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AMCON seeks judiciary’s support to recover N5.4tn debt
by Ifeanyi OnubaIfeanyi Onuba, Abuja
the Asset Management Corporation of Nigeria is seeking the support of the judiciary to recover over N5.4tn debt owed the corporation by chronic debtors.
The Managing Director/Chief Executive Officer, AMCON, Mr Ahmed Kuru, said this at the 2019 Annual Seminar for Justices of the Court of Appeal.
The seminar which was held on Saturday at the Court of Appeal complex in Abuja had as its theme, “The amended AMCON Act 2019: A detailed review.”
Kuru said in view of the fact that AMCON was approaching its terminal date, it had become imperative to get the support of the courts in resolving all the pending cases currently before them.
He also told the justices that more than ever before, AMCON would need the support of the judiciary to resolve the debt obligation before the terminal date.
This, he noted, was imperative based on the conviction that obligors of AMCON were working hard to stretch the corporation to its terminal date.
He explained that if the over N5.4tn debt owed AMCON remained unrecovered, it would eventually become the burden of the Federal Government and by extension Nigerian taxpayers.
Kuru said, “The amendment (of the AMCON Act) was done to recover the loans people took from banks.
“If AMCON is not able to recover the debt, it becomes the debt of the government and when this happens, it is the taxpayers that will bear this burden of people who were reckless. This should not be allowed to happen.
“We urge you to designate some of the courts for AMCON cases. We urge you to assist in granting accelerated hearing for AMCON cases.”
He said the different challenges of AMCON in its debt recovery drive had necessitated AMCON to put machinery in motion and worked with the National Assembly to amend the Act.
The President of the Court of Appeal, Justice Zainab Bulkachuwa, in her opening address at the events said the concern raised by AMCON was becoming worrisome in view of the fact that recalcitrant obligors deployed technicalities to frustrate the corporation.
She said given the challenges faced by AMCON in its debt recovery efforts, the corporation could not operate effectively without the sustained support of the courts.
CopyrightPUNCH.
All rights reserved. This material, and other digital content on this website, may not be reproduced, published, broadcast, rewritten or redistributed in whole or in part without prior express written permission from PUNCH.
Contact: editor@punchng.com


Welcome to my game which I've named Astral Engineer. I've been a fan of space and building games for a long time so I thought combining the two would make for an excellent theme for my first game! I will also be doing the art!


I am a commerce student at Shri Ram College of Commerce, Delhi University, passionate about making products and building businesses. I'm highly interested in upcoming technologies and the business opportunities that follow. I am skilled in Android, Javascript, HTML,CSS, React, and Node.js. Apart from that, I like sharing my thoughts with like-minded people through speaking and writing on my blog. Have something interesting to work on? Let's collaborate!
We identify what customers like but do not buy. With our
patented technology and unique value proposition, we help
clients to gamify the offline retail store experience to
increase the average basket size and customer footfall.
Almost all my time at RealTell goes into building the product
- web/mobile, ML, DevOps etc.
I'm into Yoga, Meditation and anything that helps me advance
spiritually and makes me fulfilled.
I'm relatively new at this, so if you're interested, stay
tuned until I share my experiences.
I can talk all day about this, so ping me if you'd like!
I focus mainly on meditaion, productivity, tech and business. I'm also intrigued a lot by Blockchain, IoT, AR, VR, and AI (all the hyped ones). Just go through my blog to know more :)


