Miracle-dz/UniFAR-FTUs huggingface dataset:
A buffer model for evaluating R-tree performance

Performance studies of various R-tree algorithms, have used the number of nodes accessed as the primary metric. In real databases some portion of the tree is buffered in main memory. Since such buffering can significantly affect performance, we postulate that performance prediction should be baaed on number of 1/0s required to satisfy a query. To this end we present an analytical model that predicts the number of disk accesses for an LRU buffer manager given the minimum bounding rectangles (MBRs) of the R-tree nodes and a buffer size. Our model can be used to evaluate the quality of any R-tree update operation, such as node splitting policies [3] or packing algorithms [4, 6, 8], asmeasured by query performance of the resulting tree. The model is very accurate and simple to understand, making it easy for researchers to integrate it into their studies. It can eerily be modified to accommodate different buffer management policies – for example, keeping the top few levels of the R-tree in the buffer. Furthermore, the model ia not only applicable to R-trees, but can easily be modified to predict B-tree performance.
Optimal Data Transmission and Improve Efficiency through Machine Learning in Wireless Sensor Networks

Each sensor node in WSN is typically equipped with a limited capacity small battery. Energy-efficient communication is therefore considered a key component of network life extension. In addition, as the utilization of the sensor network increases, duplicate data and abnormal data is also collected to reduce the accuracy of the data in various environments. AI is used to recognize data anomaly values and increase packets' accuracy by removing out-of-range data. This can improve performance through optimal data transmission, resulting in increased network life, energy efficiency, and reliability. This paper proposes a protocol called MLQ-MAC that reflects the above. MLQ-MAC uses AI techniques to consider different types of data packets. The data collected by the sensor removes the measurement anomaly and duplicate data and stores it in a different transmission queue by priority. Efficient data transfer is possible by using an AI Discriminator for accurate classification before being stored on a transmission queue. The AI-Discriminator classifies a variety of factors, including the collection environment, characteristics of network applications, and so on. It also uses two new technologies: self-adaptation and scheduling for efficient transmission. In the protocol, the receiver adjusts the duty cycle according to to transmit urgency to improve network QoS. Finally, the simulation results show that the MLQ-MAC protocol reduces energy consumption at the receiver by up to 3.4% and per bit by up to 2.3% and improves packet delivery accuracy by up to 3%.
SEFT: a search engine for text

We present a software tool called seft which balances the convenience of search tools such as grep with the functionality of full‐text index‐based information retrieval. Based on a novel retrieval heuristic which uses term locality as a guide to relevance, seft combines the freedom of natural language queries with the benefits of a ranked answer list and easy inspection of retrieval results. While not as fast as grep‐style tools, seft provides a valuable facility for impromptu personal information retrieval tasks. Copyright © 2004 John Wiley & Sons, Ltd.
Linearizing irregular memory accesses for improved correlated prefetching

This paper introduces the Irregular Stream Buffer (ISB), a prefetcher that targets irregular sequences of temporally correlated memory references. The key idea is to use an extra level of indirection to translate arbitrary pairs of correlated physical addresses into consecutive addresses in a new structural which is visible only to the ISB. This structural address space allows the ISB to organize prefetching meta-data so that it is simultaneously temporally and spatially ordered, which produces technical benefits in terms of coverage, accuracy, and memory traffic overhead. We evaluate the ISB using the Marss full system simulator and the irregular memory-intensive programs of SPEC CPU 2006 for both single-core and multi-core systems. For example, on a single core, the ISB exhibits an average speedup of 23.1% with 93.7% accuracy, compared to 9.9% speedup and 64.2% accuracy for an idealized prefetcher that over-approximates the STMS prefetcher, the previous best temporal stream prefetcher; this ISB prefetcher uses 32 KB of on-chip storage and sees 8.4% memory traffic overhead due to meta-data accesses. We also show that a hybrid prefetcher that combines a stride-prefetcher and an ISB with just 8 KB of on-chip storage exhibits 40.8% speedup and 66.2% accuracy.
Fusion of descriptors for speech / music classification

This work addresses the soundtrack indexing of multimedia documents. We present a speech/music classification system based on three original features: entropy modulation, stationary segment duration and number of segments. They were merged by basic score maximisation with the classical 4 Hertz modulation energy. We validate this fusion approach with the use of the probability theory and the evidence theory. The system is tested on radio corpora. Systems are simple, robust and could be improved on every corpus without training or adaptation.
Large vocabulary speech recognition system: SPOJUS++

