Strayer University

This paper introduces the Republic Of Korea Imaging Test System (ROKITS) onboard the Compact Advanced Satellite 500-3 and outlines its science objectives. ROKITS is an imaging camera designed to observe Earth's auroras and airglow in the visible wavelength range. With a 90° field of view, it can capture auroral structures, which are most prominent in the polar regions, with an image swath of approximately 700 km. The primary science objective of ROKITS is to identify the auroral oval boundary from auroral images. A secondary objective is to demonstrate the capability of extracting atmospheric waves and ionospheric disturbances from airglow emissions at wavelength of 557.7 nm and 630.0 nm. To this end, we analyze observational data from Enhanced Polar Outflow Probe/Fast Auroral Imager (e-POP/FAI) onboard the CAScade, Smallsat and Ionospheric Polar Explorer (CASSIOPE) satellite, Special Sensor Ultraviolet Spectrograph Imager (SSUSI) onboard the Defense Meteorological Satellite Program (DMSP) satellite, Ionosphere, Mesosphere, Upper Atmosphere And Plasmasphere/Visible And Near-Infrared Spectral Imager (IMAP/VISI) and Atmospheric Waves Experiment (AWE) aboard the International Space Station. The analysis focuses on the ionospheric and upper atmospheric phenomena that ROKITS aims to observe and assesses the potential applications of ROKITS data. Based on these results, we anticipate ROKITS will enhance our understanding of the ionosphere and upper atmosphere and provide valuable data set for space weather prediction.

In the European range of the critically endangered European hamster Cricetus cricetus , both in situ and ex situ conservation programmes are in place to breed these animals and to release captive-bred individuals into natural populations to enhance for their demographic and genetic diversity. The study analysed the behaviour of individuals following their release into the wild, as well as the importance of sex, age and origin for the frequency of behaviours crucial for survival in the wild. The hypothesis was also formulated that the timing of leaving the aviary was independent of an individual’s age, sex and origin. In 2020–2021, 115 hamsters were released into acclimatization aviaries and their behaviour was observed. Thirty-four behavioural categories were distinguished with the most frequent being vigilance (42 %) and exploration (30 %). Hamsters also exhibited behaviours characteristic of captive-raised animals (14 %). Differences in vigilance were found between individuals of different origins. More of these behaviours were exhibited by hamsters with at least one wild parent compared to those whose both parents from a captive background. The time taken to leave the aviary was not dependent on either the age or the sex. However, a highly significant relationship was found between the hamsters' origin and the time when they left the aviary. Juvenile females and males born of captive-born parents were the fastest to leave the aviary. Juvenile females of mixed parentage, adult males born of captive-born parents and adult males caught in the wild took the longest time to leave the reintroduction site. The data obtained are crucial for the conservation of this endangered species.

In the post-pandemic digital economy, customer-centricity has evolved from a marketing ideal into a strategic necessity. As organizations confront shifting consumer expectations, intensified competition, and rapid technological advancement, the ability to align culture, processes, and technology around customer value has become the defining factor of sustainable growth. This paper examines the convergence of customer-centric strategy, hyper-personalization, and new digital business models between 2023 and 2025. Drawing on academic research and industry evidence, it argues that artificial intelligence (AI), data analytics, and automation are not merely tools for efficiency but foundational enablers of intelligent, predictive, and emotionally resonant engagement. Through theoretical lenses such as the Resource-Based View, Dynamic Capabilities Theory, and Service-Dominant Logic, the study shows how data-driven insights and adaptive capabilities create lasting competitive advantage. It further explores emerging digital business models including subscriptions, platforms, and product-as-a-service that leverage personalization to enhance customer lifetime value (CLV). Ethical governance, data privacy, and responsible AI design are identified as critical prerequisites for trust and long-term differentiation. The paper concludes by proposing a six-dimensional strategic framework: Customer Insight, Culture, Capabilities, Channels, Continuous Learning, and Conscience, that operationalizes customer-centric transformation. Ultimately, the research demonstrates that organizations capable of integrating technological intelligence with human empathy will define the next decade of business leadership, where profitability is inseparable from purpose, trust, and personalized value creation.

