Miracle-dz/UniFAR-FTUs huggingface dataset:
On the dimension of a certain measure in the plane

We study the Hausdorff dimension of a measure related to a positive weak solution of a certain partial differential equation in a simply connected domain in the plane. Our work generalizes work of Lewis and coauthors when the measure is $p$ harmonic and also for $p=2$, the well known theorem of Makarov regarding the Hausdorff dimension of harmonic measure relative to a point in a simply connected domain.
Exploratory Factor Analysis of Entrepreneurial Behaviour Among Business Owners in Food Processing Industry

The purpose of this paper is to identify the key domains of entrepreneurial behaviour among business owner in food processing industry. The study utilized a deductive research design and quantitative method. There are twenty-one statements about entrepreneurial behaviour to discover a core action associated with entrepreneurial behaviour. An entrepreneurial behaviour is defined as small family business strategic behaviour that captures specific entrepreneurial aspects (Walker and Brown, 2004). In additions, it is the actions taken by the small business owner to achieve business performance (Delmar, 1996). According to Kirkley (2015), entrepreneurial behaviour as self determined human action is based on a specific set of values which the individual uses to make decisions about how to behave in situations that a meaningful to their business. The questionnaires focused primarily on the meaning of entrepreneurial behaviour as self-determination to be succeed in business. There were 70 respondents were selected by simple random sampling. The data were analysed by Exploratory Factor Analysis (EFA) and categorised into relevant domains. The result shows four specific domains of entrepreneurial behaviour business owner in food processing industry, namely, leadership, pro- activeness, committed and risk taking. The finding items to each of these domains are consistent with the small family business perspective. The practical implication is the presence of the specific core action associated with entrepreneurial behaviour. The business owner should employ the four core action to sustain the business. The result of this study is importance to academician in small business area, business advisor from government and non government sectors, and small family business owner.
Using Machine Learning and Probabilistic Frameworks to Enhance Incident and Problem Management: Automated Ticket Classification and Structuring

Problem determination and resolution (PDR) is at the core of Incident and Problem Management. PDR is the process of detecting an anomaly in a monitored system, identifying the nature of the anomaly in view of routing to the appropriate support team, determining the root cause responsible for the anomaly and fixing or eliminating the cause of the problem. The cost of PDR represents a substantial part of operational costs, and faster, more effective PDR can contribute to a substantial reduction in system administration costs. The methodologies described by the authors in this chapter relate to automation of critical aspects of PDR, such as problem classification for targeted diagnosis and structuring of solved problem tickets for offering systematized resolution to the support personnel.
Youth as Stakeholders and Their Engagement Towards Government Programmes (GP)

The study looks into youth as Stakeholders and their engagement in government programmes. The implementation of programmes by a country, government or company will generate fruitful outcomes if the plans and programmes are well received by the stakeholders. Stakeholders are both internal and external. However, the focus of this study is the external stakeholders namely the citizens of this country with specific focus on youth. In the context of Malaysia, generally government programmes are implemented with the aim of improving the quality of life of the people. This study is carried out using focus group discussions (FGD). It presents the findings from the FGD focussing on the young adults of different ethnics. The research questions aimed to answer the following: What are the government programmes identified by the stakeholders? What are the reactions of the stakeholders toward the identified programmes? And to what extent do the stakeholders engage in the identified programmes? From the FGD, it was found that stakeholders identified government programmes from five sectors namely housing projects, transportation, healthcare, education and financial support. Several stakeholders reacted positively toward the benefits of the programmes, however they had negative reactions on certain programmes. Some stakeholders stressed that regardless of the positive and negative aspects of the government programmes, they monitored and showed concern on the effectiveness of the programmes implemented. This is evidence of how engaged youth were in the government programmes. Recommendations were offered by the stakeholders for successful implementation of current and future government programmes. Keywords: Stakeholders, engagement, reaction, youth, government programmes.
Rising Above the Clouds: A Review of the Implications that Cloud Computing Technologies Hold for Education

As technology develops, it transforms the manner in which we engage with each other and society. Thus, it becomes increasingly incumbent upon us to question how the nature and purpose of education should address such transformations. Cloud computing occupies the apex of a developing technological shift in how we construct, access, manipulate and communicate with information through services. As such, it is often argued that the technology has the potential to positively change education not only at the institutional level (schools, universities, etc.) but also at the fundamental level of the students' relationship with their own learning.
Assessing the potential of a region for human capital development