Haroldbot is a tool that checks the equivalence of arithmetic expressions with 32-bit bitvector semantics, running entirely on the client. This task is mostly accomplished by encoding the expression as an array of 32 binary decision diagrams, one for each bit. Since for a given variable ordering a BDD of a boolean function is canonical, this representation offers and easy equivalence test, at the cost of having to build the BDD first.
Some types of expressions, most notably expressions that involve the product of two variables, cannot be encoded as a small BDD. For those expressions, haroldbot can fall back to using a SAT solver, by encoding the whole expression as a boolean circuit first and then using the Tseytin transformation to convert the problem to CNF.
Haroldbot can also (sometimes) find step-by-step proofs for true statements, this is done by applying expression rewrite rules from both ends of proof until a match is found that "connects" the two.
BDDs, specifically reduced ordered binary decision diagrams (ROBDD) with a fixed order and with "complement edges", form the backbone of haroldbot and have been part of it the longest, with the SAT fallback and proof finder being added during later stages of development.
A BDD is a directed acyclic graph consisting of internal nodes with exactly two children that represent testing a boolean variable and taking either the "low" or the "high" edge, and two leaf nodes that represent the constant results 0 and 1. The "reduced" part of ROBDD means that a node that refers to the same child the same way twice (representing a "choice" between two equal things) is skipped and that any equivalent nodes are deduplicated.
Skipping useless nodes with two equal children is very easy, since the node-creating function can simply return the child instead of a new node, but keeping nodes deduplicated is more interesting. In abstract terms, the typical solution is to maintain a dictionary Node -> Node, where looking up a node gives you the canonical node (or nothing, in which case a new node must be created). In haroldbot this is implemented in the node storage itself, by treating the storage arrays as a hash table with open addressing.
Nodes are then referred to by their index in the table, or by the complement of the index to represent a complement edge. The indexes are non-negative, so complement edges are always negative, making them easy to distinguish. To ensure canonicity, only the low edge of a node may be a complement edge. If a node with a complement edge as its high edge is requested, the low edge, high edge, and the index of this node when it is returned are all complemented. The "bottom" sink is represented by 0, there is no "top" sink, instead a complement edge to the "bottom" sink is used.
This representation has a side effect of making some computations with nodes trivial. Any boolean function applied on sinks can be written with the equivalent bitwise operations and it will have the same effect. More interestingly, even in some special cases that do not just involve constants, computations can be done directly on node indices without going through the slower BDD-arithmetic algorithms. So the function that computes the XOR between two BDDs starts with the lines
if (f == 0 || g == 0 || f == -1 || g == -1 || f == g || f == ~g) return f ^ g;which takes care of all base cases of the recursive function that computes the XOR of f and g.
The full process of computing the XOR (for example) of two BDDs is described well in The Art of Computer Programming Volume 4A, in chapter 7.1.4 Binary decision diagrams.
In many parts of haroldbot functions are represented as arrays of 32 BDDs. Below is an example, visualized one bit at the time. Low and high edges are indicated by dashed and solid edges respectively, normal edges and complement edges are indicated by blue and red respectively. An extra root node is visualized, it is not part of the BDD but is necessary here to indicate whether the actual root node of the BDD is entered through a complement edge or through a normal edge. To prevent the visualization from blowing up it is limited to 1000 nodes, so big BDDs are only visualized partially.
This visualization uses the vis.js library, with custom node-coordinates because the built-in layout algorithms did not seem to react well to typical BDD shapes.
BDDs can easily and efficiently be combined according to a logical operation with a recursive algorithm, though the result may have as many as n*m nodes where n and m are the number of nodes in the BDDs that were combined. The potential blow-up of nodes at every bit-operation is not always a problem, for example the addition function (as by default shown above) between two n-bit variables where n>1 needs only 3n+1 nodes.
The product of two n-bit number does suffer from the blow-up of the number of nodes, so many formulas that involve multiplication cannot be handled by the BDD part of haroldbot. Originally haroldbot would just give up on functions when it ran out of space in the pre-allocated BDD storage arrays, but it now falls back to using a SAT solver to try to handle those cases, which is often succesful.
