Integrating E-Commerce and Data Mining: Architecture and Challenges

We show that the e-commerce domain can provide all the right ingredients for successful data mining and claim that it is a killer domain for data mining. We describe an integrated architecture, based on our expe-rience at Blue Martini Software, for supporting this integration. The architecture can dramatically reduce the pre-processing, cleaning, and data understanding effort often documented to take 80% of the time in knowledge discovery projects. We emphasize the need for data collection at the application server layer (not the web server) in order to support logging of data and metadata that is essential to the discovery process. We describe the data transformation bridges required from the transaction processing systems and customer event streams (e.g., clickstreams) to the data warehouse. We detail the mining workbench, which needs to provide multiple views of the data through reporting, data mining algorithms, visualization, and OLAP. We con-clude with a set of challenges.Comment: KDD workshop: WebKDD 200

Effects of Seawater Corrosion and Freeze-Thaw Cycles on Mechanical Properties of Fatigue Damaged Reinforced Concrete Beams

The effects of seawater corrosion and freeze-thaw cycles on the structural behavior of fatigue damaged reinforced concrete (FDRC) beams were experimentally studied. Results show that the residual strength of FDRC beams reduces as the fatigue load level (the ratio of maximum fatigue load to the ultimate static load) increases. The reduction in the loading capacity of FDRC beams in atmosphere environment was about 6.5% and 17.8% for given fatigue load levels of 0.2 and 0.3, respectively. However, if FDRC beams are exposed to the environment of seawater wet-dry cycles or to the environment of alternating actions of freeze-thaw and seawater immersion, as expected during the service life of RC bridge structures in coastal regions or in cold coastal regions, a more rapid reduction in the strength and stiffness of the beams is observed. The significance of an accurate simulation of working load and service condition RC bridge structures in coastal regions and cold coastal regions is highlighted

Enhancing Model Performance in Multilingual Information Retrieval with Comprehensive Data Engineering Techniques

In this paper, we present our solution to the Multilingual Information Retrieval Across a Continuum of Languages (MIRACL) challenge of WSDM CUP 2023\footnote{https://project-miracl.github.io/}. Our solution focuses on enhancing the ranking stage, where we fine-tune pre-trained multilingual transformer-based models with MIRACL dataset. Our model improvement is mainly achieved through diverse data engineering techniques, including the collection of additional relevant training data, data augmentation, and negative sampling. Our fine-tuned model effectively determines the semantic relevance between queries and documents, resulting in a significant improvement in the efficiency of the multilingual information retrieval process. Finally, Our team is pleased to achieve remarkable results in this challenging competition, securing 2nd place in the Surprise-Languages track with a score of 0.835 and 3rd place in the Known-Languages track with an average nDCG@10 score of 0.716 across the 16 known languages on the final leaderboard

Nonmetric Trait Correlation: A Look at Environmental and Biological Influences on Third Trochanter Formation Among Pre-Contact Upper Midwest Populations

Nonmetric traits of the human skeleton are thought to correlate with genetic and/or environmental influences; however, to what extent each may affect the presence of nonmetric traits has not been clearly substantiated in the literature. Nonmetric traits as defined by Larsen are, discrete or quasi-continuous anatomical entities often expressed as gradations from absence to full expression (1997:305). More precisely, nonmetric traits are anomalies that express themselves in the skeleton and are recorded as absent or present. A third trochanter is one of many nonmetric traits present in the femur and is defined by Finnegan as, a rounded tubercle that can be found at the superior end of the gluteal crest of the femur (1978:25). The third trochanter is considered an enthesopathy as well as a nonmetric trait because it is the insertion point of the gluteus maximus muscle, the most superficial muscle in the gluteal region (Gray 1918:426). Recent studies (Hawkey and Merbs 1995, Knusel 2000) indicate that enthesopathies are closely linked to patterns of subsistence, habitual activities and geographic location. It should also be noted that enthesopathies have been directly related to pathology, trauma, biological diversity, age, hormonal, and rheumatic conditions (Hawkey and Merbs 1995, Jurmain 1999). This research will examine the correlation between sex, age, pathology, and environmental influences on the presence of third trochanters in pre-contact populations of the Upper Midwest region of the United States