هدفت الدراسة الحالية إلي التوصل إلي قائمة معايير مقترح لمنصة رقمية تقوم بالتحليل (الوصفي - التشخيصي- التنبوئ - التوجيهي) لأداءات المتعلم الأكاديمية وأداءات المعلم التدريسية لتصنيف المؤسسات التعليمية في ضوء رؤية مصر 2030 علي المستوي الزمني (الحصة الدراسية- اليوم الدراسي - الفصل الدراسي - العام الدراسي) وتقديمه لعناصر المنظومة التعليمية للسياسات العامة وشركاء المنظومة التعليمية، ولتحقيق ذلك تناولت الدراسة بناء الصورة الأولية لقائمة معايير منصة رقمية لتصنيف المؤسسات التعليمية في ضوء رؤية مصر2030، وباستخدام المنهج الوصفي التحليلي والمنظومي ، ثم استخدام أسلوب دلفي الاحصائي للتوصل إلي الصورة النهائية لقائمة المعايير بعد العرض علي الخبراء في جولة أولية لقياس الصدق الظاهري وقياس معامل الثبات، وجولتين أخرتين لتحديد مستوي الموافقة لدي الخبراء عن النماذج المقترحة الذي وصل إلي نسبة مئوية في الجولة الأخيرة علي الترتيب (93.72%)، وفي ضوء ذلك قدم الباحث مجموعة من التوصيات والمقترحات بضرورة تبني قائمة المعايير في بناء منصة رقمية لتصنيف مؤسسات التعليم في مصر في ضوء رؤية مصر 2030.

Bu çalışma sportif faaliyetlerde İslam dininin etkisine ilişkin sporcu görüşlerinin incelenmesi amacını taşımaktadır. Çalışma betimsel tarama modeli kapsamında yürütülmüştür. Tarama araştırma modeli bir konuyla veya olayla ilişkili katılımcıların beceri, ilgi, yetenek, tutum ve görüşlerinin belirlendiği bir araştırma çeşidi olarak adlandırılmaktadır. Çalışmanın evreninin amatör ve profesyonel sporcular oluşturmakta olup, örneklem grubu ise 245 sporcu kapsamındadır. Veri toplama sürecinde Taş ve ark., (2020) tarafından geliştirilen Sportif Faaliyetlerde İslam Dini Etki Ölçeği (SFİDEÖ) kullanılmıştır. Katılımcıların ölçek maddelerine verdiği cevaplardan elde edilen toplam puanların kişisel bilgi formundaki değişkenlere göre normal dağılım gösterip göstermediği Kolmogorov-Smirnov ve Shapiro-Wilk testi ile belirlenmiştir. Çalışmada, ölçek toplam puanların ve alt boyut toplam puanlarının cinsiyet, branş vb. değişkenlere göre farklılık gösterip göstermediği Student testi ile; eğitim durumu, gelir düzeyi, dindarlık boyutu vb. gibi değişkenlere göre farklılık gösterip göstermediği ise Tek Yönlü Varyans Analizi (One-way ANOVA) ve Tukey çoklu karşılaştırma testi ile belirlenmiştir. Araştırmada, katılımcıların yaşı ve spor yaşı ile Sportif Faaliyetlerde İslam Dini Etki ölçeği ortalama puanları ve alt boyut ortalama puanları arasında anlamlı bir ilişki tespit edilememiştir. Aynı zamanda çalışmada katılımcıların cinsiyet, gelir düzeyi ve eğitim durumu değişkeni açısından Sportif Faaliyetlerde İslam Dini Etki ölçeği ortalama puanları ve alt boyut ortalama puanları arasında anlamlı bir farklılık olmadığı sonucuna ulaşılmıştır. Diğer taraftan profesyonel, dini eğitim almış ve bireysel spor branşına sahip katılımcıların İslam dininin sportif faaliyetlerde daha yüksek düzeyde etkili olduğu görüşünde olduğu saptanmıştır. Sonuç olarak, bu bulgular İslam'ın spor faaliyetlerine etkisinin kompleks olduğunu ve demografik faktörlerden ziyade sporcuların dini eğitimi, profesyonellikleri ve spor branşları gibi özelliklerine bağlı olarak değişebileceğini göstermektedir.

