Miracle-dz/UniFAR-FTUs huggingface dataset:
The real numbers in Z

Exact real number computation is a fast growing field with applications varying from debugging to specification of numerical to program. We present a specification of the real numbers represented as infinite lists of signed digits in Z. The expressive power and closeness to usual set theoretical mathematical notation gives us a clean and readable specification which is further directly implementable. A comparison with other formal methods is given together with a partial proof that the object being specified is actually the real numbers.
Proposal of New Medication Sensor to Take Medicines on Time

Currently, there are a lot of diabetes patients all over the world. However, patients can receive treatments such as medical diet, therapeutic exercise, and pharmacotherapy. But, these treatments can’t show effectiveness with some patients because some of the patients lack in daily exercises and 60 percent of the patients forget to take medicines on time. In order to solve such problems, a database system was developed to support the nursing of diabetes patients using mobile phones. However, this system didn’t behave as expected due to the reason that patients are required to keep in mind of the amount of exercise they are doing daily. It is difficult for patients to keep in mind correctly of the exercise amount. Therefore, we had developed a supporting system for diabetes patients. This system can record the amount of exercise of the user automatically, and offer advice accordingly. This system can also recognize the situation of medication, and suggest the correct medication to the user. However, the system is inconvenient because the size of the medication sensor is large. In this study, we proposed a new medication sensor to take medicines on time. This medication sensor is much smaller than the previous medication sensor. This sensor can also recognize the situation of medication, and suggest the correct medication to the user.
A New Distributed Intrusion Detection System Based on Multi-Agent System for Cloud Environment

Cloud computing, like any distributed computing system, is continually exposed to many threats and attacks of various origins. Thus, cloud security is now a very important concern for both providers and users. Intrusion detection systems (IDSs) are used to detect attacks in this environment. The goal of security administrators (for both customers and providers) is to prevent and detect attacks while avoiding disruption of the smooth operation of the cloud. Making IDSs efficient is not an easy task in a distributed environment such as the cloud. This problem remains open, and to our knowledge, there are no satisfactory solutions for the automated evaluation and analysis of cloud security. The features of the multi-agent system paradigm, such as adaptability, collaboration, and distribution, make it possible to handle this evolution of cloud computing in an efficient and controlled manner. As a result, multi-agent systems are well suited to the effective management of cloud security. In this paper, we propose an efficient, reliable and secure distributed IDS (DIDS) based on a multi-agent approach to identify and prevent new and complex malicious attacks in this environment. Moreover, some experiments were conducted to evaluate the performance of our model.
Retaining learners by establishing harmonious relationships in e-learning environment

ABSTRACT Drawing from social resource-social capital theory, this paper aims to clarify and characterize the role of harmonious learner–instructor and learner–learner relationships in promoting experience and retaining learners in online learning environments. Hypotheses are tested by applying a structural equation model and the data are collected from a survey of online learning website (n = 539). The results suggest that harmonious relationships have a positive impact on learners’ experience (i.e. perceived performance, enjoyment and social presence), which, in turn, strengthen learners’ continuous intention to use the e-learning platform. And learners’ expertise moderates the relationships between harmonious relationships and learner experience. Based on the analysis results, this study can provide educational institutions with useful tactics to retain learners in the e-learning environments.
DPWeVote: differentially private weighted voting protocol for cloud-based decision-making

ABSTRACT With the advent of Industry 4.0, cloud computing techniques have been increasingly adopted by industry practitioners to achieve better workflows. One important application is cloud-based decision-making, in which multiple enterprise partners need to arrive an agreed decision. Such cooperative decision-making problem is sometimes formed as a weighted voting game, in which enterprise partners express ‘YES/NO’ opinions. Nevertheless, existing cryptographic approaches to Cloud-Based Weighted Voting Game have restricted collusion tolerance and heavily rely on trusted servers, which are not always available. In this work, we consider the more realistic scenarios of having semi-honest cloud server/partners and assuming maximal collusion tolerance. To resolve the privacy issues in such scenarios, the DPWeVote protocol is proposed which incorporates Randomized Response technique and consists the following three phases: the Randomized Weights Collection phase, the Randomized Opinions Collection phase, and the Voting Results Release phase. Experiments on synthetic data have demonstrated that the proposed DPWeVote protocol managed to retain an acceptable utility for decision-making while preserving privacy in semi-honest environment.
Modeling Advanced Persistent Threats to enhance anomaly detection techniques

