Miracle-dz/UniFAR-FTUs huggingface dataset:
Instance Generator and Problem Representation to Improve Object Oriented Code Coverage

Search-based approaches have been extensively applied to solve the problem of software test-data generation. Yet, test-data generation for object-oriented programming (OOP) is challenging due to the features of OOP, e.g., abstraction, encapsulation, and visibility that prevent direct access to some parts of the source code. To address this problem we present a new automated search-based software test-data generation approach that achieves high code coverage for unit-class testing. We first describe how we structure the test-data generation problem for unit-class testing to generate relevant sequences of method calls. Through a static analysis, we consider only methods or constructors changing the state of the class-under-test or that may reach a test target. Then we introduce a generator of instances of classes that is based on a family of means-of-instantiation including subclasses and external factory methods. It also uses a seeding strategy and a diversification strategy to increase the likelihood to reach a test target. Using a search heuristic to reach all test targets at the same time, we implement our approach in a tool, JTExpert, that we evaluate on more than a hundred Java classes from different open-source libraries. JTExpert gives better results in terms of search time and code coverage than the state of the art, EvoSuite, which uses traditional techniques.
Motivating Commodity Multi-Core Processor Design for System-level Error Protection

—In this paper we analyze the reliability and availability features in several commodity chip multiprocessors (CMPs) and find that they have numerous single points of failure. Failures in some system components, e.g., interconnect, cache controller and memory controller logic, leave CMPs susceptible to error even if the computation is dual modular redundant (DMR) or triple modular redundant (TMR). Furthermore, even though some replicated resources are present in CMPs, they can not be used effectively for providing system-level protection because of the lack of fault isolation in shared components. We describe a CMP design that can provide system-level error protection. The proposed design provides mode configuration features in hardware to tolerate errors in any component. The proposed CMP has two modes: a high performance mode where most of the resources are applied towards performance and a high-availability mode that uses resources, in a redundant manner, to provide tolerance against errors. Our design requires minimal hardware changes and can retain the commodity economics and performance advantages of current CMPs.
Distinct Internalization Pathways of Human Amylin Monomers and Its Cytotoxic Oligomers in Pancreatic Cells

Toxic human amylin oligomers and aggregates are implicated in the pathogenesis of type 2 diabetes mellitus (TTDM). Although recent studies have shown that pancreatic cells can recycle amylin monomers and toxic oligomers, the exact uptake mechanism and trafficking routes of these molecular forms and their significance for amylin toxicity are yet to be determined. Using pancreatic rat insulinoma (RIN-m5F) beta (β)-cells and human islets as model systems we show that monomers and oligomers cross the plasma membrane (PM) through both endocytotic and non-endocytotic (translocation) mechanisms, the predominance of which is dependent on amylin concentrations and incubation times. At low (≤100 nM) concentrations, internalization of amylin monomers in pancreatic cells is completely blocked by the selective amylin-receptor (AM-R) antagonist, AC-187, indicating an AM-R dependent mechanism. In contrast at cytotoxic (µM) concentrations monomers initially (1 hour) enter pancreatic cells by two distinct mechanisms: translocation and macropinocytosis. However, during the late stage (24 hours) monomers internalize by a clathrin-dependent but AM-R and macropinocytotic independent pathway. Like monomers a small fraction of the oligomers initially enter cells by a non-endocytotic mechanism. In contrast a majority of the oligomers at both early (1 hour) and late times (24 hours) traffic with a fluid-phase marker, dextran, to the same endocytotic compartments, the uptake of which is blocked by potent macropinocytotic inhibitors. This led to a significant increase in extra-cellular PM accumulation, in turn potentiating amylin toxicity in pancreatic cells. Our studies suggest that macropinocytosis is a major but not the only clearance mechanism for both amylin’s molecular forms, thereby serving a cyto-protective role in these cells.
The Incidence of Domestic Violence Against Women and Children: An Analysis of Reported Cases Within the Domestic Violence and Victims Support Unit (Dovvsu) At The Asokwa Police Station in Kumasi-Ghana