A BDD representation of a boolean formula can be used to easily count for how many inputs it is true or false in time linear in the size of the BDD. This makes it feasible to count the number of solutions (or counter examples) even if it is very high.
The Boolean Satisfiability Problem (SAT) is perhaps the best known NP-complete problem. Nevertheless, modern Conflict-Driven Clause Learning (CDCL) solvers can solve many instances that are of practical interest. Haroldbot uses MiniSat compiled to JavaScript with Emscripten.
SAT by definition only handles boolean formulas, and solvers typically need the formula in conjunctive normal form (CNF). In order to convert formulas over 32bit integers to CNF, haroldbot first builds a boolean circuit and then converts that to CNF by working backwards from the outputs and applying the Tseytin transformation to the backwards-reachable gates. Gates can become disconnected from any output while the circuit is built up. Disconnected gates are not deallocated, instead they are ignored during the conversion to CNF.
Haroldbot prevents the creation of many trivially-equivalent gates by maintaining a fixed-size hash table of gates. Hash collisions are resolved by simply overwriting the old entry, the table does not need to be complete because it is not required for correctness, it is only used to prevent some unnecessary duplication of gates.
The types of gate used in haroldbot are the 2-input OR and XOR gates, and a 3-input "carry" gate which outputs true iff 2 or 3 inputs are true.
Similar to in the BDD, both normal edges and complement edges are used. Complement edges are simpler to handle in the conversion to CNF than explicit negation gates, because they simply correspond to using the complement of the output-variable of the referenced gate and so don't require any CNF clauses. They also create more opportunities for gate-deduplication.
Before converting to CNF, functions are represented by an array of 32 gate-references. Below is an example (visualized one bit at the time), normal edges and complement edges are indicated by blue and red edges respectively. The output (at the top) and inputs (leaf nodes) are not gates, they only exist in the visualization. As with the BDD visualization, there is a limit of 1000 nodes.
This visualization uses the vis.js library, again with custom layout. Because the circuits tend to be deeper than wide (they're not meant for hardware, so depth isn't much of a concern), edges are often drawn through nodes in ways that make them seems connected in odd ways. Nodes can be selected or dragged to make it clear how they are connected.
Automatic proof generation in haroldbot is based on a simple bidirectional exploration of the search space. The search space consists of expressions that are equal to either the left hand side of the top level equality operator or equal to the right hand side. The neighbours of a node in the search space are all the expressions that are one rewrite rule away from it.
Below is a visualization of the process, though only nodes that have been taken out of the priority queues are drawn, not all nodes that have ever been generated. It was actually meant to visualize the latter (that would more accurately reflect the process), but for interesting proofs so many nodes are generated that visualizing them is hopelessly slow.
Naturally, this is an exponential time (and space) algorithm. This is made worse by the fact that many rewrites increase the size of the expression. In haroldbot that is prevented a bit by preferentially expanding small expressions. Small expressions tend to make the proof nicer (though sometimes longer) and are more likely to go in the "right direction".
In order to rewrite and determine structural equivalences efficiently, expressions are hashed in two different ways. A local hash, which depends only on the the top level operator and its direct children, is used to select likely-applicable rewrite rules. A total hash, which depends on the entire expression, is used to detect duplicate expressions within each expression cloud and to detect a match that connects both clouds with a path (which represents a proof).
Thanks to the local hash, at most rewrite rules are tried per node in an expression, instead of all three hundred rules. Usually fewer, typically around 5. Most rules operate on a fixed top level operator and so are generally not applied to an expression node that represents a different operator, except when the hashes collide.
After the expression-steps of a proof have been found, the explanations are then generated separately. This allows more steps to have a "forward" explanation, which is often nicer than a "backwards" explanation. As part of this process, the node-ids of the expression in the explanation itself are rewritten to the ids found in the actual expression. The front-end wraps each node of an expression in a span-tag and uses the id to calculate a class-attribute which is used to highlight corresponding expressions on hover.