Advanced Persistent Threats (APTs) are characterized by their complexity and ability to stay relatively dormant and undetected on a computer system before launching a devastating attack. Numerous unsuccessful attempts have utilized machine learning techniques and rule-based technologies to try and detect these sophisticated attacks. In this paper, we opt for a more theoretical approach to identify unique APT characteristics, distinguishable from other multi-stage attacks. We model four well-known APTs, based on the kill chain framework, and we identify common behavior to create abstract models which describe generalized APT behavior. We ﬁnd that attributes from the Command and Control phase of these attacks provide unique features that can be used by any anomaly detection systems. We further validate how expressive our abstract models are by formalizing a ﬁfth APT and examining the behavior that was not captured.
Time and (Un)conscious Processes - Predictive Anticipatory Activity and Potential Applications

Predictive Anticipatory Activity (PAA) is the physiological and behavioral activity in an organism related to gathering accurate information about future events not through the usual senses, inference, or directly causing the events themselves to occur. It has been demonstrated and replicated in multiple independent and controlled laboratory experiments examining human behavior and physiology and in two animal experimental systems. Aside from the versions of PAA explicitly developed through conscious training, spontaneous PAA may represent an unconscious attempt to prepare organisms for future events. The mechanisms underlying PAA are unknown, and it is not clear that physical laws actually forbid it. It is thus possible that information about physical events is time symmetric in nature, and that conscious experience generally only presents us with a unidirectional flow that we call the “arrow of time. ” Based on these ideas, in this position paper the argument is made that PAA can be thought of as a glimpse into physical reality, not as it is presented to us via the mechanisms that create our conscious experiences, but as it is “beyond the veil” of the conscious mind. Potential research and practical applications for PAA, especially with regard to consciousness in AI systems, are briefly discussed.
Differential Evolution and Local Search based Monarch Butterfly Optimization Algorithm with Applications

Global optimization for nonlinear function is a challenging issue. In this paper, an improved monarch butterfly algorithm based on local search and differential evolution is proposed. Local search strategy is first embedded into original monarch butterfly optimization to enhance the searching capability. Then, differential evolution is incorporated with the aim of balancing the exploration and exploitation. To evaluate the performance of proposed algorithm, some widely-used benchmark functions are tested, and the experiment results show its significant superiority compared with other state-of-the-art methods. In addition, the proposed algorithm is applied to PID tuning and FIR filter design, the superiority of solving practical problems is verified.
MASTER THESIS JELLE HOFLAND

—Automation in a domestic environment is not ﬂawless and human interference will be necessary, for implementing robots in this environment. When remotely controlling semi-autonomous robots, proposed concepts can be divided into two main concepts: To trade control back and forth between the human and the operator and to share control continuously. However, a deep analysis lacks about when either of these meth-ods is useful. This study focuses on comparing task completion time and task behavior Trading Control (TC) and Haptic Shared Control (HSC) using a mix of accurate models of the tasks and models with a small translational offset. These are examined in the current mix as well as separated into models that were accurate or did contain an offset. In remote execution of a constraint motion task, we hypothesize Haptic Shared control to have a lower task completion time compared to Trading Control when inaccuracies are present. When the model is fully accurate, on the other hand, we hypothesize Trading Control to have a lower task completion time compared to haptic shared control. Participants used a 6DOF haptic manipulator to control a virtual robot arm, in order to open a simulated drawer. An autonomous controller was developed based on a model that was perfectly accurate (50% of the time), or that had an effective endpoint error (50% of the time). Control over the automation was either traded by pressing a space bar or continuously shared through haptic shared control. In trials with a translational offset, Haptic shared control had a lower task completion time compared to trading control. In the trials with a perfectly accurate model of the task, Trading Control had the beneﬁt of lowering peak collision force and increasing smoothness of the master input. Therefore more research is needed to better understand when trading control is beneﬁcial compared to haptic shared control.
Verfahren der INLINE-Qualitätssicherung und der zerstörungsfreien Prüfung innerhalb der Fertigungslinie von Faser-Metall-Laminaten