The incidence of domestic violence is a source of great worry to society at large. Victims are suffering while perpetrators seem to be enjoying the act. While children and women are been abused at homes and domestic settings, authorities responsible to protect and safeguard themselves show gross reluctant in their operations and measures to help victims of domestic violence. This is an act serious violation of human right calls for empirical investigation on reported cases of domestic violence against women with the domestic violence and victims support unit at the Asokwa Police station in Kumasi-Ghana. The study sought to identify the major causes of domestic violence at victims home, the effects of domestic violence on women and children and ways to curb domestic violence against women and children. The study adopted a case study design where data was collected through questionnaire and victims records on reported domestic violence. The study revealed that domestic violence has negative effects on victims as respondents indicated that they suffered from injuries, guilt, anger, depression/anxiety, shyness, nightmares, disruptiveness, irritability, and problems getting along with others. The study found that children who experience domestic violence perform poor in schools and experience vicarious trauma, show signs of exaggerated startle response, hyper-vigilance, nightmares, and intrusive thoughts. The study recommended that law enforcement authority such as the police should victims by ensuring that perpetrators are given the right punishment to serve as deterrence for future offenders.
MOTHER: a new generation of talking heads providing a flexible articulatory control for video-realistic speech animation

This article presents the first version of a talking head, called MOTHER (MOrphable Talking Head for Enhanced Reality), based on an articulatory model describing the degrees-offreedom of visible (lips, cheeks.) but also partially or indirectly visible (jaw, tongue.) speech articulators. Skin details are rendered using texture mapping/blending techniques. We illustrate here the flexibility of such an articulatory control of video-realistic speaking faces by first demonstrating its ability in tracking facial movements by an optical-to-articulatory inversion using an analysis-by-synthesis technique. The stability and reliability of the results allow the automatic inversion of large video sequences. Inversion results are here used to build automatically a coarticulation model for the generation of facial movements from text. It improves the previous Text-To- AudioVisual-Speech (TTAVS) synthesizer developed at the ICP both in terms of the accuracy and realism.
MENTAL HEALTH AND EMOTION REGULATION AMONG REFUGEE STUDENTS IN MALAYSIA

Title of Thesis: MENTAL HEALTH AND EMOTION REGULATION AMONG REFUGEE STUDENTS IN MALAYSIA Nicole Marie Gosnell, Master of Arts, 2017 Thesis Directed By: Professor, Colleen R. O’Neal, Counseling, Higher Education, and Special Education The global refugee crisis has propelled over 65.3 million refugees into flight, including 33 million children (UNHCR, 2016). This study utilizes a mixed-methods design to examine mental health and emotion regulation among post-conflict Southeast Asian refugee children. To understand stressors that may cause mental health challenges, this study explores themes raised in qualitative interviews addressing oppression in Burma, flight to Malaysia, and life in Malaysia. Quantitative study participants included 90 refugee children in Malaysia aged 10-19 years (M = 14.22, 74.4% Burmese, 51.1% female). Measures included the Kiddie-Schedule for Affective Disorders and Schizophrenia-Present and Lifetime Version (K-SADS-PL) and the Emotions as a Child (EAC) Qualitative participants included four refugee boys who participated in a group interview about their individual experiences. This study examined: rates of PTSD and MDD among refugee students, the relation between emotion regulation and mental health, and the unique post-conflict stressors experienced by refugee children. MENTAL HEALTH AND EMOTION REGULATION AMONG REFUGEE STUDENTS IN MALAYSIA By Nicole Marie Gosnell Thesis submitted to the Faculty of the Graduate School of the University of Maryland, College Park, in partial fulfillment of the requirements for the degree of Master of the Arts 2017 Advisory Committee: Professor Colleen O’Neal, Chair Professor Mary Ann Hoffman Professor Emeritus William Strein © Copyright by Nicole Marie Gosnell 2017
Hot Data Identification for Flash Memory Using Multiple Bloom Filters Dongchul Park and

Hot data identification can be applied to a variety of fields. Particularly in flash memory, it has a critical impact on its performance(due to garbage collection) as well as its li fespan (due to wear leveling). Although this is an issue of paramount importance in flash memory, it is the least investigated one. Moreover, all existing schemes focus only or mainly on a frequency viewpoint. However, recency factor also must be considered as much importantly as the frequency for hot data identification. In this paper, we propose anovel hot data identification scheme adopting multi ple bloom filters to efficiently capture finer-grained recency as well as frequency. In addition to this scheme, we propose awindow-based direct addresscounting(named WDAC) algorithm to approximate an ideal hot dataidentificationasour baseline. Unlike the existing baseline algorithm that cannot appropriately capture recency information due to its exponential batch decay, our WDAC algorithm using a sliding window concept can capture very fine-grained recency information. Our experimental evaluation with diverse realistic workloads including real SSD traces demonstrates that our proposed scheme outperforms the state-of-the-art hot dataidentificationscheme. In particular, our schemenot only consumes lessmemory (50% less) and requires lesscomputational overhead up to 58%, but also improves its performanceup to 65%.
Performance of artificial neural networks in forecasting Costa Rican inflation