The article presents the results of the research, the purpose of which was to develop a methodology for assessing the potential of a region for the development of its human capital. The proposed methodology is based on a quantitative model for the analysis of indicators of the demographic, economic, educational qualification, psychophysiological and innovation components of a region’s potential that determine the conditions for the development of human capital. When developing the methodology, an index method and a linear scaling method were used. As an object of testing and verification of the methodology, regions belonging to the Siberian Federal District were taken. The object of the research was the Kemerovo region. The calculations that illustrate the application of the proposed methodology, allowed to carry out rapid diagnosis and characterize the potential of the Kemerovo region in the development of human capital in the region. At the same time, the suitability of the methodology was established to identify priority measures to reduce the gap in the values of indicators of the potential of leading regions and outsider regions, to search for the most effective regional management practices that contribute to the development of human capital at the regional level. The results of the assessment of the potential of a region for the development of human capital can be, first of all, the information basis for the activities of regional authorities in the formation of priority goals and objectives, programs and projects for the strategic management of regional socio-economic development aimed at creating conditions for the development of human capital in the territory. The application of a methodology for assessing the potential of a region can be embedded in the process of developing and making strategic and operational decisions on the development of human capital.
Type-Intertwined Separation Logic

Static program analysis can improve programmer productivity and software reliability by definitively ruling out entire classes of programmer mistakes. For mainstream imperative languages such as C, C++, and Java, static analysis about the heap—memory that is dynamically allocated at run time—is particularly challenging because heap memory acts as global, mutable state. This dissertation describes how to soundly combine two static analyses that each take vastly different approaches to reasoning about the heap: type systems and separation logic. Traditional type systems take an alias-agnostic, global view of the heap that affords both fast verification and light-weight annotation of invariants holding over the entire program. Separation logic, in contrast, provides an alias-aware, local view of the heap in which invariants can vary at each program point. In this work, I show how type systems and separation logic can be safely and efficiently combined. The result is type-intertwined separation logic, an analysis that applies traditional type-based reasoning to some regions of the program and separation logic to others—converting between analysis representations at region boundaries—and summarizes some portions of the heap with coarse type invariants and others with precise separation logic invariants. The key challenge that this dissertation addresses is the communication and preservation of heap invariants between analyses. I tackle this challenge with two core contributions. The first is type-consistent summarization and materialization, which enables type-intertwined separation logic to both leverage and selectively violate the global type invariant. This mechanism allows the analysis to efficiently and precisely verify invariants that hold almost everywhere. Second, I describe gated separating conjunction, a non-commutative strengthening of standard separating conjunction that expresses local “dis-pointing” relationships between sub-heaps. Gated separation
Performance of Bridging Algorithms in IEEE 802.15.3 Multi-Piconet Networks

In this chapter, we introduce the bridging problem from the viewpoint of the recent IEEE 802.15. 3 high data rate WPAN, and present alternative solutions that are possible in 802.15. 3 networks. Then, we investigate the performance of a network with two piconets interconnected in a parent-child manner and linked through a bridge device which operates in a master-slave fashion. We have designed an adaptive bandwidth allocation algorithm for bridge down link CTA allocation, and examined the impact of the value of the smoothing constant and threshold hysteresis on the throughput, blocking probability, and average queue size for the downlink queue at the bridge.
Tracking and detecting objects in image sequence

Tracking and detecting arbitrary objects are important in many applications such as video surveillance, video analytics and human-machine interactions. Although many promising methods have been proposed in this area, it is still very challenging to track and detect arbitrary objects due to issues such as complicated motion transformations and occlusions. In this thesis, four pieces of works are developed to address these problems in tracking and detecting objects. The first piece of work addresses learning hierarchical features for visual object tracking by using deep learning. Previously, raw pixel values or hand-crafted features are used to represent target objects. However, these representations are not able to handle large appearance variations of arbitrary target objects. Recently, deep learning has achieved very promising results in speech recognition and image classification. Nevertheless, it is non-trivial to apply deep learning to visual object tracking. Usually, deep neural networks require a lot of training data to learn a large number of network parameters. However, training data is not sufficient for visual object tracking as annotations of a target object are only available in the first frame of a test sequence. To solve this problem, a feature learning algorithm is proposed for visual object tracking by using domain adaptation. First, hierarchical features are learned from auxiliary video sequences by using a two-layer neural network. Embedding the temporal slowness constraint into the stacked network architecture makes learned features robust to complicated motion transformations, and this manipulation is important for visual object tracking. Then, given a target image sequence, a domain adaptation module is proposed to adapt the pre-learned features according to the specific target object. The adaptation is conducted in both two layers of the neural network to include appearance information of the specific target object. As a result, learned hierarchical features can
Peer-to-Peer Protocol (P2PP)

