Saleh Abdullahi

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Autism is a neuro developmental disorder affecting individuals from Childhood mostly characterized by abnormal behavior, inadequate social interaction, lack of proper communication and repetitive behaviors. Before now, Autism was classified into 3 classes (Infertile Autism, Asperger's disorder and Pervasive Developmental Disorder not otherwise specified) as in the Diagnostic of Statistical Manual of Mental Disorders 4 (DSM 4) but in the year 2013 DSM 4 was upgraded to DSM 5 making all classes be in one class namely Autism Spectrum Disorder (ASD). In this paper, we did a literature review of some Autism Diagnosis Expert Systems and Mobile applications. From our research, we found out that most system/tools have adopted the DSM 5 criteria, most tools have either used the existing assessment tools or used Augmented reality for diagnosis. And also most of the expert system is mostly designed to diagnose children very few considered adult. None of the tools or expert system can give the level of Autism based on the DSM 5 diagnosis therefore there is need for tools to be developed for making such diagnosis.

The Round Robin (RR) CPU scheduling algorithm is a fair scheduling algorithm that gives equal time quantum to all processes. The decision on how to select the time quantum is extremely important because the time quantum has a great effect on the algorithm's performance. This paper introduces an algorithm called Improved Group Based Time Quantum with Controlled Pre-emption (IGBTQ) that further improves on the Group Based Time Quantum (GBTQ) Round Robin algorithm. This algorithm (IGBTQ) is implemented and evaluated against Classical Round Robin (RR), Dynamic Round Robin with Controlled Pre-emption (DRRCP) and Group Based Time Quantum (GBTQ) Round Robin algorithms by using Gaussian and Uniform statistical distribution functions to generate the burst times of the processes. The improved algorithm (IGBTQ) is better than the other three scheduling algorithms under consideration (RR, GBTQ and DRRCP) for systems that adopt RR CPU scheduling.

CPU scheduling involves a careful examination of pending processes to determine the most efficient way to service the requests. This research works in the field of Round Robin (RR) CPU scheduling by carefully studying various popular RR scheduling algorithms to propose an option, Modified Median Round Robin Algorithm (MMRRA), to compete alongside others. A lot of research papers on dynamic RR have been published and they provide better solution to the Classical RR. Some major challenges to most of these dynamic RR scheduling are: They do not include Average Response Time (ART) as a criteria for comparison, they do not bother much on preempting processes with negligible left over of burst time which will lead to an increase on the number of context switching (NCS). Using MMRRA, variable quantum time is used to eliminate these shortcomings. A simulator program has been designed and tested against five selected algorithms, which in turns proved to perform better in most of the criteria.

Multiprogramming is an important aspect of operating systems (OS); it requires several processes to be kept simultaneously in the memory, the aim of which is maximum CPU utilization. Among other CPU scheduling algorithms, like the First Come First Serve (FCFS), Shortest Job First (SJF) and Priority Scheduling (PS); Round Robin is considered the most widely used scheduling algorithm in time sharing and real time OS for allocating the CPU to the processes in the memory in order to achieve the aim mentioned above. This paper proposed a more improvement in the Round Robin CPU scheduling algorithm by improving the algorithm by Manish and AbdulKadir. By experimental analysis, this proposed algorithm performs better than the simple Round Robin and the Improved Round Robin CPU scheduling algorithms in terms of minimizing average waiting time, average turnaround time and number of context switches.

The behaviours of most Death Row inmates in pre-prison era typically involve neurological insult, developmental histories of trauma, family disruption, and substance abuse. These behaviours lead them to commit crimes that finally land them into death row in prison. Rates of psychological disorder among death row inmates are high, where environments and conditions of confinement appear to aggravate such disorders. The last statements of Death row inmates can be deeply emotional. Several Machine Learning (ML) algorithms can be used to classify these emotions. Although simple, the Naive Bayes algorithm is a popular algorithm that has proven to be robust in text mining. In this study, the Naive Bayes and benchmark data available from the Texas Department of Criminal Justice to detect and classify emotions from the lasts statements of youth executed on death row. Friedman’s test with Bonferroni Adjustment was employed to examine whether the executed inmate’s ethnic race has an effect on t...

Once an individual employs the use of the Internet for accessing information; carrying out transactions and sharing of data on the Cloud, they are connected to diverse computers on the network. As such, security of such transmitted data is most threatened and then potentially creating privacy risks of users on the federated identity management system in the Cloud. Usually, User’s attributes or Personal Identifiable Information (PII) are needed to access Services on the Cloud from different Service Providers (SPs). Sometime these SPs may by themselves violate user’s privacy by the reuse of user’s attributes offered them for the release of services to the users without their consent and then carrying out activities that may appear malicious and then causing damage to the users. Similarly, it should be noted that sensitive user’s attributes (e.g. first name, email, address and the likes) are received in their original form by needed SPs in plaintext. As a result of these problems, user’s privacy is being violated. Since these SPs may reuse them or connive with other SPs to expose a user’s identity in the cloud environment. This research is motivated to provide a protective and novel approach that shall no longer release original user’s attributes to SPs but pseudonyms that shall prevent the SPs from violating user’s privacy through connivance to expose the user’s identity or other means. The paper introduces a conceptual framework for the proposed user’s attributes privacy protection in a federated identity management system for the cloud. On the proposed system, the use of pseudonymous technique also called Privacy Token (PT) is employed. The pseudonymous technique ensures users’ original attributes values are not sent directly to the SP but auto generated pseudo attributes values. The PT is composed of: Pseudo Attribute values, Timestamp and SP_ID. These composition of the PT makes it difficult for the User’s PII to be revealed and further preventing the SPs from being able to keep them or reuse them in the future without the user’s consent for any purpose. Another important feature of the PT is its ability to forestall collusion among several collaborating service providers. This is due to the fact that each SP receives pseudo values that have no direct link to the identity of the user. The prototype was implemented with Java programming language and its performance tested on CloudAnalyst simulation.

