he later got
his PhD.
He returned to Maiduguri in 1994. He is also a
Fellow of the College of Veterinary Surgeons
(2010) and through pair reviewer.
He is one time Director of Unimaid Veterinary
Teaching Hospital (1997-2000). Head of
Department (2005-2010). Acting Dean of vet
faculty (2008-2010). Before his death, he was
again the Director of Unimaid Veterinary
Teaching Hospital.
He held several positions in committees both
within and outside the University. He also held
a number of positions in the Nigerian Veterinary
Medical Association (NVMA).
Professor Aliyu Usman Mani is Happily Married
with two children. He is one of the peaceful
Lecturers in his Faculty.
Prof. Aliyu Usman Mani died to bomb blast on
Monday (16th January, 2017) in the Mosque
inside University of Maiduguri while observing
the dawn (fajr) prayer. confluencenewsbit..in/2017/01/profile-of-university-prof-killed-in.html?m=1

Super Eagles captain John Obi Mikel has hinted that Tianjin Teda will be his final bus stop in football, if all things go on well with him in China. Mikel signed a three-year deal with the Chinese Super League club currently training in Malaga, Spain after being frozen out at Chelsea, where he spent close to eleven years winning titles. Mikel Obi “Of course, I want to stay in a team for a long time, I left Chelsea after eleven years, I hope to stay in TEDA for a long time, not one or two seasons, “ Mikel was quoted as saying by Netease Sports. “If the club will not let me go, I hope to stay until the end of my career, TEDA will be my last stop.” Mikel scored his first goal for his new club in their 6-2 loss to German side St. Pauli yesterday. His goal came off a header from a well delivered free kick, which left the goalkepper of St. Pauli stranded in goal as the ball flew into the net. http://confluencenewsbit..co.ke/?m=1

Ola Ajayi, Ibadan No fewer than 12 people reportedly died in an accident on Oyo/Ogbomoso Road when a commuter bus skidded off the road and plunged into Odo-Oba River yesterday. According to eye witnesses, the accident occurred when the bus was trying to avoid a head on collision with an articulated vehicle that lost control and veered off its lane. Oyo State Sector Commander of the Federal Road Safety Commission (FRSC), Mr Yusuf Salami and the Police Public Relations Officer, Oyo State Command, SP Adekunle Ajisebutu, confirmed the accident. The police spokesperson said the bodies of the victims had been taken to Ladoke Akintola University of Technology Teaching Hospital, Ogbomoso. Ajisebutu said, “The driver of the Mazda bus lost control of the vehicle and plunged into the Odo-Oba River. Nine adults and three kids died on the spot and their bodies have been deposited at the LAUTECH Teaching Hospital in Ogbomoso. There were three survivors. The police, with assistance from local drivers, pulled the bodies and passengers out of the river. The vehicle is still in the river.” In his own account, Salami said. “From the report I had, the bus was travelling to Ilorin and as it approached the slope leading to the small bridge over the river, an articulated truck took over the path of the road and, in an effort to avoid collision with it, the bus driver veered off the road and plunged into the river. “It was difficult pulling the passengers out of the river despite volunteer rescuers that arrived at the scene early. 12 people died immediately.” http://confluencenewsbit..co.ke/?m=1

General Instructions Nationality: Applicant must be of Nigerian origin. Age: Applicants must be between the ages of 17 and 22 years for non- tradesmen/women, 17 and 24 years for tradesmen/women by 31 December 2017. Those applying as drivers must be between the ages of 18 and 28 years by 31 December 2017 Marital Status: All applicants must be single. Height: Minimum height is 1.68 meters or 5.5ft for males and 1.65m or 5.4ft for females. Medical Fitness All applicants must be medically fit and meet the Nigerian Air Force medical and employment standards. Academic/Professional Qualification Non-Tradesmen/Women Applicants must possess a minimum of 3 credits including Mathematics and English Language in SSCE/NECO/GCE / NABTEB In addition, applicants are also required to possess their school's testimonials. Tradesmen/Women Applicants must possess OND, NABTEB. Candidate with only Trade Test Certificate are required to also have a minimum of 3 passes in GCE/SSCE/NECO including English. In addition, applicants applying as tradesmen/ tradeswomen must possess ND (with minimum of Lower Credit) or other relevant trade qualification from government-approved institutions. Note that applicants with HND or First Degrees/ Post- Graduate Certificates, University Diplomas and Grade II Teacher's certificates will not be considered for recruitment as airmen/airwomen into the Nigerian Air Force and should not apply. Attestation Forms Applicant's attestation form must be signed by a military officer from the same state as the applicant and not below the rank of Squadron Leader or equivalent in the Nigerian Army and the Nigerian Navy, and Police Officer of the rank of Assistant CP and above. Local Governments Chairmen/Secretaries, magistrates and principals of government Secondary Schools from applicants' state of origin can also sign the attestation forms. The signees passport photograph and either photocopy of drivers licence or international passport must be attached. In addition, applicants are to bring with them a letter of attestation of good character from any of the officers above to the Zonal Recruitment Centers and final selection interview. Requirements: Applicants are advised to carefully read the requirements below before filling the form: Note : online registration starts on 14 January 2017 and closes 17 February 2017. zonal recruitment exercise will hold from 23 February - 16 march 2017.