This document defines the Peer-to-Peer Protocol (P2PP), an application-layer protocol, for creating and maintaining an overlay of participant nodes. The overlay can be created using various structured and unstructured peer-to-peer protocols such as Chord, Pastry, Kademlia, Gnutella, and Gia.
Semantic Behavior of Indexed Co-inductive Data Type in Fibrational Setting

Traditional methods such as category theory and coalgebra have some drawbacks to analyze semantic behavior of indexed co-inductive data type. Aiming at the problem above, this paper explored indexed co-inductive data type in programming by Fibrations theory. Our main work was that we firstly made some basic logical structures of indexed co-inductive data type over a fibration such as truth and quotient functor; using endo-functor in base categories and their equation-preserving lifting in total categories, then we analyzed semantic behavior of indexed co-inductive data type; at last we briefly introduced applications of Fibrations theory on indexed co-inductive data type by example. Compared with traditional methods, brief descriptions and flexible expansibility of Fibrations theory can analyze semantic behavior of indexed co-inductive data type accurately, and superior abstractness of Fibrations theory doesn’t rely on particular computing environments to compute semantics.
An Isolated 3 Phase Multilevel Inverter for PV Cell Applications

This study presents a novel topology for multilevel inverters so called cascaded transformer inverter (CTRSI). This topology consists of one DC source and several single-phase transformers. Each single-phase transformers generates three levels with four semiconductor switches and only two switches for all transformers alter the direction of single DC source. Whereas each single-phase transformers in conventional cascaded transformer multilevel inverter includes more switches. Hence, CTRSI has the advantage of a reduced number of components compared with conventional cascaded transformer multilevel inverter. Simulation results carried out by MATLAB/SIMULINK. The results show that the proposed inverter topology is able to reach high-quality output voltages. THD of output voltage is verified using FFT analysis tool
Self-referentiality and neoliberalism in contemporary Argentine cinema

ABSTRACT This chapter examines ways in which filmmaking becomes a self-referential theme in Argentine films in the neoliberal era. Three films will be referred to: Adolfo Aristarain’s Martín (hache) from 1997; Daniel Burak’s Bar El Chino from 2003, and Alejo Flah’s Sexo fácil, películas tristes from 2014. These films all depict the making of international film co-productions primarily between Argentina and Spain and are explicitly concerned with the figure of the Argentine filmmaker, who in the process of filmmaking experiences neoliberalism from the margins of the world economy and more often than not succumbs to its international demands. This body of films criticizes while simultaneously testifying to neoliberal filmmaking practices of the last two decades. The films thus raise meta-critical questions about both their cinematic context and the prevailing economic system in contemporary Argentina to which they belong.
A Note on the Eigenvalues for Periodic Three-Dimensional Jacobi-Perron Algorithms

In their profound study on the connections between Lyapunov theory and approximation properties of Jacobi-Perron algorithm BROISE-ALAMICHEL and GUIVARC’H 2001 proved a generalization of an inequality due to PALEY and URSELL [2]. In this note this inequality is slightly refined for dimension n ¼ 3. This shows that for the
A Range Image Segmentation Algorithm Based on Gaussian Mixture Model

A range image segmentation algorithm based on Gaussian mixture model of surface normal is proposed. It decreases the times of clustering computing by fully utilizing the physical meaning of Gaussian mixture model of surface normal, and achieves automatic model selection via the posterior probabilities computed from the model parameter estimated by Expectation-Maximization (EM) algorithm. Experimental results on 60 real range images from two kinds of range cameras are compared objectively with some popular segmentation algorithms.
Supporting Humans in an Intelligent Manner with Awareness of the Human’s State Using Artificial Intelligence & Machine Learning

: The Artificial Intelligence is the modern era technology which plays a vital role in the modern engineering by using which we can enhance the technology. It not only influence the technology but also it provides a wide range of sophisticated paths for the humans to put his thoughts in terms of machine intelligence. The major factor lies in the Human learning is the decision taking ability is poor. So we are moving towards the Machine and to make a machine more interactive, we think for intelligence. Machine learning as widely used concept in Artificial Intelligence. It is the concept which teaches machines to detect different patterns and to adapt to new circumstances. Now-a-days the concept of machine learning is used in many applications and is a core concept for intelligent systems which leads to the introduction innovative technology and more advance concepts of artificial thinking. Machine Learning can be both experience and explanation based learning. In the field of robotics machine learning plays a vital role, it helps in taking an optimized decision for the machine which eventually increases the efficiency of the machine and more organized way of performing a particular task.
A surgically-implanted intramuscular electrode for an implantable neuromuscular stimulation system

