On Lightweight Privacy-Preserving Collaborative Learning for IoT Objects

The Internet of Things (IoT) will be a main data generation infrastructure for achieving better system intelligence. This paper considers the design and implementation of a practical privacy-preserving collaborative learning scheme, in which a curious learning coordinator trains a better machine learning model based on the data samples contributed by a number of IoT objects, while the confidentiality of the raw forms of the training data is protected against the coordinator. Existing distributed machine learning and data encryption approaches incur significant computation and communication overhead, rendering them ill-suited for resource-constrained IoT objects. We study an approach that applies independent Gaussian random projection at each IoT object to obfuscate data and trains a deep neural network at the coordinator based on the projected data from the IoT objects. This approach introduces light computation overhead to the IoT objects and moves most workload to the coordinator that can have sufficient computing resources. Although the independent projections performed by the IoT objects address the potential collusion between the curious coordinator and some compromised IoT objects, they significantly increase the complexity of the projected data. In this paper, we leverage the superior learning capability of deep learning in capturing sophisticated patterns to maintain good learning performance. Extensive comparative evaluation shows that this approach outperforms other lightweight approaches that apply additive noisification for differential privacy and/or support vector machines for learning in the applications with light data pattern complexities.Comment: 12 pages,IOTDI 201

False-Name Manipulation in Weighted Voting Games is Hard for Probabilistic Polynomial Time

False-name manipulation refers to the question of whether a player in a weighted voting game can increase her power by splitting into several players and distributing her weight among these false identities. Analogously to this splitting problem, the beneficial merging problem asks whether a coalition of players can increase their power in a weighted voting game by merging their weights. Aziz et al. [ABEP11] analyze the problem of whether merging or splitting players in weighted voting games is beneficial in terms of the Shapley-Shubik and the normalized Banzhaf index, and so do Rey and Rothe [RR10] for the probabilistic Banzhaf index. All these results provide merely NP-hardness lower bounds for these problems, leaving the question about their exact complexity open. For the Shapley--Shubik and the probabilistic Banzhaf index, we raise these lower bounds to hardness for PP, "probabilistic polynomial time", and provide matching upper bounds for beneficial merging and, whenever the number of false identities is fixed, also for beneficial splitting, thus resolving previous conjectures in the affirmative. It follows from our results that beneficial merging and splitting for these two power indices cannot be solved in NP, unless the polynomial hierarchy collapses, which is considered highly unlikely

The Least-core and Nucleolus of Path Cooperative Games

Cooperative games provide an appropriate framework for fair and stable profit distribution in multiagent systems. In this paper, we study the algorithmic issues on path cooperative games that arise from the situations where some commodity flows through a network. In these games, a coalition of edges or vertices is successful if it enables a path from the source to the sink in the network, and lose otherwise. Based on dual theory of linear programming and the relationship with flow games, we provide the characterizations on the CS-core, least-core and nucleolus of path cooperative games. Furthermore, we show that the least-core and nucleolus are polynomially solvable for path cooperative games defined on both directed and undirected network

Novel diffusion mechanism on the GaAs(001) surface: the role of adatom-dimer interaction

Employing first principles total energy calculations we have studied the behavior of Ga and Al adatoms on the GaAs(001)-beta2 surface. The adsorption site and two relevant diffusion channels are identified. The channels are characterized by different adatom-surface dimer interaction. Both affect in a novel way the adatom migration: in one channel the diffusing adatom jumps across the surface dimers and leaves the dimer bonds intact, in the other one the surface dimer bonds are broken. The two channels are taken into account to derive effective adatom diffusion barriers. From the diffusion barriers we conclude a strong diffusion anisotropy for both Al and Ga adatoms with the direction of fastest diffusion parallel to the surface dimers. In agreement with experimental observations we find higher diffusion barriers for Al than for Ga.Comment: 4 pages, 2 figures, Phys. Rev. Lett. 79 (1997). Other related publications can be found at http://www.rz-berlin.mpg.de/th/paper.htm

Superconductivity in Cu_xTiSe_2

Charge density waves (CDWs) are periodic modulations of the conduction electron density in solids. They are collective states that arise from intrinsic instabilities often present in low dimensional electronic systems. The layered dichalcogenides are the most well-studied examples, with TiSe_2 one of the first CDW-bearing materials known. The competition between CDW and superconducting collective electronic states at low temperatures has long been held and explored, and yet no chemical system has been previously reported where finely controlled chemical tuning allows this competition to be studied in detail. Here we report how, upon controlled intercalation of TiSe_2 with Cu to yield Cu_xTiSe_2, the CDW transition is continuously suppressed, and a new superconducting state emerges near x = 0.04, with a maximum T_c of 4.15 K found at x = 0.08. Cu_xTiSe_2 thus provides the first opportunity to study the CDW to Superconductivity transition in detail through an easily-controllable chemical parameter, and will provide new insights into the behavior of correlated electron systems.Comment: Accepted to Nature Physic

