Kiintymysmallit ja opettaja-oppilassuhde kiintymyssuhdeteorian valossa

Tiivistelmä. Tutkielman aiheena on kiintymysmallit ja opettaja-oppilassuhde kiintymyssuhdeteorian valossa. Tutkielmassa käsitellään eri kiintymysmalleja ja niiden ilmenemismuotoja kouluikäisellä lapsella luokkahuonekontekstissa. Tutkielmassa tarkastellaan myös näkökulmia, joita kiintymyssuhdeteorian avulla on saatu opettaja-oppilassuhteen ja sen laadun määrittelyyn. Lisäksi selvitetään lapsen kiintymyssuhteen laadun vaikutusta opettaja-oppilassuhteen laatuun. Tutkielma on rajattu koskemaan keskilapsuutta. Tavoitteena on koota yhteen aikaisempaa kirjallisuutta ja tutkimustietoa edellä mainituista aihepiireistä narratiivisen kirjallisuuskatsauksen keinoin. Tutkielmassa on kolme tutkimuskysymystä. Ensimmäinen tutkimuskysymys on, mitä eri kiintymysmalleilla tarkoitetaan ja miten ne ilmenevät kouluikäisellä lapsella luokkahuonekontekstissa. Toinen tutkimuskysymys on, millaisia näkökulmia kiintymyssuhdeteorian avulla on saatu opettaja-oppilassuhteen ja sen laadun määrittelyyn. Kolmas tutkimuskysymys on, miten lapsen kiintymyssuhteen laatu vaikuttaa opettaja-oppilassuhteen laatuun. Tutkimustulosten mukaan kiintymysmalli viittaa lapsen tapaan säädellä läheisyyttä vanhempaan stressitilanteissa, kuten myös vanhemman tapaan vastata lapsen pyrkimyksiin läheisyyden säätelyssä. Tämän perusteella on eroteltu neljä eri kiintymysmallia, jotka ovat turvallinen, välttelevä, ristiriitainen ja jäsentymätön kiintymysmalli. Näiden mallien tyypilliset piirteet saattavat ilmetä lapsen käyttäytymisessä luokkahuonekontekstissa etenkin silloin, kun lapsi on stressaantunut. Kiintymyssuhdeteorian näkökulmien mukaan opettaja-oppilassuhdetta ei voida pitää kiintymyssuhteena, mutta siinä on havaittu olevan samankaltaisia kiintymyskomponentteja kuin vanhemman ja lapsen välisessä kiintymyssuhteessa. Opettaja-oppilassuhteen laatu liittyy näihin kiintymyskomponentteihin ja sitä määritellään kolmella suhdeulottuvuudella, jotka ovat läheisyys, konflikti ja riippuvuus. Tutkimustulokset viittaavat myös siihen, että lapsen kiintymyssuhteen laadulla saattaa olla samansuuntaisia vaikutuksia opettaja-oppilassuhteen laatuun.The attachment styles and teacher-student relationship in the light of attachment theory. Abstract. The topic of this bachelor’s thesis is the attachment styles and teacher-student relationship in the light of attachment theory. The thesis deals with the different attachment styles and their manifestation in a school-aged child in the classroom context. The thesis also examines the perspectives that have been obtained with the help of attachment theory to define teacher-student relationship and its quality in the primary school context. In addition, the thesis also reports the effect of the quality/type of child’s attachment on the quality of teacher-student relationship. The thesis concerns middle childhood. The aim of the thesis is to gather literature and scientific research about the above-mentioned topics by the means of narrative literature review. The thesis has three research questions. The first research question is, how are the different attachment styles defined in the previous literature and how do they manifest in a school-aged child in a classroom context. The second research question is, what kind of perspectives have been obtained with the help of attachment theory to define teacher-student relationship and its quality. The third research question is, how does the quality of child’s attachment affect the quality of teacher-student relationship. According to the research results, the attachment styles refer to child’s way of regulating proximity with parent in stressful situations as well as parent’s response to child’s efforts to regulate proximity. Based on this, there are four different attachment styles which have been defined as secure, avoidant, ambivalent and disorganized style. Typical features of these styles may be manifested in child’s behavior in the classroom context, especially when the child is stressed. From the perspectives of attachment theory, teacher-student relationship cannot be considered as an attachment relationship, but it has been found to have similar attachment components to parent-child attachment. The quality of teacher-student relationship is related to these attachment components and is defined by three dimensions which are closeness, conflict and dependence. Research findings also suggest that the quality of child’s attachment may have parallel effects on the quality of teacher-student relationship

