13,578 research outputs found

    Combined Nutrition and Exercise Interventions in Community Groups

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    Diet and physical activity are two key modifiable lifestyle factors that influence health across the lifespan (prevention and management of chronic diseases and reduction of the risk of premature death through several biological mechanisms). Community-based interventions contribute to public health, as they have the potential to reach high population-level impact, through the focus on groups that share a common culture or identity in their natural living environment. While the health benefits of a balanced diet and regular physical activity are commonly studied separately, interventions that combine these two lifestyle factors have the potential to induce greater benefits in community groups rather than strategies focusing only on one or the other. Thus, this Special Issue entitled “Combined Nutrition and Exercise Interventions in Community Groups” is comprised of manuscripts that highlight this combined approach (balanced diet and regular physical activity) in community settings. The contributors to this Special Issue are well-recognized professionals in complementary fields such as education, public health, nutrition, and exercise. This Special Issue highlights the latest research regarding combined nutrition and exercise interventions among different community groups and includes research articles developed through five continents (Africa, Asia, America, Europe and Oceania), as well as reviews and systematic reviews

    Towards A Practical High-Assurance Systems Programming Language

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    Writing correct and performant low-level systems code is a notoriously demanding job, even for experienced developers. To make the matter worse, formally reasoning about their correctness properties introduces yet another level of complexity to the task. It requires considerable expertise in both systems programming and formal verification. The development can be extremely costly due to the sheer complexity of the systems and the nuances in them, if not assisted with appropriate tools that provide abstraction and automation. Cogent is designed to alleviate the burden on developers when writing and verifying systems code. It is a high-level functional language with a certifying compiler, which automatically proves the correctness of the compiled code and also provides a purely functional abstraction of the low-level program to the developer. Equational reasoning techniques can then be used to prove functional correctness properties of the program on top of this abstract semantics, which is notably less laborious than directly verifying the C code. To make Cogent a more approachable and effective tool for developing real-world systems, we further strengthen the framework by extending the core language and its ecosystem. Specifically, we enrich the language to allow users to control the memory representation of algebraic data types, while retaining the automatic proof with a data layout refinement calculus. We repurpose existing tools in a novel way and develop an intuitive foreign function interface, which provides users a seamless experience when using Cogent in conjunction with native C. We augment the Cogent ecosystem with a property-based testing framework, which helps developers better understand the impact formal verification has on their programs and enables a progressive approach to producing high-assurance systems. Finally we explore refinement type systems, which we plan to incorporate into Cogent for more expressiveness and better integration of systems programmers with the verification process

    In-context Autoencoder for Context Compression in a Large Language Model

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    We propose the In-context Autoencoder (ICAE) for context compression in a large language model (LLM). The ICAE has two modules: a learnable encoder adapted with LoRA from an LLM for compressing a long context into a limited number of memory slots, and a fixed decoder which is the target LLM that can condition on the memory slots for various purposes. We first pretrain the ICAE using both autoencoding and language modeling objectives on massive text data, enabling it to generate memory slots that accurately and comprehensively represent the original context. Then, we fine-tune the pretrained ICAE on a small amount of instruct data to enhance its interaction with various prompts for producing desirable responses. Our experimental results demonstrate that the ICAE learned with our proposed pretraining and fine-tuning paradigm can effectively produce memory slots with 4×4\times context compression, which can be well conditioned on by the target LLM to respond to various prompts. The promising results demonstrate significant implications of the ICAE for its novel approach to the long context problem and its potential to reduce computation and memory overheads for LLM inference in practice, suggesting further research effort in context management for an LLM. Our code and data will be released shortly.Comment: Work in progres

    IR Design for Application-Specific Natural Language: A Case Study on Traffic Data

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    In the realm of software applications in the transportation industry, Domain-Specific Languages (DSLs) have enjoyed widespread adoption due to their ease of use and various other benefits. With the ceaseless progress in computer performance and the rapid development of large-scale models, the possibility of programming using natural language in specified applications - referred to as Application-Specific Natural Language (ASNL) - has emerged. ASNL exhibits greater flexibility and freedom, which, in turn, leads to an increase in computational complexity for parsing and a decrease in processing performance. To tackle this issue, our paper advances a design for an intermediate representation (IR) that caters to ASNL and can uniformly process transportation data into graph data format, improving data processing performance. Experimental comparisons reveal that in standard data query operations, our proposed IR design can achieve a speed improvement of over forty times compared to direct usage of standard XML format data