Latviešu valodas institūta žurnāls

Objective. To prospectively evaluate the effects of resistance training combined with increased energy intake or protein-supplementation on lean body-mass, resting metabolic-rate (RMR) and cardiovascular risk factors. Methods. Twenty-four healthy males (aged 19-32 years) performed resistance exercise for 12 weeks aiming for at least 1 hour training-sessions 3 times a week. The participants were randomized to consume extra protein (33 g whey protein/day) or a meal of fast-food/day (1350 kcal, 41 g protein). Body-composition was measured with Dual-Energy X-ray Absorptiometry (DEXA) and RMR by indirect calorimetry. Fasting blood samples were drawn before and after the 3-month training period and after 12 months. Results. The body weight increased from 75.1 +/- 6.9 kg to 78.7 +/- 7.2 kg (p andlt; 0.0001), without differences between the groups. RMR increased from 1787 +/- 143 kcal/24 h to 1954 +/- 187 kcal/24 h (p andlt; 0.0001, N = 24), which was more than expected from the increase in lean body-mass (increase from 59.7 +/- 4.3 kg to 61.8 +/- 4.1 kg p = 0.004). Fasting serum-insulin levels increased in the fast-food group compared with the extra-protein group (p = 0.03). ApoB increased from 0.691 +/- 0.14 g/L to 0.768 +/- 0.17 g/L, p = 0.004, in the fast-food group only. Long-term follow up after 12 months showed that RMR, body weight, total fat and lean body-masses did not differ from baseline (n = 19). Conclusions. Resistance training for 12 weeks increased RMR and lean body-mass similarly when based on either an increased energy-intake or protein supplement. However, the increase in RMR was higher than expected from the increase in lean body-mass. Thus resistance training could potentially decrease the risk of obesity by induction of increased RMR.Funding Agencies|University Hospital of Linkoping Research Funds||Linkoping University||Gamla Tjanarinnor||Medical Research Council of Southeast Sweden||Diabetes Research Centre of Linkoping University||</p

Group schema therapy for cluster-C personality disorders:A multicentre open pilot study

BackgroundGroup schema therapy (GST) is increasingly popular as a treatment for personality disorders (PDs), including Cluster-C PDs. Individual ST has proven to be effective for Cluster-C PD patients, while the evidence for GST is limited. This study aimed to investigate the effectiveness of GST for Cluster-C PD. Moreover, differ- ences between the specific Cluster-C PDs (avoidant PD, dependent PD and obsessive-compulsive PD) were explored.MethodsA multicentre open trial was conducted, including 137 patients with a Cluster-C PD (avoidant PD: n = 107, dependent PD: n = 11 and obsessive- compulsive PD: n = 19). Patients received 30 weekly GST sessions with a maximum of 180 min of individual ST and five optional monthly booster sessions. Outcome measures including Cluster-C PD severity, general psychopathological symptoms, quality of life, functional impairment, happiness, PD-related beliefs, self-esteem, self- ideal discrepancy, schemas and schema modes were assessed at baseline until 2-year follow-up with semi-structured interviews and self-report measures. Change over time and differences between the specific Cluster-C PDs were analysed with mixed regression analyses.ResultsThe outcome measures showed significant improvements for all Cluster-C PDs, with medium to large effect sizes after 2 years. A treatment dropout rate of 11.7% was found. There were some indications for differences between the Cluster-C PDs in severity at baseline, change trajectories and effectiveness of GST. ConclusionsThis study demonstrated that GST is a promising treatment for Cluster-C PDs. The following step is a randomized controlled trial to further document the (cost-)effectiveness of GST. <br/

A computational study of the influence of methyl substituents on competitive ring closure to α- and β-lactones

Ring-closure of substituted 2-chlorosuccinates to α- or β-lactones has been studied by means of MP2/6-311+G(d,p)//MP2/6-31+G(d) calculations in water treated as a polarised continuum (PCM) and in vacuum. Optimised geometries have been obtained for 2-chlorosuccinate and its 2-methyl, 3,3-dimethyl, and 2,3,3-trimethyl derivatives, along with the transition structures and products for intramolecular nucleophilic displacement leading to the 3- or 4-membered rings. Relative enthalpies and Gibbs free energies of activation and reaction are presented, along with key geometrical parameters, and changes in electrostatic-potential-derived atomic charges. The difference in free-energy barriers for α- and β-lactone formation from the 2-methyl substrate at 298 K is less than 1 kJ mol−1. Primary 14C kinetic isotope effects calculated for substitution at C2 are significantly smaller for α-lactone formation than for β, suggesting a possible way to distinguish between the competing pathways of reaction. The B3LYP method without dispersion corrections predicts the wrong relative stability order for methyl-substituted succinate dianions in PCM water