Pengembangan Multimedia E-Book 3D Berbasis Mobile Learning untuk Mata Pelajaran Geografi SMA Guna Mendukung Pembelajaran Jarak Jauh

Multimedia E-Book 3D berbasis Mobile Learningdi kembangkan karena dapat membantu penyampaian materi lebih mudah, lebih menarik untuk belajar secara mandiri, serta tidak terbatas dalam ruang dan waktu. Tujuan penelitian ini adalah memberi informasi dan referensi bagi guru. Model Pengembangan yang digunakan yaitu model ADDIE. Pengujian tingkat kesesuaian antara konten aplikasi dengan ekspektasi pengguna dilakukan melalui uji coba ahli media, materi, dan kelompok pengguna. Hasil akhir penelitian ini adalah aplikasi multimedia E-book 3D yang dapat di aplikasikan di dekstop dan smartphone (Mobile Learning). Teknik pengumpulan data dilakukan dengan observasi, wawancara, dan angket. Instrumen penelitian berupa panduan observasi dan wawancara untuk analisis kebutuhan, sedangkan untuk uji produk digunakan kuesioner. Berdasarkan hasil pengembangan produk ini diperoleh hasil uji kelayakan ahli media, ahli materi, dan siswa. Hasil uji coba menunjukkan hasil yang baik, yaitu  kategori layak sampai sangat layak dengan rincian: (1) uji ahli materi mendapat modus skor 4 dengan persentase 60% sangat layak untuk aspek pembelajaran dan modus skor 4 sangat layak dengan persentase 75%, (2) uji ahli media mendapatkan hasil dari modus skor 4 sangat layak dengan persentase 64,71%, (3) uji oleh siswa memperoleh hasil kategori layak dengan modus 3 dan persentase 58,49% untuk kelayakan media. Berdasarkan hasil uji kelayakan maka produk multimedia layak untuk digunakan sebagai media pembelajaran mata pelajaran geografi di SMA

Empirical analysis of rough set categorical clustering techniques based on rough purity and value set

Clustering a set of objects into homogeneous groups is a fundamental operation in data mining. Recently, attention has been put on categorical data clustering, where data objects are made up of non-numerical attributes. The implementation of several existing categorical clustering techniques is challenging as some are unable to handle uncertainty and others have stability issues. In the process of dealing with categorical data and handling uncertainty, the rough set theory has become well-established mechanism in a wide variety of applications including databases. The recent techniques such as Information-Theoretic Dependency Roughness (ITDR), Maximum Dependency Attribute (MDA) and Maximum Significance Attribute (MSA) outperformed their predecessor approaches like Bi-Clustering (BC), Total Roughness (TR), Min-Min Roughness (MMR), and standard-deviation roughness (SDR). This work explores the limitations and issues of ITDR, MDA and MSA techniques on data sets where these techniques fails to select or faces difficulty in selecting their best clustering attribute. Accordingly, two alternative techniques named Rough Purity Approach (RPA) and Maximum Value Attribute (MVA) are proposed. The novelty of both proposed approaches is that, the RPA presents a new uncertainty definition based on purity of rough relational data base whereas, the MVA unlike other rough set theory techniques uses the domain knowledge such as value set combined with number of clusters (NoC). To show the significance, mathematical and theoretical basis for proposed approaches, several propositions are illustrated. Moreover, the recent rough categorical techniques like MDA, MSA, ITDR and classical clustering technique like simple K-mean are used for comparison and the results are presented in tabular and graphical forms. For experiments, data sets from previously utilized research cases, a real supply base management (SBM) data set and UCI repository are utilized. The results reveal significant improvement by proposed techniques for categorical clustering in terms of purity (21%), entropy (9%), accuracy (16%), rough accuracy (11%), iterations (99%) and time (93%). vi

The Reliability of Red Flags in Spinal Cord Compression

Background: Acute low back pain is a common cause for presentation to the emergency department (ED). Since benign etiologies account for 95% of cases, red flags are used to identify sinister causes that require prompt management. Objectives: We assessed the effectiveness of red flag signs used in the ED to identify spinal cord and cauda equine compression. Patients and Methods: It was a retrospective cohort study of 206 patients with acute back pain admitted from the ED. The presence or absence of the red flag symptoms was assessed against evidence of spinal cord or cauda equina compression on magnetic resonance imaging (MRI). Results: Overall, 32 (15.5%) patients had compression on MRI. Profound lower limb neurologic examination did not demonstrate a statistically significant association with this finding. The likelihood ratio (LR) for bowel and bladder dysfunction (sensitivity of 0.65 and specificity of 0.73) was 2.45. Saddle sensory disturbance (sensitivity of 0.27 and specificity of 0.87) had a LR of 2.11. When both symptoms were taken together (sensitivity of 0.27 and specificity of 0.92), they gave a LR of 3.46. Conclusions: The predictive value of the two statistically significant red flags only marginally raises the clinical suspicion of spinal cord or cauda equina compression. Effective risk stratification of patients presenting to the ED with acute back pain is crucial; however, this study did not support the use of these red flags in their current form

Study of one class boundary method classifiers for application in a video-based fall detection system

