Reviewerly/exHarmony huggingface dataset:
A Unified Approach to Nested and Non-Nested Slots for Spoken Language Understanding

As chatbots become more popular, multi-intent spoken language understanding (SLU) has received unprecedented attention. Multi-intent SLU, which primarily comprises the two subtasks of multiple intent detection (ID) and slot filling (SF), has the potential for widespread implementation. The two primary issues with the current approaches are as follows: (1) They cannot solve the problem of slot nesting; (2) The performance and inference rate of the model are not high enough. To address these issues, we suggest a multi-intent joint model based on global pointers to handle nested and non-nested slots. Firstly, we constructed a multi-dimensional type-slot label interaction network (MTLN) for subsequent intent decoding to enhance the implicit correlation between intents and slots, which allows for more adequate information about each other. Secondly, the global pointer network (GP) was introduced, which not only deals with nested and non-nested slots and slot incoherence but also has a faster inference rate and better performance than the baseline model. On two multi-intent datasets, the proposed model achieves state-of-the-art results on MixATIS with 1.6% improvement of intent Acc, 0.1% improvement of slot F1 values, 3.1% improvement of sentence Acc values, and 1.2%, 1.1% and 4.5% performance improvements on MixSNIPS, respectively. Meanwhile, the inference rate is also improved.
MalDBA: Detection for Query-Based Malware Black-Box Adversarial Attacks

The increasing popularity of Industry 4.0 has led to more and more security risks, and malware adversarial attacks emerge in an endless stream, posing great challenges to user data security and privacy protection. In this paper, we investigate the stateful detection method for artificial intelligence deep learning-based malware black-box attacks, i.e., determining the presence of adversarial attacks rather than detecting whether the input samples are malicious or not. To this end, we propose the MalDBA method for experiments on the VirusShare dataset. We find that query-based black-box attacks produce a series of highly similar historical query results (also known as intermediate samples). By comparing the similarity among these intermediate samples and the trend of prediction scores returned by the detector, we can detect the presence of adversarial samples in indexed samples and thus determine whether an adversarial attack has occurred, and then protect user data security and privacy. The experimental results show that the attack detection rate can reach 100%. Compared to similar studies, our method does not require heavy feature extraction tasks or image conversion and can be operated on complete PE files without requiring a strong hardware platform.
Parallelization Strategies for Graph-Code-Based Similarity Search

The volume of multimedia assets in collections is growing exponentially, and the retrieval of information is becoming more complex. The indexing and retrieval of multimedia content is generally implemented by employing feature graphs. Feature graphs contain semantic information on multimedia assets. Machine learning can produce detailed semantic information on multimedia assets, reflected in a high volume of nodes and edges in the feature graphs. While increasing the effectiveness of the information retrieval results, the high level of detail and also the growing collections increase the processing time. Addressing this problem, Multimedia Feature Graphs (MMFGs) and Graph Codes (GCs) have been proven to be fast and effective structures for information retrieval. However, the huge volume of data requires more processing time. As Graph Code algorithms were designed to be parallelizable, different paths of parallelization can be employed to prove or evaluate the scalability options of Graph Code processing. These include horizontal and vertical scaling with the use of Graphic Processing Units (GPUs), Multicore Central Processing Units (CPUs), and distributed computing. In this paper, we show how different parallelization strategies based on Graph Codes can be combined to provide a significant improvement in efficiency. Our modeling work shows excellent scalability with a theoretical speedup of 16,711 on a top-of-the-line Nvidia H100 GPU with 16,896 cores. Our experiments with a mediocre GPU show that a speedup of 225 can be achieved and give credence to the theoretical speedup. Thus, Graph Codes provide fast and effective multimedia indexing and retrieval, even in billion-scale use cases.
Continuity: Sharing Space in teamLab’s Digital Ecosystems

In 2021, the Asian Art Museum of San Francisco inaugurated the opening of its new contemporary wing with teamLab: Continuity. The immersive exhibition spanned six galleries and was fully interactive via sensors and digital projection mapping technology; flowers bloom and grow, flying crows burst into colorful chrysanthemums, and butterflies are born or killed at a moment’s touch. The digital objects dynamically interact with one another and with humans, blurring boundaries between art, participant, and technology. This article examines Continuity as a “collective interactive experience” situated within a digital ecosystem. It explores teamLab’s approach to the natural environment and its digital replication, with a focus on the relationship between humans and machines in shared exhibition spaces.
The Syntax–Pragmatics Interface in Heritage Languages: The Use of anche (“Also”) in German Heritage Speakers of Italian