Der Einsatz von glasfaserverstarktem Aluminium ermoglicht aufgrund der geringen Dichte und der Konstruktionsmoglichkeiten eines Laminates eine signifikante Gewichtsreduzierung gegenuber einem herkommlichen Rumpfhautfeld aus monolithischen Aluminiumwerkstoffen. Neben der Entwicklung einer Bauweise fur sehr dunne Faser-Metall-Laminate, welche gleichzeitig eine deutlich grosere Leistungsfahigkeit im Hinblick auf Ermudung, Schadenstoleranz und Impact-Verhalten gegenuber herkommlichen Bauteilen aus Aluminium aufweisen, steht eine neue Prozesskette fur die automatisierte Rumpfschalenherstellung im Mittelpunkt der Arbeiten. Der Fertigungsprozess fur Faser-Metall-Laminate besteht aus vielen Einzelschritten, die letztlich zum Endbauteil fuhren. Anstatt die Qualitat des Bauteils nach jedem der Einzelschritte zu untersuchen, sollen auftretende Abweichungen dann entdeckt werden, wenn sie auftreten. Auf diese Weise konnen rechtzeitig Korrekturmasnahmen bereitgestellt und in den laufenden Prozess eingegriffen werden. Somit konnen Prozessabweichungen vermieden und aufwandige Reparaturen und Ausschuss verringert werden. Wahrend fur die Einzelschritte im Fertigungsprozess von Faser-Metall-Laminaten eine Inline-Qualitatssicherung entwickelt und integriert wird, wird das Endbauteil zerstorungsfrei gepruft. Neben neuen Konzepten steht hierbei die automatisierte Auswertung der erhobenen Messdaten im Fokus, das die bisherigen Aufwande wesentlich reduzieren soll. Im Rahmen dieser Veroffentlichung werden die oben genannten Themen der Inline-Qualitatssicherung und der zerstorungsfreien Prufung mit automatisierter Auswertung detailliert dargestellt.
Bitcoin Price Prediction with Neural Networks

In this work, we use the LSTM version of Recurrent Neural Networks, to predict the price of Bitcoin. In order to develop a better understanding on its price influencers and the general vision of this brilliant innovation, we first give a brief perspective on Bitcoin and its economics. Then we describe the dataset, which is comprised of data from stock market indices, sentiment, blockchain and Coinmarketcap. Further on this investigation, we show the usage of LSTM architecture with the aforementioned time series. To conclude, we outline the results of predicting Bitcoin price for 30 and 60 days ahead.
FutureCrafting. A Speculative Method for an Imaginative AI

The issue I explore with this position paper concerns dominant cultural scripts around Artificial Intelligence (AI) and the need to imagine different narratives in light of machine learning’s autonomous performativity. The aim is to offer a philosophical reflection, not only to sidestep narratives of techno-determinism, dystopia and existential risk to mankind, but also to speculate on how to imagine a (more) benevolent AI based on uncertainty and the co-evolution of humans and technology. The paper presents the speculative methodology I call FutureCrafting: a forensic, diagnostic and divinatory method that investigates the possibility of other discourses, equally powerful in building reality, constructing futures and having tangible impact. FutureCrafting is speculation at the juncture of design and philosophy, pivoting around the open-ended figuration of the what if…? It articulates collaboration rather than competition, coevolution rather than antagonism, and privileges the indeterminate and the imaginative. To conclude, the paper makes reference to the non-human intelligence of the octopus and to how this can inform a more imaginative AI.
An introduction to persuasive systems design for sustainability (Invited Talk)

— Persuasive systems design can be applied to applications for green information systems and technology and sustainability. Beyond sustainability, we claim that the topics addressed in this presentation will play a centermost role in most of software design in future and they will become relevant for all software business. Results from a variety of research projects utilizing the PSD model and the BCSS framework will be presented
Conflict Resolution Analysis on the Revitalization Plan of Tradisional Market: A study on Kiaracondong traditional market in Bandung city

Traditional market in Indonesia is in poor condition in terms of store image and market governance. One of the most crowded traditional market in Indonesia, Kiaracondong Market, is certainly not an exception. One common problem that has caused prolonged conflicts in Kiaracondong Market is the behavior of street vendors who sell in front of the market and block the flow of consumers. This behavior has provoked traditional market tenants that have been put at huge disadvantage. In response to that conflict, the municipal government of Bandung City decided to revitalize Kiaracondong market in 2017. Unexpectedly, this plan even adds more conflict between the three parties: municipal government, street vendors, and market tenants. This study aims to seek for stable solution for conflicts that rose from the revitalization plan of Kiaracondong market. The data used in the analysis are collected by interviewing the representative of street vendors, market tenants, and the municipal government of Bandung City. Then, the results are analyzed by using Graph Model for Conflict Resolution (GMCR). The results of stability and sensitivity analysis are also being discussed. Based on the analysis of the first phase of conflict, the stable solution found on which market tenants are suggested to hold the protest to municipal government about the behavior of street vendors. Meanwhile the street vendors are advised to continue to trade around Kiaracondong Market. In respect to stable solution for the second frame, market tenants are suggested to demand for free kiosk and approve market revitalization as planned by The Government of Bandung City. Keywords—traditional market; conflict resolution; street vendor; market revitalization; GMCR.
Biometric Encryption using image processing

