Allied Program Areas and Specializations within LIS: UNT Experience

This presentation was presented as part of a panel on "The Benefits and Challenges of Allied Programs and Specializations in LIS Units" as part of the opening plenary panel at the 2018 Association for Library and Information Science Education (ALISE) Conference. This presentation discusses the rewards and challenges of Library and Information Science (LIS) programs, with a detailed overview of LIS programs offered at the University of North Texas

Assessment of anxiety and depression after lower limb amputation in Jordanian patients

Ziad M Hawamdeh1, Yasmin S Othman2, Alaa I Ibrahim31Department of Physical Therapy, Faculty of Rehabilitation Sciences, University of Jordan, Amman, Jordan; 2Department of Orthotics and Prosthetics, Faculty of Rehabilitation Sciences, University of Jordan, Amman, Jordan; 3Lecturer, Department of Physical Therapy for Pediatrics and Pediatric surgery, Faculty of Physical Therapy, Cairo University, Giza, EgyptObjective: This study aimed to assess the prevalence of anxiety and depression among Jordanian lower limb amputees with different clinical characteristics and sociodemographic data (gender, marital status, social support, income, type and level of amputation, and occupation).Methods: Participants were 56 patients with unilateral lower limb amputation with mean duration (8.4 ± 5.75 years). They were recruited from inpatient and outpatient clinics of Jordan University hospital, Royal Farah Rehabilitation Center, and Al-basheer hospital in Amman, Jordan. Participants responded to a questionnaire that included a battery of questions requesting brief information about sociodemographic variables and characteristics of amputation. The level of depression and anxiety in each participating patient was assessed by the Hospital Anxiety and Depression Scale (HADS).Results: The prevalence of anxiety and depressive symptoms were 37% and 20%, respectively. Factors associated with high prevalence of psychological symptoms included female gender, lack of social support, unemployment, traumatic amputation, shorter time since amputation, and amputation below the knee. These findings were confirmed by a significant reduction of anxiety and depression scores in patients who received social support, patients with amputation due to disease, and patients with amputation above the knee. Presence of pain and use of prosthesis had no effect on the prevalence.Conclusions: The findings of the present study highlight the high incidence of psychiatric disability and depression in amputees; it also showed the importance of sociodemographic factors in psychological adjustment to amputation. It is suggested that psychiatric evaluation and adequate rehabilitation should form a part of their overall management.Keywords: amputees, depression; anxiety, rehabilitatio

A Sociolinguistic Investigation of Two Hōrāni Features in Sūf, Jordan

This study investigates sociolinguistic variation in the traditional dialect of Sūf, a Hōrāni town in northern Jordan. Two variables are examined: (k): depalatalization of /k/; and (l): develarization of /l/, according to internal linguistic constrains and two external social factors: namely age and sex. Conditioned palatlalization of /k/ and the presence of a dark allophone of /l/ are two of the most salient phonological features of the dialects of Hōrān in general. The present study provides a quantitative analysis within the framework of Variationist Theory, using the multiple logistic regression program Rbrul. Palatalization of /k/ is treated at two levels and thus involves two variables: 1. Phonological variable (k); the pool of data for this variable includes tokens of /k/ in the stem of the word. 2. Morphophonemic variable (–ik); the pool of data includes tokens of /k/ in the feminine suffix -ik. Analysis of the data shows that the rate of palatalization in the stem is relatively low (11%), and the palatalized variant [ʧ] may be disappearing, constrained by preceding and following linguistic environments, age and gender. By contrast, the palatalized variant in the suffix shows a relatively high rate of maintenance (70%), and variation in its use in the suffix is constrained by the social variables only. With respect to (l), the study found that dark /l/ is used only in (12%), and Rbrul analysis returned preceding and following linguistic environments, and gender as constraining factors. Overall, the results show that women are more conservative with respect to the usage of both of these traditional features, thus indicating that women preserve the local way of speech more consistently. The thesis adopts a method of interpretation of the results that focuses on local issues, including the social structure of the community, space, the local mode of production and gender roles

Effect of Task-Based Learning on EFL Grade Ten Students’ Achievement in English Collocations

In this paper, we investigated the impact of task-based learning instruction on the development of English collocation skills among Grade 10 EFL students in a Jordanian secondary school. The 64 participants were divided into a control and an experimental group, with data collected during the first semester of the 2022-2023 school year. The experimental group used task-based instruction, while the control group used a traditional method. Data were collected using FL writing pre- and post-tests and analyzed using descriptive statistics, paired samples T-Test, and independent samples T-Test. The results showed that the experimental group achieved significant improvement in using FL collocations. The study recommends the use of task-based teaching techniques to enhance the achievement of Grade 10 basic secondary school students in using FL collocations

