Let $p$ be an odd prime. Define the Gaussian power sum \[ G_n(p)=\sum_{a=1}^{p-1}\sum_{b=1}^{p-1}(a+bi)^n\in\mathbb Z[i]. \] We determine $G_p(p)$ modulo high powers of $p$: if $p\equiv 1\pmod 4$ then $$G_p(p)\equiv p^2(1+i)\pmod{p^3},$$ while for $p\equiv 3\pmod 4, p\ge 7$ we prove the supercongruence \[ G_p(p)\equiv -\frac{p^5}{12}(p-1)^2(p-2)\,B_{p-3}\,(1-i)\pmod{p^6}, \] where $B_m$ denotes the $m$-th Bernoulli number. We also formulate several conjectures suggested by extensive computations.
This study aims to explore the efforts of school superintendents in managing the changes caused by the Covid-19 pandemic, which has led to a decline in the quality of process standards in schools, and to measure the results. Examining the issue of declining the quality of process standard by using change management strategy has not been conducted in earlier studies. This research used a qualitative approach with a phenomenological type. This research took place at elementary school in Ponorogo. The informants in this research consisted of school superintendents who are members of Ponorogo Branch of the Indonesian School Supervisors Association (APSI) as well as principals of elementary schools in Ponorogo. The results of this research revealed that: first, school supervisors have managed the changes that occur in their target schools through ADKAR steps combined with technology, namely: awareness, desire, knowledge, ability and reinforcement which are supported by using information technology. Second, the success of change management in improving the quality of process standards could be divided into three points, namely improvement, stagnation and decline.
The role of a halal lifestyle is a form of personal awareness in implementing practices following Islamic teachings. This is related to a person's lifestyle in making an investment decision. The purpose of this study is to see how the role of an investor's halal lifestyle in their investment decisions, seen from Islamic financial literacy, and also their financial behavior. This study examines an investor, a student at Cokroaminoto University, who invests in the stock market. This study employs a qualitative approach, utilizing a case study design. The findings of this study indicate that the role of a halal lifestyle, as reflected in Islamic financial literacy and the financial behavior of investors, can influence the decisions made in their investments.
If an irreducible fraction $\frac mn>0$ can be decomposed into the sum of several irreducible proper fractions with different denominators, and the positive number smaller than $\frac mn$ in fractional ideal $\frac 1n\mathbb Z$ can not be obtained by replacing some numerator with smaller non-negative integers, then the decomposition is said to be faithful. For $t\in\mathbb Z$, we prove that the length of faithful decomposition of an irreducible fraction $\frac mn$ with $2\le t\le\frac mn<t+1$ is at least $t+2$. In addition, we show a faithful decomposition of rationals consisting only of unit fractions except for one term. And we write $\frac 4n$ as a faithful decomposition with three fractions at most one non-unit fraction.
Vision-Language Models (VLMs) excel in integrating visual and textual information for vision-centric tasks, but their handling of inconsistencies between modalities is underexplored. We investigate VLMs' modality preferences when faced with visual data and varied textual inputs in vision-centered settings. By introducing textual variations to four vision-centric tasks and evaluating ten Vision-Language Models (VLMs), we discover a \emph{``blind faith in text''} phenomenon: VLMs disproportionately trust textual data over visual data when inconsistencies arise, leading to significant performance drops under corrupted text and raising safety concerns. We analyze factors influencing this text bias, including instruction prompts, language model size, text relevance, token order, and the interplay between visual and textual certainty. While certain factors, such as scaling up the language model size, slightly mitigate text bias, others like token order can exacerbate it due to positional biases inherited from language models. To address this issue, we explore supervised fine-tuning with text augmentation and demonstrate its effectiveness in reducing text bias. Additionally, we provide a theoretical analysis suggesting that the blind faith in text phenomenon may stem from an imbalance of pure text and multi-modal data during training. Our findings highlight the need for balanced training and careful consideration of modality interactions in VLMs to enhance their robustness and reliability in handling multi-modal data inconsistencies.
Fitriani Fitriani, Hasan Basri, Andewi Suhartini
et al.