This paper deals with the use of anche (“also”) by German heritage speakers of Italian (“IHSs”). Previous research showed that anche and its German counterpart auch share many features but also display language-specific characteristics. According to previous research on bilingualism, heritage speakers show cross-linguistic influence (“CLI”) when a linguistic phenomenon is at the syntax–pragmatics interface and there is a partial overlap in the two languages at stake. Therefore, we expect the use of anche in IHSs to be influenced by CLI. By analysing data from a semi-spontaneous corpus, we investigate the production of anche in order to understand which factors shape the grammar of the IHSs. Our results indicate that a subset of IHSs uses anche in the same way as in homeland Italian. The other informants display CLI effects of different types: on the one hand, they have two positions in the clausal structure for anche dedicated to different syntactic–pragmatic contexts, as in German, and they overextend the use of anche as a modal particle. On the other hand, the intonational properties of anche are not affected by CLI.
On the Informationization Development of University Education Management

With the development of information technology, it is also very necessary for the construction of university management information technology. It can not only improve the management level and quality of the university, but also promote better progress and development of the university. The realization of management informatization is based on computer technology and information technology. In the reform of university management, information technology and management must be combined together. The author mainly starts from the main factors affecting the construction of university management information, aiming at the existing problems, puts forward several strategies to solve the problems, hoping to promote the construction of university management information better.
Studying the Effects of Being Einstein: An Experiment in Social Virtual Reality

Previous research has found that when using virtual reality, a person can have a sense of ownership over the body that is being substituted for their own in the virtual world, and that the body&amp;rsquo;s appearance may lead to different behavioral, attitudinal, and perceptual changes. As Virtual Reality (VR) becomes more widespread, it is increasingly important to understand the effects on its users. This study utilized a novel methodology to conduct remote testing in virtual reality, leveraging a popular social virtual reality platform to test whether participants using Einstein as their virtual body performed better at a cognitive task than participants using other virtual bodies, and did not find any effect or correlation of the virtual body with any of the factors measured. The results suggest that the effects of virtual embodiment on the user stemming from the virtual body&amp;#39;s appearance is more complex than previously assumed, warranting further study.
A Gradient‐Cost Multiobjective Alternate Framework for Variational Quantum Eigensolver with Variable Ansatz

Abstract Variational quantum eigensolver (VQE), aiming at determining the ground state energy of a quantum system described by a Hamiltonian on noisy intermediate scale quantum (NISQ) devices. However, the accuracy and trainability of the current VQE algorithm are significantly influenced due to the barren plateau (BP), the non‐negligible gate error and limited coherence time in NISQ devices. To tackle these issues, a gradient‐cost multiobjective alternate framework with variable ansatz is proposed. A theoretical framework is first proposed for VQE with variable ansatz (VA‐VQE) via alternately solving a multiobjective optimization problem defined by cost function values and gradient magnitudes and the original VQE problem. Then, a novel implementation method based on the double ε‐greedy strategy with the candidate tree and modified multiobjective genetic algorithm is proposed. As a result, the local optima are avoided both in ansatz and parameter perspectives, the BP phenomenon is alleviated, and the stability of output ansatz is enhanced. The experimental results indicate that this framework shows considerably average improvement of the error and stability by 59.6% and 78.8% compared with the state‐of‐the‐art cost‐criterion‐based VA‐VQE implementation, and 54.1% and 73.5% compared with the gradient‐criterion‐based counterpart, respectively, with lower quantum costs.
Study of vertically mounted photovoltaic modules and their influence on the production of electrical energy in free-standing photovoltaic systems using PVGIS-CMSAF

Abstract The paper inhere explores the impact of the azimuth angle of vertically mounted bifacial photovoltaic modules on annual electricity generation. At the recent years bifacial photovoltaic modules are introduced to the market, opening new opportunities for increasing efficiency of electricity production and decreasing of the space needed for installation. The purpose of the current study is to obtain and evaluate the annual electricity production of bifacial vertically mounted photovoltaic modules in dependence on the orientation. Comparative analysis has been made between the efficiency and annual energy yield of bifacial vertically mounted PV modules and classically installed PV modules. All the calculations and analyses have been made with the aid of the software product PVGIS-CMSAF. Despite of the controversial increase of efficiency of bifacial vertically mounted photovoltaic modules compared to classically installed photovoltaic modules, the study had confirmed some of their advantages: they require less space for installation; can be used also as PV fences or noise barriers; in some cases the land of installation can be cultivated, used for agriculture or animal husbandry.
CSMOT: Make One-Shot Multi-Object Tracking in Crowded Scenes Great Again