ValueFuture(result: T)
A naive future implementation to wrap a given result. It executes on the calling thread synchronously.
result
val future: Future<String> = ValueFuture("hello") val result: String = future.await()


your-project
Collection: your-collection
This example injects a search interface into a page.
It includes a minimal set of styles, code and config to get you up and running:
?q=set+search+using+query+param
to set the default search. Give it a try!

Take a look at the page source to start your own integration.
1. From a user filled text box
2. From a user focusing a text box or clicking a button


--- layout: content title: Resume permalink: /resume/ --- Download
|
Sai Sanjay Yepuri<PHONE_NUMBER>
|<EMAIL_ADDRESS>|
|||||||||||
|
Education |
The University of Texas at Austin – B.S. in
Computer Science |
Aug. 2017 – May
2021 |
|||||||||
|
Relevant Coursework:
|
|||||||||||
|
Experience |
Full-Stack Developer, Reveal Energy
Services, Houston, Texas |
Sept. 2016 – Sept.
2017 |
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|
Reveal Energy Services, a Statoil Spinoff, specializes
in hydraulic fracture and proppant mapping technology using their patented
ImageFrac software. ·
Implemented a
front-end web application with Angular 2 for ImageFrac. ·
Deployed an
internal Elasticsearch cluster with Docker for indexing and searching
operations data. ·
Built a hybrid
web/native search client with React.js and Electron. |
|||||||||||
|
Software Developer Intern, Sigma Cubed Inc., Houston, Texas |
Jun. 2016 – Sept.
2016 |
||||||||||
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Sigma Cubed Inc. provides microseismic services to
hydraulic fracture operators to map fractures in order to measure the output
and efficiency of wells. ·
Built a native
application for use by analysts with Electron, Angular 2, and the Polymer
Project to interface with code written in R. ·
Implemented 2D and
3D plots of fractures and report generation in R with Plot.ly and ReporteRs. |
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|
Projects |
Cloud Bricks -
Best
Cloud Database Hack & Best Software Hack Schools Out Hackathon 4 |
Aug. 2017 |
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Lightweight pluggable cloud services with a beginner
friendly UI that educates developers and young programmers. ·
Implemented a
layer of abstraction on top of Docker with Node.JS that handled the creation
and destruction of containers as well as the network configuration. |
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Compete-Engine |
Apr. 2014 |
||||||||||
|
|
A distributed application to manage computer science
competitions that enables 300+ competitors to submit their solutions for evaluation
and judging. ·
Developed with
MongoDB, Express, Node.js, RabbitMQ and Angular 2. |
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|
Knight 64 |
Aug. 2013 |
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An iOS game that challenges players to complete the
Knight’s Tour around the chess board as fast as they can. ·
Developed solely
in Objective-C using Apple’s UIKit framework. |
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Awards |
·
Lockheed Martin Code
Quest National Champion ·
Science Olympiad –
Wright Stuff National Champion ·
Trinity University
High School Programming Competition First place |
Apr. 2017 May. 2016 Apr. 2016 |
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|
·
Proficient in
Java, C#, JavaScript, and TypeScript. Familiar with R, Python, C/C++. ·
Experienced with
Docker, MongoDB, MySQL, Express, Angular 2, Node.js, Git, Shell/PowerShell
Scripting, RabbitMQ, Elasticsearch, and React. ·
Interested in
machine learning, data science, photography, astronomy, custom keyboards, and
piano |
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you can whitelist nodes that you trust, and swaps will be quicker
you can also do 0conf trades
Hollowman900014-Oct-18 01:05 AM
If you scroll down to the pirate section of our discord, you’ll see an #deleted-channel channel, if you don’t want pirate ($ARRR) I can send you the KMD equivalent @Geocold51
Alright14-Oct-18 01:05 AM
with KMD
0x0314-Oct-18 01:05 AM
how comes you want to 'hack coins' (so says your twitter) - but have to ask questions like this?
come ON
Geocold5114-Oct-18 01:06 AM
ok
Japesmith14-Oct-18 01:06 AM
If he doesn't want his pirate coins, I'll take them
Geocold5114-Oct-18 01:06 AM
@0x03 I mean, I'm not engaged in your little world on KMD.