THE EFFECTIVENESS OF USING COMMUNICATIVE LANGUAGE TEACHING APPROACH (CLT) IN DEVELOPING STUDENTS’ SPEAKING SKILLS FROM TEACHERS’ PERCEPTIONS

The current study mainly aims at investigating the effectiveness of using Communicative Language Teaching (CLT) approach in developing students’ speaking skills at Sudanese secondary school levels from English language teachers’ perceptions. Also, the study seeks to find out the problems that hinder the teachers’ from implementing the CLT approach. To meet these aims and objectives the researcher employed a quantitative approach using a descriptive design. The researcher used the survey to collect data from the participants of the study. The random sampling technique was applied to select the sample out of all English language teachers at Omdurman Locality. Therefore, (100) female and male teachers have participated in this study. The information gained from the surveys was analyzed using the software Statistical Package for Social Sciences (SPSS). The study revealed the following findings: First of all, the majority of participants strongly agree that there is a positive relationship between teachers’ attitudes and effective usage of the communicative approach. The mains statements that gathered the highest level of response are: I think using CLT in my classroom helps my whole teaching process and using CLT in my class helps me share ideas and opinions with my learners. This means that most of the study participants assured that the use of CLT in the classrooms helped them to share the knowledge and facilitated their teaching process. Secondly, the majority of participants agree that there are effective factors that hinder teachers from using communicative approach to develop students speaking skills. The main statements which gathered their highest level of response are the following: Lack of authentic materials hinder the use of CLA in my and classroom size makes using CLT in my classroom more difficult. This clearly shows that the most effective factors that hinder teachers from implementing CLT in their classes are lacking of authentic material and classroom size. Finally, the majority of participants strongly agree that the communicative approach to develop students speaking skills – in general, and the main statements which gathered their highest level of response: Using CLA enhances students speaking skills, and I think using CLT motivates my student to speak accurately inside and outside the classroom. This result indicates that their participants of the study confirmed that using CLT in classroom enhanced their students speaking skill and motivated them to speak fluently.  Article visualizations

Equitable proof-of-work mining rewards

We present Reward-All Nakamoto-Consensus (Reward-All), a Proof-of-Work cryptocurrency that rewards each miner with a number of coins that is directly proportional to its individual mining power, rather than in proportion to its relative share of the entire network’s mining power as done in Bitcoin. Unlike their Bitcoin counterparts, miners in Reward-All do not have to win the leader-election process to earn coins, and only lose earned coins after block reorganizations of a configurable minimum length occur. We present a detailed specification of Reward-All, along with a prototype implementation, and an evaluation of its practicality and efficiency. Additionally, we provide an analysis of the security of Reward-All, where mining is modeled as a Markov Decision Process, and the advantages of optimal mining strategies are quantified. Under reasonable configurations, Reward-All achieves near-perfect incentive compatibility, and near-zero censorship susceptibility, for adversarial mining shares up to 45%, while retaining the same chain quality as Bitcoin’s Nakamoto Consensus (Nakamoto). However, Reward-All pays for these advantages with a regression in subversion gain resilience compared to Nakamoto. Furthermore, under Reward-All’s approach, the growth rate of the total coin supply correlates closely with the growth rate of mining power invested in the network. This enables miners to mint coins at a stable hash-based cost of production, and enables all rewarded coins to correspond to an approximately equal number of hashing attempts on average. Consequently, depending on the network transaction-fees, Reward-All improves miners’ waiting times for rewards, and incentivizes forming mining pools smaller than required in Bitcoin for an equal level of reward stability. Moreover, rewards in Reward-All exhibit significantly lower variance for non-majority miners compared to Nakamoto, enabling unprecedented reward stability.Open Acces

Eye Abnormalities in Fetal Alcohol Syndrome

Fetal alcohol syndrome (FAS) – a condition caused by chronic maternal alcohol consumption during pregnancy1 – is important both in terms of its prevalence and its effects: it is estimated to be the commonest non-inherited cause of learning disability1. Diagnosis is based on the presence of characteristic facial dysmorphism, postnatal growth retardation and functional or structural central nervous system deficits1. In this review, however, we propose that the eye is a sensitive and reliable marker of teratogenesis and provides a useful adjunct to the diagnosis of FAS, with eye abnormalities having been shown to occur in over 90 % of children with the condition2. It is our objective, then, to describe the effects of prenatal alcohol exposure on the eye, quantify their incidence and comment on their importance in diagnosis of children with FAS