The current popular one-shot multi-object tracking (MOT) algorithms are dominated by the joint detection and embedding paradigm, which have high inference speeds and accuracy, but their tracking performance is unstable in crowded scenes. Not only does the detection branch have difficulty in obtaining the accurate object position, but the ambiguous appearance of features extracted by the re-identification (re-ID) branch also leads to identity switches. Focusing on the above problems, this paper proposes a more robust MOT algorithm, named CSMOT, based on FairMOT. First, on the basis of the encoder-decoder network, a coordinate attention module is designed to enhance the information interaction between channels (horizontal and vertical coordinates), which improves its object-detection abilities. Then, an angle-center loss that effectively maximizes intra-class similarity is proposed to optimize the re-ID branch, and the extracted re-ID features are made more discriminative. We further redesign the re-ID feature dimension to balance the detection and re-ID tasks. Finally, a simple and effective data association mechanism is introduced, which associates each detection instead of just the high-score detections during the tracking process. The experimental results show that our one-shot MOT algorithm achieves excellent tracking performance on multiple public datasets and can be effectively applied to crowded scenes. In particular, CSMOT decreases the number of ID switches by 11.8% and 33.8% on the MOT16 and MOT17 test datasets, respectively, compared to the baseline.
The impact of work pressure and work completion justification on intentional nonmalicious information security policy violation intention

As businesses have had to change how they operate due to the coronavirus pandemic, the need for remote work has risen. With the continuous advancements in technology and increases in typical job demands, employees need to increase their work productivity beyond regular work hours in the office. This type of work environment creates even more opportunities for security breaches due to employees intentionally violating information security policy violations. Although explicitly prohibited by information security policies (ISP), organizations have observed that employees bring critical data out of the office to complete their work responsibilities remotely. Consequently, developing a deeper understanding of how work pressure may influence employees to violate ISPs intentionally is crucial for organizations to protect their critical information better. Based upon the fraud triangle theory, this study proposes the opportunity to copy critical data, work pressure, and work completion justification as the primary motivational factors behind why employees copy critical company data to unsecured storage devices to work at home. A survey was conducted of 207 employees from a marketing research firm. The results suggest that opportunity, work pressure, and work completion justification are positively related to nonmalicious ISP violation intentions. Furthermore, the interaction effect between work completion justification and work pressure on the ISP violation intention is significant and positive. This study provides new insights into our understanding of the roles of work pressure and work completion justification on intentional nonmalicious ISP violation behaviors.
Building the Leeds Monolingual and Parallel Legal Corpora of Arabic and English Countries’ Constitutions: Methods, Challenges and Solutions

Abstract Arabic corpora have existed since the last decade of the past century. Although they are constantly increasing, more advanced tools and morpho-syntactically annotated Arabic corpora are still needed for research and teaching. Likewise, parallel and specialised corpora are rare despite the growing need to use them in empirical linguistic investigations of authentic Arabic texts and for language and translation teaching. Therefore, building legal corpora will pave the way for more research in Arabic legal translation, an area which is under-researched worldwide. This paper aims to discuss the building of a collection of specialised parallel and monolingual legal corpora. In particular, it will discuss the building of diachronic corpora, which include all available constitutions of 22 Arabic countries. The aim of building all available versions of these constitutions is two-fold: (1) interdisciplinary corpus-based and socio-cultural investigations and (2) research-led and blended-learning pedagogical approaches to translation teaching and learning. Thus, these corpora are of great value to translation trainers and researchers, law academics and professionals, and governmental, non-governmental and international organisations. The paper will demonstrate the process of building these specialised complex corpora and the challenges encountered throughout this process. Among the challenges faced during the data collection and processing phases are (1) limitations of finding the original constitutions for each Arabic country since some of them date back to 1922; (2) file conversion and the difficulty of choosing one Optical Character Recognition (OCR) tool to rely on for the Arabic language since many lack accuracy, efficiency as well as encoding issues in Arabic.
Web-based Faculty Development Management System