Using Deep Mixture-of-Experts to Detect Word Meaning Shift for TempoWiC

This paper mainly describes the dma submission to the TempoWiC task, which achieves a macro-F1 score of 77.05% and attains the first place in this task. We first explore the impact of different pre-trained language models. Then we adopt data cleaning, data augmentation, and adversarial training strategies to enhance the model generalization and robustness. For further improvement, we integrate POS information and word semantic representation using a Mixture-of-Experts (MoE) approach. The experimental results show that MoE can overcome the feature overuse issue and combine the context, POS, and word semantic features well. Additionally, we use a model ensemble method for the final prediction, which has been proven effective by many research works

Understanding the Robustness of 3D Object Detection with Bird's-Eye-View Representations in Autonomous Driving

3D object detection is an essential perception task in autonomous driving to understand the environments. The Bird's-Eye-View (BEV) representations have significantly improved the performance of 3D detectors with camera inputs on popular benchmarks. However, there still lacks a systematic understanding of the robustness of these vision-dependent BEV models, which is closely related to the safety of autonomous driving systems. In this paper, we evaluate the natural and adversarial robustness of various representative models under extensive settings, to fully understand their behaviors influenced by explicit BEV features compared with those without BEV. In addition to the classic settings, we propose a 3D consistent patch attack by applying adversarial patches in the 3D space to guarantee the spatiotemporal consistency, which is more realistic for the scenario of autonomous driving. With substantial experiments, we draw several findings: 1) BEV models tend to be more stable than previous methods under different natural conditions and common corruptions due to the expressive spatial representations; 2) BEV models are more vulnerable to adversarial noises, mainly caused by the redundant BEV features; 3) Camera-LiDAR fusion models have superior performance under different settings with multi-modal inputs, but BEV fusion model is still vulnerable to adversarial noises of both point cloud and image. These findings alert the safety issue in the applications of BEV detectors and could facilitate the development of more robust models.Comment: 8 pages, CVPR202

An Alternative Method for Understanding User-Chosen Passwords

We present in this paper an alternative method for understanding user-chosen passwords. In password research, much attention has been given to increasing the security and usability of individual passwords for common users. Few of them focus on the relationships between passwords; therefore we explore the relationships between passwords: modification-based, similarity-based, and probability-based. By regarding passwords as vertices, we shed light on how to transform a dataset of passwords into a password graph. Subsequently, we introduce some novel notions from graph theory and report on a number of inner properties of passwords from the perspective of graph. With the assistance of Python Graph-tool, we are able to visualize our password graph to deliver an intuitive grasp of user-chosen passwords. Five real-world password datasets are used in our experiments to fulfill our thorough experiments. We discover that (1) some passwords in a dataset are tightly connected with each other; (2) they have the tendency to gather together as a cluster like they are in a social network; (3) password graph has logarithmic distribution for its degrees. Top clusters in password graph could be exploited to obtain the effective mangling rules for cracking passwords. Also, password graph can be utilized for a new kind of password strength meter

Toward improving control performance of myoelectric arm prosthesis by adding wrist position feedback

Wearing a myoelectric prosthesis is a basic way for limb amputees to restore their lost limb functions in the activities of daily living (ADLs). However, it is estimated that around 40% of amputees refuse the prosthesis. One of the primary reasons would be that the current prostheses lack appropriate sensory feedback. Currently, the amputees only depend on their visual feedback (Vis-FB) when using their arm prostheses. It would be difficult for them to accurately control the wrist position, which is vital for flexible manipulation in ADLs. This manuscript designed a myoelectric arm prosthesis with wrist position feedback (WP-FB). To study the effect level of position feedback on prosthetic control, two tests were performed. The vibrotactile perception range test aims to analyze the perception sensitivity of the vibration in humans and obtain the optimal perception range utilized in the sensory feedback test. The sensory feedback test analyzes the effectiveness of the position feedback by comparing three feedback methods of Vis-FB, WP-FB, and a combination of Vis-FB and WP-FB (VP-FB). These tests were conducted by asking six able-bodied subjects to perform 20 movement combinations of five target positions. The WP-FB was transiently activated with five vibrating motors embedded in an armband to stimulate the arm stump when the prosthetic wrist rotates to the target positions. Our experimental results showed that when WP-FB was added to the prosthetic control, the absolute angular error (AAE) of the prosthetic wrist declined from 4.50° to 1.08° while the success rate 3 (SR3) increased from 0.34 to 0.84, respectively. This study demonstrates the importance of WP-FB to the effective control of the arm prosthesis