An intramuscular electrode developed for functional neuromuscular stimulation applications, to be used in conjunction with a surgically implanted neuromuscular receiver-stimulator, is described. In vitro experiments indicate that the electrode will maintain a stable position, but is capable of being removed intact, if removal is necessary. When tested in an unbuffered saline environment at the maximum stimulation parameters, the stimulating surface experienced minimal nonprogressive corrosion. A preliminary animal evaluation, comparing four surgically implanted intramuscular electrodes with four epimysial electrodes, is discussed. The intramuscular electrodes all operated properly, producing functional responses indistinguishable from those obtained with epimysial electrodes. <<ETX>>
BIG DATA: INKONSISTENSI DATA DAN SOLUSINYA

Produksi data dunia saat ini mengalami peningkatan eksponensial dari tahun ke tahun. Pertumbuhan volume data yang pesat seiring dengan transaksi data di internet yang terjadi secara masif, bervariasi, serta memiliki struktur yang kompleks ketika data masuk ke media penyimpanan dikenal dengan istilah big data. Big data datang dari berbagai sumber dan memiliki sifat yang heterogen. Karena sifatnya yang heterogen, data bisa saja mengalami ketidakkonsistenan. Data yang mengalami konflik sangat menyulitkan dalam analisis big data untuk pengambilan keputusan. Tulisan ini akan membahas tentang konflik atau inkonsistensi data dalam big data. Di bagian akhir akan dibahas tentang beberapa metode dan algoritma yang digunakan untuk menyelesaikan problem ini.
Energy Efficiency Strategy in D2D Cognitive Networks Using Channel Selection Based on Game Theory and Collaboration

The growth of Device-to-Device (D2D) communications and the extensive use of Wireless Sensor Networks (WSNs) bring new problems such as spectral coexistence and spectrum saturation. Cognitive Radio (CR) appears as a paradigm to solve these problems. The introduction of CR into WSNs as a solution to the spectrum utilization problem could be used not only to increase the reliability of communications, but also to optimize energy consumption. The contribution of this paper is a cognitive lightweight strategy based on game theory and collaboration proposed to save energy consumption in Cognitive Wireless Sensor Networks (CWSNs). The proposed strategy takes advantage of the two main capabilities of CWSNs, the ability to adapt communication parameters, specifically channel allocation, and collaboration among devices. The decision making is modeled through a light noncooperative game designed for low resources networks. Despite the fact that the game used is a noncooperative game, the decision process takes advantage of the collaboration among CWSN nodes in a distributed way. Simulations over Castalia Simulator have been carried out in order to validate the strategy in different scenarios with different interference schemes showing increases in energy savings around 50% depending on the scenario.
Analysis and Visualization of OpenFlow Rule Conflicts

In traditional networks the control and data plane are highly coupled, hindering development. With Software Defined Networking (SDN), the two planes are separated, allowing innovations on either one independently of the other. Here, the control plane is formed by the applications that specify an organization’s policy and the data plane contains the forwarding logic. The application sends all commands to an SDN controller which then performs the requested action on behalf of the application. Generally, the requested action is a modification to the flow tables, present in the switches, to reflect a change in the organization’s policy. There are a number of ways to control the network using the SDN principles, but the most widely used approach is OpenFlow. With the applications now having direct access to the flow table entries, it is easy to have inconsistencies arise in the flow table rules. Since the flow rules are structured similar to firewall rules, the research done in analyzing and identifying firewall rule conflicts can be adapted to work with OpenFlow rules. The main work of this thesis is to implement flow conflict detection logic in OpenDaylight and inspect the applicability of techniques in visualizing the conflicts. A hierarchical edge-bundling technique coupled with a Reingold-Tilford tree is employed to present the relationship between the conflicting rules. Additionally, a table-driven approach is also implemented to display the details of each flow. Both types of visualization are then tested for correctness by providing them with flows which are known to have conflicts. The conflicts were identified properly and displayed by the views.
User experience measurement in the wild

User experience measurement is important for HCI research and for the industry that produce interactive services and products. We want to develop a context-aware user experience measurement. In this paper, we propose a user experience measurement scale, and discuss how to validate the scale in different contexts, implement the scale in context aware prototypes, and evaluate the prototypes in real-life user contexts.