eneral Instructions Nationality: Applicant must be of Nigerian origin. Age: Applicants must be between the ages of 17 and 22 years for non- tradesmen/women, 17 and 24 years for tradesmen/women by 31 December 2017. Those applying as drivers must be between the ages of 18 and 28 years by 31 December 2017 Marital Status: All applicants must be single. Height: Minimum height is 1.68 meters or 5.5ft for males and 1.65m or 5.4ft for females. Medical Fitness All applicants must be medically fit and meet the Nigerian Air Force medical and employment standards. Academic/Professional Qualification Non-Tradesmen/Women Applicants must possess a minimum of 3 credits including Mathematics and English Language in SSCE/NECO/GCE / NABTEB In addition, applicants are also required to possess their school's testimonials. Tradesmen/Women Applicants must possess OND, NABTEB, RN/RM or City & Guild Certificate. Candidate with only Trade Test Certificate are required to also have a minimum of 3 passes in GCE/SSCE/NECO including English. In addition, applicants applying as tradesmen/ tradeswomen must possess ND (with minimum of Lower Credit) or other relevant trade qualification from government-approved institutions. Note that applicants with HND or First Degrees/ Post- Graduate Certificates, University Diplomas and Grade II Teacher's certificates will not be considered for recruitment as airmen/airwomen into the Nigerian Air Force and should not apply. Attestation Forms Applicant's attestation form must be signed by a military officer from the same state as the applicant and not below the rank of Squadron Leader or equivalent in the Nigerian Army and the Nigerian Navy, and Police Officer of the rank of Assistant CP and above. Local Governments Chairmen/Secretaries, magistrates and principals of government Secondary Schools from applicants' state of origin can also sign the attestation forms. The signees passport photograph and either photocopy of drivers licence or international passport must be attached. In addition, applicants are to bring with them a letter of attestation of good character from any of the officers above to the Zonal Recruitment Centers and final selection interview. Requirements: Applicants are advised to carefully read the requirements below before filling the form: Note : online registration starts on 14 January 2017 and closes 17 February 2017. zonal recruitment exercise will hold from 23 February - 16 march 2017. WWW.airforce.mil.ng

General Instructions Nationality: Applicant must be of Nigerian origin. Age: Applicants must be between the ages of 17 and 22 years for non-tradesmen/women, 17 and 24 years for tradesmen/women by 31 December 2017. Those applying as drivers must be between the ages of 18 and 28 years by 31 December 2017 Marital Status: All applicants must be single. Height: Minimum height is 1.68 meters or 5.5ft for males and 1.65m or 5.4ft for females. Medical Fitness All applicants must be medically fit and meet the Nigerian Air Force medical and employment standards. Academic/Professional Qualification Non-Tradesmen/Women Applicants must possess a minimum of 3 credits including Mathematics and English Language in SSCE/NECO/GCE /NABTEB In addition, applicants are also required to possess their school's testimonials. Tradesmen/Women Applicants must possess OND, NABTEB, RN/RM or City & Guild Certificate. Candidate with only Trade Test Certificate are required to also have a minimum of 3 passes in GCE/SSCE/NECO including English. In addition, applicants applying as tradesmen/ tradeswomen must possess ND (with minimum of Lower Credit) or other relevant trade qualification from government-approved institutions. Note that applicants with HND or First Degrees/ Post-Graduate Certificates, University Diplomas and Grade II Teacher's certificates will not be considered for recruitment as airmen/airwomen into the Nigerian Air Force and should not apply. Attestation Forms Applicant's attestation form must be signed by a military officer from the same state as the applicant and not below the rank of Squadron Leader or equivalent in the Nigerian Army and the Nigerian Navy, and Police Officer of the rank of Assistant CP and above. Local Governments Chairmen/Secretaries, magistrates and principals of government Secondary Schools from applicants' state of origin can also sign the attestation forms. The signees passport photograph and either photocopy of drivers licence or international passport must be attached. In addition, applicants are to bring with them a letter of attestation of good character from any of the officers above to the Zonal Recruitment Centers and final selection interview. Requirements: Applicants are advised to carefully read the requirements below before filling the form: Note : online registration starts on 14 January 2017 and closes 17 February 2017. zonal recruitment exercise will hold from 23 February - 16 march 2017.