This research aims to discuss the evaluation of the religious development of students at SMP Hikmah Teladan based on religious dimensions in fostering independence in worship. This study uses a qualitative approach, a field research type, and employs a descriptive method, using the descriptive analysis model by Miles and Huberman (Qualitative Data Analysis), which includes data reduction, data presentation, and conclusion drawing. Data collection techniques include interviews, observation, and documentation. The results of this study indicate that the religious development of students at SMP Hikmah Teladan in fostering independence in worship must continue to be pursued by referring to religious dimensions. The novelties in this research include: 1) categorizing religious programs based on religious dimensions; 2) conducting evaluations systematically; 3) measuring target achievement using independence indicators, so that progress can be more measurable. Therefore, the religious development program for students at SMP Hikmah Teladan supports the formation of independence in worship.
Christopher Chang, Simeon Hellsten, Mario Marcos Losada
et al.
We develop methods to show that infinite-dimensional modules over the Iwasawa algebra $KG$ of a uniform pro-p group are faithful and apply them to show that the metaplectic representation for the symplectic group is faithful.
Grasping the themes of social media content is key to understanding the narratives that influence public opinion and behavior. The thematic analysis goes beyond traditional topic-level analysis, which often captures only the broadest patterns, providing deeper insights into specific and actionable themes such as "public sentiment towards vaccination", "political discourse surrounding climate policies," etc. In this paper, we introduce a novel approach to uncovering latent themes in social media messaging. Recognizing the limitations of the traditional topic-level analysis, which tends to capture only overarching patterns, this study emphasizes the need for a finer-grained, theme-focused exploration. Traditional theme discovery methods typically involve manual processes and a human-in-the-loop approach. While valuable, these methods face challenges in scalability, consistency, and resource intensity in terms of time and cost. To address these challenges, we propose a machine-in-the-loop approach that leverages the advanced capabilities of Large Language Models (LLMs). To demonstrate our approach, we apply our framework to contentious topics, such as climate debate and vaccine debate. We use two publicly available datasets: (1) the climate campaigns dataset of 21k Facebook ads and (2) the COVID-19 vaccine campaigns dataset of 9k Facebook ads. Our quantitative and qualitative analysis shows that our methodology yields more accurate and interpretable results compared to the baselines. Our results not only demonstrate the effectiveness of our approach in uncovering latent themes but also illuminate how these themes are tailored for demographic targeting in social media contexts. Additionally, our work sheds light on the dynamic nature of social media, revealing the shifts in the thematic focus of messaging in response to real-world events.
To interpret Vision Transformers, post-hoc explanations assign salience scores to input pixels, providing human-understandable heatmaps. However, whether these interpretations reflect true rationales behind the model's output is still underexplored. To address this gap, we study the faithfulness criterion of explanations: the assigned salience scores should represent the influence of the corresponding input pixels on the model's predictions. To evaluate faithfulness, we introduce Salience-guided Faithfulness Coefficient (SaCo), a novel evaluation metric leveraging essential information of salience distribution. Specifically, we conduct pair-wise comparisons among distinct pixel groups and then aggregate the differences in their salience scores, resulting in a coefficient that indicates the explanation's degree of faithfulness. Our explorations reveal that current metrics struggle to differentiate between advanced explanation methods and Random Attribution, thereby failing to capture the faithfulness property. In contrast, our proposed SaCo offers a reliable faithfulness measurement, establishing a robust metric for interpretations. Furthermore, our SaCo demonstrates that the use of gradient and multi-layer aggregation can markedly enhance the faithfulness of attention-based explanation, shedding light on potential paths for advancing Vision Transformer explainability.
Faithfulness is a common assumption in causal inference, often motivated by the fact that the faithful parameters of linear Gaussian and discrete Bayesian networks are typical, and the folklore belief that this should also hold for other classes of Bayesian networks. We address this open question by showing that among all Bayesian networks over a given DAG, the faithful Bayesian networks are indeed `typical': they constitute a dense, open set with respect to the total variation metric. This does not directly imply that faithfulness is typical in restricted classes of Bayesian networks that are often considered in statistical applications. To this end we consider the class of Bayesian networks parametrised by conditional exponential families, for which we show that under regularity conditions, the faithful parameters constitute a dense and open set, the unfaithful parameters have Lebesgue measure zero, and the induced faithful distributions are open and dense in the weak topology. This extends the existing results for linear Gaussian and discrete Bayesian networks. We also show for nonparametric classes of Bayesian networks with uniformly equicontinuous and uniformly bounded conditional densities that the faithful Bayesian networks are open and dense in the weak topology. All these results also hold for Bayesian networks with latent variables, if faithfulness is only required to hold with respect to the latent projection. Finally, for the considered conditional exponential family parametrisations and nonparametric conditional density models, the topological properties of conditional independence imply the existence of a consistent conditional independence test. Together with the topological properties of faithfulness, this implies that sound constraint-based causal discovery algorithms like PC and FCI are consistent on an open and dense -- and hence `typical' -- set of Bayesian networks.
