SAUDI SPECIAL EDUCATION TEACHERS’ KNOWLEDGE, SKILLS, AND PROFESSIONAL DEVELOPMENT NEEDS OF ASSISTIVE TECHNOLOGY IN THE CLASSROOM

This project assesses Saudi Arabian special education teachers’ perceptions about their competencies and professional development needs on assistive technology (AT). The researcher developed an online self-administrated 27 question survey in order to evaluate special education teachers’ perceived knowledge regarding AT, as well as to investigate their needs for professional development. The survey webpage link was sent via email to 110 special education teachers at General Directorate of Education in Unaizah, Saudi Arabia. A total of 37 teachers participate in this study for a 33.6% response rate. The findings indicate that special education teachers are not confident in their ability to correctly utilize AT in a classroom. The results also show that participants are interested in receiving AT training. In addition, it indicates that special education teachers preferred face-to-face learning methods for AT training

Rancang Bangun Aplikasi Kamus Fisika Dasar Menggunakan Algoritma String Matching Brute Force

Dictionary is a kind of reference book that is composed by abzad and lists of words and their meanings. Dictionaries are needed in the world of education to figure out the word that we want to know its meaning. Dictionary of physics is composed of various terms and explanations, which, if used as an application then the search he will take a long time, because the mobile is not able to display all terms, to ease the problem of finding the word, the dictionary is designed using the algorithm string matching. String matching algorithm is an algorithm used to solve the problem of matching the text to other texts. String algorithm used is brute force algorithm

Detection of Anomalous Behavior of IoT/CPS Devices Using Their Power Signals

Embedded computing devices, in the Internet of Things (IoT) or Cyber-Physical Systems (CPS), are becoming pervasive in many domains around the world. Their wide deployment in simple applications (e.g., smart buildings, fleet management, and smart agriculture) or in more critical operations (e.g., industrial control, smart power grids, and self-driving cars) creates significant market potential ($ 4-11 trillion in annual revenue is expected by 2025). A main requirement for the success of such systems and applications is the capacity to ensure the performance of these devices. This task includes equipping them to be resilient against security threats and failures. Globally, several critical infrastructure applications have been the target of cyber attacks. These recent incidents, as well as the rich applicable literature, confirm that more research is needed to overcome such challenges. Consequently, the need for robust approaches that detect anomalous behaving devices in security and safety-critical applications has become paramount. Solving such a problem minimizes different kinds of losses (e.g., confidential data theft, financial loss, service access restriction, or even casualties). In light of the aforementioned motivation and discussion, this thesis focuses on the problem of detecting the anomalous behavior of IoT/CPS devices by considering their side-channel information. Solving such a problem is extremely important in maintaining the security and dependability of critical systems and applications. Although several side-channel based approaches are found in the literature, there are still important research gaps that need to be addressed. First, the intrusive nature of the monitoring in some of the proposed techniques results in resources overhead and requires instrumentation of the internal components of a device, which makes them impractical. It also raises a data integrity flag. Second, the lack of realistic experimental power consumption datasets that reflect the normal and anomalous behaviors of IoT and CPS devices has prevented fair and coherent comparisons with the state of the art in this domain. Finally, most of the research to date has concentrated on the accuracy of detection and not the novelty of detecting new anomalies. Such a direction relies on: (i) the availability of labeled datasets; (ii) the complexity of the extracted features; and (iii) the available compute resources. These assumptions and requirements are usually unrealistic and unrepresentative. This research aims to bridge these gaps as follows. First, this study extends the state of the art that adopts the idea of leveraging the power consumption of devices as a signal and the concept of decoupling the monitoring system and the devices to be monitored to detect and classify the "operational health'' of the devices. Second, this thesis provides and builds power consumption-based datasets that can be utilized by AI as well as security research communities to validate newly developed detection techniques. The collected datasets cover a wide range of anomalous device behavior due to the main aspects of device security (i.e., confidentiality, integrity, and availability) and partial system failures. The extensive experiments include: a wide spectrum of various emulated malware scenarios; five real malware applications taken from the well-known Drebin dataset; distributed denial of service attack (DDOS) where an IoT device is treated as: (1) a victim of a DDOS attack, and (2) the source of a DDOS attack; cryptomining malware where the resources of an IoT device are being hijacked to be used to advantage of the attacker’s wish and desire; and faulty CPU cores. This level of extensive validation has not yet been reported in any study in the literature. Third, this research presents a novel supervised technique to detect anomalous device behavior based on transforming the problem into an image classification problem. The main aim of this methodology is to improve the detection performance. In order to achieve the goals of this study, the methodology combines two powerful computer vision tools, namely Histograms of Oriented Gradients (HOG) and a Convolutional Neural Network (CNN). Such a detection technique is not only useful in this present case but can contribute to most time-series classification (TSC) problems. Finally, this thesis proposes a novel unsupervised detection technique that requires only the normal behavior of a device in the training phase. Therefore, this methodology aims at detecting new/unseen anomalous behavior. The methodology leverages the power consumption of a device and Restricted Boltzmann Machine (RBM) AutoEncoders (AE) to build a model that makes them more robust to the presence of security threats. The methodology makes use of stacked RBM AE and Principal Component Analysis (PCA) to extract feature vector based on AE's reconstruction errors. A One-Class Support Vector Machine (OC-SVM) classifier is then trained to perform the detection task. Across 18 different datasets, both of our proposed detection techniques demonstrated high detection performance with at least ~ 88% accuracy and 85% F-Score on average. The empirical results indicate the effectiveness of the proposed techniques and demonstrated improved detection performance gain of 9% - 17% over results reported in other methods