Technology advances by the day and computers can be considered as valuable to almost every learned person. One of the most uses of computers nowadays is for internet surfing and social networking. Computers in this context are not restricted to desktop or laptop computers only. Internet surfing and social networking has made interactions between people and computers very easy, where people can communicate using their languages thus making processing of these languages a useful task for the computers to interpret. The correct processing of these languages on the computer relies on the correct identification of parts of speech (POS) in sentences which has been an active area of research for a long time. This paper presents a review parts of speech tagging, comparison of different tagging techniques, their characteristics, difficulties, limitation, and Multilingual Parts of Speech (POS) tagging approaches.

Autism Spectrum Disorder (ASD) is neurodevelopmental condition characterized by social interaction and communication difficulties, along with narrow and repetitive behaviors and interest. Since autistic children suffers from learning disabilities and communication barriers, this research aim to survey mobile and computer applications that are developed to provide better learning environment and communication platform for autistic children. It also outline the type of techniques used for developing Applications used for children with Autism. We found out that several techniques have been implemented and tested on children living with autism and they serve the purpose for which the application was built for. Most of the applications have given Great improvements and usefulness for children living on the Spectrum. With more recent publication, there is need to update on the recent techniques for people to use.

Highest Response Ratio Next (HRRN) scheduling is a non-preemptive discipline, in which the priority of each job is dependent on its estimated run time and the amount of time it has spent waiting. Jobs gain higher priority the longer they wait, which prevents indefinite postponement (process starvation). Also, the jobs that have spent a long time waiting compete against those estimated to have short run times. HRRN prevents indefinite postponements but is neither preemptive nor suitable for priority systems. In this research, HRRN has been modified to accommodate external priority and to include preemption. Hence, a preemptive modified HRRN (PMHRRN) algorithm has been developed.

... When a reference is destroyed, however, the pointer weight must be decremented from the reference count of the cell in order to preserve the rule that sum of the weights must equal the reference ... Generational reference counting (GRC), Benjamin [1989] solves this problem. ...

A multiprogramming operating system allows more than one process to be loaded into the executable memory at a time and for the loaded process to share the CPU using time-multiplexing. Part of the reason for using multiprogramming is that the operating system itself is implemented as one or more processes, so there must be a way for the operating system and application processes to share the CPU. The assignment of physical processors to processes allows processors to accomplish work. The problem of determining when processors should be assigned and to which processes is called CPU scheduling. How do we select a CPU Scheduling algorithm for a particular system? Since we have different scheduling algorithm with its own parameter selection can be difficult. To select an algorithm we must first define the relative importance of CPU Scheduling criteria. Next we use an evaluation method. This paper presents an algorithm and a life simulation of the CPU Scheduling algorithms using exponenti...

Round Robin (RR), one of the oldest CPU scheduling algorithms has found its importance in time sharing systems. In an ideal RR an equal quantum time is allocated to each process residing in the ready queue. A process which is assigned a CPU may run to completion if and only if its quantum time is greater than its CPU burst. Otherwise, after the process exhausted its quantum time the process must be preempted to take turn in the next round. Some major challenges in classical RR are: poor response time, unnecessary context switching and poor multiprogramming. Using Half Life Variable Quantum Time Round Robin (HLVQTRR), variable quantum time is used to eliminate those challenges. All dataset used for the evaluation are generated using normal distribution function. Keywords— Round Robin (RR), turnaround time, waiting time, context switching (CS), quantum time (QT).

Round Robin (RR) CPU scheduling algorithm has been designed chiefly for time sharing systems. The RR algorithm has proven to be more useful in multiprogramming environment in which time slice or quantum is given to processes in the ready queue. An ideal classical RR uses a static quantum time which is gotten from the average of processes in the ready queue. One of the major challenges in classical RR is poor timing in performing context switching. This will eventually lead to unnecessary context switching. Using Dynamic Round Robin with Controlled Preemption (DRRCP), variable quantum time is used to eliminate this shortcoming. In an attempt to eliminate unnecessary context switching, the average waiting time, average turnaround time and number of context switching were as well improved. All dataset used for this analysis are generated using normal distribution function.

Page 1. Empirical Studies of Distributed Garbage Collection by Saleh El-Yakub ABDULLAHI A thesis submitted to the University of London in fulfilment of the requirements for the degree of Doctor of Philosophy in Computer Science Department of Computer Science ...

Internet programming languages such as Java present new challenges to garbage collection design. The spectrum of garbage-collection schema for linked structures distributed over a network are reviewed here. Distributed garbage collectors are
classified first because they evolved from single-address-space collectors. This taxonomy is used as a framework to explore distribution issues: locality of action, communication overhead and indeterministic communication latency.