As Allah Ta'ala started the series of Prophets to guide the people and sent down His orders to those who were not only explained but also became an example in practice. In the same way, Allah revealed the last book to the Holy Prophet (peace and blessings of Allah be upon him) and commanded the Messenger of Allah (peace and blessings of Allah be upon him)“And We have sent down the Dhikr to you so that you may make it clear to the people who Something has been sent down to them so that they may reflect" (Surat al-Nahl). And this is how the Holy Prophet (peace and blessings of Allah be upon him) explained the interpretation of the Qur'an. And in the same way, the companions of the Holy Prophet (peace and blessings of Allah be upon him) also passed on this trust. And finally, this series of commentary took the form of the first book in the form of Ibn Jarir al-Tabari's commentary "Jami al-Bayan fi Taweel Al-Qur'an" and this series of commentary that started from the era of Prophethood is still ongoing and is a link of the same series. Tafsir Bayan al-Qur'an is also. It is the result of the religious services of Dr. Israr Ahmed. Dr. Asrar Ahmad, may Allah have mercy on him, is considered one of the great scholars and commentators of the Qur'an of the present century. And among the special rewards of Allah Almighty, Allah Almighty gave him this opportunity to show him a period in his life when the whole world It is present in people's pockets, and that is why his interpretations of the Holy Qur'an have been heard by him not only in Pakistan but also in the whole world. Dr. Sahib Raha's efforts and efforts have been published in a commentary form, which began in his own lifetime, and the first volume of his Tafsir Bayan al-Qur'an was published in his lifetime, which the case was written by Dr. Asrar Ahmad Rahmatullah Alaihi himself. Dr. Asrar Ahmad Rehmatullah Alaihi's Tafsir Bayan Al-Qur'an is not his authorship or compilation but is taken from his translation of the Al-Qur'an which was preserved in CDs and DVDs.
Penelitian ini meneliti peran manajemen kepala madrasah dalam meningkatkan kinerja guru di era Revolusi Industri 6.0, dengan studi kasus di MIN 1, MIN 2, dan MIN 3 OKU Timur. Latar belakangnya adalah transformasi global dalam pendidikan yang dipicu oleh kemajuan teknologi digital seperti AI, IoT, dan big data, yang menuntut perubahan paradigma dalam pengelolaan lembaga pendidikan, termasuk madrasah. Tujuan penelitian ini adalah untuk mengidentifikasi strategi manajemen yang efektif yang diterapkan oleh kepala madrasah untuk meningkatkan kinerja guru dalam menghadapi tantangan era digital. Metode penelitian menggunakan pendekatan kualitatif dengan desain deskriptif, melibatkan observasi, wawancara, dan dokumentasi untuk mengumpulkan data. Hasil penelitian menunjukkan bahwa kepala madrasah memainkan peran kunci dalam perencanaan, pelaksanaan, dan evaluasi manajemen yang berfokus pada integrasi teknologi dalam pembelajaran dan peningkatan profesionalisme guru. Kesimpulannya, manajemen yang efektif oleh kepala madrasah sangat penting untuk meningkatkan kinerja guru dan mempersiapkan peserta didik dalam menghadapi tantangan global di era Revolusi Industri 6.0. Penelitian ini berkontribusi pada pengembangan manajemen pendidikan Islam dan memberikan wawasan praktis bagi kepala madrasah dan pemangku kepentingan lainnya dalam merancang strategi yang inovatif dan adaptif.
Purpose − Analyze the psychology of patients related to halal healthcare tools that impact their loyalty intentions to Sharia hospitals in Indonesia for health visits and the implications of word of mouth on the community.