As the world kicks back from the aftermath of the COVID-19 pandemic, educational institutions have thus embraced the significant contribution of digitization in their day-to-day operations. As a university, Cebu Technological University Tuburan Campus had also implemented hybrid transactions, providing digital measures to most of its processes including delivery of instructions, students information systems as well as biometric daily time record. This project was developed to provide a database for faculty profile which is responsive to the professional growth of faculty members in order to provide ready reference where needed like organizational changes, among others. The system was built using PHP, HTML, CSS, Bootstrap, JavaScript, and MySQL. Upon testing, the web-based faculty development management system was able to accept faculty registration, handle profile enhancement by individual faculty users as well as output reports according to pre-specified keyword such as subjects handled, designations, academic rank and educational background. Further improvements of the system were also noted like research expertise matching for the purposes of peer reviews and references for consultancy and expert opinions.
Research on Synchronous Cooperation between Computer Information Technology and Network Security Application

The development and application of computer information technology is based on the major premise of the network security environment. To achieve the sustainable development of computer information technology, it is necessary to establish a safe and stable network environment. The advancement and development of network security technology is driven by computers. Information technology is developed based on the problems presented in the development process. From this point of view, there is a complementary relationship between the development of computer information technology and network security. This article is a research on the synchronization and coordination between the development of computer information technology and network security, and aims to promote the development of computer information technology through the establishment of a network security environment.
Current Situation and Development Direction of Medical Image Processing Technology in the Background of Big Data

With the progress of society and the development of technology, digital technology has been widely used in current life practices. From the perspective of practical application effects, digital technology has not only greatly improved people's work efficiency, but also significantly improved the quality of work. From the perspective of the current application of digital technology, digital image processing is very common. This work benefits from the digital technology and computer foundation, so the quality of image processing is higher, and the use effect is higher. The emergence and development of the main content of image enhancement and restoration, image segmentation, and image analysis, and based on the latest progress in this field, this paper briefly describes the latest hotspots in five main research areas of digital image processing technology, and finally summarizes the main challenges and future development directions in the field of digital image processing technology.
The varieties of bifocal Grassmann tensors

Abstract Grassmann tensors arise from classical problems of scene reconstruction in computer vision. In particular, bifocal Grassmann tensors, related to a pair of projections from a projective space onto view spaces of varying dimensions, generalize the classical notion of fundamental matrices. In this paper, we study in full generality the variety of bifocal Grassmann tensors focusing on its birational geometry. To carry out this analysis, every object of multi-view geometry is described both from an algebraic and geometric point of view, e.g., the duality between the view spaces, and the space of rays is explicitly described via polarity. Next, we deal with the moduli of bifocal Grassmann tensors, thus showing that this variety is both birational to a suitable homogeneous space and endowed with a dominant rational map to a Grassmannian.
Research into the fundamental building block of quantum theorem of the unified force field

This is a work based on the extension of the work of Professor James Clerk Maxwell and Albert Einstein into a new framework of science built on provable mathematical theorem which serves as a basis for unifications of the fundamental forces which all together have become impossible to unify under the current framework of General relativity and Quantum Field theory. It is to be used as a piece for inspiring new innovations, discovering and exploring the terrains of the difficult pathways in physics where our modern physical theories have failed. This work is meant to be adapted and used by various physics professionals who are working on extending the frontiers of physics or providing solutions to problems that cannot be handled by current physics framework. In summary it is an inspirational tool that hopefully will help our professional in physics out there. It interpretations and applications is subject to the personal inspirations the reader who is a professional can derived from the work for his or her personal usage.
Malignant breast lesions detection in histopathological images based on the combination of bioinspired texture descriptors and deep features

Breast cancer is a neoplasm resulting from the multiplication of abnormal cells in the breast tissue that initially form nodules or thickening. The survival of patients with the disease can be highly effective in cases where the diagnosis is early. However, this diagnosis requires the analysis of extensive histopathological breast tissue samples by specialists. This task is considered complex and may require the attention of the pathologist for a long period of time. Fortunately, computational methods, which include digital image processing and deep learning, can help quickly identify tumour malignancies on images from these scans and speed up diagnosis. Thus, this work proposes a methodology for the automatic diagnosis of malignant breast lesions on histopathological images based on the mutual measurement of bioinspired texture features (BiT) and deep learning features. Additionally, in this study, we also evaluated the effect of methods of colour normalisation to reduce colour variation in the images. The proposed methodology obtained a result of 92.9% accuracy with the random forest classifier. These numbers show that a combination of BiT with deep features produces better results than the techniques applied individually, and show that the proposed method can be used to compose computer-aided detection systems.