Phonocardiogram-based diagnosis using machine learning : parametric estimation with multivariant classification

The heart sound signal, Phonocardiogram (PCG) is difficult to interpret even for experienced cardiologists. Interpretation are very subjective depending on the hearing ability of the physician. mHealth has been the adopted approach towards quick diagnosis using mobile devices. However, it has been challenging due to the required high quality of data, high computation load, and high-power consumption. The aim of this paper is to diagnose the heart condition based on Phonocardiogram analysis using Machine Learning techniques assuming limited processing power to be encapsulated later in a mobile device. The cardiovascular system is modelled in a transfer function to provide PCG signal recording as it would be recorded at the wrist. The signal is, then, decomposed using filter bank and the analysed using discriminant function. The results showed that PCG with a 19 dB Signal-to-Noise-Ratio can lead to 97.33% successful diagnosis.fi=vertaisarvioitu|en=peerReviewed

A Study on the Effects of Staff Development on Teachers’ Satisfaction and Perceptions of Change in Teaching Performance

Staff development is vital to the success of any academic institution as it ensures that staff maintains and enhances their skills and knowledge that can be used to improve quality and performance in their job role.  Therefore, assessing the satisfaction of staff towards staff development activities is becoming increasingly important to its success. This paper aims to focus on the reasons why academic staff attends staff development workshops/sessions, to determine their satisfaction levels towards staff development and whether participation in such activities enhances their perceptions of their teaching practices and how effective they are as a teacher. Data was gathered through a questionnaire survey. The results indicated that the two main reasons for attending staff development are to ‘gain knowledge and skills’ and for ‘personal development’. However, the two external factors that constrained them from attending all the workshops/sessions were ‘time conflict’ and ‘administrative workload’. A significant positive relationship between satisfaction with staff development and enhancing staff’s effectiveness as a teacher, teaching practices and applying the knowledge and techniques acquired in their lectures and classes was also found. Keywords: staff development, satisfaction, perceptions, performance, higher educatio

Machine learning and wearable devices for Phonocardiogram-based diagnosis

The heart sound signal, Phonocardiogram (PCG) is difficult to interpret even for experienced cardiologists. Interpretation are very subjective depending on the hearing ability of the physician. mHealth has been the adopted approach towards simplifying that and getting quick diagnosis using mobil devices. However, it has been challenging due to the required high quality of data, high computation load, and high-power consumption. The aim of this paper is to diagnose the heart condition based on Phonocardiogram analysis using Machine Learning techniques assuming limited processing power to be encapsulated later in a wearable device. The cardiovascular system is modelled in a transfer function to provide PCG signal recording as it would be recorded at the wrist. The signal is, then, decomposed using filter bank and the analysed using discriminant function. The results showed that PCG with a 19 dB Signal-to-Noise-Ratio can lead to 97.33% successful diagnosis. The same decomposed signal is then analysed using pattern recognition neural network, and the classification was 100% successful with 83.3% trust level.© CS & IT-CSCP 2019fi=vertaisarvioitu|en=peerReviewed

Performance of Different Tomato Genotypes in the Arid Tropics of Sudan during the Summer Season. II. Generative Development

Eleven tomato genotypes of diverse origin were grown in Shambat, University of Khartoum, Sudan, in a randomized block design with three replications for two successive seasons (2002/2003, 2003/2004). The same genotypes were firstly evaluated under glasshouse conditions at the Humboldt University of Berlin, Germany during 2002. Highly significant differences were encountered among the different genotypes for most of the generative characters, such as number of days to flowering, number of flowers per plant, number of fruits per plant, fruit fresh weight per plant and fruit set percentage. Based on results obtained from this study, the genotype ‘Summerset’ proved to be high yielding under high temperature conditions in comparison to other genotypes