The underlying processes that generate economic series such as inflation, unemployment or output gaps are potentially quite complex. Undoubtedly that makes it very difficult to forecast them and has traditionally bent attention to relatively simple linear approaches when trying to model them. Trying to capture nonlinear relationships among inflation and its determinants, this paper applies Artificial Neural Networks (ANN) to forecast Costa Rican inflation. A innovative technique that systematically discriminates among different networks in order to overcome the problem of “over-fitting” a ANN was applied. Forecasts are compared with those obtained from “thick” models and traditional linear techniques. The potentially complex nonlinear relationships between inflation and its short run determinants in an expectations-augmented Phillips Curve scheme are captured with a systematically chosen ANN. Forecasts at different horizons are computed in a rolling exercise in order to test the hypothesis of a better performance of the nonlinear parameterization. Evidence shows that linear techniques do not outperform ANN and, in the case of a Phillips Curve, networks forecasts statistically improve upon linear approaches especially for short run forecast horizons. In most cases, “thick” modeled ANN’s forecasts showed a weak performance compared with systematically chosen ANNs.
Predicting object interactions from contact distributions

Contacts between objects play an important role in manipulation tasks. Depending on the locations of contacts, different manipulations or interactions can be performed with the object. By observing the contacts between two objects, a robot can learn to detect potential interactions between them. Rather than defining a set of features for modeling the contact distributions, we propose a kernel-based approach. The contact points are first modeled using a Gaussian distribution. The similarity between these distributions is computed using a kernel function. The contact distributions are then classified using kernel logistic regression. The proposed approach was used to predict stable grasps of an elongated object, as well as to construct towers out of assorted toy blocks.
Bimanual Motor Coordination in Older Adults Is Associated with Increased Functional Brain Connectivity – A Graph-Theoretical Analysis

In bimanual coordination, older and younger adults activate a common cerebral network but the elderly also have additional activation in a secondary network of brain areas to master task performance. It remains unclear whether the functional connectivity within these primary and secondary motor networks differs between the old and the young and whether task difficulty modulates connectivity. We applied graph-theoretical network analysis (GTNA) to task-driven fMRI data in 16 elderly and 16 young participants using a bimanual coordination task including in-phase and anti-phase flexion/extension wrist movements. Network nodes for the GTNA comprised task-relevant brain areas as defined by fMRI activation foci. The elderly matched the motor performance of the young but showed an increased functional connectivity in both networks across a wide range of connectivity metrics, i.e., higher mean connectivity degree, connection strength, network density and efficiency, together with shorter mean communication path length between the network nodes and also a lower betweenness centrality. More difficult movements showed an increased connectivity in both groups. The network connectivity of both groups had “small world” character. The present findings indicate (a) that bimanual coordination in the aging brain is associated with a higher functional connectivity even between areas also activated in young adults, independently from task difficulty, and (b) that adequate motor coordination in the context of task-driven bimanual control in older adults may not be solely due to additional neural recruitment but also to aging-related changes of functional relationships between brain regions.
Effect of turning vs. supine position under phototherapy on neonates with hyperbilirubinemia: a systematic review.

AIMS AND OBJECTIVES To determine the most effective position jaundiced neonates should assume during phototherapy from appraised randomised controlled trials. BACKGROUND Many local hospitals still alternate positions of jaundiced neonates receiving phototherapy despite the safe infant sleeping protocol of placing them supine. DESIGN A systematic review was conducted. METHODS Databases that included Cumulative Index to Nursing and Allied Health Literature, ScienceDirect, Embase and The Cochrane Library were used. Randomized controlled trials published in English language that evaluate the best position for healthy jaundiced neonates aged day 1 to 14 under phototherapy were searched. In addition, any positioning done every 2-3 hours during phototherapy with the outcome measures being bilirubin reduction and duration of phototherapy were also searched and included (n = 5). Physiotherapy Evidence Database scale was adopted for quality assessment. All processes were conducted by both reviewers independently. Discrepancies were resolved by a third reviewer. Preferred Reporting Items for Systematic Reviews and Meta-Analyses Guideline were utilised. Out of 20 papers, five were included for qualitative synthesis. Data extraction was based on the template (participants, study designs etcetera) agreed by both authors. RESULTS All five studies possessed external validity. One paper scored 7, three scored 5 while one scored 3. Four of these studies reported no difference in bilirubin reduction and duration of phototherapy. Only one study reported a significant drop in serum bilirubin and shorter duration of phototherapy in the supine group. CONCLUSION It has been proved that keeping the jaundiced newborns in the supine position throughout phototherapy is as effective as turning them periodically based on the appraised studies. RELEVANCE TO CLINICAL PRACTICE It is unnecessary to alternate positions of the jaundiced neonates when conventional phototherapy is delivered to lighten nurses' workload.
Performance Evaluation of Non-tunneling Edge-Overlay Model on 40GbE Environment