Biometric EncryptionTM is an algorithm which has been developed to securely link and retrieve a digital key using the interaction of a biometric image, such as a fingerprint, with a secure block of data, known as a BioscryptTM. The key can be used, for example, as an encryption/decryption key. The BioscryptTM comprises a filter function, which is calculated using an image processing algorithm, and other information which is required to first retrieve, and then verify the validity of, the key. The key is retrieved using information from an output pattern formed via the interaction of the biometric image with the filter function. Therefore, the filter function must be designed so that it produces a consistent output pattern (and thus, key). The filter function must also be designed to be secure (i.e. information about the fingerprint cannot be retrieved from the filter function). The consistency of the output pattern and the security of the filter function are the two topics discussed in this paper.
FLASH: Is the 20th Century Hero Really Gone? Large-Scale Evaluation on Flash Usage & Its Security and Privacy Implications

Although the Adobe Flash browser plugin steadily lost popularity throughout the last few years, Flash content still regularly appears when browsing the web. Known for its infamous security track record, Flash remains a challenge in making web browsing more secure. In this paper, we present a largescale measurement of the current uses of Flash, based on a crawl of the top 1 million websites. The different types of measurements result in most detailed classification of Flash uses to date. In particular, special attention is payed to Flash usage related to user tracking, as well as to malicious Flash files used by malvertising or exploit kits. We present Garrick, a novel crawling framework, which is based on a full-fledged Mozilla Firefox browser. Garrick is able to mimic any browser, plugin and operating system configuration so that fingerprinting scripts can be tricked to deliver malicious Flash files. Our measurements show that Flash is still used by approximately 7.5% of the top 1 million websites, with 62% of the Flash content coming from third-parties such as ad networks. In general, on popular websites Flash usage is higher compared to less prominent websites and a bigger share of Flash content on these sites comes from third-parties. From a security perspective, malicious Flash files served by highly targeted malvertising campaigns are an ongoing challenge.
Node Activities Learning(NAL)Approach to Build Secure and Privacy-Preserving Routing in Wireless Sensor Networks

Wireless networks are becoming the most popular in today communication systems, where users prefer to have wireless connectivity regardless of its geographic location. But the open environment of wireless communication increasing threat on the wireless networks under diverse network circumstances. The random and dynamic activity increases the vulnerability due to the complete dependency on the intermediate nodes which frequently join and leave the network. It is extremely significant to have a secure routing in such a dynamic network to preserve the data privacy. In this paper, we propose a secure and privacy routing based on Node Activities Learning (NAL) approach. This approach knows the runtime activities of the node to predict the probability of activity transformation for the intentional and unintentional activities which interrupt the data communication and affects the privacy. The mean of privacy is decided based on the node individual trust factor. It also suggests a method for the node which loses their trust due to the unintentional activities. A simulation-based evaluation study shows positive improvisation in secure routing in different malicious node environment.
The Act-Editor User''s Guide: A Manual for Version2

An electrical connector for providing a leakproof releasable electrical connection through a wall even over a wide temperature range. The connector has at least one terminal with the terminal including a ceramic annulus having a sleeve secured at one end that is secured to a base of the connector and a cap secured on the other end with a closed tube to which the electrical connection is made extending through the annulus and being secured to the cap.
Realization of 2-D Variable IIR Digital Filter Structures with a Small Amount of Calculations for Coefficient Update

This paper proposes 2-D variable IIR digital filter structures with a small amount of calculations for coefficient update. The proposed realization method uses the 2-D parallel allpass structure derived from the separable denominator 2-D filter as the prototype structure for 2-D variable digital filters. In order to reduce the amount of calculations, all the redundant first-order complex allpass sections are combined by modularization of the variable structure. Furthermore, we can realize a very compact variable structure with a minimal number of first-order complex allpass sections by combining complex allpass sections with their complex conjugate allpass sections. Comparison of the calculation loads of the variable structures is presented to demonstrate that the amount of calculations for coefficient update of the proposed variable structure is far less than that of the original and the modular variable structure.
Max‐min energy‐efficient subchannel assignment and power allocation in interference‐limited OFDMA heterogeneous networks with QoS guarantee

This paper investigates fairness among all small‐cell users (SCUs) in terms of energy efficiency for the uplink transmission of interference‐limited orthogonal frequency‐division multiple access–based heterogeneous networks. Each SCU is treated by a minimum data rate. In addition, a maximum tolerable interference for the macro base station has been considered. The resulting resource allocation problem is formulated as a nonconvex mixed‐integer nonlinear problem. In order to solve the mixed‐integer nonlinear problem, the subchannel assignment and the power allocation are applied separately; an efficient subchannel assignment algorithm has been proposed where the co‐tier and cross‐tier interference in the most general form has been taken into account. Then, to solve the power allocation subproblem, an iterative algorithm has been proposed by applying generalized fractional programming and sequential convex programming when a specified subchannel assignment is in hand. Performance of the proposed model has been evaluated, and simulation results indicate a fair resource allocation with a very high energy efficiency among SCUs comparing the state‐of‐the‐art solutions.