    Бази даних NoSQL. Конспект лекцій

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    У навчальному посібнику наведено матеріали, необхідні для практичної апробації теоретичних знань з організації баз даних NoSQL і використання їх у сучасних інформаційних системах. Подано блок навчально-методичного забезпечення, який включає перелік знань і вмінь по кожній темі, термінологічний словник, фрагменти навчального коду і завдання для самоконтролю студентами засвоєння знань. Конспект лекцій призначено для студентів вищих навчальних закладів, що навчаються за спеціальністю спеціальності 121 «Інженерія програмного забезпечення», освітньої програми «Інженерія програмного забезпечення мультимедійних та інформаційно-пошукових систем» та вивчають навчальну дисципліну «Програмне забезпечення інформаційно-пошукових систем 1. Бази даних NoSQL».The training manual contains the materials necessary for practical testing of theoretical knowledge on the organization of NoSQL databases and their use in modern information systems. A block of educational and methodological support is provided, which includes a list of knowledge and skills on each topic, a glossary, fragments of the educational code and tasks for self-monitoring by students of knowledge acquisition. The lecture notes are intended for students of higher educational institutions studying in the specialty 121 "Software engineering" of the educational program "Software engineering of multimedia and information-search systems" and studying the discipline "Software of information-search systems 1. NoSQL databases "

    AIDA: Legal Judgment Predictions for Non-Professional Fact Descriptions via Partial-and-Imbalanced Domain Adaptation

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    In this paper, we study the problem of legal domain adaptation problem from an imbalanced source domain to a partial target domain. The task aims to improve legal judgment predictions for non-professional fact descriptions. We formulate this task as a partial-and-imbalanced domain adaptation problem. Though deep domain adaptation has achieved cutting-edge performance in many unsupervised domain adaptation tasks. However, due to the negative transfer of samples in non-shared classes, it is hard for current domain adaptation model to solve the partial-and-imbalanced transfer problem. In this work, we explore large-scale non-shared but related classes data in the source domain with a hierarchy weighting adaptation to tackle this limitation. We propose to embed a novel pArtial Imbalanced Domain Adaptation technique (AIDA) in the deep learning model, which can jointly borrow sibling knowledge from non-shared classes to shared classes in the source domain and further transfer the shared classes knowledge from the source domain to the target domain. Experimental results show that our model outperforms the state-of-the-art algorithms.Comment: 13 pages, 15 figure

    A Lightweight Type System with Uniqueness and Typestates for the Java Cryptography API

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    Java cryptographic APIs facilitate building secure applications, but not all developers have strong cryptographic knowledge to use these APIs correctly. Several studies have shown that misuses of those cryptographic APIs may cause significant security vulnerabilities, compromising the integrity of applications and exposing sensitive data. Hence, it is an important problem to design methodologies and techniques, which can guide developers in building secure applications with minimum effort, and that are accessible to non-experts in cryptography. In this thesis, we present a methodology that reasons about the correct usage of Java cryptographic APIs with types, specifically targeting to cryptographic applications. Our type system combines aliasing control and the abstraction of object states into typestates, allowing users to express a set of user-defined disciplines on the use of cryptographic APIs and invariants on variable usage. More specifically, we employ the typestate automaton to depict typestates within our type system, and we control aliases by applying the principle of uniqueness to sensitive data. We mainly focus on the usage of initialization vectors. An initialization vector is a binary vector used as the input to initialize the state for the encryption of a plaintext block sequence. Randomization and uniqueness are crucial to an initialization vector. Failing to maintain a unique initialization vector for encryption can compromise confidentiality. Encrypting the same plaintext with the same initialization vector always yields the same ciphertext, thereby simplifying the attacker's task of guessing the cipher pattern. To address this problem practically, we implement our approach as a pluggable type system on top of the EISOP Checker Framework. To minimize the cryptographic expertise required by application developers looking to incorporate secure computing concepts into their software, our approach allows cryptographic experts to plug in the protocols into the system. In this setting, developers merely need to provide minimal annotations on sensitive data—requiring little cryptographic knowledge. We also evaluated our work by performing experiments over one benchmark and 7 real-world Java projects from Github. We found that 6 out 7 projects have security issues. In summary, we found 12 misuses in initialization vectors

    Accurate Battery Modelling for Control Design and Economic Analysis of Lithium-ion Battery Energy Storage Systems in Smart Grid