Diagnostic value of Autoantibodies to GAD65 and IA-2 in Patients with Latent Autoimmune Diabetes in Adult (LADA)

Background: Latent autoimmune diabetes in adults (LADA) accounts for11 % of all cases of diabetes and often misdiagnosed as type 2diabetes. LADA resembles type 1diabetes and shares common physiological characteristics of type 1 but it does not affect children and has beenclassified distinctly as being separate from juvenile diabetes.  Autoantibodies against glutamic acid decarboxylase 65 (GADA) and tyrosine phosphatase (IA-2) are found frequently in patients withLADA. The presence of these autoantibodies in LADA predicts inevitable M cell failure and poor response to oral hypoglycemic therapy i.e., patients with LADA do not respond to oral hypoglycemic therapy.Objective: To determine an immunological marker to diagnose patients not responding to oral hypoglycemic therapy.Patients and methods: A facility-based cross sectional study was  conducted in Jabbir Abu Eliz Diabetes Center, located at Khartoum 2. Venous blood samples were obtained from the study patients. They were divided into three groups, group1 included 27 diabetic patients treated withinsulin, group2 included 15 diabetic patients of type 2 diabetes as controls, and group3 included 15 newly diagnosed patients older than 35 years at onset of diabetes. A standardized pre-tested administered questionnaire was used for data collection and the collected data were analyzed.Results: Males encountered in the study were 28 (49.1%). On patient recently diagnosed to have type 2 diabetes mellitus (T2DM) was positive for autoantibodies to GDA/IA-2. These autoantibodies were also positive in 15 patients with diabetes mellitus type 1 (T1DM)Conclusions: Autoimmune diagnostics is of particular importance in adults to discriminate between type 1 and type 2 diabetes and to assess the diagnosis of latent autoimmune diabetes in adults. The current study results revealed that autoantibodies to GAD/IA-2 are good marker for diagnosis of latent onset DM type 1. On the other hand, data indicate that the vast majority of cases of type 1 diabetes may be considered as immune-mediated, that multiple autoantibody to GAD/IA-2 analysisare of prognostic value to predict complications e.g., retinopathy. The current study recommends using of anti-GAD/IA-2 antibodies as marker for diagnosis of latent autoimmune diabetes in adults (LADA) who are not responding to oral hypoglycemic and may be at risk for getting complications. On the other hand, the study recommends using of anti-GAD/IA-2 antibodies for prognosis of the clinical progression of diabetes type 1 for prediction of insulin dependence

Preoperative paracetamol infusion reduces sevoflurane consumption during thyroidectomy under general anesthesia with spectral entropy monitoring

AbstractBackgroundIntravenous (IV) paracetamol has a significant opioid-sparing effect. We investigated the effect of paracetamol infusion on sevoflurane consumption during entropy monitored general anesthesia.MethodsSixty-two ASA I and II patients undergoing thyroidectomy under general anesthesia were included in a prospective, randomized, double-blind and placebo controlled study. The patients were randomized to receive a slow infusion of either 1g paracetamol (paracetamol group, n=31) or saline (control group, n=31) just before induction of anesthesia. Sevoflurane concentration was titrated to keep the state entropy value between 40 and 50. End-tidal sevoflurane concentration, sevoflurane consumption, recovery characteristics, time to first analgesic request and meperidine consumption during the first 6 postoperative hours were recorded.ResultsThe mean±SD estimated sevoflurane consumption was significantly lower in the paracetamol treated patients (36.2±15 vs 44.9±13.9ml, in the control group; p=0.021). Patients receiving paracetamol had a faster post-anesthetic recovery profile (extubation time, time to eye opening to command and time to state name and mention his/her home address) than the other group (p<0.05). Mean±SD time to first analgesic request was significantly prolonged in paracetamol group compared to control group (48.4±14.0 vs 40.7±11.5min, respectively; p=0.021). Meperidine consumption was higher in control group than in paracetamol group (28.7±10.2 vs 23.1±9.0mg, respectively; p=0.025).ConclusionPreoperative IV paracetamol infusion improved consumption and emergence from entropy monitored sevoflurane anesthesia with enhancement of the early postoperative analgesia