Routine Learning: from Reactive to Proactive Environments

Abstract Technological development and various information services becoming common has had the effect that data from everyday situations is available. Utilizing this technology and the data it produces in an efficient manner is called context-aware or ubiquitous computing. The research includes the specifications of each application, the requirements of the communication systems, issues of privacy, and human - computer interaction, for example. The environment should learn from the user's behaviour and communicate with the user. The communication should not be only reactive, but proactive as well. This thesis is divided into two parts, both representing methodology for enabling intelligence in our everyday surroundings. In part one, three different applications are defined for studying context-recognition and routine learning: a health monitoring system, a context-aware health club application, and automatic device configuration in an office space. The path for routine learning is straight forward and it is closely related to pattern recognition research. Sensory data is collected from users in various different situations, the signals are pre-processed, and the contexts recognized from this sensory data. Furthermore, routine learning is realized through association rules. The routine learning paradigm developed here can utilize already recognized contexts despite their meaning in the real world. The user makes the final decision on whether the routine is important or not, and has authority over every action of the system. The second part of the thesis is built on experiments on identifying a person walking on a pressure-sensitive floor. Resolving the characteristics of the special sensor producing the measurements, which lies under the normal flooring, is one of the tasks of this research. The identification is tested with Hidden Markov models and Learning Vector Quantization. The methodology developed in this thesis offers a step along the long road towards functional and calm intelligent environments

Non-interactive zero-knowledge for blockchain:a survey

Abstract We survey the state-of-the-art non-interactive zero-knowledge argument schemes and their applications in confidential transactions and private smart contracts on blockchain. The main goal of this paper is to serve as a reference for blockchain application developers in finding the most suitable scheme for a particular use case. We give an overview and compare the state-of-the-art protocols for confidential transactions and private smart contracts regarding the protection of the transaction graph and amounts, data and functionality. However, our main focus is on state-of-the-art zero-knowledge argument schemes. We briefly describe their backgrounds, proof lengths and computational complexities and discuss their cryptographic security models. Our focus is on seminal, otherwise notable and, especially, implemented methods that are ready to be applied in practice. We also survey the existing implementations of transforming computations into circuit representations required by those methods. We note that the existing schemes have different strengths and drawbacks regarding usability, setup, proof length and proving and verification costs

CNN4GCDD:a one-dimensional convolutional neural network-based model for gear crack depth diagnosis

Abstract Gear crack is one of the common failures in transmission systems. With the gradual expansion of cracks, it may cause tooth fracture. Therefore, it is of great significance to study the fault diagnosis of gear cracks. Vibration signals with time sequence are widely used in gear fault diagnosis. Extracting key fault features from vibration signals determines the accuracy of fault diagnosis models. This paper takes spur gears as research objects, and proposes a model for diagnosing gear crack depth based on one-dimensional convolutional neural network (short for CNN4GCDD). In order to identify crack depths, we collect the vibration signals from three gears with various crack depths and a normal gear without cracks. CNN4GCDD uses the original vibration signal as the input, adaptively extracts features, and makes crack depth diagnosis through the convolutional neural network. The experimental results demonstrate that CNN4GCDD can directly use the original time-domain signal for crack depth diagnosis, and make a high accurate prediction