In this paper, we describe Large vocabulary Continuous Speech Recognition (LVCSR) system SPOJUS++ which has been developed in our laboratory for over 20 years and recently fully reimplemented from scratch. SPOJUS++ employs a context-dependent Hidden Markov Model (HMM) as an acoustic model and an N-gram model as a language model to decode speech. SPOJUS++ has many novel features including a dynamic expansion of linear dictionary, a use of likelihood index for efficient handling of the inter-word dependency and one pass decoding. SPOJUS++ can decode speech in real time on current standard PC without painful degradation of the performance even though it uses a context-dependent HMM and a high order N-gram language model (N >= 3). Also, SPOJUS++ can construct a confusion network which leads to word error rate minimization recognition. Constructed confusion networks can be used in many kinds of post-processing applications which require automatic speech recognition results. We evaluated SPOJUS++ in terms of word accuracy, real time factor and search error. Experimental results showed that SPOJUS++ is comparable to state-of-the-arts.
Solution-Focused Counseling for Eating Disorders

Counseling Association by Dr. Garry R. Walz and Dr. Jeanne C. Bleuer of Counseling Outfitters, LLC. Its purpose is to provide a means of capturing the ideas, information and experiences generated by the annual ACA Conference and selected ACA Division Conferences. Papers on a program or practice that has been validated through research or experience may also be submitted. This digital collection of peer-reviewed articles is authored by counselors, for counselors. VISTAS Online contains the full text of over 500 proprietary counseling articles published from 2004 to present.
Combining Supervised and Unsupervised Models via Unconstrained Probabilistic Embedding

In this study, we consider an ensemble problem in which we combine outputs coming from models developed in the supervised and unsupervised modes. By jointly considering the grouping results coming from unsupervised models we aim to improve the classification accuracy of supervised model ensemble. Here, we formulate the ensemble task as an Unconstrained Probabilistic Embedding (UPE) problem. Specifically, we assume both objects and classes/clusters have latent coordinates without constraints in a D-dimensional Euclidean space, and consider the mapping from the embedded space into the space of model results as a probabilistic generative process. A solution to this embedding can be obtained using the quasi-Newton method, which makes objects and classes/clusters with high co-occurrence weights are embedded close. Then, prediction is determined by taking the distances between the object and the classes in the embedded space. We demonstrate the benefits of this unconstrained embedding method by running extensive and systematic experiments on real-world datasets. Furthermore, we conduct experiments to investigate how the quality and the number of clustering models affect the performance of this ensemble method. We also show the robustness of the proposed model.
Relationship between invariant chain expression and major histocompatibility complex class II transport into early and late endocytic compartments

Invariant chain (Ii), which associates with major histocompatibility complex (MHC) class II molecules in the endoplasmic reticulum, contains a targeting signal for transport to intracellular vesicles in the endocytic pathway. The characteristics of the target vesicles and the relationship between Ii structure and class II localization in distinct endosomal subcompartments have not been well defined. We demonstrate here that in transiently transfected COS cells expressing high levels of the p31 or p41 forms of Ii, uncleaved Ii is transported to and accumulates in transferrin-accessible (early) endosomes. Coexpressed MHC class II is also found in this same compartment. These early endosomes show altered morphology and a slower rate of content movement to later parts of the endocytic pathway. At more moderate levels of Ii expression, or after removal of a highly conserved region in the cytoplasmic tail of Ii, coexpressed class II molecules are found primarily in vesicles with the characteristics of late endosomes/prelysosomes. The Ii chains in these late endocytic vesicles have undergone proteolytic cleavage in the lumenal region postulated to control MHC class II peptide binding. These data indicate that the association of class II with Ii results in initial movement to early endosomes. At high levels of Ii expression, egress to later endocytic compartments is delayed and class II-Ii complexes accumulate together with endocytosed material. At lower levels of Ii expression, class II- Ii complexes are found primarily in late endosomes/prelysosomes. These data provide evidence that the route of class II transport to the site of antigen processing and loading involves movement through early endosomes to late endosomes/prelysosomes. Our results also reveal an unexpected ability of intact Ii to modify the structure and function of the early endosomal compartment, which may play a role in regulating this processing pathway.
Construction of a Plasmodium falciparum Rab-interactome identifies CK1 and PKA as Rab-effector kinases in malaria parasites