Methodology − The research employed quantitative techniques by utilizing cross-sectional survey information gathered from Sharia hospital patients in Indonesia, selected through convenience sampling methods. The study analyzed a total of 229 patient responses through the application of structural equation modeling.
Findings − Sharia facilities, doctor-nurse services, medical expertise and administrative conduct as indicators of halal health services affect patient satisfaction in sharia hospitals. However, there is resistance to the influence of the medical facility atmosphere on satisfaction caused by the concentration of patients in medical services and solving health problems. Patient satisfaction affects loyalty which in turn gives a positive word of mouth effect.
Implications − Islamic hospitals should prioritize patient assessment and satisfaction by reviewing their physical facilities, cleanliness, comfort, and spiritual needs. Medical personnel should enhance communication and sharia-compliant practices. Digitalization and improved service standards are essential, requiring adaptability and technology integration. Regular evaluations and external monitoring are vital. The government should collaborate with relevant ministries and organizations to intensively monitor and improve the quality of sharia hospitals.
Originality − This study develops new knowledge on indicators of special services for sharia hospitals according to halal standards by integrating the outputs of satisfaction, loyalty and Word of Mouth (WoM) outputs which have been separated so far but have a chronological sequence in line with existing marketing theory.
Nowadays, IEEE 802.11, i.e., Wi-Fi has emerged as a prevailing technology for broadband wireless networking. To meet the tremendous rise of demand for future generation wireless LANs, a robust and efficient MAC protocol is required for the Wi-Fi network. However, traditional MAC mechanisms are not suitable for next-generation communications due to some inherent constraints. In this regard, OFDMA technology could be adopted to design an efficient MAC protocol for the Wi-Fi network. The purpose of this research is to provide a high-speed network for Wi-Fi users. The thesis presents three MAC protocols, namely, HTFA (High Throughput and Fair Access), ERA (Efficient Resource Allocation), and PRS (Proportional Resource Scheduling), by employing the OFDMA technology. The novel protocols improve Wi-Fi communication using the latest IEEE 802.11ax standard, i.e., Wi-Fi 6. In particular, the protocols improve several performance parameters of the MAC protocol, such as increasing the throughput, goodput, fairness index, and reducing the packet retransmissions, collisions, etc. Simulation results validate that the new protocols are far better than the existing protocols. The protocols designed in this thesis are compliant with the latest IEEE 802.11ax standard that promises to enhance the throughput at least four times per user and support ten times users. Thus, the new protocols can ensure uninterrupted and smooth communication in highly dense environments. The thesis contains a lot of resources such as the state of the art of MAC protocols, analysis of contemporary protocols and their performance matrix; architecture of Wi-Fi system, OFDMA constraints and regulations; framework of protocols; analytical models; relevant data, theory, and methods; etc. that would be the valuable resources to the future researchers for the research on the Wi-Fi network.
Niful Islam, Md. Mehedi Hasan Jony, Emam Hasan
et al.
Improper disposal of e-waste poses global environmental and health risks, raising serious concerns. The accurate classification of e-waste images is critical for efficient management and recycling. In this paper, we have presented a comprehensive dataset comprised of eight different classes of images of electronic devices named the E-Waste Vision Dataset. We have also presented EWasteNet, a novel two-stream approach for precise e-waste image classification based on a data-efficient image transformer (DeiT). The first stream of EWasteNet passes through a sobel operator that detects the edges while the second stream is directed through an Atrous Spatial Pyramid Pooling and attention block where multi-scale contextual information is captured. We train both of the streams simultaneously and their features are merged at the decision level. The DeiT is used as the backbone of both streams. Extensive analysis of the e-waste dataset indicates the usefulness of our method, providing 96% accuracy in e-waste classification. The proposed approach demonstrates significant usefulness in addressing the global concern of e-waste management. It facilitates efficient waste management and recycling by accurately classifying e-waste images, reducing health and safety hazards associated with improper disposal.