Determinants of Farmers’ Willingness to Pay for Blue Nile River Protection: The Case of Gilgel Abay River Mouth, Ethiopia

The paper examines the determinants of farmer’s willingness to pay for protection of Abay River. This study employed Contingent Valuation Method with a double bounded elicitation format followed by open ended questions. A total of 158 randomly selected households were interviewed. Descriptive statistics and Econometrics Models particularly Probit and Seemingly Unrelated Bivariate Probit models were applied. Result of the study showed annual income, education, number of dependents in the household, family size, total cultivated land, extension contact, and community bylaw were determinant variables of farmers WTP in cash. Response to the hypothetical scenario revealed that the mean WTP in cash is 74.22 ETB per year per household with an aggregate value of 171,411.09 ETB per annum (1US$=28.3birr). In addition, extension contact and age of the respondents were important variables in determining labor contribution. While the mean labor WTP for household to be 17.46 labor days per year with an aggregate benefit of 41,291 labor days per year which is equivalent to 2,477,460 ETB Birr ( daily labor payment is 60 birr/per day). This indicates that aggregate WTP in labor is greater than cash payment. Therefore, the government should engage farmers in labor during River protection. Besides, socioeconomic and institutional variables should also be considers while deign river protection. Keywords: Blue Nile River, improved river protection, Contingent valuation method, Willingness-to-Pay, Ethiopia DOI: 10.7176/CER/11-12-04 Publication date: December 31st 201

An Evaluation of Smartphone Resources Used by Web Advertisements

With the rapid advancement of mobile devices, people have become more attached to them than ever. This rapid growth combined with millions of applications (apps) make smartphones a favourite means of communication among users. In general, the available contents on smartphones, apps and the web, come into two versions: (i) free contents that are monetized via advertisements (ads), and (ii) paid ones that are monetized by user subscription fees. However, the resources (energy, bandwidth, processing power) on-board are limited, and the existence of ads in either websites or free apps can adversely impact these resources. These issues brought the need for good understanding of the mobile advertising eco-system and how such limited resources can be efficiently used. This thesis focuses on mobile web browsing. Surfing web-pages on smatphones is one of the most commonly used task among smartphone users. However, web-page complexity is increasing, especially when designed for desktop computers. On one hand, the existence of ads in web-pages is essential for publishers' monetization strategy. On the other hand, their existence in webpages leads to even higher complexity of the webpages. This complexity in the smartphone environment, where the battery and bandwidth resources are limited, is reflected in longer loading time, more energy consumed, and more bytes transferred. With this view, quantifying the energy consumption due to web ads in smartphones is essential for publishers to optimize their webpages, and for system designers to develop an energy-aware applications (browsers) and protocols. Apart from their energy impact, ads consume network bandwidth as well. Therefore, quantifying the bandwidth consumption due to downloading web ads is crucial to creating more energy and bandwidth aware applications. This thesis first classifies web content into: (i) core information, and (ii) forced ``unwanted" information, namely ads. Then, describes an approach that enables the separation of web content in a number of a websites. Having done so, the energy cost due to downloading, rendering, and displaying web ads over Wi-Fi and 3G networks is evaluated. That is, how much energy web ads contribute to the total consumed energy when a user accesses the web. Furthermore, the bandwidth consumed by web ads in a number of well-known websites is also evaluated. Motivated by our findings about ads' impact on the energy and bandwidth, the thesis proposes and implements a novel web-browsing technique that adapts the webpages delivered to smartphones, based on a smartphone's current battery level and the network type. Webpages are adapted by controlling the amount of ads to be displayed. Validation tests confirm that the system, in some cases, can extend smartphone battery life by up to ~ 30\% and save wireless bandwidth up to ~ 44\%

Global stability analysis of the disease-free equilibrium state of a mathematical model of trypanosomiasis

The global stability analysis represents a compound failure, mechanism which provides lower calculated factors of safety. In this research, the global stability analysis was used to propose a mathematically model of the transmission dynamics and control of Trypanosomiasis, known as African sleeping sickness. We obtained the Disease-free equilibrium state and present graphical profile of some of the compartments.Keywords: Equilibrium state, trypanosome, sleeping sickness, stabilit