The pathology causing stages of the human malaria parasite Plasmodium falciparum reside within red blood cells that are devoid of any regulated transport system. The parasite, therefore, is entirely responsible for mediating vesicular transport within itself and in the infected erythrocyte cytoplasm, and it does so in part via its family of 11 Rab GTPases. Putative functions have been ascribed to Plasmodium Rabs due to their homology with Rabs of yeast, particularly with Saccharomyces that has an equivalent number of rab/ypt genes and where analyses of Ypt function is well characterized.
Analyzing the communication topology of concurrent programs

Concurrent languages present complex problems for program analysis. Existing analyses are either imprecise, exponential, or apply only to languages with statically-allocated processes and channels. We present a new polynomial-time analysis using abstract interpret ation that addresses the general problem of determining the communication topology of programs in a subset of Concurrent ML with arbitrary data structures, recursive higher-order functions, dynamic processor allocation, dynamic channel creation, and synchronous message-passing operations transmit and receive. The analysis addresses the following question: Whtch occurrences o~transmit can match whzch occurrences of receive? The notion of occurrence is formalized as a control path in a small-step semantics, which provides a powerful basis for distinguishing recursive communication topologies. The analysis is relational, in that it relates pairs of processes, and non-rmi~orm, in that it distinguishes between iterations in an infinite recursive communication pattern. The results are thus precise enough to aid processor allocation, scheduling, and sequentialization on both uniprocessors and multiprocessors.
Assessing and neutralizing multi-tiered security threats in blockchain systems

Blockchain technology, the backbone of digital cryptocurrencies, has rapidly ascended as a pivotal tool in modern commerce due to its decentralized, immutable nature. It offers fresh, innovative avenues for overcoming trust issues inherent in traditional trading systems. Yet, the unique traits that make blockchain advantageous also render it vulnerable. Cybercriminals are ceaselessly innovating, devising new tactics to exploit these vulnerabilities and resulting in a surge of security incidents that have led to substantial economic losses. The increasing frequency and sophistication of these attacks jeopardize the integrity and stability of blockchain networks. This paper offers a comprehensive study of blockchain system architecture, the principles underlying various attack methods, and viable defense strategies, all organized within a hierarchical framework. Initially, the paper categorizes blockchain attacks according to the hierarchy of blockchain systems, providing a detailed exploration of the characteristics and principles behind these attacks at each level. Next, the paper summarizes existing countermeasures and proposes effective new strategies for bolstering blockchain security. The paper concludes with a recap of its key findings and outlines the landscape for future research in blockchain security.
Keyboard and mouse errors due to motor disabilities

There are many people who find the standard computer input devices? the keyboard and mouse? difficult to use due to a motor disability. A number of keyboard and mouse configuration options designed to overcome physical difficulties exist. However, formal empirical evaluation of such facilities is rare. There is, in fact, little data available on the precise nature of physical difficulties with input devices. Hence, it is difficult to gauge the adequacy of existing access provision. This paper presents an empirical study of the keyboard and mouse errors encountered in a sample of 20 computer users with motor disabilities, and six without disabilities. Six important classes of keyboard difficulty are identified, involving significant correction time for participants with disabilities. Difficulties with all aspects of mouse usage were observed, particularly pointing and dragging. Many of the difficulties observed would be amenable to automatic detection. It is hoped that these results will help to inform the development of more accessible software and hardware.
The Price of Anarchy in Auctions

This survey outlines a general and modular theory for proving approximation guarantees for equilibria of auctions in complex settings. This theory complements traditional economic techniques, which generally focus on exact and optimal solutions and are accordingly limited to relatively stylized settings. We highlight three user-friendly analytical tools: smoothness-type inequalities, which immediately yield approximation guarantees for many auction formats of interest in the special case of complete information and deterministic strategies; extension theorems, which extend such guarantees to randomized strategies, no-regret learning outcomes, and incomplete-information settings; and composition theorems, which extend such guarantees from simpler to more complex auctions. Combining these tools yields tight worst-case approximation guarantees for the equilibria of many widely-used auction formats.
Customized expression recognition for performance-driven cutout character animation