Fıkıh-siyaset arasındaki ilişkinin en yoğun gerçekleştiği dönemlerden birisi Muhavvid Devleti dönemidir. Bu dönemde İbn Tûmert önderliğinde yürütülen fıkhî-siyâsî hareket önceleri kısmen başarıya ulaşmıştır. Sonrasında ise İbn Tûmert’in iyiliği emretme kötülükten nehyetme ilkesi çerçevesinde icrâ ettiği uygulamalar toplum tarafından hoşnutsuzlukla karşılanmıştır. Bu çalışmada İbn Tûmert’in bir fakih ve devlet idarecisi olarak izlediği dini uygulamaların izi sürülmektedir. Bu bağlamda İbn Tûmert’in namaz kılmayanlara yönelik verdiği cezalar, içki yasağı kapsamında öngördüğü cezalar ve kadınların tesettürü ile toplum içindeki görünürlükleri üzerindeki yaptırımları olmak üzere üç örnek olay incelenmektedir. İncelenen uygulamalar değerlendirildiğinde bunların fıkhî yorumdan öte siyasî ictihadlar olduğu sonucuna varılmıştır. Çalışmada nitel bir araştırma metodu olan doküman analizi yoluyla literatür taraması yapılmış ve veriler eleştirel bir şekilde ortaya konulmuştur. Çalışmanın din kaynaklı katı uygulamaların sonuçlarının doğru okunması ve günümüz tatbikatına fikir vermesi açısından İslam hukuk tarihine katkı sağlaması amaçlanmaktadır. Murâbıtlar Devleti’nin yıkılmasıyla doğan belirsiz ve istikrarsız ortamdan faydalanan İbn Tûmert ve taraftarları, katı uygulamaları ile başlangıçta benimsedikleri ilkelerden verdikleri tavizler nedeniyle toplum desteğini kaybederek kendi sonlarını hazırlamışlardır. İbn Tûmert’in öncülüğünde kurulan Muvahhidler Devleti başlangıçta Kur’ân ve Sünnet’e dönüş ve gerçek İslam’ı yaşatmak gayesiyle yola çıkmışlar ancak sonunda katı tedbirlerin uygulandığı bir İslam yorumuna dönüşmüşlerdir. Çünkü İslam adına uyguladıkları hükümlerin Kur’ân ve Sünnet’in bizzat kendisi olmadığı, Kur’ân ve Sünnet’in genel maksadından üretilmiş sosyolojik temelleri olan fıkhî yorum veya siyâsî ictihad olduğu gerçeği gözardı edilmiştir. Bu sebeple İbn Tûmert’in İslam adına uyguladığı fıkhî görüşler halk tarafından huzursuzlukla karşılanmıştır. İbn Tûmert’in iyiliği emretme kötülükten nehyetme adı altında yaptığı uygulamaların, kanuni müeyyidesi kamu hukukunu ilgilendirmediği sürece suç unsuru teşkil etmeyen fiiller olduğu görülmektedir. Kaldı ki bu cezalar sadece İslam devleti başkanı tarafından verilebilecek iken İbn Tûmert, aynı ilkeye dayanarak devlet kurma girişiminde bulunmadan önce de bu cezaları tebliğ kapsamında uygulatmak istemiştir. İçki içene uygulanacak cezaya sadece devlet başkanının hükmedebileceği bilinmektedir. Devlete isyan anlamı yoksa namaz kılmamaya verilecek ceza da aynı şekildedir. Tesettürü örfe veya dinî inancına göre farklı biçimlerde uygulamak gibi fiiller ise kamuya yansıyacak sonuçları olmadığı sürece dinin farklı uygulamaları ve yorumlanma biçimleridir. Hz. Peygamber’in insanların kusurlarını ve ayıplarını mümkün olduğunca örtmeyi tavsiye etmesi ve bunu ahlakî bir davranış olarak değerlendirmesi bu fiillerin kul ile Allah arasında kalan ve manevî müeyyideye dayalı eylemler olduğunu göstermektedir. İbn Tûmert’in fıkhî uygulamalarına bakıldığında bunların samimi bir Müslüman olma gayretinin ve tebliğ faaliyetinin sonucu olduğu anlaşılmaktadır. Ancak fakihler arasında tercih edilmeyen bazı yorumlarda bulunduğu, bunları uygulatmak için de siyasi iktidarı bir araç olarak kullandığı ve kendi dini anlayışını hâkim kılmaya çalıştığı da görülmektedir. Murâbıt Devleti’nin meşrûiyetini sorgularken dinî hükümlerin uygulanmayışını gerekçe göstermesi siyâsî hedeflerinin de bulunduğunu akla getirmektedir. Nitekim hareketini oluştururken Mehdîlik iddiasında bulunması, vaaz ve nasihat olarak başlayan hareketinin siyâsi ağırlıklı olduğunu düşündürmektedir. Oysa her fakihin dini yorum ve algısı kendi ictihadları çerçevesinde gerçekleşir. Buna rağmen fakîh İbn Tûmert’in bazı ictihâdlarında katı ve aşırı yorumlarda bulunması hatta daha ileri giderek devleti eleştirip bir hareket başlatması ve siyâsi güce ulaşma süreci, siyasetin fıkıhla ilişkisinin boyutları açısından ibret verici bir örnektir.