Network virtualization is an essential technology for cloud datacenters that provide multi-tenancy services. Cutting-edge SDN-enabled datacenters have introduced an edge-overlay (distributed tunneling) model to construct virtual tenant networks. The edge-overlay model generally uses L2-in-L3 tunneling protocols, and VXLAN is a representative of such protocols. However, the tunneling-based edge-overlay model has some performance and compatibility problems. We have proposed yet another edge-overlay model that does not rely on L2-in-L3 tunneling protocols so far. Our model utilizes two methods, OpenFlow-based address translation and host-based VLAN. The former method replaces VMs' MAC addresses to physical servers' ones, which prevents unnecessary IP fragmentation as well as unnecessary MAC address learning by physical switches. The later method breaks a limitation of the number of VLAN-based virtual tenant networks (4094) by allocating entire VLAN ID space to each physical server and by mapping VLAN ID to VM with OpenFlow controller support. Our previous study has shown that performance of the proposed model is superior to existing other models on 1GbE environment. However, the upper bound of our proposed method, performance behavior with large packet size, and effect of hardware-assisted technology like segmentation offload have not been evaluated. In this paper, we evaluate performance effects of these aspects on high-bandwidth (40GbE) environment. The results show that the performance of VM-to-VM communication with the proposed model is close to that of physical communication and exceeds 10Gbps throughput with large TCP segment.
Model checking sequential software programs via mixed symbolic analysis

We present an efficient symbolic search algorithm for software model checking. Our algorithms perform word-level reasoning by using a combination of decision procedures in Boolean and integer and real domains, and use novel symbolic search strategies optimized specifically for sequential programs to improve scalability. Experiments on real-world C programs show that the new symbolic search algorithms can achieve several orders-of-magnitude improvements over existing methods based on bit-level (Boolean) reasoning.
Scalable IP lookups using shape graphs

Recently, there has been much renewed interest in developing compact data structures for packet processing functions such as longest prefix-match for IP lookups. This has been motivated by several factors: (1) The advent of 100Gbps interfaces necessitating correspondingly fast packet processing algorithms with a compact memory footprint; (2) network virtualization leading to virtualization of physical router platforms making it critical to reduce high-speed memory needs per virtual router; (3) software routers built on multi-core processors requiring the use of compact data-structures that fit in on-chip caches for good performance. In this paper, we revisit this issue of developing compact data structures for key packet-processing functions. We develop a new data structure, called the shape graph, that significantly compacts the trie data-structure used for IP lookups. We accomplish this by identifying considerable structural similarities in IP lookup tries that have not previously been used in the literature for scalable IP lookups. We use these similarities to store lookup tries in a new graph data structure that has a significantly lower memory-footprint. Using real IP forwarding tables, we compare the memory usage of this new data structure to that of multi-bit tries and of Bloom filters used for IP lookups. The shape graph requires significantly less memory and allows the far more effective use of on-chip memory. This effective use of on-chip memory combined with multi-threading on a multi-core processor makes shape-graph-based IP lookups well suited for 100Gbps lookups. The small footprint also makes it well suited for use in router platforms that host a large number of virtual routers.
Automatic emotion detection model from facial expression

The human face plays a prodigious role for automatic recognition of emotion in the field of identification of human emotion and the interaction between human and computer for some real application like driver state surveillance, personalized learning, health monitoring etc. Most reported facial emotion recognition systems, however, are not fully considered subject-independent dynamic features, so they are not robust enough for real life recognition tasks with subject (human face) variation, head movement and illumination change. In this article we have tried to design an automated framework for emotion detection using facial expression. For human-computer interaction facial expression makes a platform for non-verbal communication. The emotions are effectively changeable happenings that are evoked as a result of impelling force. So in real life application, detection of emotion is very challenging task. Facial expression recognition system requires to overcome the human face having multiple variability such as color, orientation, expression, posture and texture so on. In our framework we have taken frame from live streaming and processed it using Grabor feature extraction and neural network. To detect the emotion facial attributes extraction by principal component analysis is used and a clusterization of different facial expression with respective emotions. Finally to determine facial expressions separately, the processed feature vector is channeled through the already learned pattern classifiers.
A large‐scale study of the evolution of Web pages

How fast does the Web change? Does most of the content remain unchanged once it has been authored, or are the documents continuously updated? Do pages change a little or a lot? Is the extent of change correlated to any other property of the page? All of these questions are of interest to those who mine the Web, including all the popular search engines, but few studies have been performed to date to answer them.