Performance-driven character animation enables users to create expressive results by performing the desired motion of the character with their face and/or body. However, for cutout animations where continuous motion is combined with discrete artwork replacements, supporting a performance-driven workflow has some unique requirements. To trigger the appropriate artwork replacements, the system must reliably detect a wide range of customized facial expressions that are challenging for existing recognition methods, which focus on a few canonical expressions (e.g., angry, disgusted, scared, happy, sad and surprised). Also, real usage scenarios require the system to work in realtime with minimal training. In this paper, we propose a novel customized expression recognition technique that meets all of these requirements. We first use a set of handcrafted features combining geometric features derived from facial landmarks and patch-based appearance features through group sparsity-based facial component learning. To improve discrimination and generalization, these handcrafted features are integrated into a custom-designed Deep Convolutional Neural Network (CNN) structure trained from publicly available facial expression datasets. The combined features are fed to an online ensemble of SVMs designed for the few training sample problem and performs in realtime. To improve temporal coherence, we also apply a Hidden Markov Model (HMM) to smooth the recognition results. Our system achieves state-of-the-art performance on canonical expression datasets and promising results on our collected dataset of customized expressions.
Isolation and Culture of Arterial Smooth Muscle Cells From Human Placenta

Abstract—A simple and economical technique was developed to isolate and culture human arterial smooth muscle cells from chorionic plate vessels. Placentas from healthy women were collected at the time of term delivery. Chorionic plate arteries were identified, excised, and cut into small pieces. An explant technique was used to grow cultures of placental arterial smooth muscle (PASM) cells. Small pieces of vessel with lumens down were placed in 100-mm culture plates and grown in Dulbecco modified eagle medium and 10% fetal bovine serum. Cells appeared from explants within 1 week and grew to confluence in approximately 4 weeks. At confluence, PASM cell cultures had a uniform cell morphology that was characterized by elongated cells in parallel rows, typical of smooth muscle cells. Smooth muscle cell phenotype was evaluated by morphology and by immunoblotting and immunofluorescence of smooth muscle myofilament proteins. All PASM cell cultures expressed &agr;-smooth muscle actin, &bgr;-tropomyosin, and h-caldesmon. Expression was similar to that of human aortic smooth muscle cells, but not to endothelial cells or fibroblasts. PASM cells stained uniformly for &agr;-smooth muscle actin and lacked staining for a fibroblast-specific antigen. PASM cells were evaluated for their response to inflammatory mediators, tumor necrosis factor-&agr;, and interleukin-1&bgr; by measurement of interleukin-8 production. Cells cultured for 18 hours showed a progressive increase in interleukin-8 production with time. Treatment with inflammatory mediators increased interleukin-8 production by 3-fold as compared with media control. This technique provides a simple method to obtain normal human arterial smooth muscle cells for in vitro studies of physiology and pathophysiology.
Visualizing water infrastructure with Sankey maps: a case study of mapping the Los Angeles Aqueduct, California

ABSTRACT Creating resilience for urban water supply systems requires innovative thematic visualizations of the interface between infrastructure, ecology, and culture to viscerally engage lay audiences in the policy making process. Sankey maps (a hybrid Sankey diagram/flow map) embed the systemic accounting of flows between sources and sinks into a spatial framework. This allows a hierarchy of visual variables to encode environmental conditions and historical data, providing a rich multivariate context supporting public discourse, policy making, and system operations. The article features a Sankey map of the Los Angeles Aqueduct system (California, USA) (not to scale).
Mandarin Chinese Prosodic Phrase Grouping and Modeling — Method and Implications

One major feature of the prosody of Mandarin Chinese speech flow is prosodic phrase grouping [1, 2, and 3]. Phrasal and sentential intonations are governed by a prosody framework that structurally group phrases into a larger/longer and identifiable unit. An overall prosody pattern of such phrase grouping with prosodic specifications is superimposed on phrase group. In turn, individual phrasal intonation under prosody grouping has to adjust in accordance with structural specification from the prosody framework. The output is then seen as derived outcome. The aim of the present paper is to experiment how to simulate prosodic phrase grouping using the Fujisaki intonation model that originally specifies only phrasal or sentential intonations, and how such an intonation model can be further enhanced by incorporating prosodic specifications such as boundaries and breaks, prosody levels/layers and phrase positions under the notion of phrase grouping. The experiments began with aligning the phrase command of the intonation model to boundaries of breaks in the speech flow, then examining prosodic characteristics such as relative position of the target phrase within a prosodic phrase group. Finally, using a linear regression model to predict prosody output from prosodic words upward, predictions of an overall pattern for prosodic phrase grouping was derived. The pattern matched with a prosody base form aimed at prosodic phrase grouping; it also accounted for how and why phrasal intonations were modified in relation to prosody organization. Hence, phrasal intonation is seen as components of prosodic phrase grouping.