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    Adoption of lithium-ion battery energy storage systems (Li-ion BESSs) as a flexible energy source (FES) has been rapid, particularly for active network management (ANM) schemes to facilitate better utilisation of inverter based renewable energy sources (RES) in power systems. However, Li-ion BESSs display highly nonlinear performance characteristics, which are based on parameters such as state of charge (SOC), temperature, depth of discharge (DOD), charge/discharge rate (C-rate), and battery-aging conditions. Therefore, it is important to include the dynamic nature of battery characteristics in the process of the design and development of battery system controllers for grid applications and for techno-economic studies analyzing the BESS economic profitability. This thesis focuses on improving the design and development of Li-ion BESS controllers for ANM applications by utilizing accurate battery performance models based on the second-order equivalent-circuit dynamic battery modelling technique, which considers the SOC, C-rate, temperature, and aging as its performance affecting parameters. The proposed ANM scheme has been designed to control and manage the power system parameters within the limits defined by grid codes by managing the transients introduced due to the intermittence of RESs and increasing the RES penetration at the same time. The validation of the ANM scheme and the effectiveness of controllers that manage the flexibilities in the power system, which are a part of the energy management system (EMS) of ANM, has been validated with the help of simulation studies based on an existing real-life smart grid pilot in Finland, Sundom Smart Grid (SSG). The studies were performed with offline (short-term transient-stability analysis) and real-time (long-term transient analysis) simulations. In long-term simulation studies, the effect of battery aging has also been considered as part of the Li-ion BESS controller design; thus, its impact on the overall power system operation can be analyzed. For this purpose, aging models that can determine the evolving peak power characteristics associated with aging have been established. Such aging models are included in the control loop of the Li-ion BESS controller design, which can help analyse battery aging impacts on the power system control and stability. These analyses have been validated using various use cases. Finally, the impact of battery aging on economic profitability has been studied by including battery-aging models in techno-economic studies.Aurinkosähköjärjestelmien ja tuulivoiman laajamittainen integrointi sähkövoimajärjestelmän eri jännitetasoille on lisääntynyt nopeasti. Uusiutuva energia on kuitenkin luonteeltaan vaihtelevaa, joka voi aiheuttaa nopeita muutoksia taajuudessa ja jännitteessä. Näiden vaihteluiden hallintaan tarvitaan erilaisia joustavia energiaresursseja, kuten energiavarastoja, sekä niiden tehokkaan hyödyntämisen mahdollistaviea älykkäitä ja aktiivisia hallinta- ja ohjausjärjestelmiä. Litiumioniakkuihin pohjautuvien invertteriliitäntäisten energian varastointijärjestelmien käyttö joustoresursseina aktiiviseen verkonhallintaan niiden pätö- ja loistehon ohjauksen avulla on lisääntynyt nopeasti johtuen niiden kustannusten laskusta, modulaarisuudesta ja teknisistä ominaisuuksista. Litiumioniakuilla on erittäin epälineaariset ominaisuudet joita kuvaavat parametrit ovat esimerkiksi lataustila, lämpötila, purkaussyvyys, lataus/ purkausnopeus ja akun ikääntyminen. Akkujen ominaisuuksien dynaaminen luonne onkin tärkeää huomioida myös akkujen sähköverkkoratkaisuihin liittyvien säätöjärjestelmien kehittämisessä sekä teknis-taloudellisissa kannattavuusanalyyseissa. Tämä väitöstutkimus keskittyy ensisijaisesti aktiiviseen verkonhallintaan käytettävien litiumioniakkujen säätöratkaisuiden parantamiseen hyödyntämällä tarkkoja, dynaamisia akun suorituskykymalleja, jotka perustuvat toisen asteen ekvivalenttipiirien akkumallinnustekniikkaan, jossa otetaan huomioon lataustila, lataus/purkausnopeus ja lämpötila. Työssä kehitetyn aktiivisen verkonhallintajärjestelmän avulla tehtävät akun pätö- ja loistehon ohjausperiaatteet on validoitu laajamittaisten simulointien avulla, esimerkiksi paikallista älyverkkopilottia Sundom Smart Gridiä simuloimalla. Simuloinnit tehtiin sekä lyhyen aikavälin offline-simulaatio-ohjelmistoilla että pitkän aikavälin simulaatioilla hyödyntäen reaaliaikasimulointilaitteistoa. Pitkän aikavälin simulaatioissa akun ikääntymisen vaikutus otettiin huomioon litiumioniakun ohjauksen suunnittelussa jotta sen vaikutusta sähköjärjestelmän kokonaistoimintaan voitiin analysoida. Tätä tarkoitusta varten luotiin akun ikääntymismalleja, joilla on mahdollista määrittää akun huipputehon muutos sen ikääntyessä. Akun huipputehon muutos taas vaikuttaa sen hyödynnettävyyteen erilaisten pätötehon ohjaukseen perustuvien joustopalveluiden tarjoamiseen liittyen. Lisäksi väitöstutkimuksessa tarkasteltiin akkujen ikääntymisen vaikutusta niiden taloudelliseen kannattavuuteen sisällyttämällä akkujen ikääntymismalleja teknis-taloudellisiin tarkasteluihin.fi=vertaisarvioitu|en=peerReviewed
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