In this paper, we introduce a video-based robust fall detection system for monitoring an elderly person in a smart room environment. Video features, namely the centroid and orientation of a voxel person, are extracted. The boundary method, which is an example one class classification technique, is then used to determine whether the incoming features lie in the ‘fall region’ of the feature space, and thereby effectively distinguishing a fall from other activities, such as walking, sitting, standing, crouching or lying. Four different types of boundary methods, k-center, k-th nearest neighbor, one class support vector machine and single class minimax probability machine are assessed on representative test datasets. The comparison is made on the following three aspects: 1). True positive rate, false positive rate and geometric means in detection 2). Robustness to noise in the training dataset 3). The computational time for the test phase. From the comparison results, we show that the single class minimax probability machine achieves the best overall performance. By applying one class classification techniques with 3-d features, we can obtain a more efficient fall detection system with acceptable performance, as shown in the experimental part; besides, it can avoid the drawbacks of other traditional fall detection methods

Assessing and Optimizing University Students\u27 Academic Performance via Control Charts and A Hat Relationship

تُطبّق هذه الدراسة تقنيات ضبط الجودة الإحصائية (SPC)، مثل خرائط المراقبة ومؤشرات كفاءة العمليات، لتقييم وتحسين الأداء الأكاديمي لطلاب جامعة إب الذين درّسهم الباحث خلال الأعوام 2017 إلى 2020 في ثلاث مقررات تأسيسية: نظرية الاحتمالات، البرمجة الخطية، والإحصاء الرياضي. وباعتبار التعليم عملية قابلة للقياس، أظهرت التحليلات استقرارًا عامًا في الأداء، حيث بقيت خرائط المراقبة ضمن الحدود المقبولة، باستثناء عام واحد تم فيه التدريس باللغة الإنجليزية بدلاً من اللغة الأم، مما أدى إلى ارتفاع معدلات الرسوب. وبعد تصحيح هذا الخلل اللغوي، تحقق تحسّن ملحوظ في النتائج. أشار مؤشر كفاءة العملية (Cpk = 1.333) إلى أداء جيد مع وجود مجال للتحسين. كما كشفت الدراسة عن نمط غير خطي يُعرف بـ"علاقة القبعة"، يوضح أن النجاح في مقرر الإحصاء الرياضي يعتمد بدرجة كبيرة على الأداء في المقررات التأسيسية السابقة. وتؤكد النتائج أهمية تعزيز التعليم في المراحل التأسيسية لضمان النجاح في المقررات المتقدمة. وتوصي الدراسة بتكييف المؤشرات الصناعية مثل Cpk لتتناسب مع البيئات التعليمية، وتدعو إلى استخدام خرائط المراقبة كأدوات فعالة لمتابعة وتحسين العملية التعليمية استنادًا إلى بيانات موضوعية.This study applies Statistical Process Control (SPC) techniques control charts and process capability indices to evaluate and enhance the academic performance of Ibb University students taught by the researcher from 2017 to 2020 in three foundation courses: Probability Theory, Linear Programming, and Mathematical Statistics. Treating education as a measurable process, the analysis revealed general process stability, with all control charts within limits except for one year when instruction was in English instead of the native language, leading to a spike in failure rates. Once the language issue was addressed, performance improved significantly. The process capability index (Cpk = 1.333) reflects good performance with room for improvement. A nonlinear pattern, termed the "Hat Relationship," shows that success in Mathematical Statistics depends strongly on prior performance in the prerequisite courses. The results underscore the importance of reinforcing foundation-level education to ensure success in advanced subjects. The study recommends adapting industrial metrics like Cpk for educational settings and promotes the use of control charts as practical tools for monitoring and improving the learning process, thereby supporting data-driven decision-making in teaching and curriculum design

Health-related quality of life as measured with EQ-5D among populations with and without specific chronic conditions: A population-based survey in Shaanxi province, China

© 2013 Tan et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.Introduction: The aim of this study was to examine health-related quality of life (HRQoL) as measured by EQ-5D and to investigate the influence of chronic conditions and other risk factors on HRQoL based on a distributed sample located in Shaanxi Province, China. Methods: A multi-stage stratified cluster sampling method was performed to select subjects. EQ-5D was employed to measure the HRQoL. The likelihood that individuals with selected chronic diseases would report any problem in the EQ-5D dimensions was calculated and tested relative to that of each of the two reference groups. Multivariable linear regression models were used to investigate factors associated with EQ VAS. Results: The most frequently reported problems involved pain/discomfort (8.8%) and anxiety/depression (7.6%). Nearly half of the respondents who reported problems in any of the five dimensions were chronic patients. Higher EQ VAS scores were associated with the male gender, higher level of education, employment, younger age, an urban area of residence, access to free medical service and higher levels of physical activity. Except for anemia, all the selected chronic diseases were indicative of a negative EQ VAS score. The three leading risk factors were cerebrovascular disease, cancer and mental disease. Increases in age, number of chronic conditions and frequency of physical activity were found to have a gradient effect. Conclusion: The results of the present work add to the volume of knowledge regarding population health status in this area, apart from the known health status using mortality and morbidity data. Medical, policy, social and individual attention should be given to the management of chronic diseases and improvement of HRQoL. Longitudinal studies must be performed to monitor changes in HRQoL and to permit evaluation of the outcomes of chronic disease intervention programs. © 2013 Tan et al.National Nature Science Foundation (No. 8107239

Influence of Laser Irradiation Times on Properties of Porous Silicon

Porous silicon (P-Si) has been produced in this work by photoelectrochemical (PEC) etching process. The irradiation has been achieved using diode laser of (2 W) power and 810 nm wavelength. The influence of various irradiation times on the properties of P-Si material such as P-Si layer thickness, surface aspect, pore diameter and the thickness of walls between pores as well as porosity and etching rate was investigated by depending on the scanning electron micrograph (SEM) technique and gravimetric measurements