At the end of 2019, a new kind of coronavirus (SARS-CoV-2) suffered worldwide and has become the pandemic coronavirus (COVID-19). The outbreak of this virus let to crisis around the world and kills millions of people globally. On March 2020, WHO (World Health Organization) declared it as pandemic disease. The first symptom of this virus is identical to flue and it destroys the human respiratory system. For the identification of this disease, the first key step is the screening of infected patients. The easiest and most popular approach for screening of the COVID-19 patients is chest X-ray images. In this study, our aim to automatically identify the COVID-19 and Pneumonia patients by the X-ray image of infected patient. To identify COVID19 and Pneumonia disease, the convolution Neural Network was training on publicly available dataset on GitHub and Kaggle. The model showed the 98% and 96% training accuracy for three and four classes respectively. The accuracy scores showed the robustness of both model and efficiently deployment for identification of COVID-19 patients.

182 Background: Home-based symptom monitoring using patient reported outcomes has been shown to reduce symptom burden and hospitalizations, while improving quality of life and overall. The primary goal of this study was to evaluate the early feasibility of home-based symptom monitoring. Methods: This prospective single-arm pilot study evaluated a two-part education and technology intervention (home-based symptom monitoring) for clinicians treating Multiple Myeloma (MM) and Acute Myeloid Leukemia (AML) patients. Inclusion criteria included patients ≥ 60 who were anticipating a treatment decision. Participants completed a baseline survey and then enrolled into the PROmpt® symptom monitoring platform, which used text or email to prompt weekly symptom surveys. Patients receive an auto-generated self-management plan based on electronic patient reported outcomes (ePRO). If severe symptoms were reported (score of > 7/10), alerts were sent to clinical nurses. Outcomes for this study included proportion of patient approach who agreed to participate, patient completion rates (completion of weekly surveys), compliance rate (completion of total surveys), number of alerts generated, and type of alert. Feasibility was defined as a completion rate of > 70%. Results: Between September 1, 2020 –May 19, 2021; 114 patients were screened, 77 were approached, and 35 were enrolled (18) MM, (17) AML patients. Of non-participants, 11 were not seeking care at the institution, 10 patients were uninterested or did not have a smartphone, 9 patients were ineligible, and 9 were unsure and left with information about the study, 3 declined enrollment. The majority (80%) or participants were ages 60-74; 20% of patients were ages 75+. Over the 13-week period, AML patients completed 195/220 (compliance rate of 89%). The average completion rate was 92%. For MM, 192/233 surveys were completed (82% compliance rate). The average completion rate was 94%. For AML, 9 was the average number of completed surveys and the average number for MM was 8. Over 3 months, there were 294 moderate to severe alerts generated for AML and MM patients. For AML patients, there were 40 fatigue, 25 constipation, 21 pain, 17 decreased appetite, 11 insomnia, 11 rash, 6 anxiety, 7 dyspnea/cough, 7 diarrhea, 5 depression/sadness, 4 nausea/ vomiting, 4 mouth/ throat sores, 3 neuropathy, 3 fever, and 2 alerts for other symptoms. Within a 3 month time span for MM patients, there was 35 pain, 21 constipation, 18 fatigue, 11 rash, 10 neuropathy, 9 anxiety, 7 insomnia, 6 depression/sadness, 4 decreased appetite, 4 other symptom, and 1 nausea/vomiting alert. Conclusions: This study demonstrated early feasibility with over 80% of patient completing their surveys with a high compliance rate. Future analysis will include both final implementation outcomes as well as patient outcomes for all patients within the study.