International Conference on Knowledge Management

Global warming is the term used to describe critical environmental issues and concerns. Social media such as Twitter provides a platform for people to share information, exchange ideas, and express their opinions about current and timely issues. This study utilized contextual analysis to analyze data collected from Twitter for the hashtag "global warming" during the period 2010 & 2011. Using sentiment analysis and topic modeling, the study aimed first at assessing people's perception towards global warming issues, and second study the impact of misinformation from the standpoint of social noise on people's perception of global warming during critical environmental events. The outcome of this study helps create a better understanding of the environmental issues discussed on social media. The sentiment analysis from the data analyzed so far shows that most of the tweets were based on Twitter users' personal opinions and not science. The topic modeling results suggest that Twitter users typically tweeted when a major environmental event occurred due to global warming. Topic modeling also aids in the identification of terms that is associated with social noise. The presence of social noise suggests that misinformation does exist and spreads faster

International Conference on Knowledge Management

The 17th International Conference on Knowledge Management was held in the historic city of Potsdam, Germany. Since the conference was among the first post-pandemic face to face conferences, the overall theme of the 17th edition of the ICKM conference rightly focused on “Knowledge, Uncertainty and Risks: From individual to global scale” at different levels of analysis and agency. This document highlighted one of the panels that provide an overview of the different methodologies and theories of sense-making from several of the seminal originators of sensemaking

Prevalence, types and demographic features of child labour among school children in Nigeria

BACKGROUND: To determine the prevalence, types and demographic features of child labour among school children in Nigeria. METHODS: A cross-sectional interview study of 1675 randomly selected public primary and secondary school pupils aged 5 to less than 18 years was conducted in the Sagamu Local Government Area of Ogun State, Nigeria from October 1998 to September 1999. RESULTS: The overall prevalence of child labour was 64.5%: 68.6% among primary and 50.3% among secondary school pupils. Major economic activities included street trading (43.6%), selling in kiosks and shops (25.4%) and farming (23.6%). No child was involved in bonded labour or prostitution. Girls were more often involved in labour activities than boys (66.8% versus 62.1%, p = 0.048): this difference was most obvious with street trading (p = 0.0004). Most of the children (82.2%) involved in labour activities did so on the instruction of one or both parents in order to contribute to family income. Children of parents with low socio-economic status or of poorly educated parents were significantly involved in labour activities (p = 0.01 and p = 0.001 respectively). Child labour was also significantly associated with increasing number of children in the family size (p = 0.002). A higher prevalence rate of child labour was observed among children living with parents and relations than among those living with unrelated guardians. CONCLUSION: It is concluded that smaller family size, parental education and family economic enhancement would reduce the pressure on parents to engage their children in labour activities

Automated Detection of Breast Cancer Using Artificial Neural Networks and Fuzzy Logic

Our aim was to develop a diagnostic system that could classify breast tumors as either malignant or benign to provide a faster and more reliable method for patients. In order to accomplish this, we built two systems: one is based on Artificial Neural Networks (ANN) with a resilient back propagation and the other is based on fuzzy logic. We used the dataset provided by the University of California Irvine (UCI) Machine Learning Repository: the Wisconsin Diagnostic Breast Cancer (WDBC) dataset which describes characteristics of the cell nuclei presented in the images. The dataset is composed of features computed from digitized images of a Fine Needle Aspirate (FNA) of the breast mass. The system is based on ANN and was built using a feed-forward neural network with a Resilient Back Propagation (Rprop) algorithm that used to train the network, the number of hidden layers and hidden neurons determined by performing experiments and selecting the highest architectural accuracy. In order to obtain general architecture and to identify the accuracy of this system, we used ten-folds cross validation. The second system is based on fuzzy logic, and we built a Fuzzy Inference System (FIS). The decision tree was used to define the membership functions and the rules. The experiments were performed on two types of FIS: Sugeno-type and Mamdani-type. For the system based on ANN, Feed-Forward Neural Network presented the highest accuracy at 97.6%. While for fuzzy system, Sugeno FIS showed the highest accuracy at 94.8%. Since breast tumors, both malignant and benign, share structural similarities, the process of their detection is extremely difficult and time consuming if it is to be manually classified. Laboratory analysis or biopsies of the tumor is a manual, time consuming process yet it is accurate system of prediction. It is, however, prone to human errors. Consequently, a need of creating an automated system to provide a faster and more reliable method of diagnosis and prediction for patients is rising. In this paper, we developed two kinds of artificial intelligence systems that can help physicians to classify breast cancer tumors as either malignant or benign

International Conference on Knowledge Management

The 17th International Conference on Knowledge Management was held in the historic city of Potsdam, Germany. Since the conference was among the first post-pandemic face to face conferences, the overall theme of the 17th edition of the ICKM conference rightly focused on “Knowledge, Uncertainty and Risks: From individual to global scale” at different levels of analysis and agency. This document highlighted one of the panels and the panelists argue that open access to scholarly knowledge production should be the modus operandi in the time and age we live in. Open access to knowledge is critical not just to accelerate advances in finding solutions to societal issues, but also to meet the growing expectations around higher education institutions’ social responsibilities in times of uncertainties

Revisiting the Evolving Landscape of Open Access and Scholarly Communication

Presentation at the 2018 Annual Conference of the Association for Library and Information Science Education. This presentation contains questions and topics of discussion for the panelists