Weathering the reallocation storm:large-scale analysis of edge server workload

Abstract Efficient service placement and workload allocation methods are necessary enablers for the actively studied topic of edge computing. In this paper, we show that under certain circumstances, the number of superfluous workload reallocations from one edge server to another may grow to a significant proportion of all user tasks — a phenomenon we present as a reallocation storm. We showcase this phenomenon on a city-scale edge server deployment by simulating the allocation of user task workloads in a number of scenarios capturing likely edge computing deployments and usage patterns. The simulations are based on a large real-world data set of city-wide Wi-Fi network connections in 2013—2014, with more than 47M connections over ca. 800 access points. We identify the conditions for avoiding the reallocation storm for three common edge-based reallocation strategies, and study the latency-workload trade-off related to each strategy. As a result, we find that the superfluous reallocations vanish when the edge server capacity is increased above a certain threshold, unique for each reallocation strategy, peaking at ca. 35% of top ES workload. Further, while a reallocation strategy aiming to minimize reallocation distance consistently resulted in the worst reallocation storms, the two other strategies, namely, a random reallocation strategy, and a bottom-up strategy which always chooses the edge server with the lowest workload as a reallocation target, behave nearly identically in terms of latency as well as the reallocation storm in dense edge deployments. Since the random strategy requires much less coordination, we recommend it over the bottom-up one in dense ES deployments

The intersection of blockchain and 6G technologies

Abstract The fifth generation (5G) wireless networks are on the way to be deployed around the world. The 5G technologies target to support diverse vertical applications by connecting heterogeneous devices and machines with drastic improvements in terms of high quality of service, increased network capacity and enhanced system throughput. However, 5G systems still remain a number of security challenges that have been mentioned by researchers and organizations, including decentralization, transparency, risks of data interoperability, and network privacy vulnerabilities. Furthermore, the conventional techniques may not be sufficient to deal with the security requirements of 5G. As 5G is generally deployed in heterogeneous networks with massive ubiquitous devices, it is quite necessary to provide secure and decentralized solutions. Motivated from these facts, in this paper we provide a state-of-the-art survey on the integration of blockchain with 5G networks and beyond. In this detailed survey, our primary focus is on the extensive discussions on the potential of blockchain for enabling key 5G technologies, including cloud computing, edge computing, Network Function Virtualization, Network Slicing, and D2D communications. We then explore and analyse the opportunities that blockchain potentially empowers important 5G services, ranging from spectrum management, data sharing, network virtualization, resource management to interference management, federated learning, privacy and security provision. The recent advances in the applications of blockchain in 5G Internet of Things are also surveyed in a wide range of popular use-case domains, such as smart healthcare, smart city, smart transportation, smart grid and UAVs. The main findings derived from the comprehensive survey on the cooperated blockchain-5G networks and services are then summarized, and possible research challenges with open issues are also identified. Lastly, we complete this survey by shedding new light on future directions of research on this newly emerging area

SemanPhone:combining semantic and phonetic word association in verbal learning context

Abstract This paper proposes an effective way to discover and memorize new English vocabulary based on both semantic and phonetic associations. The method we proposed aims to automatically find out the most associated words of a given target word. The measurement of semantic association was achieved by calculating cosine similarity of two-word vectors, and the measurement of phonetic association was achieved by calculating the longest common subsequence of phonetic symbol strings of two words. Finally, the method was implemented as a web application

Blockchain-based mobility-as-a-service

Abstract In this paper, we present a vision for a blockchain-based Mobility-as-a-Service (MaaS) as an application of edge computing. In current MaaS systems, a central MaaS operator plays a crucial role serving an intermediate layer which manages and controls the connections between transportation providers and passengers with several other features. Since the willingness of public and private transportation providers to connect to this layer is essential in the current realization of MaaS, in our vision, to eliminate this layer, a novel blockchain-based MaaS is proposed. The solution also improves trust and transparency for all stakeholders as well as eliminates the need to make commercial agreements with separate MaaS agents. From a technical perspective, the power of computing and resources are distributed to different transportation providers at the edge of the network providing trust in a decentralised way. The blockchain-based MaaS has the potential to emerge as the main component for a smart city transportation offering efficiency and reducing carbon dioxide emissions