Zubayer Islam, Mohamed Abdel-Aty, Amrita Goswamy
et al.
Intersection safety often relies on the correct modelling of signal phasing and timing parameters. A slight increase in yellow time or red time can have significant impact on the rear end crashes or conflicts. This paper aims to identify the relationship between surrogate safety measures and signal phasing. Unmanned Aerial Vehicle (UAV) video data has been used to study an intersection. Post Encroachment Time (PET) between vehicles was calculated from the video data as well as speed, heading and relevant signal timing parameters such as all red time, red clearance time, yellow time, etc. Random Parameter Ordered Logit Model was used to model the relationship between PET and these signal timing parameters. Overall, the results showed that yellow time and red clearance time is positively related to PETs. The model was also able to idendity certain signal phases that could be a potential safety hazard and would need to be retimed by considering the PETs. The odds ratios from the models also indicates that increasing the yellow and red clearance times by one second can improve the PET levels by 16% and 3% respectively.
We investigate the electrical and thermal transport properties of the $α-T_3$ based normal metal-insulator-superconductor (NIS) junction using Blonder-Tinkham-Klapwijk (BTK) theory. We show that the tunneling conductance of the NIS junction is an oscillatory function of the effective barrier potential ($χ$) of the insulating region upto a thin barrier limit. The periodicity and the amplitudes of the oscillations largely depend on the values of $α$ and the gate voltage of the superconducting region, namely, $U_0$. Further, the periodicity of the oscillation changes from $π$ to $π/2$ as we increase $U_0$. To assess the thermoelectric performance of such a junction, we have computed the Seebeck coefficient, the thermoelectric figure of merit, maximum power output, efficiency at the maximum output power of the system, and the thermoelectric cooling of the NIS junction as a self-cooling device. Our results on the thermoelectric cooling indicate practical realizability and usefulness for using our system as efficient cooling detectors, sensors, etc., and hence could be crucial to the experimental success of the thermoelectric applications of such junction devices. Furthermore, for an $α-T_3$ lattice, whose limiting cases denote a graphene or a dice lattice, it is interesting to ascertain which one is more suitable as a thermoelectric device and the answer seems to depend on the $U_0$. We observe that for an $α-T_3$ lattice corresponding to $U_0=0$, graphene ($α=0$) is more feasible for constructing a thermoelectric device, whereas for $U_0 \gg E_F$, the dice lattice ($α=1$) has a larger utility.
Few-shot graph classification aims at predicting classes for graphs, given limited labeled graphs for each class. To tackle the bottleneck of label scarcity, recent works propose to incorporate few-shot learning frameworks for fast adaptations to graph classes with limited labeled graphs. Specifically, these works propose to accumulate meta-knowledge across diverse meta-training tasks, and then generalize such meta-knowledge to the target task with a disjoint label set. However, existing methods generally ignore task correlations among meta-training tasks while treating them independently. Nevertheless, such task correlations can advance the model generalization to the target task for better classification performance. On the other hand, it remains non-trivial to utilize task correlations due to the complex components in a large number of meta-training tasks. To deal with this, we propose a novel few-shot learning framework FAITH that captures task correlations via constructing a hierarchical task graph at different granularities. Then we further design a loss-based sampling strategy to select tasks with more correlated classes. Moreover, a task-specific classifier is proposed to utilize the learned task correlations for few-shot classification. Extensive experiments on four prevalent few-shot graph classification datasets demonstrate the superiority of FAITH over other state-of-the-art baselines.