RANCANG BANGUN APLIKASI KAMUS FISIKA DASAR MENGGUNAKAN ALGORITMA STRING MATCHING BRUTE FORCE

Dictionary is a kind of reference book that is composed by abzad and lists of words and their meanings. Dictionaries are needed in the world of education to figure out the word that we want to know its meaning. Dictionary of physics is composed of various terms and explanations, which, if used as an application then the search he will take a long time, because the mobile is not able to display all terms, to ease the problem of finding the word, the dictionary is designed using the algorithm string matching. String matching algorithm is an algorithm used to solve the problem of matching the text to other texts. String algorithm used is brute force algorithm

Adverse drug reactions caused by methotrexate in Saudi population

AbstractAimThe aim of this study is to document adverse drug reactions (ARDs) of methotrexate (MTX) in Saudi patients.MethodsCross sectional study of adult patients on MTX, attending rheumatology drug monitoring clinics in a university hospital, over a period of 24weeks. Adverse drug reactions were sought by patient interview, files review and laboratory abnormalities.ResultsData collected included patients’ demographics, diagnoses, co-morbidities, MTX dose and duration, other medications, laboratory abnormalities and adverse reactions, their severity, preventability, and outcome. Out of a total of 593 patients screened, 186 (31.4%) using MTX were interviewed. Most of the patients were female (88.5%). Adverse drug reactions (ADRs) were detected in 61 patients (32.8%). Patients with ADRs took a mean dose of 12.9mg (2.5–22.5mg). Ten ADRs (16.4% of total reactions) were preventable; they ranged between severe, moderate and mild. The most common ADRs were gastrointestinal (GI) (52.5%), followed by anemia (8.2%) and chest tightness (6.6%). The duration of the reaction ranged from few hours to 4years.ConclusionIn conclusion our patients with adverse reactions were younger, took less medications and had less co-morbidities. Our results were different from those published in the literature relating MTX toxicity

THE INFLUENCE OF THE APPLICATION OF DIFFERENT PLANT AQUEOUS EXTRACTS ON GRAIN AND PROTEIN YIELD IN SOYBEAN PRODUCTION

The aim of this study was to investigate the influence of aqueous extracts of different plant species on the grain and protein yield of soybean. The testing was conducted at the Institute of Field and Vegetable Crops in Novi Sad on the seeds of the NS Apolo variety. The aqueous extracts of the above-ground part of nettle, the above-ground part of nettle and comfrey, whole banana fruit, banana peel, onion bulbs leaves, the top parts of willow twigs and the top parts of soybean plants were foliarly applied. In addition to the untreated control variant, the experiment also included a distilled water control. Control with distilled water was to show whether the effect of aqueous plant extracts was due to plant material or just water. The results of the experiment showed that the use of aqueous extracts contributed to the increase in grain and protein yield. The increase in grain yield ranged from 9.48% to 15.34%, and the increase in protein yield from 9.31% to 16.16%. The best effect was achieved by applying the aqueous extract of the whole banana fruit and the aqueous extract of the mix of nettle and comfrey. By applying them each year, a significantly higher yield was achieved in relation to the control with distilled water

Bacteriological Investigation of Sudanese Beef

Animals of every kind are in continual contact with microorganisms.  Bacteria occur most abundantly in habitats where they find food, bacterial contamination affects human health,  and the study will cater for investigation of other meat contaminants in cattle meat. This study is undertaken to fill the gap in this area.  Three  hundred and twenty four bacterial isolates belonging to twenty seven bacterial genera were recovered from 460 specimens from meat samples and rectal swaps from apparently healthy carcasses from two slaughter houses; Ghanawa- Khartoum (beef brought from all over the country) and West Al Gash (Kassala),that for microbial examination .  Bacteria were isolated in the period from March, 2011 to June, 2013 involving four seasons.  Isolation of bacteria was performed by conventional microbiological methods and identified according to the cultural and biochemical tests.  Cambylobacters isolated in accordance with ISO 2006 method and particular attention was made to provide microaerophillic conditions at 42?C.   Statistical analysis of the obtained results showed a significant difference with respect to the seasons for the isolates but no significant difference was indicated among the different types of the carcasses parts from which the specimens were taken.   This study explained a high level of bacterial contamination of beef carcasses without identification of the source of contamination. The least encountered isolates were Clostridium spp.  and Streptobacillus spp. with prevailed at   (00.74%). Although cambylobacters demonstrated a prevalence of 13.33.% in Summer, 2012 nevertheless, their presence of great concern as a zoonotic pathogen.  Arcobacter cryaerophilus was isolated with a low prevalence however, it`s isolation is of great significance as this species is recently recognized as an emerging pathogen.The study recommend that, highly strict measures should be applied to curtail the contamination levels or to lessen it to the minimum, development of methodologies to appropriate management by application of Hazard Analysis Critical Control Point system, and national survey for the identification of meat contaminants should be adopted and executed using both microbilogical culturing methods and molecular biology methods